browser-use/examples/web_navigation_example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Web Navigation Example using AI Agent\n",
    "\n",
    "This notebook demonstrates how to use the AI agent for general web navigation tasks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime\n",
    "import os\n",
    "from langchain_openai import ChatOpenAI\n",
    "from src.agent.service import AgentService\n",
    "from src.agent.service import AgentService\n",
    "from src.controller.service import ControllerService\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialize services\n",
    "task = \"\"\"\n",
    "Go to wikipedia.org, search for \"Artificial Intelligence\", \n",
    "find the section about machine learning, and extract the key points.\n",
    "\"\"\"\n",
    "controller = ControllerService()\n",
    "model = ChatOpenAI(model='gpt-4o')\n",
    "agent = AgentService(task, model, controller, use_vision=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step 11:\n",
      "\n",
      "Action:\n",
      "search_google=None go_to_url=None nothing=None go_back=None done=None click_element=None input_text=None extract_page_content=True valuation_previous_goal='Extract key points about machine learning from the article.' goal='Extract key points about machine learning from the article.' ask_human=None\n",
      "\n",
      "Result:\n",
      "done=False extracted_content='[![Page semi-protected](//upload.wikimedia.org/wikipedia/en/thumb/1/1b/Semi-\\nprotection-shackle.svg/20px-Semi-protection-\\nshackle.svg.png)](/wiki/Wikipedia:Protection_policy#semi \"This article is\\nsemi-protected.\")\\n\\nFrom Wikipedia, the free encyclopedia\\n\\nIntelligence of machines\\n\\n\"AI\" redirects here. For other uses, see [AI\\n(disambiguation)](/wiki/AI_\\\\(disambiguation\\\\) \"AI \\\\(disambiguation\\\\)\"),\\n[Artificial intelligence\\n(disambiguation)](/wiki/Artificial_intelligence_\\\\(disambiguation\\\\) \"Artificial\\nintelligence \\\\(disambiguation\\\\)\"), and [Intelligent\\nagent](/wiki/Intelligent_agent \"Intelligent agent\").\\n\\nPart of a series on  \\n---  \\nArtificial intelligence  \\n[![](//upload.wikimedia.org/wikipedia/commons/thumb/6/64/Dall-\\ne_3_%28jan_%2724%29_artificial_intelligence_icon.png/100px-Dall-\\ne_3_%28jan_%2724%29_artificial_intelligence_icon.png)](/wiki/File:Dall-\\ne_3_\\\\(jan_%2724\\\\)_artificial_intelligence_icon.png)  \\nshowMajor goals\\n\\n  * [Artificial general intelligence](/wiki/Artificial_general_intelligence \"Artificial general intelligence\")\\n  * [Intelligent agent](/wiki/Intelligent_agent \"Intelligent agent\")\\n  * [Recursive self-improvement](/wiki/Recursive_self-improvement \"Recursive self-improvement\")\\n  * [Planning](/wiki/Automated_planning_and_scheduling \"Automated planning and scheduling\")\\n  * [Computer vision](/wiki/Computer_vision \"Computer vision\")\\n  * [General game playing](/wiki/General_game_playing \"General game playing\")\\n  * [Knowledge reasoning](/wiki/Knowledge_representation_and_reasoning \"Knowledge representation and reasoning\")\\n  * [Natural language processing](/wiki/Natural_language_processing \"Natural language processing\")\\n  * [Robotics](/wiki/Robotics \"Robotics\")\\n  * [AI safety](/wiki/AI_safety \"AI safety\")\\n\\n  \\nshowApproaches\\n\\n  * [Machine learning](/wiki/Machine_learning \"Machine learning\")\\n  * [Symbolic](/wiki/Symbolic_artificial_intelligence \"Symbolic artificial intelligence\")\\n  * [Deep learning](/wiki/Deep_learning \"Deep learning\")\\n  * [Bayesian networks](/wiki/Bayesian_network \"Bayesian network\")\\n  * [Evolutionary algorithms](/wiki/Evolutionary_algorithm \"Evolutionary algorithm\")\\n  * [Hybrid intelligent systems](/wiki/Hybrid_intelligent_system \"Hybrid intelligent system\")\\n  * [Systems integration](/wiki/Artificial_intelligence_systems_integration \"Artificial intelligence systems integration\")\\n\\n  \\nshow[Applications](/wiki/Applications_of_artificial_intelligence \"Applications\\nof artificial intelligence\")\\n\\n  * [Bioinformatics](/wiki/Machine_learning_in_bioinformatics \"Machine learning in bioinformatics\")\\n  * [Deepfake](/wiki/Deepfake \"Deepfake\")\\n  * [Earth sciences](/wiki/Machine_learning_in_earth_sciences \"Machine learning in earth sciences\")\\n  * [ Finance ](/wiki/Applications_of_artificial_intelligence#Finance \"Applications of artificial intelligence\")\\n  * [Generative AI](/wiki/Generative_artificial_intelligence \"Generative artificial intelligence\")\\n    * [Art](/wiki/Artificial_intelligence_art \"Artificial intelligence art\")\\n    * [Audio](/wiki/Generative_audio \"Generative audio\")\\n    * [Music](/wiki/Music_and_artificial_intelligence \"Music and artificial intelligence\")\\n  * [Government](/wiki/Artificial_intelligence_in_government \"Artificial intelligence in government\")\\n  * [Healthcare](/wiki/Artificial_intelligence_in_healthcare \"Artificial intelligence in healthcare\")\\n  * [Industry](/wiki/Artificial_intelligence_in_industry \"Artificial intelligence in industry\")\\n    * [Mental health](/wiki/Artificial_intelligence_in_mental_health \"Artificial intelligence in mental health\")\\n  * [Machine translation](/wiki/Machine_translation \"Machine translation\")\\n  * [ Military ](/wiki/Artificial_intelligence_arms_race \"Artificial intelligence arms race\")\\n  * [Physics](/wiki/Machine_learning_in_physics \"Machine learning in physics\")\\n  * [Projects](/wiki/List_of_artificial_intelligence_projects \"List of artificial intelligence projects\")\\n\\n  \\nshow[Philosophy](/wiki/Philosophy_of_artificial_intelligence \"Philosophy of\\nartificial intelligence\")\\n\\n  * [Artificial consciousness](/wiki/Artificial_consciousness \"Artificial consciousness\")\\n  * [Chinese room](/wiki/Chinese_room \"Chinese room\")\\n  * [Friendly AI](/wiki/Friendly_artificial_intelligence \"Friendly artificial intelligence\")\\n  * [Control problem](/wiki/AI_control_problem \"AI control problem\")/[Takeover](/wiki/AI_takeover \"AI takeover\")\\n  * [Ethics](/wiki/Ethics_of_artificial_intelligence \"Ethics of artificial intelligence\")\\n  * [Existential risk](/wiki/Existential_risk_from_artificial_general_intelligence \"Existential risk from artificial general intelligence\")\\n  * [Turing test](/wiki/Turing_test \"Turing test\")\\n  * [Regulation](/wiki/Regulation_of_artificial_intelligence \"Regulation of artificial intelligence\")\\n\\n  \\nshow[History](/wiki/History_of_artificial_intelligence \"History of artificial\\nintelligence\")\\n\\n  * [Timeline](/wiki/Timeline_of_artificial_intelligence \"Timeline of artificial intelligence\")\\n  * [Progress](/wiki/Progress_in_artificial_intelligence \"Progress in artificial intelligence\")\\n  * [AI winter](/wiki/AI_winter \"AI winter\")\\n  * [AI boom](/wiki/AI_boom \"AI boom\")\\n\\n  \\nshowGlossary\\n\\n  * [Glossary](/wiki/Glossary_of_artificial_intelligence \"Glossary of artificial intelligence\")\\n\\n  \\n  \\n  * [v](/wiki/Template:Artificial_intelligence \"Template:Artificial intelligence\")\\n  * [t](/wiki/Template_talk:Artificial_intelligence \"Template talk:Artificial intelligence\")\\n  * [e](/wiki/Special:EditPage/Template:Artificial_intelligence \"Special:EditPage/Template:Artificial intelligence\")\\n\\n  \\n  \\n**Artificial intelligence** (**AI**), in its broadest sense, is\\n[intelligence](/wiki/Intelligence \"Intelligence\") exhibited by\\n[machines](/wiki/Machine \"Machine\"), particularly [computer\\nsystems](/wiki/Computer_systems \"Computer systems\"). It is a [field of\\nresearch](/wiki/Field_of_research \"Field of research\") in [computer\\nscience](/wiki/Computer_science \"Computer science\") that develops and studies\\nmethods and [software](/wiki/Software \"Software\") that enable machines to\\n[perceive their environment](/wiki/Machine_perception \"Machine perception\")\\nand use [learning](/wiki/Machine_learning \"Machine learning\") and intelligence\\nto take actions that maximize their chances of achieving defined goals.[1]\\nSuch machines may be called AIs.\\n\\nSome high-profile [applications of AI](/wiki/Applications_of_AI \"Applications\\nof AI\") include advanced [web search engines](/wiki/Web_search_engine \"Web\\nsearch engine\") (e.g., [Google Search](/wiki/Google_Search \"Google Search\"));\\n[recommendation systems](/wiki/Recommendation_systems \"Recommendation\\nsystems\") (used by [YouTube](/wiki/YouTube \"YouTube\"),\\n[Amazon](/wiki/Amazon_\\\\(company\\\\) \"Amazon \\\\(company\\\\)\"), and\\n[Netflix](/wiki/Netflix \"Netflix\")); interacting [via human\\nspeech](/wiki/Natural-language_understanding \"Natural-language understanding\")\\n(e.g., [Google Assistant](/wiki/Google_Assistant \"Google Assistant\"),\\n[Siri](/wiki/Siri \"Siri\"), and [Alexa](/wiki/Amazon_Alexa \"Amazon Alexa\"));\\n[autonomous vehicles](/wiki/Autonomous_vehicles \"Autonomous vehicles\") (e.g.,\\n[Waymo](/wiki/Waymo \"Waymo\"));\\n[generative](/wiki/Generative_artificial_intelligence \"Generative artificial\\nintelligence\") and [creative](/wiki/Computational_creativity \"Computational\\ncreativity\") tools (e.g., [ChatGPT](/wiki/ChatGPT \"ChatGPT\"), and [AI\\nart](/wiki/AI_art \"AI art\")); and [superhuman](/wiki/Superintelligence\\n\"Superintelligence\") play and analysis in [strategy games](/wiki/Strategy_game\\n\"Strategy game\") (e.g., [chess](/wiki/Chess \"Chess\") and\\n[Go](/wiki/Go_\\\\(game\\\\) \"Go \\\\(game\\\\)\")). However, many AI applications are not\\nperceived as AI: \"A lot of cutting edge AI has filtered into general\\napplications, often without being called AI because once something becomes\\nuseful enough and common enough it\\'s [not labeled AI anymore](/wiki/AI_effect\\n\"AI effect\").\"[2][3]\\n\\nThe various subfields of AI research are centered around particular goals and\\nthe use of particular tools. The traditional goals of AI research include\\n[reasoning](/wiki/Automated_reasoning \"Automated reasoning\"), [knowledge\\nrepresentation](/wiki/Knowledge_representation \"Knowledge representation\"),\\n[planning](/wiki/Automated_planning_and_scheduling \"Automated planning and\\nscheduling\"), [learning](/wiki/Machine_learning \"Machine learning\"), [natural\\nlanguage processing](/wiki/Natural_language_processing \"Natural language\\nprocessing\"), perception, and support for [robotics](/wiki/Robotics\\n\"Robotics\").[a] [General intelligence](/wiki/Artificial_general_intelligence\\n\"Artificial general intelligence\")—the ability to complete any task\\nperformable by a human on an at least equal level—is among the field\\'s long-\\nterm goals.[4] To reach these goals, AI researchers have adapted and\\nintegrated a wide range of techniques, including\\n[search](/wiki/State_space_search \"State space search\") and [mathematical\\noptimization](/wiki/Mathematical_optimization \"Mathematical optimization\"),\\n[formal logic](/wiki/Formal_logic \"Formal logic\"), [artificial neural\\nnetworks](/wiki/Artificial_neural_network \"Artificial neural network\"), and\\nmethods based on [statistics](/wiki/Statistics \"Statistics\"), [operations\\nresearch](/wiki/Operations_research \"Operations research\"), and\\n[economics](/wiki/Economics \"Economics\").[b] AI also draws upon\\n[psychology](/wiki/Psychology \"Psychology\"), [linguistics](/wiki/Linguistics\\n\"Linguistics\"), [philosophy](/wiki/Philosophy_of_artificial_intelligence\\n\"Philosophy of artificial intelligence\"), [neuroscience](/wiki/Neuroscience\\n\"Neuroscience\"), and other fields.[5]\\n\\nArtificial intelligence was founded as an academic discipline in 1956,[6] and\\nthe field went through multiple cycles of optimism,[7][8] followed by periods\\nof disappointment and loss of funding, known as [AI winter](/wiki/AI_winter\\n\"AI winter\").[9][10] Funding and interest vastly increased after 2012 when\\n[deep learning](/wiki/Deep_learning \"Deep learning\") outperformed previous AI\\ntechniques.[11] This growth accelerated further after 2017 with the\\n[transformer architecture](/wiki/Transformer_architecture \"Transformer\\narchitecture\"),[12] and by the early 2020s hundreds of billions of dollars\\nwere being invested in AI (known as the \"[AI boom](/wiki/AI_boom \"AI boom\")\").\\nThe widespread use of AI in the 21st century exposed several unintended\\nconsequences and harms in the present and raised concerns about [its\\nrisks](/wiki/AI_risk \"AI risk\") and [long-term\\neffects](/wiki/AI_aftermath_scenarios \"AI aftermath scenarios\") in the future,\\nprompting discussions about [regulatory\\npolicies](/wiki/Regulation_of_artificial_intelligence \"Regulation of\\nartificial intelligence\") to ensure the [safety and benefits of the\\ntechnology](/wiki/AI_safety \"AI safety\").\\n\\n## Goals\\n\\nThe general problem of simulating (or creating) intelligence has been broken\\ninto subproblems. These consist of particular traits or capabilities that\\nresearchers expect an intelligent system to display. The traits described\\nbelow have received the most attention and cover the scope of AI research.[a]\\n\\n### Reasoning and problem-solving\\n\\nEarly researchers developed algorithms that imitated step-by-step reasoning\\nthat humans use when they solve puzzles or make logical\\n[deductions](/wiki/Deductive_reasoning \"Deductive reasoning\").[13] By the late\\n1980s and 1990s, methods were developed for dealing with\\n[uncertain](/wiki/Uncertainty \"Uncertainty\") or incomplete information,\\nemploying concepts from [probability](/wiki/Probability \"Probability\") and\\n[economics](/wiki/Economics \"Economics\").[14]\\n\\nMany of these algorithms are insufficient for solving large reasoning problems\\nbecause they experience a \"combinatorial explosion\": They become exponentially\\nslower as the problems grow.[15] Even humans rarely use the step-by-step\\ndeduction that early AI research could model. They solve most of their\\nproblems using fast, intuitive judgments.[16] Accurate and efficient reasoning\\nis an unsolved problem.\\n\\n### Knowledge representation\\n\\n[![](//upload.wikimedia.org/wikipedia/commons/thumb/e/e8/General_Formal_Ontology.svg/260px-\\nGeneral_Formal_Ontology.svg.png)](/wiki/File:General_Formal_Ontology.svg)An\\nontology represents knowledge as a set of concepts within a domain and the\\nrelationships between those concepts.\\n\\n[Knowledge representation](/wiki/Knowledge_representation \"Knowledge\\nrepresentation\") and [knowledge engineering](/wiki/Knowledge_engineering\\n\"Knowledge engineering\")[17] allow AI programs to answer questions\\nintelligently and make deductions about real-world facts. Formal knowledge\\nrepresentations are used in content-based indexing and retrieval,[18] scene\\ninterpretation,[19] clinical decision support,[20] knowledge discovery (mining\\n\"interesting\" and actionable inferences from large [databases](/wiki/Database\\n\"Database\")),[21] and other areas.[22]\\n\\nA [knowledge base](/wiki/Knowledge_base \"Knowledge base\") is a body of\\nknowledge represented in a form that can be used by a program. An\\n[ontology](/wiki/Ontology_\\\\(information_science\\\\) \"Ontology \\\\(information\\nscience\\\\)\") is the set of objects, relations, concepts, and properties used by\\na particular domain of knowledge.[23] Knowledge bases need to represent things\\nsuch as objects, properties, categories, and relations between objects;[24]\\nsituations, events, states, and time;[25] causes and effects;[26] knowledge\\nabout knowledge (what we know about what other people know);[27] [default\\nreasoning](/wiki/Default_reasoning \"Default reasoning\") (things that humans\\nassume are true until they are told differently and will remain true even when\\nother facts are changing);[28] and many other aspects and domains of\\nknowledge.\\n\\nAmong the most difficult problems in knowledge representation are the breadth\\nof commonsense knowledge (the set of atomic facts that the average person\\nknows is enormous);[29] and the sub-symbolic form of most commonsense\\nknowledge (much of what people know is not represented as \"facts\" or\\n\"statements\" that they could express verbally).[16] There is also the\\ndifficulty of [knowledge acquisition](/wiki/Knowledge_acquisition \"Knowledge\\nacquisition\"), the problem of obtaining knowledge for AI applications.[c]\\n\\n### Planning and decision-making\\n\\nAn \"agent\" is anything that perceives and takes actions in the world. A\\n[rational agent](/wiki/Rational_agent \"Rational agent\") has goals or\\npreferences and takes actions to make them happen.[d][32] In [automated\\nplanning](/wiki/Automated_planning \"Automated planning\"), the agent has a\\nspecific goal.[33] In [automated decision-making](/wiki/Automated_decision-\\nmaking \"Automated decision-making\"), the agent has preferences—there are some\\nsituations it would prefer to be in, and some situations it is trying to\\navoid. The decision-making agent assigns a number to each situation (called\\nthe \"[utility](/wiki/Utility \"Utility\")\") that measures how much the agent\\nprefers it. For each possible action, it can calculate the \"[expected\\nutility](/wiki/Expected_utility \"Expected utility\")\": the\\n[utility](/wiki/Utility \"Utility\") of all possible outcomes of the action,\\nweighted by the probability that the outcome will occur. It can then choose\\nthe action with the maximum expected utility.[34]\\n\\nIn [classical\\nplanning](/wiki/Automated_planning_and_scheduling#classical_planning\\n\"Automated planning and scheduling\"), the agent knows exactly what the effect\\nof any action will be.[35] In most real-world problems, however, the agent may\\nnot be certain about the situation they are in (it is \"unknown\" or\\n\"unobservable\") and it may not know for certain what will happen after each\\npossible action (it is not \"deterministic\"). It must choose an action by\\nmaking a probabilistic guess and then reassess the situation to see if the\\naction worked.[36]\\n\\nIn some problems, the agent\\'s preferences may be uncertain, especially if\\nthere are other agents or humans involved. These can be learned (e.g., with\\n[inverse reinforcement learning](/wiki/Inverse_reinforcement_learning \"Inverse\\nreinforcement learning\")), or the agent can seek information to improve its\\npreferences.[37] [Information value theory](/wiki/Information_value_theory\\n\"Information value theory\") can be used to weigh the value of exploratory or\\nexperimental actions.[38] The space of possible future actions and situations\\nis typically [intractably](/wiki/Intractably \"Intractably\") large, so the\\nagents must take actions and evaluate situations while being uncertain of what\\nthe outcome will be.\\n\\nA [Markov decision process](/wiki/Markov_decision_process \"Markov decision\\nprocess\") has a [transition model](/wiki/Finite-state_machine \"Finite-state\\nmachine\") that describes the probability that a particular action will change\\nthe state in a particular way and a [reward function](/wiki/Reward_function\\n\"Reward function\") that supplies the utility of each state and the cost of\\neach action. A [policy](/wiki/Reinforcement_learning#Policy \"Reinforcement\\nlearning\") associates a decision with each possible state. The policy could be\\ncalculated (e.g., by [iteration](/wiki/Policy_iteration \"Policy iteration\")),\\nbe [heuristic](/wiki/Heuristic \"Heuristic\"), or it can be learned.[39]\\n\\n[Game theory](/wiki/Game_theory \"Game theory\") describes the rational behavior\\nof multiple interacting agents and is used in AI programs that make decisions\\nthat involve other agents.[40]\\n\\n### Learning\\n\\n[Machine learning](/wiki/Machine_learning \"Machine learning\") is the study of\\nprograms that can improve their performance on a given task automatically.[41]\\nIt has been a part of AI from the beginning.[e]\\n\\nThere are several kinds of machine learning. [Unsupervised\\nlearning](/wiki/Unsupervised_learning \"Unsupervised learning\") analyzes a\\nstream of data and finds patterns and makes predictions without any other\\nguidance.[44] [Supervised learning](/wiki/Supervised_learning \"Supervised\\nlearning\") requires a human to label the input data first, and comes in two\\nmain varieties: [classification](/wiki/Statistical_classification \"Statistical\\nclassification\") (where the program must learn to predict what category the\\ninput belongs in) and [regression](/wiki/Regression_analysis \"Regression\\nanalysis\") (where the program must deduce a numeric function based on numeric\\ninput).[45]\\n\\nIn [reinforcement learning](/wiki/Reinforcement_learning \"Reinforcement\\nlearning\"), the agent is rewarded for good responses and punished for bad\\nones. The agent learns to choose responses that are classified as \"good\".[46]\\n[Transfer learning](/wiki/Transfer_learning \"Transfer learning\") is when the\\nknowledge gained from one problem is applied to a new problem.[47] [Deep\\nlearning](/wiki/Deep_learning \"Deep learning\") is a type of machine learning\\nthat runs inputs through biologically inspired [artificial neural\\nnetworks](/wiki/Artificial_neural_networks \"Artificial neural networks\") for\\nall of these types of learning.[48]\\n\\n[Computational learning theory](/wiki/Computational_learning_theory\\n\"Computational learning theory\") can assess learners by [computational\\ncomplexity](/wiki/Computational_complexity \"Computational complexity\"), by\\n[sample complexity](/wiki/Sample_complexity \"Sample complexity\") (how much\\ndata is required), or by other notions of [optimization](/wiki/Optimization\\n\"Optimization\").[49]\\n\\n### Natural language processing\\n\\n[Natural language processing](/wiki/Natural_language_processing \"Natural\\nlanguage processing\") (NLP)[50] allows programs to read, write and communicate\\nin human languages such as [English](/wiki/English_\\\\(language\\\\) \"English\\n\\\\(language\\\\)\"). Specific problems include [speech\\nrecognition](/wiki/Speech_recognition \"Speech recognition\"), [speech\\nsynthesis](/wiki/Speech_synthesis \"Speech synthesis\"), [machine\\ntranslation](/wiki/Machine_translation \"Machine translation\"), [information\\nextraction](/wiki/Information_extraction \"Information extraction\"),\\n[information retrieval](/wiki/Information_retrieval \"Information retrieval\")\\nand [question answering](/wiki/Question_answering \"Question answering\").[51]\\n\\nEarly work, based on [Noam Chomsky](/wiki/Noam_Chomsky \"Noam Chomsky\")\\'s\\n[generative grammar](/wiki/Generative_grammar \"Generative grammar\") and\\n[semantic networks](/wiki/Semantic_network \"Semantic network\"), had difficulty\\nwith [word-sense disambiguation](/wiki/Word-sense_disambiguation \"Word-sense\\ndisambiguation\")[f] unless restricted to small domains called \"[micro-\\nworlds](/wiki/Blocks_world \"Blocks world\")\" (due to the common sense knowledge\\nproblem[29]). [Margaret Masterman](/wiki/Margaret_Masterman \"Margaret\\nMasterman\") believed that it was meaning and not grammar that was the key to\\nunderstanding languages, and that [thesauri](/wiki/Thesauri \"Thesauri\") and\\nnot dictionaries should be the basis of computational language structure.\\n\\nModern deep learning techniques for NLP include [word\\nembedding](/wiki/Word_embedding \"Word embedding\") (representing words,\\ntypically as [vectors](/wiki/Vector_space \"Vector space\") encoding their\\nmeaning),[52] [transformers](/wiki/Transformer_\\\\(machine_learning_model\\\\)\\n\"Transformer \\\\(machine learning model\\\\)\") (a deep learning architecture using\\nan [attention](/wiki/Attention_\\\\(machine_learning\\\\) \"Attention \\\\(machine\\nlearning\\\\)\") mechanism),[53] and others.[54] In 2019, [generative pre-trained\\ntransformer](/wiki/Generative_pre-trained_transformer \"Generative pre-trained\\ntransformer\") (or \"GPT\") language models began to generate coherent\\ntext,[55][56] and by 2023, these models were able to get human-level scores on\\nthe [bar exam](/wiki/Bar_exam \"Bar exam\"), [SAT](/wiki/SAT \"SAT\") test,\\n[GRE](/wiki/GRE \"GRE\") test, and many other real-world applications.[57]\\n\\n### Perception\\n\\n[Machine perception](/wiki/Machine_perception \"Machine perception\") is the\\nability to use input from sensors (such as cameras, microphones, wireless\\nsignals, active [lidar](/wiki/Lidar \"Lidar\"), sonar, radar, and [tactile\\nsensors](/wiki/Tactile_sensor \"Tactile sensor\")) to deduce aspects of the\\nworld. [Computer vision](/wiki/Computer_vision \"Computer vision\") is the\\nability to analyze visual input.[58]\\n\\nThe field includes [speech recognition](/wiki/Speech_recognition \"Speech\\nrecognition\"),[59] [image classification](/wiki/Image_classification \"Image\\nclassification\"),[60] [facial recognition](/wiki/Facial_recognition_system\\n\"Facial recognition system\"), [object recognition](/wiki/Object_recognition\\n\"Object recognition\"),[61][object tracking](/wiki/Object_tracking \"Object\\ntracking\"),[62] and [robotic perception](/wiki/Robotic_perception \"Robotic\\nperception\").[63]\\n\\n### Social intelligence\\n\\n[![](//upload.wikimedia.org/wikipedia/commons/thumb/2/27/Kismet-\\nIMG_6007-gradient.jpg/220px-Kismet-IMG_6007-gradient.jpg)](/wiki/File:Kismet-\\nIMG_6007-gradient.jpg)[Kismet](/wiki/Kismet_\\\\(robot\\\\) \"Kismet \\\\(robot\\\\)\"), a\\nrobot head which was made in the 1990s; it is a machine that can recognize and\\nsimulate emotions.[64]\\n\\n[Affective computing](/wiki/Affective_computing \"Affective computing\") is an\\ninterdisciplinary umbrella that comprises systems that recognize, interpret,\\nprocess, or simulate human [feeling, emotion, and\\nmood](/wiki/Affect_\\\\(psychology\\\\) \"Affect \\\\(psychology\\\\)\").[65] For example,\\nsome [virtual assistants](/wiki/Virtual_assistant \"Virtual assistant\") are\\nprogrammed to speak conversationally or even to banter humorously; it makes\\nthem appear more sensitive to the emotional dynamics of human interaction, or\\nto otherwise facilitate [human–computer\\ninteraction](/wiki/Human%E2%80%93computer_interaction \"Human–computer\\ninteraction\").\\n\\nHowever, this tends to give naïve users an unrealistic conception of the\\nintelligence of existing computer agents.[66] Moderate successes related to\\naffective computing include textual [sentiment\\nanalysis](/wiki/Sentiment_analysis \"Sentiment analysis\") and, more recently,\\n[multimodal sentiment analysis](/wiki/Multimodal_sentiment_analysis\\n\"Multimodal sentiment analysis\"), wherein AI classifies the affects displayed\\nby a videotaped subject.[67]\\n\\n### General intelligence\\n\\nA machine with [artificial general\\nintelligence](/wiki/Artificial_general_intelligence \"Artificial general\\nintelligence\") should be able to solve a wide variety of problems with breadth\\nand versatility similar to [human intelligence](/wiki/Human_intelligence\\n\"Human intelligence\").[4]\\n\\n## Techniques\\n\\nAI research uses a wide variety of techniques to accomplish the goals\\nabove.[b]\\n\\n### Search and optimization\\n\\nAI can solve many problems by intelligently searching through many possible\\nsolutions.[68] There are two very different kinds of search used in AI: [state\\nspace search](/wiki/State_space_search \"State space search\") and [local\\nsearch](/wiki/Local_search_\\\\(optimization\\\\) \"Local search \\\\(optimization\\\\)\").\\n\\n#### State space search\\n\\n[State space search](/wiki/State_space_search \"State space search\") searches\\nthrough a tree of possible states to try to find a goal state.[69] For\\nexample, [planning](/wiki/Automated_planning_and_scheduling \"Automated\\nplanning and scheduling\") algorithms search through trees of goals and\\nsubgoals, attempting to find a path to a target goal, a process called [means-\\nends analysis](/wiki/Means-ends_analysis \"Means-ends analysis\").[70]\\n\\n[Simple exhaustive searches](/wiki/Brute_force_search \"Brute force\\nsearch\")[71] are rarely sufficient for most real-world problems: the [search\\nspace](/wiki/Search_algorithm \"Search algorithm\") (the number of places to\\nsearch) quickly grows to [astronomical numbers](/wiki/Astronomically_large\\n\"Astronomically large\"). The result is a search that is [too\\nslow](/wiki/Computation_time \"Computation time\") or never completes.[15]\\n\"[Heuristics](/wiki/Heuristics \"Heuristics\")\" or \"rules of thumb\" can help\\nprioritize choices that are more likely to reach a goal.[72]\\n\\n[Adversarial search](/wiki/Adversarial_search \"Adversarial search\") is used\\nfor [game-playing](/wiki/Game_AI \"Game AI\") programs, such as chess or Go. It\\nsearches through a [tree](/wiki/Game_tree \"Game tree\") of possible moves and\\ncounter-moves, looking for a winning position.[73]\\n\\n#### Local search\\n\\n[![](//upload.wikimedia.org/wikipedia/commons/thumb/a/a3/Gradient_descent.gif/220px-\\nGradient_descent.gif)](/wiki/File:Gradient_descent.gif)Illustration of\\n[gradient descent](/wiki/Gradient_descent \"Gradient descent\") for 3 different\\nstarting points; two parameters (represented by the plan coordinates) are\\nadjusted in order to minimize the [loss function](/wiki/Loss_function \"Loss\\nfunction\") (the height)\\n\\n[Local search](/wiki/Local_search_\\\\(optimization\\\\) \"Local search\\n\\\\(optimization\\\\)\") uses [mathematical\\noptimization](/wiki/Mathematical_optimization \"Mathematical optimization\") to\\nfind a solution to a problem. It begins with some form of guess and refines it\\nincrementally.[74]\\n\\n[Gradient descent](/wiki/Gradient_descent \"Gradient descent\") is a type of\\nlocal search that optimizes a set of numerical parameters by incrementally\\nadjusting them to minimize a [loss function](/wiki/Loss_function \"Loss\\nfunction\"). Variants of [gradient descent](/wiki/Gradient_descent \"Gradient\\ndescent\") are commonly used to train neural networks.[75]\\n\\nAnother type of local search is [evolutionary\\ncomputation](/wiki/Evolutionary_computation \"Evolutionary computation\"), which\\naims to iteratively improve a set of candidate solutions by \"mutating\" and\\n\"recombining\" them, [selecting](/wiki/Artificial_selection \"Artificial\\nselection\") only the fittest to survive each generation.[76]\\n\\nDistributed search processes can coordinate via [swarm\\nintelligence](/wiki/Swarm_intelligence \"Swarm intelligence\") algorithms. Two\\npopular swarm algorithms used in search are [particle swarm\\noptimization](/wiki/Particle_swarm_optimization \"Particle swarm optimization\")\\n(inspired by bird [flocking](/wiki/Flocking \"Flocking\")) and [ant colony\\noptimization](/wiki/Ant_colony_optimization \"Ant colony optimization\")\\n(inspired by [ant trails](/wiki/Ant_trail \"Ant trail\")).[77]\\n\\n### Logic\\n\\nFormal [logic](/wiki/Logic \"Logic\") is used for\\n[reasoning](/wiki/Automatic_reasoning \"Automatic reasoning\") and [knowledge\\nrepresentation](/wiki/Knowledge_representation \"Knowledge\\nrepresentation\").[78] Formal logic comes in two main forms: [propositional\\nlogic](/wiki/Propositional_logic \"Propositional logic\") (which operates on\\nstatements that are true or false and uses [logical\\nconnectives](/wiki/Logical_connective \"Logical connective\") such as \"and\",\\n\"or\", \"not\" and \"implies\")[79] and [predicate logic](/wiki/Predicate_logic\\n\"Predicate logic\") (which also operates on objects, predicates and relations\\nand uses [quantifiers](/wiki/Quantifier_\\\\(logic\\\\) \"Quantifier \\\\(logic\\\\)\") such\\nas \"_Every_ _X_ is a _Y_ \" and \"There are _some_ _X_ s that are _Y_ s\").[80]\\n\\n[Deductive reasoning](/wiki/Deductive_reasoning \"Deductive reasoning\") in\\nlogic is the process of [proving](/wiki/Logical_proof \"Logical proof\") a new\\nstatement ([conclusion](/wiki/Logical_consequence \"Logical consequence\")) from\\nother statements that are given and assumed to be true (the\\n[premises](/wiki/Premise \"Premise\")).[81] Proofs can be structured as proof\\n[trees](/wiki/Tree_structure \"Tree structure\"), in which nodes are labelled by\\nsentences, and children nodes are connected to parent nodes by [inference\\nrules](/wiki/Inference_rule \"Inference rule\").\\n\\nGiven a problem and a set of premises, problem-solving reduces to searching\\nfor a proof tree whose root node is labelled by a solution of the problem and\\nwhose [leaf nodes](/wiki/Leaf_nodes \"Leaf nodes\") are labelled by premises or\\n[axioms](/wiki/Axiom \"Axiom\"). In the case of [Horn clauses](/wiki/Horn_clause\\n\"Horn clause\"), problem-solving search can be performed by reasoning\\n[forwards](/wiki/Forward_chaining \"Forward chaining\") from the premises or\\n[backwards](/wiki/Backward_chaining \"Backward chaining\") from the problem.[82]\\nIn the more general case of the clausal form of [first-order\\nlogic](/wiki/First-order_logic \"First-order logic\"),\\n[resolution](/wiki/Resolution_\\\\(logic\\\\) \"Resolution \\\\(logic\\\\)\") is a single,\\naxiom-free rule of inference, in which a problem is solved by proving a\\ncontradiction from premises that include the negation of the problem to be\\nsolved.[83]\\n\\nInference in both Horn clause logic and first-order logic is\\n[undecidable](/wiki/Undecidable_problem \"Undecidable problem\"), and therefore\\n[intractable](/wiki/Intractable_problem \"Intractable problem\"). However,\\nbackward reasoning with Horn clauses, which underpins computation in the\\n[logic programming](/wiki/Logic_programming \"Logic programming\") language\\n[Prolog](/wiki/Prolog \"Prolog\"), is [Turing complete](/wiki/Turing_complete\\n\"Turing complete\"). Moreover, its efficiency is competitive with computation\\nin other [symbolic programming](/wiki/Symbolic_programming \"Symbolic\\nprogramming\") languages.[84]\\n\\n[Fuzzy logic](/wiki/Fuzzy_logic \"Fuzzy logic\") assigns a \"degree of truth\"\\nbetween 0 and 1. It can therefore handle propositions that are vague and\\npartially true.[85]\\n\\n[Non-monotonic logics](/wiki/Non-monotonic_logic \"Non-monotonic logic\"),\\nincluding logic programming with [negation as\\nfailure](/wiki/Negation_as_failure \"Negation as failure\"), are designed to\\nhandle [default reasoning](/wiki/Default_reasoning \"Default reasoning\").[28]\\nOther specialized versions of logic have been developed to describe many\\ncomplex domains.\\n\\n### Probabilistic methods for uncertain reasoning\\n\\n[![](//upload.wikimedia.org/wikipedia/commons/thumb/0/0e/SimpleBayesNet.svg/370px-\\nSimpleBayesNet.svg.png)](/wiki/File:SimpleBayesNet.svg)A simple [Bayesian\\nnetwork](/wiki/Bayesian_network \"Bayesian network\"), with the associated\\n[conditional probability tables](/wiki/Conditional_probability_table\\n\"Conditional probability table\")\\n\\nMany problems in AI (including in reasoning, planning, learning, perception,\\nand robotics) require the agent to operate with incomplete or uncertain\\ninformation. AI researchers have devised a number of tools to solve these\\nproblems using methods from [probability](/wiki/Probability \"Probability\")\\ntheory and economics.[86] Precise mathematical tools have been developed that\\nanalyze how an agent can make choices and plan, using [decision\\ntheory](/wiki/Decision_theory \"Decision theory\"), [decision\\nanalysis](/wiki/Decision_analysis \"Decision analysis\"),[87] and [information\\nvalue theory](/wiki/Information_value_theory \"Information value theory\").[88]\\nThese tools include models such as [Markov decision\\nprocesses](/wiki/Markov_decision_process \"Markov decision process\"),[89]\\ndynamic [decision networks](/wiki/Decision_network \"Decision network\"),[90]\\n[game theory](/wiki/Game_theory \"Game theory\") and [mechanism\\ndesign](/wiki/Mechanism_design \"Mechanism design\").[91]\\n\\n[Bayesian networks](/wiki/Bayesian_network \"Bayesian network\")[92] are a tool\\nthat can be used for [reasoning](/wiki/Automated_reasoning \"Automated\\nreasoning\") (using the [Bayesian inference](/wiki/Bayesian_inference \"Bayesian\\ninference\") algorithm),[g][94] [learning](/wiki/Machine_learning \"Machine\\nlearning\") (using the [expectation–maximization\\nalgorithm](/wiki/Expectation%E2%80%93maximization_algorithm\\n\"Expectation–maximization algorithm\")),[h][96]\\n[planning](/wiki/Automated_planning_and_scheduling \"Automated planning and\\nscheduling\") (using [decision networks](/wiki/Decision_network \"Decision\\nnetwork\"))[97] and [perception](/wiki/Machine_perception \"Machine perception\")\\n(using [dynamic Bayesian networks](/wiki/Dynamic_Bayesian_network \"Dynamic\\nBayesian network\")).[90]\\n\\nProbabilistic algorithms can also be used for filtering, prediction,\\nsmoothing, and finding explanations for streams of data, thus helping\\n[perception](/wiki/Machine_perception \"Machine perception\") systems analyze\\nprocesses that occur over time (e.g., [hidden Markov\\nmodels](/wiki/Hidden_Markov_model \"Hidden Markov model\") or [Kalman\\nfilters](/wiki/Kalman_filter \"Kalman filter\")).[90]\\n\\n[![](//upload.wikimedia.org/wikipedia/commons/thumb/6/69/EM_Clustering_of_Old_Faithful_data.gif/260px-\\nEM_Clustering_of_Old_Faithful_data.gif)](/wiki/File:EM_Clustering_of_Old_Faithful_data.gif)[Expectation–maximization](/wiki/Expectation%E2%80%93maximization_algorithm\\n\"Expectation–maximization algorithm\") [clustering](/wiki/Cluster_analysis\\n\"Cluster analysis\") of [Old Faithful](/wiki/Old_Faithful \"Old Faithful\")\\neruption data starts from a random guess but then successfully converges on an\\naccurate clustering of the two physically distinct modes of eruption.\\n\\n### Classifiers and statistical learning methods\\n\\nThe simplest AI applications can be divided into two types: classifiers (e.g.,\\n\"if shiny then diamond\"), on one hand, and controllers (e.g., \"if diamond then\\npick up\"), on the other hand. [Classifiers](/wiki/Classifier_\\\\(mathematics\\\\)\\n\"Classifier \\\\(mathematics\\\\)\")[98] are functions that use [pattern\\nmatching](/wiki/Pattern_matching \"Pattern matching\") to determine the closest\\nmatch. They can be fine-tuned based on chosen examples using [supervised\\nlearning](/wiki/Supervised_learning \"Supervised learning\"). Each pattern (also\\ncalled an \"[observation](/wiki/Random_variate \"Random variate\")\") is labeled\\nwith a certain predefined class. All the observations combined with their\\nclass labels are known as a [data set](/wiki/Data_set \"Data set\"). When a new\\nobservation is received, that observation is classified based on previous\\nexperience.[45]\\n\\nThere are many kinds of classifiers in use.[99] The [decision\\ntree](/wiki/Decision_tree \"Decision tree\") is the simplest and most widely\\nused symbolic machine learning algorithm.[100] [K-nearest\\nneighbor](/wiki/K-nearest_neighbor \"K-nearest neighbor\") algorithm was the\\nmost widely used analogical AI until the mid-1990s, and [Kernel\\nmethods](/wiki/Kernel_methods \"Kernel methods\") such as the [support vector\\nmachine](/wiki/Support_vector_machine \"Support vector machine\") (SVM)\\ndisplaced k-nearest neighbor in the 1990s.[101] The [naive Bayes\\nclassifier](/wiki/Naive_Bayes_classifier \"Naive Bayes classifier\") is\\nreportedly the \"most widely used learner\"[102] at Google, due in part to its\\nscalability.[103] [Neural networks](/wiki/Artificial_neural_network\\n\"Artificial neural network\") are also used as classifiers.[104]\\n\\n### Artificial neural networks\\n\\n[![](//upload.wikimedia.org/wikipedia/commons/thumb/e/e4/Artificial_neural_network.svg/220px-\\nArtificial_neural_network.svg.png)](/wiki/File:Artificial_neural_network.svg)A\\nneural network is an interconnected group of nodes, akin to the vast network\\nof [neurons](/wiki/Neuron \"Neuron\") in the [human brain](/wiki/Human_brain\\n\"Human brain\").\\n\\nAn artificial neural network is based on a collection of nodes also known as\\n[artificial neurons](/wiki/Artificial_neurons \"Artificial neurons\"), which\\nloosely model the [neurons](/wiki/Neurons \"Neurons\") in a biological brain. It\\nis trained to recognise patterns; once trained, it can recognise those\\npatterns in fresh data. There is an input, at least one hidden layer of nodes\\nand an output. Each node applies a function and once the\\n[weight](/wiki/Weighting \"Weighting\") crosses its specified threshold, the\\ndata is transmitted to the next layer. A network is typically called a deep\\nneural network if it has at least 2 hidden layers.[104]\\n\\nLearning algorithms for neural networks use [local\\nsearch](/wiki/Local_search_\\\\(optimization\\\\) \"Local search \\\\(optimization\\\\)\")\\nto choose the weights that will get the right output for each input during\\ntraining. The most common training technique is the\\n[backpropagation](/wiki/Backpropagation \"Backpropagation\") algorithm.[105]\\nNeural networks learn to model complex relationships between inputs and\\noutputs and [find patterns](/wiki/Pattern_recognition \"Pattern recognition\")\\nin data. In theory, a neural network can learn any function.[106]\\n\\nIn [feedforward neural networks](/wiki/Feedforward_neural_network \"Feedforward\\nneural network\") the signal passes in only one direction.[107] [Recurrent\\nneural networks](/wiki/Recurrent_neural_network \"Recurrent neural network\")\\nfeed the output signal back into the input, which allows short-term memories\\nof previous input events. [Long short term\\nmemory](/wiki/Long_short_term_memory \"Long short term memory\") is the most\\nsuccessful network architecture for recurrent networks.[108]\\n[Perceptrons](/wiki/Perceptron \"Perceptron\")[109] use only a single layer of\\nneurons; deep learning[110] uses multiple layers. [Convolutional neural\\nnetworks](/wiki/Convolutional_neural_network \"Convolutional neural network\")\\nstrengthen the connection between neurons that are \"close\" to each other—this\\nis especially important in [image processing](/wiki/Image_processing \"Image\\nprocessing\"), where a local set of neurons must [identify an\\n\"edge\"](/wiki/Edge_detection \"Edge detection\") before the network can identify\\nan object.[111]\\n\\n### Deep learning\\n\\n[![](//upload.wikimedia.org/wikipedia/commons/thumb/1/1b/AI_hierarchy.svg/170px-\\nAI_hierarchy.svg.png)](/wiki/File:AI_hierarchy.svg)\\n\\n[Deep learning](/wiki/Deep_learning \"Deep learning\")[110] uses several layers\\nof neurons between the network\\'s inputs and outputs. The multiple layers can\\nprogressively extract higher-level features from the raw input. For example,\\nin [image processing](/wiki/Image_processing \"Image processing\"), lower layers\\nmay identify edges, while higher layers may identify the concepts relevant to\\na human such as digits, letters, or faces.[112]\\n\\nDeep learning has profoundly improved the performance of programs in many\\nimportant subfields of artificial intelligence, including [computer\\nvision](/wiki/Computer_vision \"Computer vision\"), [speech\\nrecognition](/wiki/Speech_recognition \"Speech recognition\"), [natural language\\nprocessing](/wiki/Natural_language_processing \"Natural language processing\"),\\n[image classification](/wiki/Image_classification \"Image\\nclassification\"),[113] and others. The reason that deep learning performs so\\nwell in so many applications is not known as of 2023.[114] The sudden success\\nof deep learning in 2012–2015 did not occur because of some new discovery or\\ntheoretical breakthrough (deep neural networks and\\n[backpropagation](/wiki/Backpropagation \"Backpropagation\") had been described\\nby many people, as far back as the 1950s)[i] but because of two factors: the\\nincredible increase in computer power (including the hundred-fold increase in\\nspeed by switching to [GPUs](/wiki/GPU \"GPU\")) and the availability of vast\\namounts of training data, especially the giant [curated\\ndatasets](/wiki/List_of_datasets_for_machine-learning_research \"List of\\ndatasets for machine-learning research\") used for benchmark testing, such as\\n[ImageNet](/wiki/ImageNet \"ImageNet\").[j]\\n\\n### GPT\\n\\n[Generative pre-trained transformers](/wiki/Generative_pre-trained_transformer\\n\"Generative pre-trained transformer\") (GPT) are [large language\\nmodels](/wiki/Large_language_model \"Large language model\") (LLMs) that\\ngenerate text based on the semantic relationships between words in sentences.\\nText-based GPT models are pretrained on a large [corpus of\\ntext](/wiki/Corpus_of_text \"Corpus of text\") that can be from the Internet.\\nThe pretraining consists of predicting the next [token](/wiki/Lexical_analysis\\n\"Lexical analysis\") (a token being usually a word, subword, or punctuation).\\nThroughout this pretraining, GPT models accumulate knowledge about the world\\nand can then generate human-like text by repeatedly predicting the next token.\\nTypically, a subsequent training phase makes the model more truthful, useful,\\nand harmless, usually with a technique called [reinforcement learning from\\nhuman feedback](/wiki/Reinforcement_learning_from_human_feedback\\n\"Reinforcement learning from human feedback\") (RLHF). Current GPT models are\\nprone to generating falsehoods called\\n\"[hallucinations](/wiki/Hallucination_\\\\(artificial_intelligence\\\\)\\n\"Hallucination \\\\(artificial intelligence\\\\)\")\", although this can be reduced\\nwith RLHF and quality data. They are used in [chatbots](/wiki/Chatbot\\n\"Chatbot\"), which allow people to ask a question or request a task in simple\\ntext.[122][123]\\n\\nCurrent models and services include [Gemini](/wiki/Gemini_\\\\(chatbot\\\\) \"Gemini\\n\\\\(chatbot\\\\)\") (formerly Bard), [ChatGPT](/wiki/ChatGPT \"ChatGPT\"),\\n[Grok](/wiki/Grok_\\\\(chatbot\\\\) \"Grok \\\\(chatbot\\\\)\"),\\n[Claude](/wiki/Anthropic#Claude \"Anthropic\"),\\n[Copilot](/wiki/Microsoft_Copilot \"Microsoft Copilot\"), and\\n[LLaMA](/wiki/LLaMA \"LLaMA\").[124] [Multimodal](/wiki/Multimodal_learning\\n\"Multimodal learning\") GPT models can process different types of data\\n([modalities](/wiki/Modality_\\\\(human%E2%80%93computer_interaction\\\\) \"Modality\\n\\\\(human–computer interaction\\\\)\")) such as images, videos, sound, and\\ntext.[125]\\n\\n### Hardware and software\\n\\nMain articles: [Programming languages for artificial\\nintelligence](/wiki/Programming_languages_for_artificial_intelligence\\n\"Programming languages for artificial intelligence\") and [Hardware for\\nartificial intelligence](/wiki/Hardware_for_artificial_intelligence \"Hardware\\nfor artificial intelligence\")\\n\\nIn the late 2010s, [graphics processing units](/wiki/Graphics_processing_unit\\n\"Graphics processing unit\") (GPUs) that were increasingly designed with AI-\\nspecific enhancements and used with specialized [TensorFlow](/wiki/TensorFlow\\n\"TensorFlow\") software had replaced previously used [central processing\\nunit](/wiki/Central_processing_unit \"Central processing unit\") (CPUs) as the\\ndominant means for large-scale (commercial and academic) [machine\\nlearning](/wiki/Machine_learning \"Machine learning\") models\\' training.[126]\\nSpecialized [programming languages](/wiki/Programming_language \"Programming\\nlanguage\") such as [Prolog](/wiki/Prolog \"Prolog\") were used in early AI\\nresearch,[127] but [general-purpose programming languages](/wiki/General-\\npurpose_programming_language \"General-purpose programming language\") like\\n[Python](/wiki/Python_\\\\(programming_language\\\\) \"Python \\\\(programming\\nlanguage\\\\)\") have become predominant.[128]\\n\\nThe transistor density in [integrated circuits](/wiki/Integrated_circuit\\n\"Integrated circuit\") has been observed to roughly double every 18 months—a\\ntrend known as [Moore\\'s law](/wiki/Moore%27s_law \"Moore\\'s law\"), named after\\nthe [Intel](/wiki/Intel \"Intel\") co-founder [Gordon Moore](/wiki/Gordon_Moore\\n\"Gordon Moore\"), who first identified it. Improvements in [GPUs](/wiki/GPUs\\n\"GPUs\") have been even faster.[129]\\n\\n## Applications\\n\\nMain article: [Applications of artificial\\nintelligence](/wiki/Applications_of_artificial_intelligence \"Applications of\\nartificial intelligence\")\\n\\nAI and machine learning technology is used in most of the essential\\napplications of the 2020s, including: [search engines](/wiki/Search_engines\\n\"Search engines\") (such as [Google Search](/wiki/Google_Search \"Google\\nSearch\")), [targeting online advertisements](/wiki/Targeted_advertising\\n\"Targeted advertising\"), [recommendation systems](/wiki/Recommendation_systems\\n\"Recommendation systems\") (offered by [Netflix](/wiki/Netflix \"Netflix\"),\\n[YouTube](/wiki/YouTube \"YouTube\") or [Amazon](/wiki/Amazon_\\\\(company\\\\)\\n\"Amazon \\\\(company\\\\)\")), driving [internet traffic](/wiki/Internet_traffic\\n\"Internet traffic\"), [targeted\\nadvertising](/wiki/Marketing_and_artificial_intelligence \"Marketing and\\nartificial intelligence\") ([AdSense](/wiki/AdSense \"AdSense\"),\\n[Facebook](/wiki/Facebook \"Facebook\")), [virtual\\nassistants](/wiki/Virtual_assistant \"Virtual assistant\") (such as\\n[Siri](/wiki/Siri \"Siri\") or [Alexa](/wiki/Amazon_Alexa \"Amazon Alexa\")),\\n[autonomous vehicles](/wiki/Autonomous_vehicles \"Autonomous vehicles\")\\n(including [drones](/wiki/Unmanned_aerial_vehicle \"Unmanned aerial vehicle\"),\\n[ADAS](/wiki/Advanced_driver-assistance_system \"Advanced driver-assistance\\nsystem\") and [self-driving cars](/wiki/Self-driving_cars \"Self-driving\\ncars\")), [automatic language translation](/wiki/Automatic_language_translation\\n\"Automatic language translation\") ([Microsoft\\nTranslator](/wiki/Microsoft_Translator \"Microsoft Translator\"), [Google\\nTranslate](/wiki/Google_Translate \"Google Translate\")), [facial\\nrecognition](/wiki/Facial_recognition_system \"Facial recognition system\")\\n([Apple](/wiki/Apple_Computer \"Apple Computer\")\\'s [Face ID](/wiki/Face_ID\\n\"Face ID\") or [Microsoft](/wiki/Microsoft \"Microsoft\")\\'s\\n[DeepFace](/wiki/DeepFace \"DeepFace\") and [Google](/wiki/Google \"Google\")\\'s\\n[FaceNet](/wiki/FaceNet \"FaceNet\")) and [image labeling](/wiki/Image_labeling\\n\"Image labeling\") (used by [Facebook](/wiki/Facebook \"Facebook\"), Apple\\'s\\n[iPhoto](/wiki/IPhoto \"IPhoto\") and [TikTok](/wiki/TikTok \"TikTok\")). The\\ndeployment of AI may be overseen by a [Chief automation\\nofficer](/wiki/Chief_automation_officer \"Chief automation officer\") (CAO).\\n\\n### Health and medicine\\n\\nMain article: [Artificial intelligence in\\nhealthcare](/wiki/Artificial_intelligence_in_healthcare \"Artificial\\nintelligence in healthcare\")\\n\\nThe application of AI in [medicine](/wiki/Medicine \"Medicine\") and [medical\\nresearch](/wiki/Medical_research \"Medical research\") has the potential to\\nincrease patient care and quality of life.[130] Through the lens of the\\n[Hippocratic Oath](/wiki/Hippocratic_Oath \"Hippocratic Oath\"), medical\\nprofessionals are ethically compelled to use AI, if applications can more\\naccurately diagnose and treat patients.[131][132]\\n\\nFor medical research, AI is an important tool for processing and integrating\\n[big data](/wiki/Big_data \"Big data\"). This is particularly important for\\n[organoid](/wiki/Organoid \"Organoid\") and [tissue\\nengineering](/wiki/Tissue_engineering \"Tissue engineering\") development which\\nuse [microscopy](/wiki/Microscopy \"Microscopy\") imaging as a key technique in\\nfabrication.[133] It has been suggested that AI can overcome discrepancies in\\nfunding allocated to different fields of research.[133] New AI tools can\\ndeepen the understanding of biomedically relevant pathways. For example,\\n[AlphaFold 2](/wiki/AlphaFold_2 \"AlphaFold 2\") (2021) demonstrated the ability\\nto approximate, in hours rather than months, the 3D [structure of a\\nprotein](/wiki/Protein_structure \"Protein structure\").[134] In 2023, it was\\nreported that AI-guided drug discovery helped find a class of antibiotics\\ncapable of killing two different types of drug-resistant bacteria.[135] In\\n2024, researchers used machine learning to accelerate the search for\\n[Parkinson\\'s disease](/wiki/Parkinson%27s_disease \"Parkinson\\'s disease\") drug\\ntreatments. Their aim was to identify compounds that block the clumping, or\\naggregation, of [alpha-synuclein](/wiki/Alpha-synuclein \"Alpha-synuclein\")\\n(the protein that characterises Parkinson\\'s disease). They were able to speed\\nup the initial screening process ten-fold and reduce the cost by a thousand-\\nfold.[136][137]\\n\\n### Games\\n\\nMain article: [Game artificial\\nintelligence](/wiki/Game_artificial_intelligence \"Game artificial\\nintelligence\")\\n\\n[Game playing](/wiki/Game_AI \"Game AI\") programs have been used since the\\n1950s to demonstrate and test AI\\'s most advanced techniques.[138] [Deep\\nBlue](/wiki/IBM_Deep_Blue \"IBM Deep Blue\") became the first computer chess-\\nplaying system to beat a reigning world chess champion, [Garry\\nKasparov](/wiki/Garry_Kasparov \"Garry Kasparov\"), on 11 May 1997.[139] In\\n2011, in a _[Jeopardy!](/wiki/Jeopardy! \"Jeopardy!\")_ [quiz\\nshow](/wiki/Quiz_show \"Quiz show\") exhibition match, [IBM](/wiki/IBM \"IBM\")\\'s\\n[question answering system](/wiki/Question_answering_system \"Question\\nanswering system\"), [Watson](/wiki/Watson_\\\\(artificial_intelligence_software\\\\)\\n\"Watson \\\\(artificial intelligence software\\\\)\"), defeated the two greatest\\n_Jeopardy!_ champions, [Brad Rutter](/wiki/Brad_Rutter \"Brad Rutter\") and [Ken\\nJennings](/wiki/Ken_Jennings \"Ken Jennings\"), by a significant margin.[140] In\\nMarch 2016, [AlphaGo](/wiki/AlphaGo \"AlphaGo\") won 4 out of 5 games of\\n[Go](/wiki/Go_\\\\(game\\\\) \"Go \\\\(game\\\\)\") in a match with Go champion [Lee\\nSedol](/wiki/Lee_Sedol \"Lee Sedol\"), becoming the first [computer\\nGo](/wiki/Computer_Go \"Computer Go\")-playing system to beat a professional Go\\nplayer without [handicaps](/wiki/Go_handicaps \"Go handicaps\"). Then, in 2017,\\nit [defeated Ke Jie](/wiki/AlphaGo_versus_Ke_Jie \"AlphaGo versus Ke Jie\"), who\\nwas the best Go player in the world.[141] Other programs handle [imperfect-\\ninformation](/wiki/Imperfect_information \"Imperfect information\") games, such\\nas the [poker](/wiki/Poker \"Poker\")-playing program\\n[Pluribus](/wiki/Pluribus_\\\\(poker_bot\\\\) \"Pluribus \\\\(poker bot\\\\)\").[142]\\n[DeepMind](/wiki/DeepMind \"DeepMind\") developed increasingly generalistic\\n[reinforcement learning](/wiki/Reinforcement_learning \"Reinforcement\\nlearning\") models, such as with [MuZero](/wiki/MuZero \"MuZero\"), which could\\nbe trained to play chess, Go, or [Atari](/wiki/Atari \"Atari\") games.[143] In\\n2019, DeepMind\\'s AlphaStar achieved grandmaster level in [StarCraft\\nII](/wiki/StarCraft_II \"StarCraft II\"), a particularly challenging real-time\\nstrategy game that involves incomplete knowledge of what happens on the\\nmap.[144] In 2021, an AI agent competed in a PlayStation [Gran\\nTurismo](/wiki/Gran_Turismo_\\\\(series\\\\) \"Gran Turismo \\\\(series\\\\)\") competition,\\nwinning against four of the world\\'s best Gran Turismo drivers using deep\\nreinforcement learning.[145] In 2024, Google DeepMind introduced SIMA, a type\\nof AI capable of autonomously playing nine previously unseen [open-\\nworld](/wiki/Open-world \"Open-world\") video games by observing screen output,\\nas well as executing short, specific tasks in response to natural language\\ninstructions.[146]\\n\\n### Mathematics\\n\\nIn mathematics, special forms of formal step-by-step\\n[reasoning](/wiki/Automatic_reasoning \"Automatic reasoning\") are used. In\\ncontrast, LLMs such as _[GPT-4](/wiki/GPT-4 \"GPT-4\") Turbo_, _[Gemini\\nUltra](/wiki/Gemini_\\\\(chatbot\\\\) \"Gemini \\\\(chatbot\\\\)\")_ , _[Claude\\nOpus](/wiki/Claude_\\\\(language_model\\\\) \"Claude \\\\(language model\\\\)\")_ ,\\n_[LLaMa-2](/wiki/Llama_\\\\(language_model\\\\) \"Llama \\\\(language model\\\\)\")_ or\\n_[Mistral Large](/wiki/Mistral_AI \"Mistral AI\")_ are working with\\nprobabilistic models, which can produce wrong answers in the form of\\n[hallucinations](/wiki/Hallucination_\\\\(artificial_intelligence\\\\)\\n\"Hallucination \\\\(artificial intelligence\\\\)\"). Therefore, they need not only a\\nlarge database of mathematical problems to learn from but also methods such as\\n[supervised](/wiki/Supervised_learning \"Supervised learning\") [fine-\\ntuning](/wiki/Fine-tuning_\\\\(deep_learning\\\\) \"Fine-tuning \\\\(deep learning\\\\)\")\\nor trained [classifiers](/wiki/Statistical_classification \"Statistical\\nclassification\") with human-annotated data to improve answers for new problems\\nand learn from corrections.[147] A 2024 study showed that the performance of\\nsome language models for reasoning capabilities in solving math problems not\\nincluded in their training data was low, even for problems with only minor\\ndeviations from trained data.[148]\\n\\nAlternatively, dedicated models for mathematic problem solving with higher\\nprecision for the outcome including proof of theorems have been developed such\\nas _Alpha Tensor_ , _Alpha Geometry_ and _Alpha Proof_ all from [Google\\nDeepMind](/wiki/Google_DeepMind \"Google DeepMind\"),[149] _Llemma_ from\\neleuther[150] or _Julius_.[151]\\n\\nWhen natural language is used to describe mathematical problems, converters\\ntransform such prompts into a formal language such as\\n[Lean](/wiki/Lean_\\\\(proof_assistant\\\\) \"Lean \\\\(proof assistant\\\\)\") to define\\nmathematic tasks.\\n\\nSome models have been developed to solve challenging problems and reach good\\nresults in benchmark tests, others to serve as educational tools in\\nmathematics.[152]\\n\\n### Finance\\n\\nFinance is one of the fastest growing sectors where applied AI tools are being\\ndeployed: from retail online banking to investment advice and insurance, where\\nautomated \"robot advisers\" have been in use for some years.[153]\\n\\n[World Pensions](/wiki/World_Pensions_%26_Investments_Forum \"World Pensions &\\nInvestments Forum\") experts like Nicolas Firzli insist it may be too early to\\nsee the emergence of highly innovative AI-informed financial products and\\nservices: \"the deployment of AI tools will simply further automatise things:\\ndestroying tens of thousands of jobs in banking, financial planning, and\\npension advice in the process, but I\\'m not sure it will unleash a new wave of\\n[e.g., sophisticated] pension innovation.\"[154]\\n\\n### Military\\n\\nMain article: [Military artificial\\nintelligence](/wiki/Military_artificial_intelligence \"Military artificial\\nintelligence\")\\n\\nVarious countries are deploying AI military applications.[155] The main\\napplications enhance [command and control](/wiki/Command_and_control \"Command\\nand control\"), communications, sensors, integration and interoperability.[156]\\nResearch is targeting intelligence collection and analysis, logistics, cyber\\noperations, information operations, and semiautonomous and [autonomous\\nvehicles](/wiki/Autonomous_vehicles \"Autonomous vehicles\").[155] AI\\ntechnologies enable coordination of sensors and effectors, threat detection\\nand identification, marking of enemy positions, [target\\nacquisition](/wiki/Target_acquisition \"Target acquisition\"), coordination and\\ndeconfliction of distributed [Joint\\nFires](/wiki/Forward_observers_in_the_U.S._military \"Forward observers in the\\nU.S. military\") between networked combat vehicles involving manned and\\nunmanned teams.[156] AI was incorporated into military operations in Iraq and\\nSyria.[155]\\n\\nIn November 2023, US Vice President [Kamala Harris](/wiki/Kamala_Harris\\n\"Kamala Harris\") disclosed a declaration signed by 31 nations to set\\nguardrails for the military use of AI. The commitments include using legal\\nreviews to ensure the compliance of military AI with international laws, and\\nbeing cautious and transparent in the development of this technology.[157]\\n\\n### Generative AI\\n\\nMain article: [Generative artificial\\nintelligence](/wiki/Generative_artificial_intelligence \"Generative artificial\\nintelligence\")\\n\\n[![](//upload.wikimedia.org/wikipedia/commons/thumb/f/ff/Vincent_van_Gogh_in_watercolour.png/220px-\\nVincent_van_Gogh_in_watercolour.png)](/wiki/File:Vincent_van_Gogh_in_watercolour.png)[Vincent\\nvan Gogh](/wiki/Vincent_van_Gogh \"Vincent van Gogh\") in watercolour created by\\ngenerative AI software\\n\\nIn the early 2020s, [generative AI](/wiki/Generative_AI \"Generative AI\")\\ngained widespread prominence. GenAI is AI capable of generating text, images,\\nvideos, or other data using [generative models](/wiki/Generative_model\\n\"Generative model\"),[158][159] often in response to\\n[prompts](/wiki/Prompt_\\\\(natural_language\\\\) \"Prompt \\\\(natural\\nlanguage\\\\)\").[160][161]\\n\\nIn March 2023, 58% of U.S. adults had heard about [ChatGPT](/wiki/ChatGPT\\n\"ChatGPT\") and 14% had tried it.[162] The increasing realism and ease-of-use\\nof AI-based [text-to-image](/wiki/Text-to-image \"Text-to-image\") generators\\nsuch as [Midjourney](/wiki/Midjourney \"Midjourney\"), [DALL-E](/wiki/DALL-E\\n\"DALL-E\"), and [Stable Diffusion](/wiki/Stable_Diffusion \"Stable Diffusion\")\\nsparked a trend of [viral](/wiki/Viral_phenomenon \"Viral phenomenon\") AI-\\ngenerated photos. Widespread attention was gained by a fake photo of [Pope\\nFrancis](/wiki/Pope_Francis \"Pope Francis\") wearing a white puffer coat, the\\nfictional arrest of [Donald Trump](/wiki/Donald_Trump \"Donald Trump\"), and a\\nhoax of an attack on the [Pentagon](/wiki/The_Pentagon \"The Pentagon\"), as\\nwell as the usage in professional creative arts.[163][164]\\n\\n### Agents\\n\\nArtificial intelligent (AI) agents are software entities designed to perceive\\ntheir environment, make decisions, and take actions autonomously to achieve\\nspecific goals. These agents can interact with users, their environment, or\\nother agents. AI agents are used in various applications, including [virtual\\nassistants](/wiki/Virtual_assistant \"Virtual assistant\"),\\n[chatbots](/wiki/Chatbots \"Chatbots\"), [autonomous\\nvehicles](/wiki/Autonomous_vehicles \"Autonomous vehicles\"), [game-playing\\nsystems](/wiki/Video_game_console \"Video game console\"), and [industrial\\nrobotics](/wiki/Industrial_robotics \"Industrial robotics\"). AI agents operate\\nwithin the constraints of their programming, available computational\\nresources, and hardware limitations. This means they are restricted to\\nperforming tasks within their defined scope and have finite memory and\\nprocessing capabilities. In real-world applications, AI agents often face time\\nconstraints for decision-making and action execution. Many AI agents\\nincorporate learning algorithms, enabling them to improve their performance\\nover time through experience or training. Using machine learning, AI agents\\ncan adapt to new situations and optimise their behaviour for their designated\\ntasks.[165][166][167]\\n\\n### Other industry-specific tasks\\n\\nThere are also thousands of successful AI applications used to solve specific\\nproblems for specific industries or institutions. In a 2017 survey, one in\\nfive companies reported having incorporated \"AI\" in some offerings or\\nprocesses.[168] A few examples are [energy storage](/wiki/Energy_storage\\n\"Energy storage\"), medical diagnosis, military logistics, applications that\\npredict the result of judicial decisions, [foreign\\npolicy](/wiki/Foreign_policy \"Foreign policy\"), or supply chain management.\\n\\nAI applications for evacuation and [disaster](/wiki/Disaster \"Disaster\")\\nmanagement are growing. AI has been used to investigate if and how people\\nevacuated in large scale and small scale evacuations using historical data\\nfrom GPS, videos or social media. Further, AI can provide real time\\ninformation on the real time evacuation conditions.[169][170][171]\\n\\nIn agriculture, AI has helped farmers identify areas that need irrigation,\\nfertilization, pesticide treatments or increasing yield. Agronomists use AI to\\nconduct research and development. AI has been used to predict the ripening\\ntime for crops such as tomatoes, monitor soil moisture, operate agricultural\\nrobots, conduct [predictive analytics](/wiki/Predictive_analytics \"Predictive\\nanalytics\"), classify livestock pig call emotions, automate greenhouses,\\ndetect diseases and pests, and save water.\\n\\nArtificial intelligence is used in astronomy to analyze increasing amounts of\\navailable data and applications, mainly for \"classification, regression,\\nclustering, forecasting, generation, discovery, and the development of new\\nscientific insights.\" For example, it is used for discovering exoplanets,\\nforecasting solar activity, and distinguishing between signals and\\ninstrumental effects in gravitational wave astronomy. Additionally, it could\\nbe used for activities in space, such as space exploration, including the\\nanalysis of data from space missions, real-time science decisions of\\nspacecraft, space debris avoidance, and more autonomous operation.\\n\\nDuring the [2024 Indian elections](/wiki/2024_Indian_general_election \"2024\\nIndian general election\"), US$50 millions was spent on authorized AI-generated\\ncontent, notably by creating [deepfakes](/wiki/Deepfake \"Deepfake\") of allied\\n(including sometimes deceased) politicians to better engage with voters, and\\nby translating speeches to various local languages.[172]\\n\\n## Ethics\\n\\nMain article: [Ethics of artificial\\nintelligence](/wiki/Ethics_of_artificial_intelligence \"Ethics of artificial\\nintelligence\")\\n\\nAI has potential benefits and potential risks.[173] AI may be able to advance\\nscience and find solutions for serious problems: [Demis\\nHassabis](/wiki/Demis_Hassabis \"Demis Hassabis\") of [Deep Mind](/wiki/DeepMind\\n\"DeepMind\") hopes to \"solve intelligence, and then use that to solve\\neverything else\".[174] However, as the use of AI has become widespread,\\nseveral unintended consequences and risks have been identified.[175] In-\\nproduction systems can sometimes not factor ethics and bias into their AI\\ntraining processes, especially when the AI algorithms are inherently\\nunexplainable in deep learning.[176]\\n\\n### Risks and harm\\n\\n#### Privacy and copyright\\n\\nFurther information: [Information privacy](/wiki/Information_privacy\\n\"Information privacy\") and [Artificial intelligence and\\ncopyright](/wiki/Artificial_intelligence_and_copyright \"Artificial\\nintelligence and copyright\")\\n\\nMachine learning algorithms require large amounts of data. The techniques used\\nto acquire this data have raised concerns about [privacy](/wiki/Privacy\\n\"Privacy\"), [surveillance](/wiki/Surveillance \"Surveillance\") and\\n[copyright](/wiki/Copyright \"Copyright\").\\n\\nAI-powered devices and services, such as virtual assistants and IoT products,\\ncontinuously collect personal information, raising concerns about intrusive\\ndata gathering and unauthorized access by third parties. The loss of privacy\\nis further exacerbated by AI\\'s ability to process and combine vast amounts of\\ndata, potentially leading to a surveillance society where individual\\nactivities are constantly monitored and analyzed without adequate safeguards\\nor transparency.\\n\\nSensitive user data collected may include online activity records, geolocation\\ndata, video or audio.[177] For example, in order to build [speech\\nrecognition](/wiki/Speech_recognition \"Speech recognition\") algorithms,\\n[Amazon](/wiki/Amazon_\\\\(company\\\\) \"Amazon \\\\(company\\\\)\") has recorded millions\\nof private conversations and allowed [temporary\\nworkers](/wiki/Temporary_worker \"Temporary worker\") to listen to and\\ntranscribe some of them.[178] Opinions about this widespread surveillance\\nrange from those who see it as a [necessary evil](/wiki/Necessary_evil\\n\"Necessary evil\") to those for whom it is clearly [unethical](/wiki/Unethical\\n\"Unethical\") and a violation of the [right to privacy](/wiki/Right_to_privacy\\n\"Right to privacy\").[179]\\n\\nAI developers argue that this is the only way to deliver valuable\\napplications. and have developed several techniques that attempt to preserve\\nprivacy while still obtaining the data, such as [data\\naggregation](/wiki/Data_aggregation \"Data aggregation\"), [de-\\nidentification](/wiki/De-identification \"De-identification\") and [differential\\nprivacy](/wiki/Differential_privacy \"Differential privacy\").[180] Since 2016,\\nsome privacy experts, such as [Cynthia Dwork](/wiki/Cynthia_Dwork \"Cynthia\\nDwork\"), have begun to view privacy in terms of\\n[fairness](/wiki/Fairness_\\\\(machine_learning\\\\) \"Fairness \\\\(machine\\nlearning\\\\)\"). [Brian Christian](/wiki/Brian_Christian \"Brian Christian\") wrote\\nthat experts have pivoted \"from the question of \\'what they know\\' to the\\nquestion of \\'what they\\'re doing with it\\'.\"[181]\\n\\nGenerative AI is often trained on unlicensed copyrighted works, including in\\ndomains such as images or computer code; the output is then used under the\\nrationale of \"[fair use](/wiki/Fair_use \"Fair use\")\". Experts disagree about\\nhow well and under what circumstances this rationale will hold up in courts of\\nlaw; relevant factors may include \"the purpose and character of the use of the\\ncopyrighted work\" and \"the effect upon the potential market for the\\ncopyrighted work\".[182][183] Website owners who do not wish to have their\\ncontent scraped can indicate it in a \"[robots.txt](/wiki/Robots.txt\\n\"Robots.txt\")\" file.[184] In 2023, leading authors (including [John\\nGrisham](/wiki/John_Grisham \"John Grisham\") and [Jonathan\\nFranzen](/wiki/Jonathan_Franzen \"Jonathan Franzen\")) sued AI companies for\\nusing their work to train generative AI.[185][186] Another discussed approach\\nis to envision a separate _[sui generis](/wiki/Sui_generis \"Sui generis\")_\\nsystem of protection for creations generated by AI to ensure fair attribution\\nand compensation for human authors.[187]\\n\\n#### Dominance by tech giants\\n\\nThe commercial AI scene is dominated by [Big Tech](/wiki/Big_Tech \"Big Tech\")\\ncompanies such as [Alphabet Inc.](/wiki/Alphabet_Inc. \"Alphabet Inc.\"),\\n[Amazon](/wiki/Amazon_\\\\(company\\\\) \"Amazon \\\\(company\\\\)\"), [Apple\\nInc.](/wiki/Apple_Inc. \"Apple Inc.\"), [Meta Platforms](/wiki/Meta_Platforms\\n\"Meta Platforms\"), and [Microsoft](/wiki/Microsoft\\n\"Microsoft\").[188][189][190] Some of these players already own the vast\\nmajority of existing [cloud infrastructure](/wiki/Cloud_computing \"Cloud\\ncomputing\") and [computing](/wiki/Computing \"Computing\") power from [data\\ncenters](/wiki/Data_center \"Data center\"), allowing them to entrench further\\nin the marketplace.[191][192]\\n\\n#### Substantial power needs and other environmental impacts\\n\\nSee also: [Environmental impacts of artificial\\nintelligence](/wiki/Environmental_impacts_of_artificial_intelligence\\n\"Environmental impacts of artificial intelligence\")\\n\\nIn January 2024, the [International Energy\\nAgency](/wiki/International_Energy_Agency \"International Energy Agency\") (IEA)\\nreleased _Electricity 2024, Analysis and Forecast to 2026_ , forecasting\\nelectric power use.[193] This is the first IEA report to make projections for\\ndata centers and power consumption for artificial intelligence and\\ncryptocurrency. The report states that power demand for these uses might\\ndouble by 2026, with additional electric power usage equal to electricity used\\nby the whole Japanese nation.[194]\\n\\nProdigious power consumption by AI is responsible for the growth of fossil\\nfuels use, and might delay closings of obsolete, carbon-emitting coal energy\\nfacilities. There is a feverish rise in the construction of data centers\\nthroughout the US, making large technology firms (e.g., Microsoft, Meta,\\nGoogle, Amazon) into voracious consumers of electric power. Projected electric\\nconsumption is so immense that there is concern that it will be fulfilled no\\nmatter the source. A ChatGPT search involves the use of 10 times the\\nelectrical energy as a Google search. The large firms are in haste to find\\npower sources – from nuclear energy to geothermal to fusion. The tech firms\\nargue that – in the long view – AI will be eventually kinder to the\\nenvironment, but they need the energy now. AI makes the power grid more\\nefficient and \"intelligent\", will assist in the growth of nuclear power, and\\ntrack overall carbon emissions, according to technology firms.[195]\\n\\nA 2024 [Goldman Sachs](/wiki/Goldman_Sachs \"Goldman Sachs\") Research Paper,\\n_AI Data Centers and the Coming US Power Demand Surge_ , found \"US power\\ndemand (is) likely to experience growth not seen in a generation....\" and\\nforecasts that, by 2030, US data centers will consume 8% of US power, as\\nopposed to 3% in 2022, presaging growth for the electrical power generation\\nindustry by a variety of means.[196] Data centers\\' need for more and more\\nelectrical power is such that they might max out the electrical grid. The Big\\nTech companies counter that AI can be used to maximize the utilization of the\\ngrid by all.[197]\\n\\nIn 2024, the _Wall Street Journal_ reported that big AI companies have begun\\nnegotiations with the US nuclear power providers to provide electricity to the\\ndata centers. In March 2024 Amazon purchased a Pennsylvania nuclear-powered\\ndata center for $650 Million (US).[198]\\n\\nIn September 2024, [Microsoft](/wiki/Microsoft \"Microsoft\") announced an\\nagreement with [Constellation Energy](/wiki/Constellation_Energy\\n\"Constellation Energy\") to re-open the [Three Mile\\nIsland](/wiki/Three_Mile_Island \"Three Mile Island\") nuclear power plant to\\nprovide Microsoft with 100% of all electric power produced by the plant for 20\\nyears. Reopening the plant, which suffered a partial nuclear meltdown of its\\nUnit 2 reactor in 1979, will require Constellation to get through strict\\nregulatory processes which will include extensive safety scrutiny from the US\\n[Nuclear Regulatory Commission](/wiki/Nuclear_Regulatory_Commission \"Nuclear\\nRegulatory Commission\"). If approved (this will be the first ever US re-\\ncommissioning of a nuclear plant), over 835 megawatts of power – enough for\\n800,000 homes – of energy will be produced. The cost for re-opening and\\nupgrading is estimated at $1.6 billion (US) and is dependent on tax breaks for\\nnuclear power contained in the 2022 US [Inflation Reduction\\nAct](/wiki/Inflation_Reduction_Act \"Inflation Reduction Act\").[199] The US\\ngovernment and the state of Michigan are investing almost $2 billion (US) to\\nreopen the [Palisades Nuclear](/wiki/Palisades_Nuclear_Generating_Station\\n\"Palisades Nuclear Generating Station\") reactor on Lake Michigan. Closed since\\n2022, the plant is planned to be reopened in October 2025. The Three Mile\\nIsland facility will be renamed the Crane Clean Energy Center after Chris\\nCrane, a nuclear proponent and former CEO of [Exelon](/wiki/Exelon \"Exelon\")\\nwho was responsible for Exelon spinoff of Constellation.[200]\\n\\n#### Misinformation\\n\\nSee also: [YouTube § Moderation and offensive\\ncontent](/wiki/YouTube#Moderation_and_offensive_content \"YouTube\")\\n\\n[YouTube](/wiki/YouTube \"YouTube\"), [Facebook](/wiki/Facebook \"Facebook\") and\\nothers use [recommender systems](/wiki/Recommender_system \"Recommender\\nsystem\") to guide users to more content. These AI programs were given the goal\\nof [maximizing](/wiki/Mathematical_optimization \"Mathematical optimization\")\\nuser engagement (that is, the only goal was to keep people watching). The AI\\nlearned that users tended to choose [misinformation](/wiki/Misinformation\\n\"Misinformation\"), [conspiracy theories](/wiki/Conspiracy_theories \"Conspiracy\\ntheories\"), and extreme [partisan](/wiki/Partisan_\\\\(politics\\\\) \"Partisan\\n\\\\(politics\\\\)\") content, and, to keep them watching, the AI recommended more of\\nit. Users also tended to watch more content on the same subject, so the AI led\\npeople into [filter bubbles](/wiki/Filter_bubbles \"Filter bubbles\") where they\\nreceived multiple versions of the same misinformation.[201] This convinced\\nmany users that the misinformation was true, and ultimately undermined trust\\nin institutions, the media and the government.[202] The AI program had\\ncorrectly learned to maximize its goal, but the result was harmful to society.\\nAfter the U.S. election in 2016, major technology companies took steps to\\nmitigate the problem [_[citation needed](/wiki/Wikipedia:Citation_needed\\n\"Wikipedia:Citation needed\")_].\\n\\nIn 2022, [generative AI](/wiki/Generative_AI \"Generative AI\") began to create\\nimages, audio, video and text that are indistinguishable from real\\nphotographs, recordings, films, or human writing. It is possible for bad\\nactors to use this technology to create massive amounts of misinformation or\\npropaganda.[203] AI pioneer [Geoffrey Hinton](/wiki/Geoffrey_Hinton \"Geoffrey\\nHinton\") expressed concern about AI enabling \"authoritarian leaders to\\nmanipulate their electorates\" on a large scale, among other risks.[204]\\n\\n#### Algorithmic bias and fairness\\n\\nMain articles: [Algorithmic bias](/wiki/Algorithmic_bias \"Algorithmic bias\")\\nand [Fairness (machine learning)](/wiki/Fairness_\\\\(machine_learning\\\\)\\n\"Fairness \\\\(machine learning\\\\)\")\\n\\nMachine learning applications will be [biased](/wiki/Algorithmic_bias\\n\"Algorithmic bias\")[k] if they learn from biased data.[206] The developers may\\nnot be aware that the bias exists.[207] Bias can be introduced by the way\\n[training data](/wiki/Training_data \"Training data\") is selected and by the\\nway a model is deployed.[208][206] If a biased algorithm is used to make\\ndecisions that can seriously [harm](/wiki/Harm \"Harm\") people (as it can in\\n[medicine](/wiki/Health_equity \"Health equity\"), [finance](/wiki/Credit_rating\\n\"Credit rating\"), [recruitment](/wiki/Recruitment \"Recruitment\"),\\n[housing](/wiki/Public_housing \"Public housing\") or [policing](/wiki/Policing\\n\"Policing\")) then the algorithm may cause\\n[discrimination](/wiki/Discrimination \"Discrimination\").[209] The field of\\n[fairness](/wiki/Fairness_\\\\(machine_learning\\\\) \"Fairness \\\\(machine\\nlearning\\\\)\") studies how to prevent harms from algorithmic biases.\\n\\nOn June 28, 2015, [Google Photos](/wiki/Google_Photos \"Google Photos\")\\'s new\\nimage labeling feature mistakenly identified Jacky Alcine and a friend as\\n\"gorillas\" because they were black. The system was trained on a dataset that\\ncontained very few images of black people,[210] a problem called \"sample size\\ndisparity\".[211] Google \"fixed\" this problem by preventing the system from\\nlabelling _anything_ as a \"gorilla\". Eight years later, in 2023, Google Photos\\nstill could not identify a gorilla, and neither could similar products from\\nApple, Facebook, Microsoft and Amazon.[212]\\n\\n[COMPAS](/wiki/COMPAS_\\\\(software\\\\) \"COMPAS \\\\(software\\\\)\") is a commercial\\nprogram widely used by [U.S. courts](/wiki/U.S._court \"U.S. court\") to assess\\nthe likelihood of a [defendant](/wiki/Defendant \"Defendant\") becoming a\\n[recidivist](/wiki/Recidivist \"Recidivist\"). In 2016, [Julia\\nAngwin](/wiki/Julia_Angwin \"Julia Angwin\") at [ProPublica](/wiki/ProPublica\\n\"ProPublica\") discovered that COMPAS exhibited racial bias, despite the fact\\nthat the program was not told the races of the defendants. Although the error\\nrate for both whites and blacks was calibrated equal at exactly 61%, the\\nerrors for each race were different—the system consistently overestimated the\\nchance that a black person would re-offend and would underestimate the chance\\nthat a white person would not re-offend.[213] In 2017, several researchers[l]\\nshowed that it was mathematically impossible for COMPAS to accommodate all\\npossible measures of fairness when the base rates of re-offense were different\\nfor whites and blacks in the data.[215]\\n\\nA program can make biased decisions even if the data does not explicitly\\nmention a problematic feature (such as \"race\" or \"gender\"). The feature will\\ncorrelate with other features (like \"address\", \"shopping history\" or \"first\\nname\"), and the program will make the same decisions based on these features\\nas it would on \"race\" or \"gender\".[216] Moritz Hardt said \"the most robust\\nfact in this research area is that fairness through blindness doesn\\'t\\nwork.\"[217]\\n\\nCriticism of COMPAS highlighted that machine learning models are designed to\\nmake \"predictions\" that are only valid if we assume that the future will\\nresemble the past. If they are trained on data that includes the results of\\nracist decisions in the past, machine learning models must predict that racist\\ndecisions will be made in the future. If an application then uses these\\npredictions as _recommendations_ , some of these \"recommendations\" will likely\\nbe racist.[218] Thus, machine learning is not well suited to help make\\ndecisions in areas where there is hope that the future will be _better_ than\\nthe past. It is descriptive rather than prescriptive.[m]\\n\\nBias and unfairness may go undetected because the developers are\\noverwhelmingly white and male: among AI engineers, about 4% are black and 20%\\nare women.[211]\\n\\nThere are various conflicting definitions and mathematical models of fairness.\\nThese notions depend on ethical assumptions, and are influenced by beliefs\\nabout society. One broad category is [distributive\\nfairness](/wiki/Distributive_justice \"Distributive justice\"), which focuses on\\nthe outcomes, often identifying groups and seeking to compensate for\\nstatistical disparities. Representational fairness tries to ensure that AI\\nsystems do not reinforce negative [stereotypes](/wiki/Stereotype \"Stereotype\")\\nor render certain groups invisible. Procedural fairness focuses on the\\ndecision process rather than the outcome. The most relevant notions of\\nfairness may depend on the context, notably the type of AI application and the\\nstakeholders. The subjectivity in the notions of bias and fairness makes it\\ndifficult for companies to operationalize them. Having access to sensitive\\nattributes such as race or gender is also considered by many AI ethicists to\\nbe necessary in order to compensate for biases, but it may conflict with\\n[anti-discrimination laws](/wiki/Anti-discrimination_law \"Anti-discrimination\\nlaw\").[205]\\n\\nAt its 2022 [Conference on Fairness, Accountability, and\\nTransparency](/wiki/ACM_Conference_on_Fairness,_Accountability,_and_Transparency\\n\"ACM Conference on Fairness, Accountability, and Transparency\") (ACM FAccT\\n2022), the [Association for Computing\\nMachinery](/wiki/Association_for_Computing_Machinery \"Association for\\nComputing Machinery\"), in Seoul, South Korea, presented and published findings\\nthat recommend that until AI and robotics systems are demonstrated to be free\\nof bias mistakes, they are unsafe, and the use of self-learning neural\\nnetworks trained on vast, unregulated sources of flawed internet data should\\nbe curtailed.[_[dubious](/wiki/Wikipedia:Accuracy_dispute#Disputed_statement\\n\"Wikipedia:Accuracy dispute\") –\\n[discuss](/wiki/Talk:Artificial_intelligence#Dubious \"Talk:Artificial\\nintelligence\")_][220]\\n\\n#### Lack of transparency\\n\\nSee also: [Explainable AI](/wiki/Explainable_AI \"Explainable AI\"),\\n[Algorithmic transparency](/wiki/Algorithmic_transparency \"Algorithmic\\ntransparency\"), and [Right to explanation](/wiki/Right_to_explanation \"Right\\nto explanation\")\\n\\nMany AI systems are so complex that their designers cannot explain how they\\nreach their decisions.[221] Particularly with [deep neural\\nnetworks](/wiki/Deep_neural_networks \"Deep neural networks\"), in which there\\nare a large amount of non-[linear](/wiki/Linear \"Linear\") relationships\\nbetween inputs and outputs. But some popular explainability techniques\\nexist.[222]\\n\\nIt is impossible to be certain that a program is operating correctly if no one\\nknows how exactly it works. There have been many cases where a machine\\nlearning program passed rigorous tests, but nevertheless learned something\\ndifferent than what the programmers intended. For example, a system that could\\nidentify skin diseases better than medical professionals was found to actually\\nhave a strong tendency to classify images with a [ruler](/wiki/Ruler \"Ruler\")\\nas \"cancerous\", because pictures of malignancies typically include a ruler to\\nshow the scale.[223] Another machine learning system designed to help\\neffectively allocate medical resources was found to classify patients with\\nasthma as being at \"low risk\" of dying from pneumonia. Having asthma is\\nactually a severe risk factor, but since the patients having asthma would\\nusually get much more medical care, they were relatively unlikely to die\\naccording to the training data. The correlation between asthma and low risk of\\ndying from pneumonia was real, but misleading.[224]\\n\\nPeople who have been harmed by an algorithm\\'s decision have a right to an\\nexplanation.[225] Doctors, for example, are expected to clearly and completely\\nexplain to their colleagues the reasoning behind any decision they make. Early\\ndrafts of the European Union\\'s [General Data Protection\\nRegulation](/wiki/General_Data_Protection_Regulation \"General Data Protection\\nRegulation\") in 2016 included an explicit statement that this right exists.[n]\\nIndustry experts noted that this is an unsolved problem with no solution in\\nsight. Regulators argued that nevertheless the harm is real: if the problem\\nhas no solution, the tools should not be used.[226]\\n\\n[DARPA](/wiki/DARPA \"DARPA\") established the\\n[XAI](/wiki/Explainable_Artificial_Intelligence \"Explainable Artificial\\nIntelligence\") (\"Explainable Artificial Intelligence\") program in 2014 to try\\nto solve these problems.[227]\\n\\nSeveral approaches aim to address the transparency problem. SHAP enables to\\nvisualise the contribution of each feature to the output.[228] LIME can\\nlocally approximate a model\\'s outputs with a simpler, interpretable\\nmodel.[229] [Multitask learning](/wiki/Multitask_learning \"Multitask\\nlearning\") provides a large number of outputs in addition to the target\\nclassification. These other outputs can help developers deduce what the\\nnetwork has learned.[230] [Deconvolution](/wiki/Deconvolution\\n\"Deconvolution\"), [DeepDream](/wiki/DeepDream \"DeepDream\") and other\\n[generative](/wiki/Generative_AI \"Generative AI\") methods can allow developers\\nto see what different layers of a deep network for computer vision have\\nlearned, and produce output that can suggest what the network is\\nlearning.[231] For [generative pre-trained transformers](/wiki/Generative_pre-\\ntrained_transformer \"Generative pre-trained transformer\"),\\n[Anthropic](/wiki/Anthropic \"Anthropic\") developed a technique based on\\n[dictionary learning](/wiki/Dictionary_learning \"Dictionary learning\") that\\nassociates patterns of neuron activations with human-understandable\\nconcepts.[232]\\n\\n#### Bad actors and weaponized AI\\n\\nMain articles: [Lethal autonomous weapon](/wiki/Lethal_autonomous_weapon\\n\"Lethal autonomous weapon\"), [Artificial intelligence arms\\nrace](/wiki/Artificial_intelligence_arms_race \"Artificial intelligence arms\\nrace\"), and [AI safety](/wiki/AI_safety \"AI safety\")\\n\\nArtificial intelligence provides a number of tools that are useful to [bad\\nactors](/wiki/Bad_actor \"Bad actor\"), such as [authoritarian\\ngovernments](/wiki/Authoritarian \"Authoritarian\"),\\n[terrorists](/wiki/Terrorist \"Terrorist\"), [criminals](/wiki/Criminals\\n\"Criminals\") or [rogue states](/wiki/Rogue_states \"Rogue states\").\\n\\nA lethal autonomous weapon is a machine that locates, selects and engages\\nhuman targets without human supervision.[o] Widely available AI tools can be\\nused by bad actors to develop inexpensive autonomous weapons and, if produced\\nat scale, they are potentially [weapons of mass\\ndestruction](/wiki/Weapons_of_mass_destruction \"Weapons of mass\\ndestruction\").[234] Even when used in conventional warfare, it is unlikely\\nthat they will be unable to reliably choose targets and could potentially\\n[kill an innocent person](/wiki/Murder \"Murder\").[234] In 2014, 30 nations\\n(including China) supported a ban on autonomous weapons under the [United\\nNations](/wiki/United_Nations \"United Nations\")\\' [Convention on Certain\\nConventional Weapons](/wiki/Convention_on_Certain_Conventional_Weapons\\n\"Convention on Certain Conventional Weapons\"), however the [United\\nStates](/wiki/United_States \"United States\") and others disagreed.[235] By\\n2015, over fifty countries were reported to be researching battlefield\\nrobots.[236]\\n\\nAI tools make it easier for [authoritarian governments](/wiki/Authoritarian\\n\"Authoritarian\") to efficiently control their citizens in several ways.\\n[Face](/wiki/Facial_recognition_system \"Facial recognition system\") and [voice\\nrecognition](/wiki/Speaker_recognition \"Speaker recognition\") allow widespread\\n[surveillance](/wiki/Surveillance \"Surveillance\"). [Machine\\nlearning](/wiki/Machine_learning \"Machine learning\"), operating this data, can\\n[classify](/wiki/Classifier_\\\\(machine_learning\\\\) \"Classifier \\\\(machine\\nlearning\\\\)\") potential enemies of the state and prevent them from hiding.\\n[Recommendation systems](/wiki/Recommendation_systems \"Recommendation\\nsystems\") can precisely target [propaganda](/wiki/Propaganda \"Propaganda\") and\\n[misinformation](/wiki/Misinformation \"Misinformation\") for maximum effect.\\n[Deepfakes](/wiki/Deepfakes \"Deepfakes\") and [generative\\nAI](/wiki/Generative_AI \"Generative AI\") aid in producing misinformation.\\nAdvanced AI can make authoritarian [centralized decision\\nmaking](/wiki/Technocracy \"Technocracy\") more competitive than liberal and\\ndecentralized systems such as [markets](/wiki/Market_\\\\(economics\\\\) \"Market\\n\\\\(economics\\\\)\"). It lowers the cost and difficulty of [digital\\nwarfare](/wiki/Digital_warfare \"Digital warfare\") and [advanced\\nspyware](/wiki/Spyware \"Spyware\").[237] All these technologies have been\\navailable since 2020 or earlier—AI [facial recognition\\nsystems](/wiki/Facial_recognition_system \"Facial recognition system\") are\\nalready being used for [mass surveillance](/wiki/Mass_surveillance \"Mass\\nsurveillance\") in China.[238][239]\\n\\nThere many other ways that AI is expected to help bad actors, some of which\\ncan not be foreseen. For example, machine-learning AI is able to design tens\\nof thousands of toxic molecules in a matter of hours.[240]\\n\\n#### Technological unemployment\\n\\nMain articles: [Workplace impact of artificial\\nintelligence](/wiki/Workplace_impact_of_artificial_intelligence \"Workplace\\nimpact of artificial intelligence\") and [Technological\\nunemployment](/wiki/Technological_unemployment \"Technological unemployment\")\\n\\nEconomists have frequently highlighted the risks of redundancies from AI, and\\nspeculated about unemployment if there is no adequate social policy for full\\nemployment.[241]\\n\\nIn the past, technology has tended to increase rather than reduce total\\nemployment, but economists acknowledge that \"we\\'re in uncharted territory\"\\nwith AI.[242] A survey of economists showed disagreement about whether the\\nincreasing use of robots and AI will cause a substantial increase in long-term\\n[unemployment](/wiki/Unemployment \"Unemployment\"), but they generally agree\\nthat it could be a net benefit if [productivity](/wiki/Productivity\\n\"Productivity\") gains are\\n[redistributed](/wiki/Redistribution_of_income_and_wealth \"Redistribution of\\nincome and wealth\").[243] Risk estimates vary; for example, in the 2010s,\\nMichael Osborne and [Carl Benedikt Frey](/wiki/Carl_Benedikt_Frey \"Carl\\nBenedikt Frey\") estimated 47% of U.S. jobs are at \"high risk\" of potential\\nautomation, while an OECD report classified only 9% of U.S. jobs as \"high\\nrisk\".[p][245] The methodology of speculating about future employment levels\\nhas been criticised as lacking evidential foundation, and for implying that\\ntechnology, rather than social policy, creates unemployment, as opposed to\\nredundancies.[241] In April 2023, it was reported that 70% of the jobs for\\nChinese video game illustrators had been eliminated by generative artificial\\nintelligence.[246][247]\\n\\nUnlike previous waves of automation, many middle-class jobs may be eliminated\\nby artificial intelligence; _[The Economist](/wiki/The_Economist \"The\\nEconomist\")_ stated in 2015 that \"the worry that AI could do to white-collar\\njobs what steam power did to blue-collar ones during the Industrial\\nRevolution\" is \"worth taking seriously\".[248] Jobs at extreme risk range from\\n[paralegals](/wiki/Paralegal \"Paralegal\") to fast food cooks, while job demand\\nis likely to increase for care-related professions ranging from personal\\nhealthcare to the clergy.[249]\\n\\nFrom the early days of the development of artificial intelligence, there have\\nbeen arguments, for example, those put forward by [Joseph\\nWeizenbaum](/wiki/Joseph_Weizenbaum \"Joseph Weizenbaum\"), about whether tasks\\nthat can be done by computers actually should be done by them, given the\\ndifference between computers and humans, and between quantitative calculation\\nand qualitative, value-based judgement.[250]\\n\\n#### Existential risk\\n\\nMain article: [Existential risk from artificial general\\nintelligence](/wiki/Existential_risk_from_artificial_general_intelligence\\n\"Existential risk from artificial general intelligence\")\\n\\nIt has been argued AI will become so powerful that humanity may irreversibly\\nlose control of it. This could, as physicist [Stephen\\nHawking](/wiki/Stephen_Hawking \"Stephen Hawking\") stated, \"[spell the end of\\nthe human race](/wiki/Global_catastrophic_risk \"Global catastrophic\\nrisk\")\".[251] This scenario has been common in science fiction, when a\\ncomputer or robot suddenly develops a human-like \"self-awareness\" (or\\n\"sentience\" or \"consciousness\") and becomes a malevolent character.[q] These\\nsci-fi scenarios are misleading in several ways.\\n\\nFirst, AI does not require human-like \"[sentience](/wiki/Sentience\\n\"Sentience\")\" to be an existential risk. Modern AI programs are given specific\\ngoals and use learning and intelligence to achieve them. Philosopher [Nick\\nBostrom](/wiki/Nick_Bostrom \"Nick Bostrom\") argued that if one gives _almost\\nany_ goal to a sufficiently powerful AI, it may choose to destroy humanity to\\nachieve it (he used the example of a [paperclip factory\\nmanager](/wiki/Instrumental_convergence#Paperclip_maximizer \"Instrumental\\nconvergence\")).[253] [Stuart Russell](/wiki/Stuart_J._Russell \"Stuart J.\\nRussell\") gives the example of household robot that tries to find a way to\\nkill its owner to prevent it from being unplugged, reasoning that \"you can\\'t\\nfetch the coffee if you\\'re dead.\"[254] In order to be safe for humanity, a\\n[superintelligence](/wiki/Superintelligence \"Superintelligence\") would have to\\nbe genuinely [aligned](/wiki/AI_alignment \"AI alignment\") with humanity\\'s\\nmorality and values so that it is \"fundamentally on our side\".[255]\\n\\nSecond, [Yuval Noah Harari](/wiki/Yuval_Noah_Harari \"Yuval Noah Harari\")\\nargues that AI does not require a robot body or physical control to pose an\\nexistential risk. The essential parts of civilization are not physical. Things\\nlike [ideologies](/wiki/Ideologies \"Ideologies\"), [law](/wiki/Law \"Law\"),\\n[government](/wiki/Government \"Government\"), [money](/wiki/Money \"Money\") and\\nthe [economy](/wiki/Economy \"Economy\") are made of [language](/wiki/Language\\n\"Language\"); they exist because there are stories that billions of people\\nbelieve. The current prevalence of [misinformation](/wiki/Misinformation\\n\"Misinformation\") suggests that an AI could use language to convince people to\\nbelieve anything, even to take actions that are destructive.[256]\\n\\nThe opinions amongst experts and industry insiders are mixed, with sizable\\nfractions both concerned and unconcerned by risk from eventual\\nsuperintelligent AI.[257] Personalities such as [Stephen\\nHawking](/wiki/Stephen_Hawking \"Stephen Hawking\"), [Bill\\nGates](/wiki/Bill_Gates \"Bill Gates\"), and [Elon Musk](/wiki/Elon_Musk \"Elon\\nMusk\"),[258] as well as AI pioneers such as [Yoshua\\nBengio](/wiki/Yoshua_Bengio \"Yoshua Bengio\"), [Stuart\\nRussell](/wiki/Stuart_J._Russell \"Stuart J. Russell\"), [Demis\\nHassabis](/wiki/Demis_Hassabis \"Demis Hassabis\"), and [Sam\\nAltman](/wiki/Sam_Altman \"Sam Altman\"), have expressed concerns about\\nexistential risk from AI.\\n\\nIn May 2023, [Geoffrey Hinton](/wiki/Geoffrey_Hinton \"Geoffrey Hinton\")\\nannounced his resignation from Google in order to be able to \"freely speak out\\nabout the risks of AI\" without \"considering how this impacts Google.\"[259] He\\nnotably mentioned risks of an [AI takeover](/wiki/AI_takeover \"AI\\ntakeover\"),[260] and stressed that in order to avoid the worst outcomes,\\nestablishing safety guidelines will require cooperation among those competing\\nin use of AI.[261]\\n\\nIn 2023, many leading AI experts issued [the joint\\nstatement](/wiki/Statement_on_AI_risk_of_extinction \"Statement on AI risk of\\nextinction\") that \"Mitigating the risk of extinction from AI should be a\\nglobal priority alongside other societal-scale risks such as pandemics and\\nnuclear war\".[262]\\n\\nOther researchers, however, spoke in favor of a less dystopian view. AI\\npioneer [Juergen Schmidhuber](/wiki/Juergen_Schmidhuber \"Juergen Schmidhuber\")\\ndid not sign the joint statement, emphasising that in 95% of all cases, AI\\nresearch is about making \"human lives longer and healthier and easier.\"[263]\\nWhile the tools that are now being used to improve lives can also be used by\\nbad actors, \"they can also be used against the bad actors.\"[264][265] [Andrew\\nNg](/wiki/Andrew_Ng \"Andrew Ng\") also argued that \"it\\'s a mistake to fall for\\nthe doomsday hype on AI—and that regulators who do will only benefit vested\\ninterests.\"[266] [Yann LeCun](/wiki/Yann_LeCun \"Yann LeCun\") \"scoffs at his\\npeers\\' dystopian scenarios of supercharged misinformation and even,\\neventually, human extinction.\"[267] In the early 2010s, experts argued that\\nthe risks are too distant in the future to warrant research or that humans\\nwill be valuable from the perspective of a superintelligent machine.[268]\\nHowever, after 2016, the study of current and future risks and possible\\nsolutions became a serious area of research.[269]\\n\\n### Ethical machines and alignment\\n\\nMain articles: [Machine ethics](/wiki/Machine_ethics \"Machine ethics\"), [AI\\nsafety](/wiki/AI_safety \"AI safety\"), [Friendly artificial\\nintelligence](/wiki/Friendly_artificial_intelligence \"Friendly artificial\\nintelligence\"), [Artificial moral agents](/wiki/Artificial_moral_agents\\n\"Artificial moral agents\"), and [Human Compatible](/wiki/Human_Compatible\\n\"Human Compatible\")\\n\\nFriendly AI are machines that have been designed from the beginning to\\nminimize risks and to make choices that benefit humans. [Eliezer\\nYudkowsky](/wiki/Eliezer_Yudkowsky \"Eliezer Yudkowsky\"), who coined the term,\\nargues that developing friendly AI should be a higher research priority: it\\nmay require a large investment and it must be completed before AI becomes an\\nexistential risk.[270]\\n\\nMachines with intelligence have the potential to use their intelligence to\\nmake ethical decisions. The field of machine ethics provides machines with\\nethical principles and procedures for resolving ethical dilemmas.[271] The\\nfield of machine ethics is also called computational morality,[271] and was\\nfounded at an [AAAI](/wiki/AAAI \"AAAI\") symposium in 2005.[272]\\n\\nOther approaches include [Wendell Wallach](/wiki/Wendell_Wallach \"Wendell\\nWallach\")\\'s \"artificial moral agents\"[273] and [Stuart J.\\nRussell](/wiki/Stuart_J._Russell \"Stuart J. Russell\")\\'s [three\\nprinciples](/wiki/Human_Compatible#Russell\\'s_three_principles \"Human\\nCompatible\") for developing provably beneficial machines.[274]\\n\\n### Open source\\n\\nActive organizations in the AI open-source community include [Hugging\\nFace](/wiki/Hugging_Face \"Hugging Face\"),[275] [Google](/wiki/Google\\n\"Google\"),[276] [EleutherAI](/wiki/EleutherAI \"EleutherAI\") and\\n[Meta](/wiki/Meta_Platforms \"Meta Platforms\").[277] Various AI models, such as\\n[Llama 2](/wiki/LLaMA \"LLaMA\"), [Mistral](/wiki/Mistral_AI \"Mistral AI\") or\\n[Stable Diffusion](/wiki/Stable_Diffusion \"Stable Diffusion\"), have been made\\nopen-weight,[278][279] meaning that their architecture and trained parameters\\n(the \"weights\") are publicly available. Open-weight models can be freely\\n[fine-tuned](/wiki/Fine-tuning_\\\\(deep_learning\\\\) \"Fine-tuning \\\\(deep\\nlearning\\\\)\"), which allows companies to specialize them with their own data\\nand for their own use-case.[280] Open-weight models are useful for research\\nand innovation but can also be misused. Since they can be fine-tuned, any\\nbuilt-in security measure, such as objecting to harmful requests, can be\\ntrained away until it becomes ineffective. Some researchers warn that future\\nAI models may develop dangerous capabilities (such as the potential to\\ndrastically facilitate [bioterrorism](/wiki/Bioterrorism \"Bioterrorism\")) and\\nthat once released on the Internet, they cannot be deleted everywhere if\\nneeded. They recommend pre-release audits and cost-benefit analyses.[281]\\n\\n### Frameworks\\n\\nArtificial Intelligence projects can have their ethical permissibility tested\\nwhile designing, developing, and implementing an AI system. An AI framework\\nsuch as the Care and Act Framework containing the SUM values—developed by the\\n[Alan Turing Institute](/wiki/Alan_Turing_Institute \"Alan Turing Institute\")\\ntests projects in four main areas:[282][283]\\n\\n  * **Respect** the dignity of individual people\\n  * **Connect** with other people sincerely, openly, and inclusively\\n  * **Care** for the wellbeing of everyone\\n  * **Protect** social values, justice, and the public interest\\n\\nOther developments in ethical frameworks include those decided upon during the\\n[Asilomar Conference](/wiki/Asilomar_Conference_on_Beneficial_AI \"Asilomar\\nConference on Beneficial AI\"), the Montreal Declaration for Responsible AI,\\nand the IEEE\\'s Ethics of Autonomous Systems initiative, among others;[284]\\nhowever, these principles do not go without their criticisms, especially\\nregards to the people chosen contributes to these frameworks.[285]\\n\\nPromotion of the wellbeing of the people and communities that these\\ntechnologies affect requires consideration of the social and ethical\\nimplications at all stages of AI system design, development and\\nimplementation, and collaboration between job roles such as data scientists,\\nproduct managers, data engineers, domain experts, and delivery managers.[286]\\n\\nThe [UK AI Safety Institute](/wiki/AI_Safety_Institute_\\\\(United_Kingdom\\\\) \"AI\\nSafety Institute \\\\(United Kingdom\\\\)\") released in 2024 a testing toolset\\ncalled \\'Inspect\\' for AI safety evaluations available under a MIT open-source\\nlicence which is freely available on GitHub and can be improved with third-\\nparty packages. It can be used to evaluate AI models in a range of areas\\nincluding core knowledge, ability to reason, and autonomous capabilities.[287]\\n\\n### Regulation\\n\\nMain articles: [Regulation of artificial\\nintelligence](/wiki/Regulation_of_artificial_intelligence \"Regulation of\\nartificial intelligence\"), [Regulation of\\nalgorithms](/wiki/Regulation_of_algorithms \"Regulation of algorithms\"), and\\n[AI safety](/wiki/AI_safety \"AI safety\")\\n\\n[![AI Safety\\nSummit](//upload.wikimedia.org/wikipedia/commons/thumb/3/36/Vice_President_Harris_at_the_group_photo_of_the_2023_AI_Safety_Summit.jpg/260px-\\nVice_President_Harris_at_the_group_photo_of_the_2023_AI_Safety_Summit.jpg)](/wiki/File:Vice_President_Harris_at_the_group_photo_of_the_2023_AI_Safety_Summit.jpg)The\\nfirst global [AI Safety Summit](/wiki/AI_Safety_Summit \"AI Safety Summit\") was\\nheld in 2023 with a declaration calling for international co-operation.\\n\\nThe regulation of artificial intelligence is the development of public sector\\npolicies and laws for promoting and regulating AI; it is therefore related to\\nthe broader regulation of algorithms.[288] The regulatory and policy landscape\\nfor AI is an emerging issue in jurisdictions globally.[289] According to AI\\nIndex at [Stanford](/wiki/Stanford \"Stanford\"), the annual number of AI-\\nrelated laws passed in the 127 survey countries jumped from one passed in 2016\\nto 37 passed in 2022 alone.[290][291] Between 2016 and 2020, more than 30\\ncountries adopted dedicated strategies for AI.[292] Most EU member states had\\nreleased national AI strategies, as had Canada, China, India, Japan,\\nMauritius, the Russian Federation, Saudi Arabia, United Arab Emirates, U.S.,\\nand Vietnam. Others were in the process of elaborating their own AI strategy,\\nincluding Bangladesh, Malaysia and Tunisia.[292] The [Global Partnership on\\nArtificial Intelligence](/wiki/Global_Partnership_on_Artificial_Intelligence\\n\"Global Partnership on Artificial Intelligence\") was launched in June 2020,\\nstating a need for AI to be developed in accordance with human rights and\\ndemocratic values, to ensure public confidence and trust in the\\ntechnology.[292] [Henry Kissinger](/wiki/Henry_Kissinger \"Henry Kissinger\"),\\n[Eric Schmidt](/wiki/Eric_Schmidt \"Eric Schmidt\"), and [Daniel\\nHuttenlocher](/wiki/Daniel_Huttenlocher \"Daniel Huttenlocher\") published a\\njoint statement in November 2021 calling for a government commission to\\nregulate AI.[293] In 2023, OpenAI leaders published recommendations for the\\ngovernance of superintelligence, which they believe may happen in less than 10\\nyears.[294] In 2023, the United Nations also launched an advisory body to\\nprovide recommendations on AI governance; the body comprises technology\\ncompany executives, governments officials and academics.[295] In 2024, the\\n[Council of Europe](/wiki/Council_of_Europe \"Council of Europe\") created the\\nfirst international legally binding treaty on AI, called the \"[Framework\\nConvention on Artificial Intelligence and Human Rights, Democracy and the Rule\\nof\\nLaw](/wiki/Framework_Convention_on_Artificial_Intelligence_and_Human_Rights,_Democracy_and_the_Rule_of_Law\\n\"Framework Convention on Artificial Intelligence and Human Rights, Democracy\\nand the Rule of Law\")\". It was adopted by the European Union, the United\\nStates, the United Kingdom, and other signatories.[296]\\n\\nIn a 2022 [Ipsos](/wiki/Ipsos \"Ipsos\") survey, attitudes towards AI varied\\ngreatly by country; 78% of Chinese citizens, but only 35% of Americans, agreed\\nthat \"products and services using AI have more benefits than drawbacks\".[290]\\nA 2023 [Reuters](/wiki/Reuters \"Reuters\")/Ipsos poll found that 61% of\\nAmericans agree, and 22% disagree, that AI poses risks to humanity.[297] In a\\n2023 [Fox News](/wiki/Fox_News \"Fox News\") poll, 35% of Americans thought it\\n\"very important\", and an additional 41% thought it \"somewhat important\", for\\nthe federal government to regulate AI, versus 13% responding \"not very\\nimportant\" and 8% responding \"not at all important\".[298][299]\\n\\nIn November 2023, the first global [AI Safety Summit](/wiki/AI_Safety_Summit\\n\"AI Safety Summit\") was held in [Bletchley Park](/wiki/Bletchley_Park\\n\"Bletchley Park\") in the UK to discuss the near and far term risks of AI and\\nthe possibility of mandatory and voluntary regulatory frameworks.[300] 28\\ncountries including the United States, China, and the European Union issued a\\ndeclaration at the start of the summit, calling for international co-operation\\nto manage the challenges and risks of artificial intelligence.[301][302] In\\nMay 2024 at the [AI Seoul Summit](/wiki/AI_Seoul_Summit \"AI Seoul Summit\"), 16\\nglobal AI tech companies agreed to safety commitments on the development of\\nAI.[303][304]\\n\\n## History\\n\\nMain article: [History of artificial\\nintelligence](/wiki/History_of_artificial_intelligence \"History of artificial\\nintelligence\")\\n\\nFor a chronological guide, see [Timeline of artificial\\nintelligence](/wiki/Timeline_of_artificial_intelligence \"Timeline of\\nartificial intelligence\").\\n\\nThe study of mechanical or \"formal\" reasoning began with philosophers and\\nmathematicians in antiquity. The study of logic led directly to [Alan\\nTuring](/wiki/Alan_Turing \"Alan Turing\")\\'s [theory of\\ncomputation](/wiki/Theory_of_computation \"Theory of computation\"), which\\nsuggested that a machine, by shuffling symbols as simple as \"0\" and \"1\", could\\nsimulate any conceivable form of mathematical reasoning.[305][306] This, along\\nwith concurrent discoveries in [cybernetics](/wiki/Cybernetics \"Cybernetics\"),\\n[information theory](/wiki/Information_theory \"Information theory\") and\\n[neurobiology](/wiki/Neurobiology \"Neurobiology\"), led researchers to consider\\nthe possibility of building an \"electronic brain\".[r] They developed several\\nareas of research that would become part of AI,[308] such as\\n[McCullouch](/wiki/Warren_McCullouch \"Warren McCullouch\") and\\n[Pitts](/wiki/Walter_Pitts \"Walter Pitts\") design for \"artificial neurons\" in\\n1943,[115] and Turing\\'s influential 1950 paper \\'[Computing Machinery and\\nIntelligence](/wiki/Computing_Machinery_and_Intelligence \"Computing Machinery\\nand Intelligence\")\\', which introduced the [Turing test](/wiki/Turing_test\\n\"Turing test\") and showed that \"machine intelligence\" was plausible.[309][306]\\n\\nThe field of AI research was founded at [a workshop](/wiki/Dartmouth_workshop\\n\"Dartmouth workshop\") at [Dartmouth College](/wiki/Dartmouth_College\\n\"Dartmouth College\") in 1956.[s][6] The attendees became the leaders of AI\\nresearch in the 1960s.[t] They and their students produced programs that the\\npress described as \"astonishing\":[u] computers were learning\\n[checkers](/wiki/Checkers \"Checkers\") strategies, solving word problems in\\nalgebra, proving [logical theorems](/wiki/Theorem \"Theorem\") and speaking\\nEnglish.[v][7] Artificial intelligence laboratories were set up at a number of\\nBritish and U.S. universities in the latter 1950s and early 1960s.[306]\\n\\nResearchers in the 1960s and the 1970s were convinced that their methods would\\neventually succeed in creating a machine with [general\\nintelligence](/wiki/Artificial_general_intelligence \"Artificial general\\nintelligence\") and considered this the goal of their field.[313] In 1965\\n[Herbert Simon](/wiki/Herbert_A._Simon \"Herbert A. Simon\") predicted,\\n\"machines will be capable, within twenty years, of doing any work a man can\\ndo\".[314] In 1967 [Marvin Minsky](/wiki/Marvin_Minsky \"Marvin Minsky\") agreed,\\nwriting that \"within a generation ... the problem of creating \\'artificial\\nintelligence\\' will substantially be solved\".[315] They had, however,\\nunderestimated the difficulty of the problem.[w] In 1974, both the U.S. and\\nBritish governments cut off exploratory research in response to the\\n[criticism](/wiki/Lighthill_report \"Lighthill report\") of [Sir James\\nLighthill](/wiki/Sir_James_Lighthill \"Sir James Lighthill\")[317] and ongoing\\npressure from the U.S. Congress to [fund more productive\\nprojects](/wiki/Mansfield_Amendment \"Mansfield Amendment\").[318]\\n[Minsky](/wiki/Marvin_Minsky \"Marvin Minsky\")\\'s and [Papert](/wiki/Papert\\n\"Papert\")\\'s book _[Perceptrons](/wiki/Perceptron \"Perceptron\")_ was understood\\nas proving that [artificial neural networks](/wiki/Artificial_neural_networks\\n\"Artificial neural networks\") would never be useful for solving real-world\\ntasks, thus discrediting the approach altogether.[319] The \"[AI\\nwinter](/wiki/AI_winter \"AI winter\")\", a period when obtaining funding for AI\\nprojects was difficult, followed.[9]\\n\\nIn the early 1980s, AI research was revived by the commercial success of\\n[expert systems](/wiki/Expert_system \"Expert system\"),[320] a form of AI\\nprogram that simulated the knowledge and analytical skills of human experts.\\nBy 1985, the market for AI had reached over a billion dollars. At the same\\ntime, Japan\\'s [fifth generation computer](/wiki/Fifth_generation_computer\\n\"Fifth generation computer\") project inspired the U.S. and British governments\\nto restore funding for [academic research](/wiki/Academic_research \"Academic\\nresearch\").[8] However, beginning with the collapse of the [Lisp\\nMachine](/wiki/Lisp_Machine \"Lisp Machine\") market in 1987, AI once again fell\\ninto disrepute, and a second, longer-lasting winter began.[10]\\n\\nUp to this point, most of AI\\'s funding had gone to projects that used high-\\nlevel [symbols](/wiki/Symbolic_AI \"Symbolic AI\") to represent [mental\\nobjects](/wiki/Mental_objects \"Mental objects\") like plans, goals, beliefs,\\nand known facts. In the 1980s, some researchers began to doubt that this\\napproach would be able to imitate all the processes of human cognition,\\nespecially [perception](/wiki/Machine_perception \"Machine perception\"),\\n[robotics](/wiki/Robotics \"Robotics\"), [learning](/wiki/Machine_learning\\n\"Machine learning\") and [pattern recognition](/wiki/Pattern_recognition\\n\"Pattern recognition\"),[321] and began to look into \"sub-symbolic\"\\napproaches.[322] [Rodney Brooks](/wiki/Rodney_Brooks \"Rodney Brooks\") rejected\\n\"representation\" in general and focussed directly on engineering machines that\\nmove and survive.[x] [Judea Pearl](/wiki/Judea_Pearl \"Judea Pearl\"), [Lofti\\nZadeh](/wiki/Lofti_Zadeh \"Lofti Zadeh\") and others developed methods that\\nhandled incomplete and uncertain information by making reasonable guesses\\nrather than precise logic.[86][327] But the most important development was the\\nrevival of \"[connectionism](/wiki/Connectionism \"Connectionism\")\", including\\nneural network research, by [Geoffrey Hinton](/wiki/Geoffrey_Hinton \"Geoffrey\\nHinton\") and others.[328] In 1990, [Yann LeCun](/wiki/Yann_LeCun \"Yann LeCun\")\\nsuccessfully showed that [convolutional neural\\nnetworks](/wiki/Convolutional_neural_networks \"Convolutional neural networks\")\\ncan recognize handwritten digits, the first of many successful applications of\\nneural networks.[329]\\n\\nAI gradually restored its reputation in the late 1990s and early 21st century\\nby exploiting formal mathematical methods and by finding specific solutions to\\nspecific problems. This \"[narrow](/wiki/Narrow_AI \"Narrow AI\")\" and \"formal\"\\nfocus allowed researchers to produce verifiable results and collaborate with\\nother fields (such as [statistics](/wiki/Statistics \"Statistics\"),\\n[economics](/wiki/Economics \"Economics\") and\\n[mathematics](/wiki/Mathematical_optimization \"Mathematical\\noptimization\")).[330] By 2000, solutions developed by AI researchers were\\nbeing widely used, although in the 1990s they were rarely described as\\n\"artificial intelligence\" (a tendency known as the [AI effect](/wiki/AI_effect\\n\"AI effect\")).[331] However, several academic researchers became concerned\\nthat AI was no longer pursuing its original goal of creating versatile, fully\\nintelligent machines. Beginning around 2002, they founded the subfield of\\n[artificial general intelligence](/wiki/Artificial_general_intelligence\\n\"Artificial general intelligence\") (or \"AGI\"), which had several well-funded\\ninstitutions by the 2010s.[4]\\n\\n[Deep learning](/wiki/Deep_learning \"Deep learning\") began to dominate\\nindustry benchmarks in 2012 and was adopted throughout the field.[11] For many\\nspecific tasks, other methods were abandoned.[y] Deep learning\\'s success was\\nbased on both hardware improvements ([faster computers](/wiki/Moore%27s_law\\n\"Moore\\'s law\"),[333] [graphics processing\\nunits](/wiki/Graphics_processing_unit \"Graphics processing unit\"), [cloud\\ncomputing](/wiki/Cloud_computing \"Cloud computing\")[334]) and access to [large\\namounts of data](/wiki/Big_data \"Big data\")[335] (including curated\\ndatasets,[334] such as [ImageNet](/wiki/ImageNet \"ImageNet\")). Deep learning\\'s\\nsuccess led to an enormous increase in interest and funding in AI.[z] The\\namount of machine learning research (measured by total publications) increased\\nby 50% in the years 2015–2019.[292]\\n\\nIn 2016, issues of [fairness](/wiki/Algorithmic_fairness \"Algorithmic\\nfairness\") and the misuse of technology were catapulted into center stage at\\nmachine learning conferences, publications vastly increased, funding became\\navailable, and many researchers re-focussed their careers on these issues. The\\n[alignment problem](/wiki/AI_alignment \"AI alignment\") became a serious field\\nof academic study.[269]\\n\\nIn the late teens and early 2020s, [AGI](/wiki/Artificial_general_intelligence\\n\"Artificial general intelligence\") companies began to deliver programs that\\ncreated enormous interest. In 2015, [AlphaGo](/wiki/AlphaGo \"AlphaGo\"),\\ndeveloped by [DeepMind](/wiki/DeepMind \"DeepMind\"), beat the world champion\\n[Go player](/wiki/Go_player \"Go player\"). The program was taught only the\\nrules of the game and developed strategy by itself. [GPT-3](/wiki/GPT-3\\n\"GPT-3\") is a [large language model](/wiki/Large_language_model \"Large\\nlanguage model\") that was released in 2020 by [OpenAI](/wiki/OpenAI \"OpenAI\")\\nand is capable of generating high-quality human-like text.[336] These\\nprograms, and others, inspired an aggressive [AI boom](/wiki/AI_boom \"AI\\nboom\"), where large companies began investing billions in AI research.\\nAccording to AI Impacts, about $50 billion annually was invested in \"AI\"\\naround 2022 in the U.S. alone and about 20% of the new U.S. Computer Science\\nPhD graduates have specialized in \"AI\".[337] About 800,000 \"AI\"-related U.S.\\njob openings existed in 2022.[338]\\n\\n## Philosophy\\n\\nMain article: [Philosophy of artificial\\nintelligence](/wiki/Philosophy_of_artificial_intelligence \"Philosophy of\\nartificial intelligence\")\\n\\nPhilosophical debates have historically sought to determine the nature of\\nintelligence and how to make intelligent machines.[339] Another major focus\\nhas been whether machines can be conscious, and the associated ethical\\nimplications.[340] Many other topics in philosophy are relevant to AI, such as\\n[epistemology](/wiki/Epistemology \"Epistemology\") and [free\\nwill](/wiki/Free_will \"Free will\").[341] Rapid advancements have intensified\\npublic discussions on the philosophy and ethics of AI.[340]\\n\\n### Defining artificial intelligence\\n\\nSee also: [Turing test](/wiki/Turing_test \"Turing test\"), [Intelligent\\nagent](/wiki/Intelligent_agent \"Intelligent agent\"), [Dartmouth\\nworkshop](/wiki/Dartmouth_workshop \"Dartmouth workshop\"), and [Synthetic\\nintelligence](/wiki/Synthetic_intelligence \"Synthetic intelligence\")\\n\\n[Alan Turing](/wiki/Alan_Turing \"Alan Turing\") wrote in 1950 \"I propose to\\nconsider the question \\'can machines think\\'?\"[342] He advised changing the\\nquestion from whether a machine \"thinks\", to \"whether or not it is possible\\nfor machinery to show intelligent behaviour\".[342] He devised the Turing test,\\nwhich measures the ability of a machine to simulate human conversation.[309]\\nSince we can only observe the behavior of the machine, it does not matter if\\nit is \"actually\" thinking or literally has a \"mind\". Turing notes that [we can\\nnot determine these things about other people](/wiki/Problem_of_other_minds\\n\"Problem of other minds\") but \"it is usual to have a polite convention that\\neveryone thinks.\"[343]\\n\\n[![](//upload.wikimedia.org/wikipedia/commons/thumb/5/57/Weakness_of_Turing_test_1.svg/220px-\\nWeakness_of_Turing_test_1.svg.png)](/wiki/File:Weakness_of_Turing_test_1.svg)The\\nTuring test can provide some evidence of intelligence, but it penalizes non-\\nhuman intelligent behavior.[344]\\n\\n[Russell](/wiki/Stuart_J._Russell \"Stuart J. Russell\") and\\n[Norvig](/wiki/Norvig \"Norvig\") agree with Turing that intelligence must be\\ndefined in terms of external behavior, not internal structure.[1] However,\\nthey are critical that the test requires the machine to imitate humans.\\n\"[Aeronautical engineering](/wiki/Aeronautics \"Aeronautics\") texts,\" they\\nwrote, \"do not define the goal of their field as making \\'machines that fly so\\nexactly like [pigeons](/wiki/Pigeon \"Pigeon\") that they can fool other\\npigeons.\\'\"[345] AI founder [John\\nMcCarthy](/wiki/John_McCarthy_\\\\(computer_scientist\\\\) \"John McCarthy \\\\(computer\\nscientist\\\\)\") agreed, writing that \"Artificial intelligence is not, by\\ndefinition, simulation of human intelligence\".[346]\\n\\nMcCarthy defines intelligence as \"the computational part of the ability to\\nachieve goals in the world\".[347] Another AI founder, [Marvin\\nMinsky](/wiki/Marvin_Minsky \"Marvin Minsky\") similarly describes it as \"the\\nability to solve hard problems\".[348] The leading AI textbook defines it as\\nthe study of agents that perceive their environment and take actions that\\nmaximize their chances of achieving defined goals.[1] These definitions view\\nintelligence in terms of well-defined problems with well-defined solutions,\\nwhere both the difficulty of the problem and the performance of the program\\nare direct measures of the \"intelligence\" of the machine—and no other\\nphilosophical discussion is required, or may not even be possible.\\n\\nAnother definition has been adopted by Google,[349] a major practitioner in\\nthe field of AI. This definition stipulates the ability of systems to\\nsynthesize information as the manifestation of intelligence, similar to the\\nway it is defined in biological intelligence.\\n\\nSome authors have suggested in practice, that the definition of AI is vague\\nand difficult to define, with contention as to whether classical algorithms\\nshould be categorised as AI,[350] with many companies during the early 2020s\\nAI boom using the term as a marketing [buzzword](/wiki/Buzzword \"Buzzword\"),\\noften even if they did \"not actually use AI in a material way\".[351]\\n\\n### Evaluating approaches to AI\\n\\nNo established unifying theory or [paradigm](/wiki/Paradigm \"Paradigm\") has\\nguided AI research for most of its history.[aa] The unprecedented success of\\nstatistical machine learning in the 2010s eclipsed all other approaches (so\\nmuch so that some sources, especially in the business world, use the term\\n\"artificial intelligence\" to mean \"machine learning with neural networks\").\\nThis approach is mostly [sub-symbolic](/wiki/Sub-symbolic \"Sub-symbolic\"),\\n[soft](/wiki/Soft_computing \"Soft computing\") and\\n[narrow](/wiki/Artificial_general_intelligence \"Artificial general\\nintelligence\"). Critics argue that these questions may have to be revisited by\\nfuture generations of AI researchers.\\n\\n#### Symbolic AI and its limits\\n\\n[Symbolic AI](/wiki/Symbolic_AI \"Symbolic AI\") (or \"[GOFAI](/wiki/GOFAI\\n\"GOFAI\")\")[353] simulated the high-level conscious reasoning that people use\\nwhen they solve puzzles, express legal reasoning and do mathematics. They were\\nhighly successful at \"intelligent\" tasks such as algebra or IQ tests. In the\\n1960s, Newell and Simon proposed the [physical symbol systems\\nhypothesis](/wiki/Physical_symbol_systems_hypothesis \"Physical symbol systems\\nhypothesis\"): \"A physical symbol system has the necessary and sufficient means\\nof general intelligent action.\"[354]\\n\\nHowever, the symbolic approach failed on many tasks that humans solve easily,\\nsuch as learning, recognizing an object or commonsense reasoning. [Moravec\\'s\\nparadox](/wiki/Moravec%27s_paradox \"Moravec\\'s paradox\") is the discovery that\\nhigh-level \"intelligent\" tasks were easy for AI, but low level \"instinctive\"\\ntasks were extremely difficult.[355] Philosopher [Hubert\\nDreyfus](/wiki/Hubert_Dreyfus \"Hubert Dreyfus\") had\\n[argued](/wiki/Dreyfus%27_critique_of_AI \"Dreyfus\\' critique of AI\") since the\\n1960s that human expertise depends on unconscious instinct rather than\\nconscious symbol manipulation, and on having a \"feel\" for the situation,\\nrather than explicit symbolic knowledge.[356] Although his arguments had been\\nridiculed and ignored when they were first presented, eventually, AI research\\ncame to agree with him.[ab][16]\\n\\nThe issue is not resolved: [sub-symbolic](/wiki/Sub-symbolic \"Sub-symbolic\")\\nreasoning can make many of the same inscrutable mistakes that human intuition\\ndoes, such as [algorithmic bias](/wiki/Algorithmic_bias \"Algorithmic bias\").\\nCritics such as [Noam Chomsky](/wiki/Noam_Chomsky \"Noam Chomsky\") argue\\ncontinuing research into symbolic AI will still be necessary to attain general\\nintelligence,[358][359] in part because sub-symbolic AI is a move away from\\n[explainable AI](/wiki/Explainable_AI \"Explainable AI\"): it can be difficult\\nor impossible to understand why a modern statistical AI program made a\\nparticular decision. The emerging field of [neuro-symbolic artificial\\nintelligence](/wiki/Neuro-symbolic_AI \"Neuro-symbolic AI\") attempts to bridge\\nthe two approaches.\\n\\n#### Neat vs. scruffy\\n\\nMain article: [Neats and scruffies](/wiki/Neats_and_scruffies \"Neats and\\nscruffies\")\\n\\n\"Neats\" hope that intelligent behavior is described using simple, elegant\\nprinciples (such as [logic](/wiki/Logic \"Logic\"),\\n[optimization](/wiki/Optimization \"Optimization\"), or [neural\\nnetworks](/wiki/Artificial_neural_network \"Artificial neural network\")).\\n\"Scruffies\" expect that it necessarily requires solving a large number of\\nunrelated problems. Neats defend their programs with theoretical rigor,\\nscruffies rely mainly on incremental testing to see if they work. This issue\\nwas actively discussed in the 1970s and 1980s,[360] but eventually was seen as\\nirrelevant. Modern AI has elements of both.\\n\\n#### Soft vs. hard computing\\n\\nMain article: [Soft computing](/wiki/Soft_computing \"Soft computing\")\\n\\nFinding a provably correct or optimal solution is\\n[intractable](/wiki/Intractability_\\\\(complexity\\\\) \"Intractability\\n\\\\(complexity\\\\)\") for many important problems.[15] Soft computing is a set of\\ntechniques, including [genetic algorithms](/wiki/Genetic_algorithms \"Genetic\\nalgorithms\"), [fuzzy logic](/wiki/Fuzzy_logic \"Fuzzy logic\") and neural\\nnetworks, that are tolerant of imprecision, uncertainty, partial truth and\\napproximation. Soft computing was introduced in the late 1980s and most\\nsuccessful AI programs in the 21st century are examples of soft computing with\\nneural networks.\\n\\n#### Narrow vs. general AI\\n\\nMain articles: [Weak artificial\\nintelligence](/wiki/Weak_artificial_intelligence \"Weak artificial\\nintelligence\") and [Artificial general\\nintelligence](/wiki/Artificial_general_intelligence \"Artificial general\\nintelligence\")\\n\\nAI researchers are divided as to whether to pursue the goals of artificial\\ngeneral intelligence and [superintelligence](/wiki/Superintelligence\\n\"Superintelligence\") directly or to solve as many specific problems as\\npossible (narrow AI) in hopes these solutions will lead indirectly to the\\nfield\\'s long-term goals.[361][362] General intelligence is difficult to define\\nand difficult to measure, and modern AI has had more verifiable successes by\\nfocusing on specific problems with specific solutions. The sub-field of\\nartificial general intelligence studies this area exclusively.\\n\\n### Machine consciousness, sentience, and mind\\n\\nMain articles: [Philosophy of artificial\\nintelligence](/wiki/Philosophy_of_artificial_intelligence \"Philosophy of\\nartificial intelligence\") and [Artificial\\nconsciousness](/wiki/Artificial_consciousness \"Artificial consciousness\")\\n\\nThe [philosophy of mind](/wiki/Philosophy_of_mind \"Philosophy of mind\") does\\nnot know whether a machine can have a [mind](/wiki/Mind \"Mind\"),\\n[consciousness](/wiki/Consciousness \"Consciousness\") and [mental\\nstates](/wiki/Philosophy_of_mind \"Philosophy of mind\"), in the same sense that\\nhuman beings do. This issue considers the internal experiences of the machine,\\nrather than its external behavior. Mainstream AI research considers this issue\\nirrelevant because it does not affect the goals of the field: to build\\nmachines that can solve problems using intelligence.\\n[Russell](/wiki/Stuart_J._Russell \"Stuart J. Russell\") and\\n[Norvig](/wiki/Norvig \"Norvig\") add that \"[t]he additional project of making a\\nmachine conscious in exactly the way humans are is not one that we are\\nequipped to take on.\"[363] However, the question has become central to the\\nphilosophy of mind. It is also typically the central question at issue in\\n[artificial intelligence in fiction](/wiki/Artificial_intelligence_in_fiction\\n\"Artificial intelligence in fiction\").\\n\\n#### Consciousness\\n\\nMain articles: [Hard problem of\\nconsciousness](/wiki/Hard_problem_of_consciousness \"Hard problem of\\nconsciousness\") and [Theory of mind](/wiki/Theory_of_mind \"Theory of mind\")\\n\\n[David Chalmers](/wiki/David_Chalmers \"David Chalmers\") identified two\\nproblems in understanding the mind, which he named the \"hard\" and \"easy\"\\nproblems of consciousness.[364] The easy problem is understanding how the\\nbrain processes signals, makes plans and controls behavior. The hard problem\\nis explaining how this _feels_ or why it should feel like anything at all,\\nassuming we are right in thinking that it truly does feel like something\\n(Dennett\\'s consciousness illusionism says this is an illusion). While human\\n[information processing](/wiki/Information_processing_\\\\(psychology\\\\)\\n\"Information processing \\\\(psychology\\\\)\") is easy to explain, human [subjective\\nexperience](/wiki/Subjective_experience \"Subjective experience\") is difficult\\nto explain. For example, it is easy to imagine a color-blind person who has\\nlearned to identify which objects in their field of view are red, but it is\\nnot clear what would be required for the person to _know what red looks\\nlike_.[365]\\n\\n#### Computationalism and functionalism\\n\\nMain articles: [Computational theory of\\nmind](/wiki/Computational_theory_of_mind \"Computational theory of mind\"),\\n[Functionalism (philosophy of\\nmind)](/wiki/Functionalism_\\\\(philosophy_of_mind\\\\) \"Functionalism \\\\(philosophy\\nof mind\\\\)\"), and [Chinese room](/wiki/Chinese_room \"Chinese room\")\\n\\nComputationalism is the position in the [philosophy of\\nmind](/wiki/Philosophy_of_mind \"Philosophy of mind\") that the human mind is an\\ninformation processing system and that thinking is a form of computing.\\nComputationalism argues that the relationship between mind and body is similar\\nor identical to the relationship between software and hardware and thus may be\\na solution to the [mind–body problem](/wiki/Mind%E2%80%93body_problem\\n\"Mind–body problem\"). This philosophical position was inspired by the work of\\nAI researchers and cognitive scientists in the 1960s and was originally\\nproposed by philosophers [Jerry Fodor](/wiki/Jerry_Fodor \"Jerry Fodor\") and\\n[Hilary Putnam](/wiki/Hilary_Putnam \"Hilary Putnam\").[366]\\n\\nPhilosopher [John Searle](/wiki/John_Searle \"John Searle\") characterized this\\nposition as \"[strong AI](/wiki/Strong_AI_hypothesis \"Strong AI hypothesis\")\":\\n\"The appropriately programmed computer with the right inputs and outputs would\\nthereby have a mind in exactly the same sense human beings have minds.\"[ac]\\nSearle counters this assertion with his Chinese room argument, which attempts\\nto show that, even if a machine perfectly simulates human behavior, there is\\nstill no reason to suppose it also has a mind.[370]\\n\\n#### AI welfare and rights\\n\\nIt is difficult or impossible to reliably evaluate whether an advanced [AI is\\nsentient](/wiki/Sentient_AI \"Sentient AI\") (has the ability to feel), and if\\nso, to what degree.[371] But if there is a significant chance that a given\\nmachine can feel and suffer, then it may be entitled to certain rights or\\nwelfare protection measures, similarly to animals.[372][373]\\n[Sapience](/wiki/Sapience \"Sapience\") (a set of capacities related to high\\nintelligence, such as discernment or [self-awareness](/wiki/Self-awareness\\n\"Self-awareness\")) may provide another moral basis for AI rights.[372] [Robot\\nrights](/wiki/Robot_rights \"Robot rights\") are also sometimes proposed as a\\npractical way to integrate autonomous agents into society.[374]\\n\\nIn 2017, the European Union considered granting \"electronic personhood\" to\\nsome of the most capable AI systems. Similarly to the legal status of\\ncompanies, it would have conferred rights but also responsibilities.[375]\\nCritics argued in 2018 that granting rights to AI systems would downplay the\\nimportance of [human rights](/wiki/Human_rights \"Human rights\"), and that\\nlegislation should focus on user needs rather than speculative futuristic\\nscenarios. They also noted that robots lacked the autonomy to take part to\\nsociety on their own.[376][377]\\n\\nProgress in AI increased interest in the topic. Proponents of AI welfare and\\nrights often argue that AI sentience, if it emerges, would be particularly\\neasy to deny. They warn that this may be a [moral blind\\nspot](/wiki/Moral_blindness \"Moral blindness\") analogous to\\n[slavery](/wiki/Slavery \"Slavery\") or [factory farming](/wiki/Factory_farming\\n\"Factory farming\"), which could lead to [large-scale\\nsuffering](/wiki/Suffering_risks \"Suffering risks\") if sentient AI is created\\nand carelessly exploited.[373][372]\\n\\n## Future\\n\\n### Superintelligence and the singularity\\n\\nA [superintelligence](/wiki/Superintelligence \"Superintelligence\") is a\\nhypothetical agent that would possess intelligence far surpassing that of the\\nbrightest and most gifted human mind.[362]If research into [artificial general\\nintelligence](/wiki/Artificial_general_intelligence \"Artificial general\\nintelligence\") produced sufficiently intelligent software, it might be able to\\n[reprogram and improve itself](/wiki/Recursive_self-improvement \"Recursive\\nself-improvement\"). The improved software would be even better at improving\\nitself, leading to what [I. J. Good](/wiki/I._J._Good \"I. J. Good\") called an\\n\"[intelligence explosion](/wiki/Intelligence_explosion \"Intelligence\\nexplosion\")\" and [Vernor Vinge](/wiki/Vernor_Vinge \"Vernor Vinge\") called a\\n\"[singularity](/wiki/Technological_singularity \"Technological\\nsingularity\")\".[378]\\n\\nHowever, technologies cannot improve exponentially indefinitely, and typically\\nfollow an [S-shaped curve](/wiki/S-shaped_curve \"S-shaped curve\"), slowing\\nwhen they reach the physical limits of what the technology can do.[379]\\n\\n### Transhumanism\\n\\nMain article: [Transhumanism](/wiki/Transhumanism \"Transhumanism\")\\n\\nRobot designer [Hans Moravec](/wiki/Hans_Moravec \"Hans Moravec\"),\\ncyberneticist [Kevin Warwick](/wiki/Kevin_Warwick \"Kevin Warwick\") and\\ninventor [Ray Kurzweil](/wiki/Ray_Kurzweil \"Ray Kurzweil\") have predicted that\\nhumans and machines may merge in the future into [cyborgs](/wiki/Cyborg\\n\"Cyborg\") that are more capable and powerful than either. This idea, called\\n[transhumanism](/wiki/Transhumanism \"Transhumanism\"), has roots in the\\nwritings of [Aldous Huxley](/wiki/Aldous_Huxley \"Aldous Huxley\") and [Robert\\nEttinger](/wiki/Robert_Ettinger \"Robert Ettinger\").[380]\\n\\n[Edward Fredkin](/wiki/Edward_Fredkin \"Edward Fredkin\") argues that\\n\"artificial intelligence is the next step in evolution\", an idea first\\nproposed by [Samuel Butler](/wiki/Samuel_Butler_\\\\(novelist\\\\) \"Samuel Butler\\n\\\\(novelist\\\\)\")\\'s \"[Darwin among the Machines](/wiki/Darwin_among_the_Machines\\n\"Darwin among the Machines\")\" as far back as 1863, and expanded upon by\\n[George Dyson](/wiki/George_Dyson_\\\\(science_historian\\\\) \"George Dyson\\n\\\\(science historian\\\\)\") in his 1998 book _[Darwin Among the Machines: The\\nEvolution of Global\\nIntelligence](/wiki/Darwin_Among_the_Machines#Evolution_of_Global_Intelligence\\n\"Darwin Among the Machines\")_.[381]\\n\\n## In fiction\\n\\nMain article: [Artificial intelligence in\\nfiction](/wiki/Artificial_intelligence_in_fiction \"Artificial intelligence in\\nfiction\")\\n\\n[![](//upload.wikimedia.org/wikipedia/commons/thumb/8/87/Capek_play.jpg/260px-\\nCapek_play.jpg)](/wiki/File:Capek_play.jpg)The word \"robot\" itself was coined\\nby [Karel Čapek](/wiki/Karel_%C4%8Capek \"Karel Čapek\") in his 1921 play\\n_[R.U.R.](/wiki/R.U.R. \"R.U.R.\")_ , the title standing for \"Rossum\\'s Universal\\nRobots\".\\n\\nThought-capable artificial beings have appeared as storytelling devices since\\nantiquity,[382] and have been a persistent theme in [science\\nfiction](/wiki/Science_fiction \"Science fiction\").[383]\\n\\nA common [trope](/wiki/Trope_\\\\(literature\\\\) \"Trope \\\\(literature\\\\)\") in these\\nworks began with [Mary Shelley](/wiki/Mary_Shelley \"Mary Shelley\")\\'s\\n_[Frankenstein](/wiki/Frankenstein \"Frankenstein\")_ , where a human creation\\nbecomes a threat to its masters. This includes such works as [Arthur C.\\nClarke\\'s](/wiki/2001:_A_Space_Odyssey_\\\\(novel\\\\) \"2001: A Space Odyssey\\n\\\\(novel\\\\)\") and [Stanley Kubrick\\'s](/wiki/2001:_A_Space_Odyssey_\\\\(film\\\\)\\n\"2001: A Space Odyssey \\\\(film\\\\)\") _2001: A Space Odyssey_ (both 1968), with\\n[HAL 9000](/wiki/HAL_9000 \"HAL 9000\"), the murderous computer in charge of the\\n_[Discovery One](/wiki/Discovery_One \"Discovery One\")_ spaceship, as well as\\n_[The Terminator](/wiki/The_Terminator \"The Terminator\")_ (1984) and _[The\\nMatrix](/wiki/The_Matrix \"The Matrix\")_ (1999). In contrast, the rare loyal\\nrobots such as Gort from _[The Day the Earth Stood\\nStill](/wiki/The_Day_the_Earth_Stood_Still \"The Day the Earth Stood Still\")_\\n(1951) and Bishop from _[Aliens](/wiki/Aliens_\\\\(film\\\\) \"Aliens \\\\(film\\\\)\")_\\n(1986) are less prominent in popular culture.[384]\\n\\n[Isaac Asimov](/wiki/Isaac_Asimov \"Isaac Asimov\") introduced the [Three Laws\\nof Robotics](/wiki/Three_Laws_of_Robotics \"Three Laws of Robotics\") in many\\nstories, most notably with the \"[Multivac](/wiki/Multivac \"Multivac\")\" super-\\nintelligent computer. Asimov\\'s laws are often brought up during lay\\ndiscussions of machine ethics;[385] while almost all artificial intelligence\\nresearchers are familiar with Asimov\\'s laws through popular culture, they\\ngenerally consider the laws useless for many reasons, one of which is their\\nambiguity.[386]\\n\\nSeveral works use AI to force us to confront the fundamental question of what\\nmakes us human, showing us artificial beings that have [the ability to\\nfeel](/wiki/Sentience \"Sentience\"), and thus to suffer. This appears in [Karel\\nČapek](/wiki/Karel_%C4%8Capek \"Karel Čapek\")\\'s _[R.U.R.](/wiki/R.U.R.\\n\"R.U.R.\")_ , the films _[A.I. Artificial\\nIntelligence](/wiki/A.I._Artificial_Intelligence \"A.I. Artificial\\nIntelligence\")_ and _[Ex Machina](/wiki/Ex_Machina_\\\\(film\\\\) \"Ex Machina\\n\\\\(film\\\\)\")_ , as well as the novel _[Do Androids Dream of Electric\\nSheep?](/wiki/Do_Androids_Dream_of_Electric_Sheep%3F \"Do Androids Dream of\\nElectric Sheep?\")_ , by [Philip K. Dick](/wiki/Philip_K._Dick \"Philip K.\\nDick\"). Dick considers the idea that our understanding of human subjectivity\\nis altered by technology created with artificial intelligence.[387]\\n\\n## See also\\n\\n  * [Artificial general intelligence](/wiki/Artificial_general_intelligence \"Artificial general intelligence\")\\n  * [Artificial intelligence content detection](/wiki/Artificial_intelligence_content_detection \"Artificial intelligence content detection\") – Software to detect AI-generated content\\n  * [Behavior selection algorithm](/wiki/Behavior_selection_algorithm \"Behavior selection algorithm\") – Algorithm that selects actions for intelligent agents\\n  * [Business process automation](/wiki/Business_process_automation \"Business process automation\") – Automation of business processes\\n  * [Case-based reasoning](/wiki/Case-based_reasoning \"Case-based reasoning\") – Process of solving new problems based on the solutions of similar past problems\\n  * [Computational intelligence](/wiki/Computational_intelligence \"Computational intelligence\") – Ability of a computer to learn a specific task from data or experimental observation\\n  * [Digital immortality](/wiki/Digital_immortality \"Digital immortality\") – Hypothetical concept of storing a personality in digital form\\n  * [Emergent algorithm](/wiki/Emergent_algorithm \"Emergent algorithm\") – Algorithm exhibiting emergent behavior\\n  * [Female gendering of AI technologies](/wiki/Female_gendering_of_AI_technologies \"Female gendering of AI technologies\") – Gender biases in digital technologyPages displaying short descriptions of redirect targets\\n  * [Glossary of artificial intelligence](/wiki/Glossary_of_artificial_intelligence \"Glossary of artificial intelligence\") – List of definitions of terms and concepts commonly used in the study of artificial intelligence\\n  * [Intelligence amplification](/wiki/Intelligence_amplification \"Intelligence amplification\") – Use of information technology to augment human intelligence\\n  * [Mind uploading](/wiki/Mind_uploading \"Mind uploading\") – Hypothetical process of digitally emulating a brain\\n  * [Moravec\\'s paradox](/wiki/Moravec%27s_paradox \"Moravec\\'s paradox\") – Observation that perception requires more computation than reasoning\\n  * [Organoid intelligence](/wiki/Organoid_intelligence \"Organoid intelligence\") – Use of brain cells and brain organoids for intelligent computing\\n  * [Robotic process automation](/wiki/Robotic_process_automation \"Robotic process automation\") – Form of business process automation technology\\n  * [Weak artificial intelligence](/wiki/Weak_artificial_intelligence \"Weak artificial intelligence\") – Form of artificial intelligence\\n  * [Wetware computer](/wiki/Wetware_computer \"Wetware computer\") – Computer composed of organic material\\n  * [Hallucination (artificial intelligence)](/wiki/Hallucination_\\\\(artificial_intelligence\\\\) \"Hallucination \\\\(artificial intelligence\\\\)\") – Erroneous material generated by AI\\n\\n## Explanatory notes\\n\\n  1. ^ Jump up to: _**a**_ _**b**_ This list of intelligent traits is based on the topics covered by the major AI textbooks, including: Russell & Norvig (2021), Luger & Stubblefield (2004), Poole, Mackworth & Goebel (1998) and Nilsson (1998)\\n  2. ^ Jump up to: _**a**_ _**b**_ This list of tools is based on the topics covered by the major AI textbooks, including: Russell & Norvig (2021), Luger & Stubblefield (2004), Poole, Mackworth & Goebel (1998) and Nilsson (1998)\\n  3. **^** It is among the reasons that [expert systems](/wiki/Expert_system \"Expert system\") proved to be inefficient for capturing knowledge.[30][31]\\n  4. **^** \"Rational agent\" is general term used in [economics](/wiki/Economics \"Economics\"), [philosophy](/wiki/Philosophy \"Philosophy\") and theoretical artificial intelligence. It can refer to anything that directs its behavior to accomplish goals, such as a person, an animal, a corporation, a nation, or in the case of AI, a computer program.\\n  5. **^** [Alan Turing](/wiki/Alan_Turing \"Alan Turing\") discussed the centrality of learning as early as 1950, in his classic paper \"[Computing Machinery and Intelligence](/wiki/Computing_Machinery_and_Intelligence \"Computing Machinery and Intelligence\")\".[42] In 1956, at the original Dartmouth AI summer conference, [Ray Solomonoff](/wiki/Ray_Solomonoff \"Ray Solomonoff\") wrote a report on unsupervised probabilistic machine learning: \"An Inductive Inference Machine\".[43]\\n  6. **^** See [AI winter § Machine translation and the ALPAC report of 1966](/wiki/AI_winter#Machine_translation_and_the_ALPAC_report_of_1966 \"AI winter\")\\n  7. **^** Compared with symbolic logic, formal Bayesian inference is computationally expensive. For inference to be tractable, most observations must be [conditionally independent](/wiki/Conditionally_independent \"Conditionally independent\") of one another. [AdSense](/wiki/AdSense \"AdSense\") uses a Bayesian network with over 300 million edges to learn which ads to serve.[93]\\n  8. **^** Expectation–maximization, one of the most popular algorithms in machine learning, allows clustering in the presence of unknown [latent variables](/wiki/Latent_variables \"Latent variables\").[95]\\n  9. **^** Some form of deep neural networks (without a specific learning algorithm) were described by: [Warren S. McCulloch](/wiki/Warren_S._McCulloch \"Warren S. McCulloch\") and [Walter Pitts](/wiki/Walter_Pitts \"Walter Pitts\") (1943)[115] [Alan Turing](/wiki/Alan_Turing \"Alan Turing\") (1948);[116] [Karl Steinbuch](/wiki/Karl_Steinbuch \"Karl Steinbuch\") and [Roger David Joseph](/w/index.php?title=Roger_David_Joseph&action=edit&redlink=1 \"Roger David Joseph \\\\(page does not exist\\\\)\") (1961).[117] Deep or recurrent networks that learned (or used gradient descent) were developed by: [Frank Rosenblatt](/wiki/Frank_Rosenblatt \"Frank Rosenblatt\")(1957);[116] [Oliver Selfridge](/wiki/Oliver_Selfridge \"Oliver Selfridge\") (1959);[117] [Alexey Ivakhnenko](/wiki/Alexey_Ivakhnenko \"Alexey Ivakhnenko\") and [Valentin Lapa](/w/index.php?title=Valentin_Lapa&action=edit&redlink=1 \"Valentin Lapa \\\\(page does not exist\\\\)\") (1965);[118] [Kaoru Nakano](/w/index.php?title=Kaoru_Nakano&action=edit&redlink=1 \"Kaoru Nakano \\\\(page does not exist\\\\)\") (1971);[119] [Shun-Ichi Amari](/wiki/Shun-Ichi_Amari \"Shun-Ichi Amari\") (1972);[119] [John Joseph Hopfield](/wiki/John_Joseph_Hopfield \"John Joseph Hopfield\") (1982).[119] Precursors to backpropagation were developed by: [Henry J. Kelley](/wiki/Henry_J._Kelley \"Henry J. Kelley\") (1960);[116] [Arthur E. Bryson](/wiki/Arthur_E._Bryson \"Arthur E. Bryson\") (1962);[116] [Stuart Dreyfus](/wiki/Stuart_Dreyfus \"Stuart Dreyfus\") (1962);[116] [Arthur E. Bryson](/wiki/Arthur_E._Bryson \"Arthur E. Bryson\") and [Yu-Chi Ho](/wiki/Yu-Chi_Ho \"Yu-Chi Ho\") (1969);[116] Backpropagation was independently developed by: [Seppo Linnainmaa](/wiki/Seppo_Linnainmaa \"Seppo Linnainmaa\") (1970);[120] [Paul Werbos](/wiki/Paul_Werbos \"Paul Werbos\") (1974).[116]\\n  10. **^** [Geoffrey Hinton](/wiki/Geoffrey_Hinton \"Geoffrey Hinton\") said, of his work on neural networks in the 1990s, \"our labeled datasets were thousands of times too small. [And] our computers were millions of times too slow.\"[121]\\n  11. **^** In statistics, a [bias](/wiki/Bias_\\\\(statistics\\\\) \"Bias \\\\(statistics\\\\)\") is a systematic error or deviation from the correct value. But in the context of [fairness](/wiki/Fairness_\\\\(machine_learning\\\\) \"Fairness \\\\(machine learning\\\\)\"), it refers to a tendency in favor or against a certain group or individual characteristic, usually in a way that is considered unfair or harmful. A statistically unbiased AI system that produces disparate outcomes for different demographic groups may thus be viewed as biased in the ethical sense.[205]\\n  12. **^** Including [Jon Kleinberg](/wiki/Jon_Kleinberg \"Jon Kleinberg\") ([Cornell University](/wiki/Cornell_University \"Cornell University\")), Sendhil Mullainathan ([University of Chicago](/wiki/University_of_Chicago \"University of Chicago\")), Cynthia Chouldechova ([Carnegie Mellon](/wiki/Carnegie_Mellon \"Carnegie Mellon\")) and Sam Corbett-Davis ([Stanford](/wiki/Stanford \"Stanford\"))[214]\\n  13. **^** Moritz Hardt (a director at the [Max Planck Institute for Intelligent Systems](/wiki/Max_Planck_Institute_for_Intelligent_Systems \"Max Planck Institute for Intelligent Systems\")) argues that machine learning \"is fundamentally the wrong tool for a lot of domains, where you\\'re trying to design interventions and mechanisms that change the world.\"[219]\\n  14. **^** When the law was passed in 2018, it still contained a form of this provision.\\n  15. **^** This is the [United Nations](/wiki/United_Nations \"United Nations\")\\' definition, and includes things like [land mines](/wiki/Land_mines \"Land mines\") as well.[233]\\n  16. **^** See table 4; 9% is both the OECD average and the U.S. average.[244]\\n  17. **^** Sometimes called a \"[robopocalypse](/wiki/Robopocalypse \"Robopocalypse\")\"[252]\\n  18. **^** \"Electronic brain\" was the term used by the press around this time.[305][307]\\n  19. **^** Daniel Crevier wrote, \"the conference is generally recognized as the official birthdate of the new science.\"[310] [Russell](/wiki/Stuart_J._Russell \"Stuart J. Russell\") and [Norvig](/wiki/Norvig \"Norvig\") called the conference \"the inception of artificial intelligence.\"[115]\\n  20. **^** [Russell](/wiki/Stuart_J._Russell \"Stuart J. Russell\") and [Norvig](/wiki/Norvig \"Norvig\") wrote \"for the next 20 years the field would be dominated by these people and their students.\"[311]\\n  21. **^** [Russell](/wiki/Stuart_J._Russell \"Stuart J. Russell\") and [Norvig](/wiki/Norvig \"Norvig\") wrote \"it was astonishing whenever a computer did anything kind of smartish\".[312]\\n  22. **^** The programs described are [Arthur Samuel](/wiki/Arthur_Samuel_\\\\(computer_scientist\\\\) \"Arthur Samuel \\\\(computer scientist\\\\)\")\\'s checkers program for the [IBM 701](/wiki/IBM_701 \"IBM 701\"), [Daniel Bobrow](/wiki/Daniel_Bobrow \"Daniel Bobrow\")\\'s [STUDENT](/wiki/STUDENT \"STUDENT\"), [Newell](/wiki/Allen_Newell \"Allen Newell\") and [Simon](/wiki/Herbert_A._Simon \"Herbert A. Simon\")\\'s [Logic Theorist](/wiki/Logic_Theorist \"Logic Theorist\") and [Terry Winograd](/wiki/Terry_Winograd \"Terry Winograd\")\\'s [SHRDLU](/wiki/SHRDLU \"SHRDLU\").\\n  23. **^** [Russell](/wiki/Stuart_J._Russell \"Stuart J. Russell\") and [Norvig](/wiki/Norvig \"Norvig\") write: \"in almost all cases, these early systems failed on more difficult problems\"[316]\\n  24. **^** [Embodied](/wiki/Embodied_mind \"Embodied mind\") approaches to AI[323] were championed by [Hans Moravec](/wiki/Hans_Moravec \"Hans Moravec\")[324] and [Rodney Brooks](/wiki/Rodney_Brooks \"Rodney Brooks\")[325] and went by many names: [Nouvelle AI](/wiki/Nouvelle_AI \"Nouvelle AI\").[325] [Developmental robotics](/wiki/Developmental_robotics \"Developmental robotics\").[326]\\n  25. **^** Matteo Wong wrote in [The Atlantic](/wiki/The_Atlantic \"The Atlantic\"): \"Whereas for decades, computer-science fields such as natural-language processing, computer vision, and robotics used extremely different methods, now they all use a programming method called \"deep learning.\" As a result, their code and approaches have become more similar, and their models are easier to integrate into one another.\"[332]\\n  26. **^** Jack Clark wrote in [Bloomberg](/wiki/Bloomberg_News \"Bloomberg News\"): \"After a half-decade of quiet breakthroughs in artificial intelligence, 2015 has been a landmark year. Computers are smarter and learning faster than ever\", and noted that the number of software projects that use machine learning at [Google](/wiki/Google \"Google\") increased from a \"sporadic usage\" in 2012 to more than 2,700 projects in 2015.[334]\\n  27. **^** [Nils Nilsson](/wiki/Nils_Nilsson_\\\\(researcher\\\\) \"Nils Nilsson \\\\(researcher\\\\)\") wrote in 1983: \"Simply put, there is wide disagreement in the field about what AI is all about.\"[352]\\n  28. **^** Daniel Crevier wrote that \"time has proven the accuracy and perceptiveness of some of Dreyfus\\'s comments. Had he formulated them less aggressively, constructive actions they suggested might have been taken much earlier.\"[357]\\n  29. **^** Searle presented this definition of \"Strong AI\" in 1999.[367] Searle\\'s original formulation was \"The appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to understand and have other cognitive states.\"[368] Strong AI is defined similarly by [Russell](/wiki/Stuart_J._Russell \"Stuart J. Russell\") and [Norvig](/wiki/Norvig \"Norvig\"): \"Stong AI – the assertion that machines that do so are _actually_ thinking (as opposed to _simulating_ thinking).\"[369]\\n\\n## References\\n\\n  1. ^ Jump up to: _**a**_ _**b**_ _**c**_ Russell & Norvig (2021), pp. 1–4.\\n  2. **^** [AI set to exceed human brain power](http://www.cnn.com/2006/TECH/science/07/24/ai.bostrom/) [Archived](https://web.archive.org/web/20080219001624/http://www.cnn.com/2006/TECH/science/07/24/ai.bostrom/) 2008-02-19 at the [Wayback Machine](/wiki/Wayback_Machine \"Wayback Machine\") CNN.com (July 26, 2006)\\n  3. **^** Kaplan, Andreas; Haenlein, Michael (2019). \"Siri, Siri, in my hand: Who\\'s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence\". _Business Horizons_. **62** : 15–25. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1016/j.bushor.2018.08.004](https://doi.org/10.1016%2Fj.bushor.2018.08.004). [ISSN](/wiki/ISSN_\\\\(identifier\\\\) \"ISSN \\\\(identifier\\\\)\") [0007-6813](https://search.worldcat.org/issn/0007-6813). [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [158433736](https://api.semanticscholar.org/CorpusID:158433736).\\n  4. ^ Jump up to: _**a**_ _**b**_ _**c**_ [Artificial general intelligence](/wiki/Artificial_general_intelligence \"Artificial general intelligence\"): Russell & Norvig (2021, pp. 32–33, 1020–1021)  \\nProposal for the modern version: Pennachin & Goertzel (2007)  \\nWarnings of overspecialization in AI from leading researchers: Nilsson (1995),\\nMcCarthy (2007), Beal & Winston (2009)\\n\\n  5. **^** Russell & Norvig (2021, §1.2).\\n  6. ^ Jump up to: _**a**_ _**b**_ [Dartmouth workshop](/wiki/Dartmouth_workshop \"Dartmouth workshop\"): Russell & Norvig (2021, p. 18), McCorduck (2004, pp. 111–136), NRC (1999, pp. 200–201)  \\nThe proposal: McCarthy et al. (1955)\\n\\n  7. ^ Jump up to: _**a**_ _**b**_ Successful programs of the 1960s: McCorduck (2004, pp. 243–252), Crevier (1993, pp. 52–107), Moravec (1988, p. 9), Russell & Norvig (2021, pp. 19–21)\\n  8. ^ Jump up to: _**a**_ _**b**_ Funding initiatives in the early 1980s: [Fifth Generation Project](/wiki/Fifth_Generation_Project \"Fifth Generation Project\") (Japan), [Alvey](/wiki/Alvey \"Alvey\") (UK), [Microelectronics and Computer Technology Corporation](/wiki/Microelectronics_and_Computer_Technology_Corporation \"Microelectronics and Computer Technology Corporation\") (US), [Strategic Computing Initiative](/wiki/Strategic_Computing_Initiative \"Strategic Computing Initiative\") (US): McCorduck (2004, pp. 426–441), Crevier (1993, pp. 161–162, 197–203, 211, 240), Russell & Norvig (2021, p. 23), NRC (1999, pp. 210–211), Newquist (1994, pp. 235–248)\\n  9. ^ Jump up to: _**a**_ _**b**_ First [AI Winter](/wiki/AI_Winter \"AI Winter\"), [Lighthill report](/wiki/Lighthill_report \"Lighthill report\"), [Mansfield Amendment](/wiki/Mansfield_Amendment \"Mansfield Amendment\"): Crevier (1993, pp. 115–117), Russell & Norvig (2021, pp. 21–22), NRC (1999, pp. 212–213), Howe (1994), Newquist (1994, pp. 189–201)\\n  10. ^ Jump up to: _**a**_ _**b**_ Second [AI Winter](/wiki/AI_Winter \"AI Winter\"): Russell & Norvig (2021, p. 24), McCorduck (2004, pp. 430–435), Crevier (1993, pp. 209–210), NRC (1999, pp. 214–216), Newquist (1994, pp. 301–318)\\n  11. ^ Jump up to: _**a**_ _**b**_ [Deep learning](/wiki/Deep_learning \"Deep learning\") revolution, [AlexNet](/wiki/AlexNet \"AlexNet\"): Goldman (2022), Russell & Norvig (2021, p. 26), McKinsey (2018)\\n  12. **^** Toews (2023).\\n  13. **^** Problem-solving, puzzle solving, game playing, and deduction: Russell & Norvig (2021, chpt. 3–5), Russell & Norvig (2021, chpt. 6) ([constraint satisfaction](/wiki/Constraint_satisfaction \"Constraint satisfaction\")), Poole, Mackworth & Goebel (1998, chpt. 2, 3, 7, 9), Luger & Stubblefield (2004, chpt. 3, 4, 6, 8), Nilsson (1998, chpt. 7–12)\\n  14. **^** Uncertain reasoning: Russell & Norvig (2021, chpt. 12–18), Poole, Mackworth & Goebel (1998, pp. 345–395), Luger & Stubblefield (2004, pp. 333–381), Nilsson (1998, chpt. 7–12)\\n  15. ^ Jump up to: _**a**_ _**b**_ _**c**_ [Intractability and efficiency](/wiki/Intractably \"Intractably\") and the [combinatorial explosion](/wiki/Combinatorial_explosion \"Combinatorial explosion\"): Russell & Norvig (2021, p. 21)\\n  16. ^ Jump up to: _**a**_ _**b**_ _**c**_ Psychological evidence of the prevalence of sub-symbolic reasoning and knowledge: Kahneman (2011), Dreyfus & Dreyfus (1986), Wason & Shapiro (1966), Kahneman, Slovic & Tversky (1982)\\n  17. **^** [Knowledge representation](/wiki/Knowledge_representation \"Knowledge representation\") and [knowledge engineering](/wiki/Knowledge_engineering \"Knowledge engineering\"): Russell & Norvig (2021, chpt. 10), Poole, Mackworth & Goebel (1998, pp. 23–46, 69–81, 169–233, 235–277, 281–298, 319–345), Luger & Stubblefield (2004, pp. 227–243), Nilsson (1998, chpt. 17.1–17.4, 18)\\n  18. **^** Smoliar & Zhang (1994).\\n  19. **^** Neumann & Möller (2008).\\n  20. **^** Kuperman, Reichley & Bailey (2006).\\n  21. **^** McGarry (2005).\\n  22. **^** Bertini, Del Bimbo & Torniai (2006).\\n  23. **^** Russell & Norvig (2021), pp. 272.\\n  24. **^** Representing categories and relations: [Semantic networks](/wiki/Semantic_network \"Semantic network\"), [description logics](/wiki/Description_logic \"Description logic\"), [inheritance](/wiki/Inheritance_\\\\(object-oriented_programming\\\\) \"Inheritance \\\\(object-oriented programming\\\\)\") (including [frames](/wiki/Frame_\\\\(artificial_intelligence\\\\) \"Frame \\\\(artificial intelligence\\\\)\"), and [scripts](/wiki/Scripts_\\\\(artificial_intelligence\\\\) \"Scripts \\\\(artificial intelligence\\\\)\")): Russell & Norvig (2021, §10.2 & 10.5), Poole, Mackworth & Goebel (1998, pp. 174–177), Luger & Stubblefield (2004, pp. 248–258), Nilsson (1998, chpt. 18.3)\\n  25. **^** Representing events and time:[Situation calculus](/wiki/Situation_calculus \"Situation calculus\"), [event calculus](/wiki/Event_calculus \"Event calculus\"), [fluent calculus](/wiki/Fluent_calculus \"Fluent calculus\") (including solving the [frame problem](/wiki/Frame_problem \"Frame problem\")): Russell & Norvig (2021, §10.3), Poole, Mackworth & Goebel (1998, pp. 281–298), Nilsson (1998, chpt. 18.2)\\n  26. **^** [Causal calculus](/wiki/Causality#Causal_calculus \"Causality\"): Poole, Mackworth & Goebel (1998, pp. 335–337)\\n  27. **^** Representing knowledge about knowledge: Belief calculus, [modal logics](/wiki/Modal_logic \"Modal logic\"): Russell & Norvig (2021, §10.4), Poole, Mackworth & Goebel (1998, pp. 275–277)\\n  28. ^ Jump up to: _**a**_ _**b**_ [Default reasoning](/wiki/Default_reasoning \"Default reasoning\"), [Frame problem](/wiki/Frame_problem \"Frame problem\"), [default logic](/wiki/Default_logic \"Default logic\"), [non-monotonic logics](/wiki/Non-monotonic_logic \"Non-monotonic logic\"), [circumscription](/wiki/Circumscription_\\\\(logic\\\\) \"Circumscription \\\\(logic\\\\)\"), [closed world assumption](/wiki/Closed_world_assumption \"Closed world assumption\"), [abduction](/wiki/Abductive_reasoning \"Abductive reasoning\"): Russell & Norvig (2021, §10.6), Poole, Mackworth & Goebel (1998, pp. 248–256, 323–335), Luger & Stubblefield (2004, pp. 335–363), Nilsson (1998, ~18.3.3) (Poole _et al._ places abduction under \"default reasoning\". Luger _et al._ places this under \"uncertain reasoning\").\\n  29. ^ Jump up to: _**a**_ _**b**_ Breadth of commonsense knowledge: Lenat & Guha (1989, Introduction), Crevier (1993, pp. 113–114), Moravec (1988, p. 13), Russell & Norvig (2021, pp. 241, 385, 982) ([qualification problem](/wiki/Qualification_problem \"Qualification problem\"))\\n  30. **^** Newquist (1994), p. 296.\\n  31. **^** Crevier (1993), pp. 204–208.\\n  32. **^** Russell & Norvig (2021), p. 528.\\n  33. **^** [Automated planning](/wiki/Automated_planning \"Automated planning\"): Russell & Norvig (2021, chpt. 11).\\n  34. **^** [Automated decision making](/wiki/Automated_decision_making \"Automated decision making\"), [Decision theory](/wiki/Decision_theory \"Decision theory\"): Russell & Norvig (2021, chpt. 16–18).\\n  35. **^** [Classical planning](/wiki/Automated_planning_and_scheduling#classical_planning \"Automated planning and scheduling\"): Russell & Norvig (2021, Section 11.2).\\n  36. **^** Sensorless or \"conformant\" planning, contingent planning, replanning (a.k.a online planning): Russell & Norvig (2021, Section 11.5).\\n  37. **^** Uncertain preferences: Russell & Norvig (2021, Section 16.7) [Inverse reinforcement learning](/wiki/Inverse_reinforcement_learning \"Inverse reinforcement learning\"): Russell & Norvig (2021, Section 22.6)\\n  38. **^** [Information value theory](/wiki/Information_value_theory \"Information value theory\"): Russell & Norvig (2021, Section 16.6).\\n  39. **^** [Markov decision process](/wiki/Markov_decision_process \"Markov decision process\"): Russell & Norvig (2021, chpt. 17).\\n  40. **^** [Game theory](/wiki/Game_theory \"Game theory\") and multi-agent decision theory: Russell & Norvig (2021, chpt. 18).\\n  41. **^** [Learning](/wiki/Machine_learning \"Machine learning\"): Russell & Norvig (2021, chpt. 19–22), Poole, Mackworth & Goebel (1998, pp. 397–438), Luger & Stubblefield (2004, pp. 385–542), Nilsson (1998, chpt. 3.3, 10.3, 17.5, 20)\\n  42. **^** Turing (1950).\\n  43. **^** Solomonoff (1956).\\n  44. **^** [Unsupervised learning](/wiki/Unsupervised_learning \"Unsupervised learning\"): Russell & Norvig (2021, pp. 653) (definition), Russell & Norvig (2021, pp. 738–740) ([cluster analysis](/wiki/Cluster_analysis \"Cluster analysis\")), Russell & Norvig (2021, pp. 846–860) ([word embedding](/wiki/Word_embedding \"Word embedding\"))\\n  45. ^ Jump up to: _**a**_ _**b**_ [Supervised learning](/wiki/Supervised_learning \"Supervised learning\"): Russell & Norvig (2021, §19.2) (Definition), Russell & Norvig (2021, Chpt. 19–20) (Techniques)\\n  46. **^** [Reinforcement learning](/wiki/Reinforcement_learning \"Reinforcement learning\"): Russell & Norvig (2021, chpt. 22), Luger & Stubblefield (2004, pp. 442–449)\\n  47. **^** [Transfer learning](/wiki/Transfer_learning \"Transfer learning\"): Russell & Norvig (2021, pp. 281), The Economist (2016)\\n  48. **^** [\"Artificial Intelligence (AI): What Is AI and How Does It Work? | Built In\"](https://builtin.com/artificial-intelligence). _builtin.com_. Retrieved 30 October 2023.\\n  49. **^** [Computational learning theory](/wiki/Computational_learning_theory \"Computational learning theory\"): Russell & Norvig (2021, pp. 672–674), Jordan & Mitchell (2015)\\n  50. **^** [Natural language processing](/wiki/Natural_language_processing \"Natural language processing\") (NLP): Russell & Norvig (2021, chpt. 23–24), Poole, Mackworth & Goebel (1998, pp. 91–104), Luger & Stubblefield (2004, pp. 591–632)\\n  51. **^** Subproblems of [NLP](/wiki/Natural_language_processing \"Natural language processing\"): Russell & Norvig (2021, pp. 849–850)\\n  52. **^** Russell & Norvig (2021), pp. 856–858.\\n  53. **^** Dickson (2022).\\n  54. **^** Modern statistical and deep learning approaches to [NLP](/wiki/Natural_language_processing \"Natural language processing\"): Russell & Norvig (2021, chpt. 24), Cambria & White (2014)\\n  55. **^** Vincent (2019).\\n  56. **^** Russell & Norvig (2021), pp. 875–878.\\n  57. **^** Bushwick (2023).\\n  58. **^** [Computer vision](/wiki/Computer_vision \"Computer vision\"): Russell & Norvig (2021, chpt. 25), Nilsson (1998, chpt. 6)\\n  59. **^** Russell & Norvig (2021), pp. 849–850.\\n  60. **^** Russell & Norvig (2021), pp. 895–899.\\n  61. **^** Russell & Norvig (2021), pp. 899–901.\\n  62. **^** Challa et al. (2011).\\n  63. **^** Russell & Norvig (2021), pp. 931–938.\\n  64. **^** MIT AIL (2014).\\n  65. **^** [Affective computing](/wiki/Affective_computing \"Affective computing\"): Thro (1993), Edelson (1991), Tao & Tan (2005), Scassellati (2002)\\n  66. **^** Waddell (2018).\\n  67. **^** Poria et al. (2017).\\n  68. **^** [Search algorithms](/wiki/Search_algorithm \"Search algorithm\"): Russell & Norvig (2021, chpts. 3–5), Poole, Mackworth & Goebel (1998, pp. 113–163), Luger & Stubblefield (2004, pp. 79–164, 193–219), Nilsson (1998, chpts. 7–12)\\n  69. **^** [State space search](/wiki/State_space_search \"State space search\"): Russell & Norvig (2021, chpt. 3)\\n  70. **^** Russell & Norvig (2021), sect. 11.2.\\n  71. **^** [Uninformed searches](/wiki/Uninformed_search \"Uninformed search\") ([breadth first search](/wiki/Breadth_first_search \"Breadth first search\"), [depth-first search](/wiki/Depth-first_search \"Depth-first search\") and general [state space search](/wiki/State_space_search \"State space search\")): Russell & Norvig (2021, sect. 3.4), Poole, Mackworth & Goebel (1998, pp. 113–132), Luger & Stubblefield (2004, pp. 79–121), Nilsson (1998, chpt. 8)\\n  72. **^** [Heuristic](/wiki/Heuristic \"Heuristic\") or informed searches (e.g., greedy [best first](/wiki/Best-first_search \"Best-first search\") and [A*](/wiki/A*_search_algorithm \"A* search algorithm\")): Russell & Norvig (2021, sect. 3.5), Poole, Mackworth & Goebel (1998, pp. 132–147), Poole & Mackworth (2017, sect. 3.6), Luger & Stubblefield (2004, pp. 133–150)\\n  73. **^** [Adversarial search](/wiki/Adversarial_search \"Adversarial search\"): Russell & Norvig (2021, chpt. 5)\\n  74. **^** [Local](/wiki/Local_search_\\\\(optimization\\\\) \"Local search \\\\(optimization\\\\)\") or \"[optimization](/wiki/Optimization \"Optimization\")\" search: Russell & Norvig (2021, chpt. 4)\\n  75. **^** Singh Chauhan, Nagesh (18 December 2020). [\"Optimization Algorithms in Neural Networks\"](https://www.kdnuggets.com/optimization-algorithms-in-neural-networks). _KDnuggets_. Retrieved 13 January 2024.\\n  76. **^** [Evolutionary computation](/wiki/Evolutionary_computation \"Evolutionary computation\"): Russell & Norvig (2021, sect. 4.1.2)\\n  77. **^** Merkle & Middendorf (2013).\\n  78. **^** [Logic](/wiki/Logic \"Logic\"): Russell & Norvig (2021, chpts. 6–9), Luger & Stubblefield (2004, pp. 35–77), Nilsson (1998, chpt. 13–16)\\n  79. **^** [Propositional logic](/wiki/Propositional_logic \"Propositional logic\"): Russell & Norvig (2021, chpt. 6), Luger & Stubblefield (2004, pp. 45–50), Nilsson (1998, chpt. 13)\\n  80. **^** [First-order logic](/wiki/First-order_logic \"First-order logic\") and features such as [equality](/wiki/Equality_\\\\(mathematics\\\\) \"Equality \\\\(mathematics\\\\)\"): Russell & Norvig (2021, chpt. 7), Poole, Mackworth & Goebel (1998, pp. 268–275), Luger & Stubblefield (2004, pp. 50–62), Nilsson (1998, chpt. 15)\\n  81. **^** [Logical inference](/wiki/Logical_inference \"Logical inference\"): Russell & Norvig (2021, chpt. 10)\\n  82. **^** logical deduction as search: Russell & Norvig (2021, sects. 9.3, 9.4), Poole, Mackworth & Goebel (1998, pp. ~46–52), Luger & Stubblefield (2004, pp. 62–73), Nilsson (1998, chpt. 4.2, 7.2)\\n  83. **^** [Resolution](/wiki/Resolution_\\\\(logic\\\\) \"Resolution \\\\(logic\\\\)\") and [unification](/wiki/Unification_\\\\(computer_science\\\\) \"Unification \\\\(computer science\\\\)\"): Russell & Norvig (2021, sections 7.5.2, 9.2, 9.5)\\n  84. **^** Warren, D.H.; Pereira, L.M.; Pereira, F. (1977). \"Prolog-the language and its implementation compared with Lisp\". _[ACM SIGPLAN Notices](/wiki/ACM_SIGPLAN_Notices \"ACM SIGPLAN Notices\")_. **12** (8): 109–115. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1145/872734.806939](https://doi.org/10.1145%2F872734.806939).\\n  85. **^** Fuzzy logic: Russell & Norvig (2021, pp. 214, 255, 459), Scientific American (1999)\\n  86. ^ Jump up to: _**a**_ _**b**_ Stochastic methods for uncertain reasoning: Russell & Norvig (2021, chpt. 12–18, 20), Poole, Mackworth & Goebel (1998, pp. 345–395), Luger & Stubblefield (2004, pp. 165–191, 333–381), Nilsson (1998, chpt. 19)\\n  87. **^** [decision theory](/wiki/Decision_theory \"Decision theory\") and [decision analysis](/wiki/Decision_analysis \"Decision analysis\"): Russell & Norvig (2021, chpt. 16–18), Poole, Mackworth & Goebel (1998, pp. 381–394)\\n  88. **^** [Information value theory](/wiki/Information_value_theory \"Information value theory\"): Russell & Norvig (2021, sect. 16.6)\\n  89. **^** [Markov decision processes](/wiki/Markov_decision_process \"Markov decision process\") and dynamic [decision networks](/wiki/Decision_network \"Decision network\"): Russell & Norvig (2021, chpt. 17)\\n  90. ^ Jump up to: _**a**_ _**b**_ _**c**_ Stochastic temporal models: Russell & Norvig (2021, chpt. 14) [Hidden Markov model](/wiki/Hidden_Markov_model \"Hidden Markov model\"): Russell & Norvig (2021, sect. 14.3) [Kalman filters](/wiki/Kalman_filter \"Kalman filter\"): Russell & Norvig (2021, sect. 14.4) [Dynamic Bayesian networks](/wiki/Dynamic_Bayesian_network \"Dynamic Bayesian network\"): Russell & Norvig (2021, sect. 14.5)\\n  91. **^** [Game theory](/wiki/Game_theory \"Game theory\") and [mechanism design](/wiki/Mechanism_design \"Mechanism design\"): Russell & Norvig (2021, chpt. 18)\\n  92. **^** [Bayesian networks](/wiki/Bayesian_network \"Bayesian network\"): Russell & Norvig (2021, sects. 12.5–12.6, 13.4–13.5, 14.3–14.5, 16.5, 20.2–20.3), Poole, Mackworth & Goebel (1998, pp. 361–381), Luger & Stubblefield (2004, pp. ~182–190, ≈363–379), Nilsson (1998, chpt. 19.3–19.4)\\n  93. **^** Domingos (2015), chpt. 6.\\n  94. **^** [Bayesian inference](/wiki/Bayesian_inference \"Bayesian inference\") algorithm: Russell & Norvig (2021, sect. 13.3–13.5), Poole, Mackworth & Goebel (1998, pp. 361–381), Luger & Stubblefield (2004, pp. ~363–379), Nilsson (1998, chpt. 19.4 & 7)\\n  95. **^** Domingos (2015), p. 210.\\n  96. **^** [Bayesian learning](/wiki/Bayesian_learning \"Bayesian learning\") and the [expectation–maximization algorithm](/wiki/Expectation%E2%80%93maximization_algorithm \"Expectation–maximization algorithm\"): Russell & Norvig (2021, chpt. 20), Poole, Mackworth & Goebel (1998, pp. 424–433), Nilsson (1998, chpt. 20), Domingos (2015, p. 210)\\n  97. **^** [Bayesian decision theory](/wiki/Bayesian_decision_theory \"Bayesian decision theory\") and Bayesian [decision networks](/wiki/Decision_network \"Decision network\"): Russell & Norvig (2021, sect. 16.5)\\n  98. **^** Statistical learning methods and [classifiers](/wiki/Classifier_\\\\(mathematics\\\\) \"Classifier \\\\(mathematics\\\\)\"): Russell & Norvig (2021, chpt. 20),\\n  99. **^** [Ciaramella, Alberto](/wiki/Alberto_Ciaramella \"Alberto Ciaramella\"); Ciaramella, Marco (2024). _Introduction to Artificial Intelligence: from data analysis to generative AI_. Intellisemantic Editions. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-8-8947-8760-3](/wiki/Special:BookSources/978-8-8947-8760-3 \"Special:BookSources/978-8-8947-8760-3\").\\n  100. **^** [Decision trees](/wiki/Alternating_decision_tree \"Alternating decision tree\"): Russell & Norvig (2021, sect. 19.3), Domingos (2015, p. 88)\\n  101. **^** [Non-parameteric](/wiki/Nonparametric_statistics \"Nonparametric statistics\") learning models such as [K-nearest neighbor](/wiki/K-nearest_neighbor \"K-nearest neighbor\") and [support vector machines](/wiki/Support_vector_machines \"Support vector machines\"): Russell & Norvig (2021, sect. 19.7), Domingos (2015, p. 187) (k-nearest neighbor) \\n     * Domingos (2015, p. 88) (kernel methods)\\n  102. **^** Domingos (2015), p. 152.\\n  103. **^** [Naive Bayes classifier](/wiki/Naive_Bayes_classifier \"Naive Bayes classifier\"): Russell & Norvig (2021, sect. 12.6), Domingos (2015, p. 152)\\n  104. ^ Jump up to: _**a**_ _**b**_ Neural networks: Russell & Norvig (2021, chpt. 21), Domingos (2015, Chapter 4)\\n  105. **^** Gradient calculation in computational graphs, [backpropagation](/wiki/Backpropagation \"Backpropagation\"), [automatic differentiation](/wiki/Automatic_differentiation \"Automatic differentiation\"): Russell & Norvig (2021, sect. 21.2), Luger & Stubblefield (2004, pp. 467–474), Nilsson (1998, chpt. 3.3)\\n  106. **^** [Universal approximation theorem](/wiki/Universal_approximation_theorem \"Universal approximation theorem\"): Russell & Norvig (2021, p. 752) The theorem: Cybenko (1988), Hornik, Stinchcombe & White (1989)\\n  107. **^** [Feedforward neural networks](/wiki/Feedforward_neural_network \"Feedforward neural network\"): Russell & Norvig (2021, sect. 21.1)\\n  108. **^** [Recurrent neural networks](/wiki/Recurrent_neural_network \"Recurrent neural network\"): Russell & Norvig (2021, sect. 21.6)\\n  109. **^** [Perceptrons](/wiki/Perceptron \"Perceptron\"): Russell & Norvig (2021, pp. 21, 22, 683, 22)\\n  110. ^ Jump up to: _**a**_ _**b**_ [Deep learning](/wiki/Deep_learning \"Deep learning\"): Russell & Norvig (2021, chpt. 21), Goodfellow, Bengio & Courville (2016), Hinton _et al._ (2016), Schmidhuber (2015)\\n  111. **^** [Convolutional neural networks](/wiki/Convolutional_neural_networks \"Convolutional neural networks\"): Russell & Norvig (2021, sect. 21.3)\\n  112. **^** Deng & Yu (2014), pp. 199–200.\\n  113. **^** Ciresan, Meier & Schmidhuber (2012).\\n  114. **^** Russell & Norvig (2021), p. 751.\\n  115. ^ Jump up to: _**a**_ _**b**_ _**c**_ Russell & Norvig (2021), p. 17.\\n  116. ^ Jump up to: _**a**_ _**b**_ _**c**_ _**d**_ _**e**_ _**f**_ _**g**_ Russell & Norvig (2021), p. 785.\\n  117. ^ Jump up to: _**a**_ _**b**_ Schmidhuber (2022), sect. 5.\\n  118. **^** Schmidhuber (2022), sect. 6.\\n  119. ^ Jump up to: _**a**_ _**b**_ _**c**_ Schmidhuber (2022), sect. 7.\\n  120. **^** Schmidhuber (2022), sect. 8.\\n  121. **^** Quoted in Christian (2020, p. 22)\\n  122. **^** Smith (2023).\\n  123. **^** [\"Explained: Generative AI\"](https://news.mit.edu/2023/explained-generative-ai-1109). 9 November 2023.\\n  124. **^** [\"AI Writing and Content Creation Tools\"](https://mitsloanedtech.mit.edu/ai/tools/writing). MIT Sloan Teaching & Learning Technologies. [Archived](https://web.archive.org/web/20231225232503/https://mitsloanedtech.mit.edu/ai/tools/writing/) from the original on 25 December 2023. Retrieved 25 December 2023.\\n  125. **^** Marmouyet (2023).\\n  126. **^** Kobielus (2019).\\n  127. **^** Thomason, James (21 May 2024). [\"Mojo Rising: The resurgence of AI-first programming languages\"](https://venturebeat.com/ai/mojo-rising-the-resurgence-of-ai-first-programming-languages). _VentureBeat_. [Archived](https://web.archive.org/web/20240627143853/https://venturebeat.com/ai/mojo-rising-the-resurgence-of-ai-first-programming-languages/) from the original on 27 June 2024. Retrieved 26 May 2024.\\n  128. **^** Wodecki, Ben (5 May 2023). [\"7 AI Programming Languages You Need to Know\"](https://aibusiness.com/verticals/7-ai-programming-languages-you-need-to-know). _AI Business_. [Archived](https://web.archive.org/web/20240725164443/https://aibusiness.com/verticals/7-ai-programming-languages-you-need-to-know) from the original on 25 July 2024. Retrieved 5 October 2024.\\n  129. **^** Plumb, Taryn (18 September 2024). [\"Why Jensen Huang and Marc Benioff see \\'gigantic\\' opportunity for agentic AI\"](https://venturebeat.com/ai/why-jensen-huang-and-marc-benioff-see-gigantic-opportunity-for-agentic-ai/). _VentureBeat_. [Archived](https://web.archive.org/web/20241005165649/https://venturebeat.com/ai/why-jensen-huang-and-marc-benioff-see-gigantic-opportunity-for-agentic-ai/) from the original on 5 October 2024. Retrieved 4 October 2024.\\n  130. **^** Davenport, T; Kalakota, R (June 2019). [\"The potential for artificial intelligence in healthcare\"](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616181). _Future Healthc J_. **6** (2): 94–98. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.7861/futurehosp.6-2-94](https://doi.org/10.7861%2Ffuturehosp.6-2-94). [PMC](/wiki/PMC_\\\\(identifier\\\\) \"PMC \\\\(identifier\\\\)\") [6616181](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616181). [PMID](/wiki/PMID_\\\\(identifier\\\\) \"PMID \\\\(identifier\\\\)\") [31363513](https://pubmed.ncbi.nlm.nih.gov/31363513).\\n  131. **^** Lyakhova, U.A.; Lyakhov, P.A. (2024). [\"Systematic review of approaches to detection and classification of skin cancer using artificial intelligence: Development and prospects\"](https://linkinghub.elsevier.com/retrieve/pii/S0010482524008278). _Computers in Biology and Medicine_. **178** : 108742. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1016/j.compbiomed.2024.108742](https://doi.org/10.1016%2Fj.compbiomed.2024.108742). [PMID](/wiki/PMID_\\\\(identifier\\\\) \"PMID \\\\(identifier\\\\)\") [38875908](https://pubmed.ncbi.nlm.nih.gov/38875908).\\n  132. **^** Alqudaihi, Kawther S.; Aslam, Nida; Khan, Irfan Ullah; Almuhaideb, Abdullah M.; Alsunaidi, Shikah J.; Ibrahim, Nehad M. Abdel Rahman; Alhaidari, Fahd A.; Shaikh, Fatema S.; Alsenbel, Yasmine M.; Alalharith, Dima M.; Alharthi, Hajar M.; Alghamdi, Wejdan M.; Alshahrani, Mohammed S. (2021). [\"Cough Sound Detection and Diagnosis Using Artificial Intelligence Techniques: Challenges and Opportunities\"](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545201). _IEEE Access_. **9** : 102327–102344. [Bibcode](/wiki/Bibcode_\\\\(identifier\\\\) \"Bibcode \\\\(identifier\\\\)\"):[2021IEEEA...9j2327A](https://ui.adsabs.harvard.edu/abs/2021IEEEA...9j2327A). [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1109/ACCESS.2021.3097559](https://doi.org/10.1109%2FACCESS.2021.3097559). [ISSN](/wiki/ISSN_\\\\(identifier\\\\) \"ISSN \\\\(identifier\\\\)\") [2169-3536](https://search.worldcat.org/issn/2169-3536). [PMC](/wiki/PMC_\\\\(identifier\\\\) \"PMC \\\\(identifier\\\\)\") [8545201](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545201). [PMID](/wiki/PMID_\\\\(identifier\\\\) \"PMID \\\\(identifier\\\\)\") [34786317](https://pubmed.ncbi.nlm.nih.gov/34786317).\\n  133. ^ Jump up to: _**a**_ _**b**_ Bax, Monique; Thorpe, Jordan; Romanov, Valentin (December 2023). [\"The future of personalized cardiovascular medicine demands 3D and 4D printing, stem cells, and artificial intelligence\"](https://doi.org/10.3389%2Ffsens.2023.1294721). _Frontiers in Sensors_. **4**. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.3389/fsens.2023.1294721](https://doi.org/10.3389%2Ffsens.2023.1294721). [ISSN](/wiki/ISSN_\\\\(identifier\\\\) \"ISSN \\\\(identifier\\\\)\") [2673-5067](https://search.worldcat.org/issn/2673-5067).\\n  134. **^** Jumper, J; Evans, R; Pritzel, A (2021). [\"Highly accurate protein structure prediction with AlphaFold\"](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371605). _Nature_. **596** (7873): 583–589. [Bibcode](/wiki/Bibcode_\\\\(identifier\\\\) \"Bibcode \\\\(identifier\\\\)\"):[2021Natur.596..583J](https://ui.adsabs.harvard.edu/abs/2021Natur.596..583J). [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1038/s41586-021-03819-2](https://doi.org/10.1038%2Fs41586-021-03819-2). [PMC](/wiki/PMC_\\\\(identifier\\\\) \"PMC \\\\(identifier\\\\)\") [8371605](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371605). 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[ISSN](/wiki/ISSN_\\\\(identifier\\\\) \"ISSN \\\\(identifier\\\\)\") [2514-9369](https://search.worldcat.org/issn/2514-9369). [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [259614124](https://api.semanticscholar.org/CorpusID:259614124). [Archived](https://web.archive.org/web/20241005170207/https://www.emerald.com/insight/content/doi/10.1108/IJOES-05-2023-0107/full/html) from the original on 5 October 2024. Retrieved 5 October 2024.\\n  287. **^** [\"AI Safety Institute releases new AI safety evaluations platform\"](https://www.gov.uk/government/news/ai-safety-institute-releases-new-ai-safety-evaluations-platform). UK Government. 10 May 2024. [Archived](https://web.archive.org/web/20241005170207/https://www.gov.uk/government/news/ai-safety-institute-releases-new-ai-safety-evaluations-platform) from the original on 5 October 2024. Retrieved 14 May 2024.\\n  288. **^** Regulation of AI to mitigate risks: Berryhill et al. (2019), Barfield & Pagallo (2018), Iphofen & Kritikos (2019), Wirtz, Weyerer & Geyer (2018), Buiten (2019)\\n  289. **^** Law Library of Congress (U.S.). Global Legal Research Directorate (2019).\\n  290. ^ Jump up to: _**a**_ _**b**_ Vincent (2023).\\n  291. **^** Stanford University (2023).\\n  292. ^ Jump up to: _**a**_ _**b**_ _**c**_ _**d**_ UNESCO (2021).\\n  293. **^** Kissinger (2021).\\n  294. **^** Altman, Brockman & Sutskever (2023).\\n  295. **^** VOA News (25 October 2023). [\"UN Announces Advisory Body on Artificial Intelligence\"](https://www.voanews.com/a/un-announces-advisory-body-on-artificial-intelligence-/7328732.html). [Archived](https://web.archive.org/web/20240918071530/https://www.voanews.com/a/un-announces-advisory-body-on-artificial-intelligence-/7328732.html) from the original on 18 September 2024. Retrieved 5 October 2024.\\n  296. **^** [\"Council of Europe opens first ever global treaty on AI for signature\"](https://www.coe.int/en/web/portal/-/council-of-europe-opens-first-ever-global-treaty-on-ai-for-signature). _Council of Europe_. 5 September 2024. [Archived](https://web.archive.org/web/20240917001330/https://www.coe.int/en/web/portal/-/council-of-europe-opens-first-ever-global-treaty-on-ai-for-signature) from the original on 17 September 2024. Retrieved 17 September 2024.\\n  297. **^** Edwards (2023).\\n  298. **^** Kasperowicz (2023).\\n  299. **^** Fox News (2023).\\n  300. **^** Milmo, Dan (3 November 2023). \"Hope or Horror? The great AI debate dividing its pioneers\". _[The Guardian Weekly](/wiki/The_Guardian_Weekly \"The Guardian Weekly\")_. pp. 10–12.\\n  301. **^** [\"The Bletchley Declaration by Countries Attending the AI Safety Summit, 1–2 November 2023\"](https://web.archive.org/web/20231101123904/https://www.gov.uk/government/publications/ai-safety-summit-2023-the-bletchley-declaration/the-bletchley-declaration-by-countries-attending-the-ai-safety-summit-1-2-november-2023). _GOV.UK_. 1 November 2023. Archived from [the original](https://www.gov.uk/government/publications/ai-safety-summit-2023-the-bletchley-declaration/the-bletchley-declaration-by-countries-attending-the-ai-safety-summit-1-2-november-2023) on 1 November 2023. Retrieved 2 November 2023.\\n  302. **^** [\"Countries agree to safe and responsible development of frontier AI in landmark Bletchley Declaration\"](https://www.gov.uk/government/news/countries-agree-to-safe-and-responsible-development-of-frontier-ai-in-landmark-bletchley-declaration). _GOV.UK_ (Press release). [Archived](https://web.archive.org/web/20231101115016/https://www.gov.uk/government/news/countries-agree-to-safe-and-responsible-development-of-frontier-ai-in-landmark-bletchley-declaration) from the original on 1 November 2023. Retrieved 1 November 2023.\\n  303. **^** [\"Second global AI summit secures safety commitments from companies\"](https://www.reuters.com/technology/global-ai-summit-seoul-aims-forge-new-regulatory-agreements-2024-05-21). Reuters. 21 May 2024. Retrieved 23 May 2024.\\n  304. **^** [\"Frontier AI Safety Commitments, AI Seoul Summit 2024\"](https://web.archive.org/web/20240523201611/https://www.gov.uk/government/publications/frontier-ai-safety-commitments-ai-seoul-summit-2024/frontier-ai-safety-commitments-ai-seoul-summit-2024). gov.uk. 21 May 2024. Archived from [the original](https://www.gov.uk/government/publications/frontier-ai-safety-commitments-ai-seoul-summit-2024/frontier-ai-safety-commitments-ai-seoul-summit-2024) on 23 May 2024. Retrieved 23 May 2024.\\n  305. ^ Jump up to: _**a**_ _**b**_ Russell & Norvig 2021, p. 9.\\n  306. ^ Jump up to: _**a**_ _**b**_ _**c**_ Copeland, J., ed. (2004). _The Essential Turing: the ideas that gave birth to the computer age_. Oxford, England: Clarendon Press. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [0-1982-5079-7](/wiki/Special:BookSources/0-1982-5079-7 \"Special:BookSources/0-1982-5079-7\").\\n  307. **^** [\"Google books ngram\"](https://books.google.com/ngrams/graph?content=electronic+brain&year_start=1930&year_end=2019&corpus=en-2019&smoothing=3). [Archived](https://web.archive.org/web/20241005170209/https://books.google.com/ngrams/graph?content=electronic+brain&year_start=1930&year_end=2019&corpus=en-2019&smoothing=3) from the original on 5 October 2024. Retrieved 5 October 2024.\\n  308. **^** AI\\'s immediate precursors: McCorduck (2004, pp. 51–107), Crevier (1993, pp. 27–32), Russell & Norvig (2021, pp. 8–17), Moravec (1988, p. 3)\\n  309. ^ Jump up to: _**a**_ _**b**_ Turing\\'s original publication of the [Turing test](/wiki/Turing_test \"Turing test\") in \"[Computing machinery and intelligence](/wiki/Computing_machinery_and_intelligence \"Computing machinery and intelligence\")\": Turing (1950) Historical influence and philosophical implications: Haugeland (1985, pp. 6–9), Crevier (1993, p. 24), McCorduck (2004, pp. 70–71), Russell & Norvig (2021, pp. 2, 984)\\n  310. **^** Crevier (1993), pp. 47–49.\\n  311. **^** Russell & Norvig (2003), p. 17.\\n  312. **^** Russell & Norvig (2003), p. 18.\\n  313. **^** Newquist (1994), pp. 86–86.\\n  314. **^** Simon (1965, p. 96) quoted in Crevier (1993, p. 109)\\n  315. **^** Minsky (1967, p. 2) quoted in Crevier (1993, p. 109)\\n  316. **^** Russell & Norvig (2021), p. 21.\\n  317. **^** Lighthill (1973).\\n  318. **^** NRC 1999, pp. 212–213.\\n  319. **^** Russell & Norvig (2021), p. 22.\\n  320. **^** [Expert systems](/wiki/Expert_systems \"Expert systems\"): Russell & Norvig (2021, pp. 23, 292), Luger & Stubblefield (2004, pp. 227–331), Nilsson (1998, chpt. 17.4), McCorduck (2004, pp. 327–335, 434–435), Crevier (1993, pp. 145–162, 197–203), Newquist (1994, pp. 155–183)\\n  321. **^** Russell & Norvig (2021), p. 24.\\n  322. **^** Nilsson (1998), p. 7.\\n  323. **^** McCorduck (2004), pp. 454–462.\\n  324. **^** Moravec (1988).\\n  325. ^ Jump up to: _**a**_ _**b**_ Brooks (1990).\\n  326. **^** [Developmental robotics](/wiki/Developmental_robotics \"Developmental robotics\"): Weng et al. (2001), Lungarella et al. (2003), Asada et al. (2009), Oudeyer (2010)\\n  327. **^** Russell & Norvig (2021), p. 25.\\n  328. **^** Crevier (1993, pp. 214–215), Russell & Norvig (2021, pp. 24, 26)\\n  329. **^** Russell & Norvig (2021), p. 26.\\n  330. **^** Formal and narrow methods adopted in the 1990s: Russell & Norvig (2021, pp. 24–26), McCorduck (2004, pp. 486–487)\\n  331. **^** AI widely used in the late 1990s: Kurzweil (2005, p. 265), NRC (1999, pp. 216–222), Newquist (1994, pp. 189–201)\\n  332. **^** Wong (2023).\\n  333. **^** [Moore\\'s Law](/wiki/Moore%27s_Law \"Moore\\'s Law\") and AI: Russell & Norvig (2021, pp. 14, 27)\\n  334. ^ Jump up to: _**a**_ _**b**_ _**c**_ Clark (2015b).\\n  335. **^** [Big data](/wiki/Big_data \"Big data\"): Russell & Norvig (2021, p. 26)\\n  336. **^** Sagar, Ram (3 June 2020). [\"OpenAI Releases GPT-3, The Largest Model So Far\"](https://analyticsindiamag.com/open-ai-gpt-3-language-model). _Analytics India Magazine_. [Archived](https://web.archive.org/web/20200804173452/https://analyticsindiamag.com/open-ai-gpt-3-language-model) from the original on 4 August 2020. Retrieved 15 March 2023.\\n  337. **^** DiFeliciantonio (2023).\\n  338. **^** Goswami (2023).\\n  339. **^** Grayling, Anthony; Ball, Brian (1 August 2024). [\"Philosophy is crucial in the age of AI\"](https://theconversation.com/philosophy-is-crucial-in-the-age-of-ai-235907). _The Conversation_. [Archived](https://web.archive.org/web/20241005170243/https://theconversation.com/philosophy-is-crucial-in-the-age-of-ai-235907) from the original on 5 October 2024. Retrieved 4 October 2024.\\n  340. ^ Jump up to: _**a**_ _**b**_ Jarow, Oshan (15 June 2024). [\"Will AI ever become conscious? It depends on how you think about biology\"](https://www.vox.com/future-perfect/351893/consciousness-ai-machines-neuroscience-mind). _Vox_. [Archived](https://web.archive.org/web/20240921035218/https://www.vox.com/future-perfect/351893/consciousness-ai-machines-neuroscience-mind) from the original on 21 September 2024. Retrieved 4 October 2024.\\n  341. **^** McCarthy, John. [\"The Philosophy of AI and the AI of Philosophy\"](https://web.archive.org/web/20181023181725/http://jmc.stanford.edu/articles/aiphil2.html). _jmc.stanford.edu_. Archived from [the original](http://jmc.stanford.edu/articles/aiphil2.html) on 23 October 2018. Retrieved 3 October 2024.\\n  342. ^ Jump up to: _**a**_ _**b**_ Turing (1950), p. 1.\\n  343. **^** Turing (1950), Under \"The Argument from Consciousness\".\\n  344. **^** Kirk-Giannini, Cameron Domenico; Goldstein, Simon (16 October 2023). [\"AI is closer than ever to passing the Turing test for \\'intelligence\\'. What happens when it does?\"](https://theconversation.com/ai-is-closer-than-ever-to-passing-the-turing-test-for-intelligence-what-happens-when-it-does-214721). _The Conversation_. [Archived](https://web.archive.org/web/20240925040612/https://theconversation.com/ai-is-closer-than-ever-to-passing-the-turing-test-for-intelligence-what-happens-when-it-does-214721) from the original on 25 September 2024. Retrieved 17 August 2024.\\n  345. **^** Russell & Norvig (2021), p. 3.\\n  346. **^** Maker (2006).\\n  347. **^** McCarthy (1999).\\n  348. **^** Minsky (1986).\\n  349. **^** [\"What Is Artificial Intelligence (AI)?\"](https://cloud.google.com/learn/what-is-artificial-intelligence). _[Google Cloud Platform](/wiki/Google_Cloud_Platform \"Google Cloud Platform\")_. [Archived](https://web.archive.org/web/20230731114802/https://cloud.google.com/learn/what-is-artificial-intelligence) from the original on 31 July 2023. Retrieved 16 October 2023.\\n  350. **^** [\"One of the Biggest Problems in Regulating AI Is Agreeing on a Definition\"](https://carnegieendowment.org/posts/2022/10/one-of-the-biggest-problems-in-regulating-ai-is-agreeing-on-a-definition?lang=en). _carnegieendowment.org_. Retrieved 31 July 2024.\\n  351. **^** [\"AI or BS? How to tell if a marketing tool really uses artificial intelligence\"](https://www.thedrum.com/opinion/2023/03/30/ai-or-bs-how-tell-if-marketing-tool-really-uses-artificial-intelligence). _The Drum_. Retrieved 31 July 2024.\\n  352. **^** Nilsson (1983), p. 10.\\n  353. **^** Haugeland (1985), pp. 112–117.\\n  354. **^** Physical symbol system hypothesis: Newell & Simon (1976, p. 116) Historical significance: McCorduck (2004, p. 153), Russell & Norvig (2021, p. 19)\\n  355. **^** [Moravec\\'s paradox](/wiki/Moravec%27s_paradox \"Moravec\\'s paradox\"): Moravec (1988, pp. 15–16), Minsky (1986, p. 29), Pinker (2007, pp. 190–191)\\n  356. **^** [Dreyfus\\' critique of AI](/wiki/Dreyfus%27_critique_of_AI \"Dreyfus\\' critique of AI\"): Dreyfus (1972), Dreyfus & Dreyfus (1986) Historical significance and philosophical implications: Crevier (1993, pp. 120–132), McCorduck (2004, pp. 211–239), Russell & Norvig (2021, pp. 981–982), Fearn (2007, chpt. 3)\\n  357. **^** Crevier (1993), p. 125.\\n  358. **^** Langley (2011).\\n  359. **^** Katz (2012).\\n  360. **^** [Neats vs. scruffies](/wiki/Neats_vs._scruffies \"Neats vs. scruffies\"), the historic debate: McCorduck (2004, pp. 421–424, 486–489), Crevier (1993, p. 168), Nilsson (1983, pp. 10–11), Russell & Norvig (2021, p. 24) A classic example of the \"scruffy\" approach to intelligence: Minsky (1986) A modern example of neat AI and its aspirations in the 21st century: Domingos (2015)\\n  361. **^** Pennachin & Goertzel (2007).\\n  362. ^ Jump up to: _**a**_ _**b**_ Roberts (2016).\\n  363. **^** Russell & Norvig (2021), p. 986.\\n  364. **^** Chalmers (1995).\\n  365. **^** Dennett (1991).\\n  366. **^** Horst (2005).\\n  367. **^** Searle (1999).\\n  368. **^** Searle (1980), p. 1.\\n  369. **^** Russell & Norvig (2021), p. 9817.\\n  370. **^** Searle\\'s [Chinese room](/wiki/Chinese_room \"Chinese room\") argument: Searle (1980). Searle\\'s original presentation of the thought experiment., Searle (1999). Discussion: Russell & Norvig (2021, pp. 985), McCorduck (2004, pp. 443–445), Crevier (1993, pp. 269–271)\\n  371. **^** Leith, Sam (7 July 2022). [\"Nick Bostrom: How can we be certain a machine isn\\'t conscious?\"](https://www.spectator.co.uk/article/nick-bostrom-how-can-we-be-certain-a-machine-isnt-conscious). _The Spectator_. [Archived](https://web.archive.org/web/20240926155639/https://www.spectator.co.uk/article/nick-bostrom-how-can-we-be-certain-a-machine-isnt-conscious/) from the original on 26 September 2024. Retrieved 23 February 2024.\\n  372. ^ Jump up to: _**a**_ _**b**_ _**c**_ Thomson, Jonny (31 October 2022). [\"Why don\\'t robots have rights?\"](https://bigthink.com/thinking/why-dont-robots-have-rights). _Big Think_. [Archived](https://web.archive.org/web/20240913055336/https://bigthink.com/thinking/why-dont-robots-have-rights/) from the original on 13 September 2024. Retrieved 23 February 2024.\\n  373. ^ Jump up to: _**a**_ _**b**_ Kateman, Brian (24 July 2023). [\"AI Should Be Terrified of Humans\"](https://time.com/6296234/ai-should-be-terrified-of-humans). _Time_. [Archived](https://web.archive.org/web/20240925041601/https://time.com/6296234/ai-should-be-terrified-of-humans/) from the original on 25 September 2024. Retrieved 23 February 2024.\\n  374. **^** Wong, Jeff (10 July 2023). [\"What leaders need to know about robot rights\"](https://www.fastcompany.com/90920769/what-leaders-need-to-know-about-robot-rights). _Fast Company_.\\n  375. **^** Hern, Alex (12 January 2017). [\"Give robots \\'personhood\\' status, EU committee argues\"](https://www.theguardian.com/technology/2017/jan/12/give-robots-personhood-status-eu-committee-argues). _The Guardian_. [ISSN](/wiki/ISSN_\\\\(identifier\\\\) \"ISSN \\\\(identifier\\\\)\") [0261-3077](https://search.worldcat.org/issn/0261-3077). [Archived](https://web.archive.org/web/20241005171222/https://www.theguardian.com/technology/2017/jan/12/give-robots-personhood-status-eu-committee-argues) from the original on 5 October 2024. Retrieved 23 February 2024.\\n  376. **^** Dovey, Dana (14 April 2018). [\"Experts Don\\'t Think Robots Should Have Rights\"](https://www.newsweek.com/robots-human-rights-electronic-persons-humans-versus-machines-886075). _Newsweek_. [Archived](https://web.archive.org/web/20241005171333/https://www.newsweek.com/robots-human-rights-electronic-persons-humans-versus-machines-886075) from the original on 5 October 2024. Retrieved 23 February 2024.\\n  377. **^** Cuddy, Alice (13 April 2018). [\"Robot rights violate human rights, experts warn EU\"](https://www.euronews.com/2018/04/13/robot-rights-violate-human-rights-experts-warn-eu). _euronews_. [Archived](https://web.archive.org/web/20240919022327/https://www.euronews.com/2018/04/13/robot-rights-violate-human-rights-experts-warn-eu) from the original on 19 September 2024. Retrieved 23 February 2024.\\n  378. **^** The [Intelligence explosion](/wiki/Intelligence_explosion \"Intelligence explosion\") and [technological singularity](/wiki/Technological_singularity \"Technological singularity\"): Russell & Norvig (2021, pp. 1004–1005), Omohundro (2008), Kurzweil (2005) [I. J. Good](/wiki/I._J._Good \"I. J. Good\")\\'s \"intelligence explosion\": Good (1965) [Vernor Vinge](/wiki/Vernor_Vinge \"Vernor Vinge\")\\'s \"singularity\": Vinge (1993)\\n  379. **^** Russell & Norvig (2021), p. 1005.\\n  380. **^** [Transhumanism](/wiki/Transhumanism \"Transhumanism\"): Moravec (1988), Kurzweil (2005), Russell & Norvig (2021, p. 1005)\\n  381. **^** AI as evolution: [Edward Fredkin](/wiki/Edward_Fredkin \"Edward Fredkin\") is quoted in McCorduck (2004, p. 401), Butler (1863), Dyson (1998)\\n  382. **^** AI in myth: McCorduck (2004, pp. 4–5)\\n  383. **^** McCorduck (2004), pp. 340–400.\\n  384. **^** Buttazzo (2001).\\n  385. **^** Anderson (2008).\\n  386. **^** McCauley (2007).\\n  387. **^** Galvan (1997).\\n\\n### AI textbooks\\n\\nThe two most widely used textbooks in 2023 (see the [Open\\nSyllabus](https://explorer.opensyllabus.org/result/field?id=Computer+Science)):\\n\\n  * [Russell, Stuart J.](/wiki/Stuart_J._Russell \"Stuart J. Russell\"); [Norvig, Peter](/wiki/Peter_Norvig \"Peter Norvig\") (2021). _[Artificial Intelligence: A Modern Approach](/wiki/Artificial_Intelligence:_A_Modern_Approach \"Artificial Intelligence: A Modern Approach\")_ (4th ed.). Hoboken: Pearson. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-0-1346-1099-3](/wiki/Special:BookSources/978-0-1346-1099-3 \"Special:BookSources/978-0-1346-1099-3\"). [LCCN](/wiki/LCCN_\\\\(identifier\\\\) \"LCCN \\\\(identifier\\\\)\") [20190474](https://lccn.loc.gov/20190474).\\n  * [Rich, Elaine](/wiki/Elaine_Rich \"Elaine Rich\"); Knight, Kevin; Nair, Shivashankar B (2010). _Artificial Intelligence_ (3rd ed.). New Delhi: Tata McGraw Hill India. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-0-0700-8770-5](/wiki/Special:BookSources/978-0-0700-8770-5 \"Special:BookSources/978-0-0700-8770-5\").\\n\\nThese were the four of the most widely used AI textbooks in 2008:\\n\\n  * [Luger, George](/w/index.php?title=George_Luger&action=edit&redlink=1 \"George Luger \\\\(page does not exist\\\\)\"); [Stubblefield, William](/wiki/William_Stubblefield \"William Stubblefield\") (2004). [_Artificial Intelligence: Structures and Strategies for Complex Problem Solving_](https://archive.org/details/artificialintell0000luge) (5th ed.). Benjamin/Cummings. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-0-8053-4780-7](/wiki/Special:BookSources/978-0-8053-4780-7 \"Special:BookSources/978-0-8053-4780-7\"). [Archived](https://web.archive.org/web/20200726220613/https://archive.org/details/artificialintell0000luge) from the original on 26 July 2020. Retrieved 17 December 2019.\\n  * [Nilsson, Nils](/wiki/Nils_Nilsson_\\\\(researcher\\\\) \"Nils Nilsson \\\\(researcher\\\\)\") (1998). [_Artificial Intelligence: A New Synthesis_](https://archive.org/details/artificialintell0000nils). Morgan Kaufmann. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-1-5586-0467-4](/wiki/Special:BookSources/978-1-5586-0467-4 \"Special:BookSources/978-1-5586-0467-4\"). [Archived](https://web.archive.org/web/20200726131654/https://archive.org/details/artificialintell0000nils) from the original on 26 July 2020. Retrieved 18 November 2019.\\n  * [Russell, Stuart J.](/wiki/Stuart_J._Russell \"Stuart J. Russell\"); [Norvig, Peter](/wiki/Peter_Norvig \"Peter Norvig\") (2003), [_Artificial Intelligence: A Modern Approach_](http://aima.cs.berkeley.edu/) (2nd ed.), Upper Saddle River, New Jersey: Prentice Hall, [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [0-13-790395-2](/wiki/Special:BookSources/0-13-790395-2 \"Special:BookSources/0-13-790395-2\").\\n  * [Poole, David](/w/index.php?title=David_Poole_\\\\(researcher\\\\)&action=edit&redlink=1 \"David Poole \\\\(researcher\\\\) \\\\(page does not exist\\\\)\"); [Mackworth, Alan](/wiki/Alan_Mackworth \"Alan Mackworth\"); [Goebel, Randy](/w/index.php?title=Randy_Goebel&action=edit&redlink=1 \"Randy Goebel \\\\(page does not exist\\\\)\") (1998). [_Computational Intelligence: A Logical Approach_](https://archive.org/details/computationalint00pool). New York: Oxford University Press. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-0-1951-0270-3](/wiki/Special:BookSources/978-0-1951-0270-3 \"Special:BookSources/978-0-1951-0270-3\"). [Archived](https://web.archive.org/web/20200726131436/https://archive.org/details/computationalint00pool) from the original on 26 July 2020. Retrieved 22 August 2020. Later edition: Poole, David; [Mackworth, Alan](/wiki/Alan_Mackworth \"Alan Mackworth\") (2017). [_Artificial Intelligence: Foundations of Computational Agents_](http://artint.info/index.html) (2nd ed.). Cambridge University Press. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-1-1071-9539-4](/wiki/Special:BookSources/978-1-1071-9539-4 \"Special:BookSources/978-1-1071-9539-4\"). [Archived](https://web.archive.org/web/20171207013855/http://artint.info/index.html) from the original on 7 December 2017. Retrieved 6 December 2017.\\n\\nOther textbooks:\\n\\n  * Ertel, Wolfgang (2017). _Introduction to Artificial Intelligence_ (2nd ed.). Springer. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-3-3195-8486-7](/wiki/Special:BookSources/978-3-3195-8486-7 \"Special:BookSources/978-3-3195-8486-7\").\\n  * [Ciaramella, Alberto](/wiki/Alberto_Ciaramella \"Alberto Ciaramella\"); Ciaramella, Marco (2024). _Introduction to Artificial Intelligence: from data analysis to generative AI_ (1st ed.). Intellisemantic Editions. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-8-8947-8760-3](/wiki/Special:BookSources/978-8-8947-8760-3 \"Special:BookSources/978-8-8947-8760-3\").\\n\\n### History of AI\\n\\n  * [Crevier, Daniel](/wiki/Daniel_Crevier \"Daniel Crevier\") (1993). _AI: The Tumultuous Search for Artificial Intelligence_. New York, NY: BasicBooks. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [0-465-02997-3](/wiki/Special:BookSources/0-465-02997-3 \"Special:BookSources/0-465-02997-3\").\\n  * [McCorduck, Pamela](/wiki/Pamela_McCorduck \"Pamela McCorduck\") (2004), _Machines Who Think_ (2nd ed.), Natick, Massachusetts: A. K. Peters, [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [1-5688-1205-1](/wiki/Special:BookSources/1-5688-1205-1 \"Special:BookSources/1-5688-1205-1\")\\n  * [Newquist, H. P.](/wiki/HP_Newquist \"HP Newquist\") (1994). _The Brain Makers: Genius, Ego, And Greed In The Quest For Machines That Think_. New York: Macmillan/SAMS. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-0-6723-0412-5](/wiki/Special:BookSources/978-0-6723-0412-5 \"Special:BookSources/978-0-6723-0412-5\").\\n\\n### Other sources\\n\\n  * [AI & ML in Fusion](https://suli.pppl.gov/2023/course/Rea-PPPL-SULI2023.pdf)\\n  * [AI & ML in Fusion, video lecture](https://drive.google.com/file/d/1npCTrJ8XJn20ZGDA_DfMpANuQZFMzKPh/view?usp=drive_link) [Archived](https://web.archive.org/web/20230702164332/https://drive.google.com/file/d/1npCTrJ8XJn20ZGDA_DfMpANuQZFMzKPh/view?usp=drive_link) 2 July 2023 at the [Wayback Machine](/wiki/Wayback_Machine \"Wayback Machine\")\\n  * Alter, Alexandra; Harris, Elizabeth A. (20 September 2023), [\"Franzen, Grisham and Other Prominent Authors Sue OpenAI\"](https://www.nytimes.com/2023/09/20/books/authors-openai-lawsuit-chatgpt-copyright.html?campaign_id=2&emc=edit_th_20230921&instance_id=103259&nl=todaysheadlines&regi_id=62816440&segment_id=145288&user_id=ad24f3545dae0ec44284a38bb4a88f1d), _The New York Times_ , [archived](https://web.archive.org/web/20240914155020/https://www.nytimes.com/2023/09/20/books/authors-openai-lawsuit-chatgpt-copyright.html?campaign_id=2&emc=edit_th_20230921&instance_id=103259&nl=todaysheadlines&regi_id=62816440&segment_id=145288&user_id=ad24f3545dae0ec44284a38bb4a88f1d) from the original on 14 September 2024, retrieved 5 October 2024\\n  * [Altman, Sam](/wiki/Sam_Altman \"Sam Altman\"); [Brockman, Greg](/wiki/Greg_Brockman \"Greg Brockman\"); [Sutskever, Ilya](/wiki/Ilya_Sutskever \"Ilya Sutskever\") (22 May 2023). [\"Governance of Superintelligence\"](https://openai.com/blog/governance-of-superintelligence). _openai.com_. [Archived](https://web.archive.org/web/20230527061619/https://openai.com/blog/governance-of-superintelligence) from the original on 27 May 2023. Retrieved 27 May 2023.\\n  * Anderson, Susan Leigh (2008). \"Asimov\\'s \"three laws of robotics\" and machine metaethics\". _AI & Society_. **22** (4): 477–493. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1007/s00146-007-0094-5](https://doi.org/10.1007%2Fs00146-007-0094-5). [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [1809459](https://api.semanticscholar.org/CorpusID:1809459).\\n  * Anderson, Michael; Anderson, Susan Leigh (2011). _Machine Ethics_. Cambridge University Press.\\n  * Arntz, Melanie; Gregory, Terry; Zierahn, Ulrich (2016), \"The risk of automation for jobs in OECD countries: A comparative analysis\", _OECD Social, Employment, and Migration Working Papers 189_\\n  * Asada, M.; Hosoda, K.; Kuniyoshi, Y.; Ishiguro, H.; Inui, T.; Yoshikawa, Y.; Ogino, M.; Yoshida, C. (2009). \"Cognitive developmental robotics: a survey\". _IEEE Transactions on Autonomous Mental Development_. **1** (1): 12–34. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1109/tamd.2009.2021702](https://doi.org/10.1109%2Ftamd.2009.2021702). [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [10168773](https://api.semanticscholar.org/CorpusID:10168773).\\n  * [\"Ask the AI experts: What\\'s driving today\\'s progress in AI?\"](https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/ask-the-ai-experts-whats-driving-todays-progress-in-ai). _McKinsey & Company_. [Archived](https://web.archive.org/web/20180413190018/https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/ask-the-ai-experts-whats-driving-todays-progress-in-ai) from the original on 13 April 2018. Retrieved 13 April 2018.\\n  * Barfield, Woodrow; Pagallo, Ugo (2018). _Research handbook on the law of artificial intelligence_. Cheltenham, UK: Edward Elgar Publishing. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-1-7864-3904-8](/wiki/Special:BookSources/978-1-7864-3904-8 \"Special:BookSources/978-1-7864-3904-8\"). [OCLC](/wiki/OCLC_\\\\(identifier\\\\) \"OCLC \\\\(identifier\\\\)\") [1039480085](https://search.worldcat.org/oclc/1039480085).\\n  * Beal, J.; [Winston, Patrick](/wiki/Patrick_Winston \"Patrick Winston\") (2009), \"The New Frontier of Human-Level Artificial Intelligence\", _IEEE Intelligent Systems_ , vol. 24, pp. 21–24, [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1109/MIS.2009.75](https://doi.org/10.1109%2FMIS.2009.75), [hdl](/wiki/Hdl_\\\\(identifier\\\\) \"Hdl \\\\(identifier\\\\)\"):[1721.1/52357](https://hdl.handle.net/1721.1%2F52357), [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [32437713](https://api.semanticscholar.org/CorpusID:32437713)\\n  * Berdahl, Carl Thomas; Baker, Lawrence; Mann, Sean; Osoba, Osonde; Girosi, Federico (7 February 2023). [\"Strategies to Improve the Impact of Artificial Intelligence on Health Equity: Scoping Review\"](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11041459). _JMIR AI_. **2** : e42936. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.2196/42936](https://doi.org/10.2196%2F42936). [ISSN](/wiki/ISSN_\\\\(identifier\\\\) \"ISSN \\\\(identifier\\\\)\") [2817-1705](https://search.worldcat.org/issn/2817-1705). [PMC](/wiki/PMC_\\\\(identifier\\\\) \"PMC \\\\(identifier\\\\)\") [11041459](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11041459). [PMID](/wiki/PMID_\\\\(identifier\\\\) \"PMID \\\\(identifier\\\\)\") [38875587](https://pubmed.ncbi.nlm.nih.gov/38875587). [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [256681439](https://api.semanticscholar.org/CorpusID:256681439).\\n  * Berryhill, Jamie; Heang, Kévin Kok; Clogher, Rob; McBride, Keegan (2019). [_Hello, World: Artificial Intelligence and its Use in the Public Sector_](https://oecd-opsi.org/wp-content/uploads/2019/11/AI-Report-Online.pdf) (PDF). Paris: OECD Observatory of Public Sector Innovation. [Archived](https://web.archive.org/web/20191220021331/https://oecd-opsi.org/wp-content/uploads/2019/11/AI-Report-Online.pdf) (PDF) from the original on 20 December 2019. Retrieved 9 August 2020.\\n  * Bertini, M; Del Bimbo, A; Torniai, C (2006). \"Automatic annotation and semantic retrieval of video sequences using multimedia ontologies\". _MM \\'06 Proceedings of the 14th ACM international conference on Multimedia_. 14th ACM international conference on Multimedia. Santa Barbara: ACM. pp. 679–682.\\n  * [Bostrom, Nick](/wiki/Nick_Bostrom \"Nick Bostrom\") (2014). [_Superintelligence: Paths, Dangers, Strategies_](/wiki/Superintelligence:_Paths,_Dangers,_Strategies \"Superintelligence: Paths, Dangers, Strategies\"). Oxford University Press.\\n  * Bostrom, Nick (2015). [\"What happens when our computers get smarter than we are?\"](https://www.ted.com/talks/nick_bostrom_what_happens_when_our_computers_get_smarter_than_we_are/transcript). [TED (conference)](/wiki/TED_\\\\(conference\\\\) \"TED \\\\(conference\\\\)\"). [Archived](https://web.archive.org/web/20200725005719/https://www.ted.com/talks/nick_bostrom_what_happens_when_our_computers_get_smarter_than_we_are/transcript) from the original on 25 July 2020. Retrieved 30 January 2020.\\n  * Brooks, Rodney (10 November 2014). [\"artificial intelligence is a tool, not a threat\"](https://web.archive.org/web/20141112130954/http://www.rethinkrobotics.com/artificial-intelligence-tool-threat). Archived from [the original](http://www.rethinkrobotics.com/artificial-intelligence-tool-threat) on 12 November 2014.\\n  * [Brooks, Rodney](/wiki/Rodney_Brooks \"Rodney Brooks\") (1990). [\"Elephants Don\\'t Play Chess\"](http://people.csail.mit.edu/brooks/papers/elephants.pdf) (PDF). _Robotics and Autonomous Systems_. **6** (1–2): 3–15. [CiteSeerX](/wiki/CiteSeerX_\\\\(identifier\\\\) \"CiteSeerX \\\\(identifier\\\\)\") [10.1.1.588.7539](https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.588.7539). [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1016/S0921-8890(05)80025-9](https://doi.org/10.1016%2FS0921-8890%2805%2980025-9). [Archived](https://web.archive.org/web/20070809020912/http://people.csail.mit.edu/brooks/papers/elephants.pdf) (PDF) from the original on 9 August 2007.\\n  * Buiten, Miriam C (2019). [\"Towards Intelligent Regulation of Artificial Intelligence\"](https://doi.org/10.1017%2Ferr.2019.8). _European Journal of Risk Regulation_. **10** (1): 41–59. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1017/err.2019.8](https://doi.org/10.1017%2Ferr.2019.8). [ISSN](/wiki/ISSN_\\\\(identifier\\\\) \"ISSN \\\\(identifier\\\\)\") [1867-299X](https://search.worldcat.org/issn/1867-299X).\\n  * Bushwick, Sophie (16 March 2023), [\"What the New GPT-4 AI Can Do\"](https://www.scientificamerican.com/article/what-the-new-gpt-4-ai-can-do/), _Scientific American_ , [archived](https://web.archive.org/web/20230822233655/https://www.scientificamerican.com/article/what-the-new-gpt-4-ai-can-do/) from the original on 22 August 2023, retrieved 5 October 2024\\n  * [Butler, Samuel](/wiki/Samuel_Butler_\\\\(novelist\\\\) \"Samuel Butler \\\\(novelist\\\\)\") (13 June 1863). [\"Darwin among the Machines\"](https://nzetc.victoria.ac.nz/tm/scholarly/tei-ButFir-t1-g1-t1-g1-t4-body.html). Letters to the Editor. _[The Press](/wiki/The_Press \"The Press\")_. Christchurch, New Zealand. [Archived](https://web.archive.org/web/20080919172551/http://www.nzetc.org/tm/scholarly/tei-ButFir-t1-g1-t1-g1-t4-body.html) from the original on 19 September 2008. Retrieved 16 October 2014 – via Victoria University of Wellington.\\n  * Buttazzo, G. (July 2001). \"Artificial consciousness: Utopia or real possibility?\". _[Computer](/wiki/Computer_\\\\(magazine\\\\) \"Computer \\\\(magazine\\\\)\")_. **34** (7): 24–30. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1109/2.933500](https://doi.org/10.1109%2F2.933500).\\n  * Cambria, Erik; White, Bebo (May 2014). \"Jumping NLP Curves: A Review of Natural Language Processing Research [Review Article]\". _IEEE Computational Intelligence Magazine_. **9** (2): 48–57. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1109/MCI.2014.2307227](https://doi.org/10.1109%2FMCI.2014.2307227). [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [206451986](https://api.semanticscholar.org/CorpusID:206451986).\\n  * Cellan-Jones, Rory (2 December 2014). [\"Stephen Hawking warns artificial intelligence could end mankind\"](https://www.bbc.com/news/technology-30290540). _[BBC News](/wiki/BBC_News \"BBC News\")_. [Archived](https://web.archive.org/web/20151030054329/http://www.bbc.com/news/technology-30290540) from the original on 30 October 2015. Retrieved 30 October 2015.\\n  * [Chalmers, David](/wiki/David_Chalmers \"David Chalmers\") (1995). [\"Facing up to the problem of consciousness\"](http://www.imprint.co.uk/chalmers.html). _[Journal of Consciousness Studies](/wiki/Journal_of_Consciousness_Studies \"Journal of Consciousness Studies\")_. **2** (3): 200–219. [CiteSeerX](/wiki/CiteSeerX_\\\\(identifier\\\\) \"CiteSeerX \\\\(identifier\\\\)\") [10.1.1.103.8362](https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.103.8362). [Archived](https://web.archive.org/web/20050308163649/http://www.imprint.co.uk/chalmers.html) from the original on 8 March 2005. Retrieved 11 October 2018.\\n  * Challa, Subhash; Moreland, Mark R.; Mušicki, Darko; Evans, Robin J. (2011). _Fundamentals of Object Tracking_. Cambridge University Press. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1017/CBO9780511975837](https://doi.org/10.1017%2FCBO9780511975837). [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-0-5218-7628-5](/wiki/Special:BookSources/978-0-5218-7628-5 \"Special:BookSources/978-0-5218-7628-5\").\\n  * [Christian, Brian](/wiki/Brian_Christian \"Brian Christian\") (2020). _[The Alignment Problem](/wiki/The_Alignment_Problem \"The Alignment Problem\"): Machine learning and human values_. W. W. Norton & Company. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-0-3938-6833-3](/wiki/Special:BookSources/978-0-3938-6833-3 \"Special:BookSources/978-0-3938-6833-3\"). [OCLC](/wiki/OCLC_\\\\(identifier\\\\) \"OCLC \\\\(identifier\\\\)\") [1233266753](https://search.worldcat.org/oclc/1233266753).\\n  * Ciresan, D.; Meier, U.; Schmidhuber, J. (2012). \"Multi-column deep neural networks for image classification\". _2012 IEEE Conference on Computer Vision and Pattern Recognition_. pp. 3642–3649. [arXiv](/wiki/ArXiv_\\\\(identifier\\\\) \"ArXiv \\\\(identifier\\\\)\"):[1202.2745](https://arxiv.org/abs/1202.2745). [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1109/cvpr.2012.6248110](https://doi.org/10.1109%2Fcvpr.2012.6248110). [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-1-4673-1228-8](/wiki/Special:BookSources/978-1-4673-1228-8 \"Special:BookSources/978-1-4673-1228-8\"). [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [2161592](https://api.semanticscholar.org/CorpusID:2161592).\\n  * Clark, Jack (2015b). [\"Why 2015 Was a Breakthrough Year in Artificial Intelligence\"](https://www.bloomberg.com/news/articles/2015-12-08/why-2015-was-a-breakthrough-year-in-artificial-intelligence). _Bloomberg.com_. [Archived](https://web.archive.org/web/20161123053855/https://www.bloomberg.com/news/articles/2015-12-08/why-2015-was-a-breakthrough-year-in-artificial-intelligence) from the original on 23 November 2016. Retrieved 23 November 2016.\\n  * CNA (12 January 2019). [\"Commentary: Bad news. Artificial intelligence is biased\"](https://www.channelnewsasia.com/news/commentary/artificial-intelligence-big-data-bias-hiring-loans-key-challenge-11097374). _CNA_. [Archived](https://web.archive.org/web/20190112104421/https://www.channelnewsasia.com/news/commentary/artificial-intelligence-big-data-bias-hiring-loans-key-challenge-11097374) from the original on 12 January 2019. Retrieved 19 June 2020.\\n  * [Cybenko, G.](/wiki/George_Cybenko \"George Cybenko\") (1988). Continuous valued neural networks with two hidden layers are sufficient (Report). Department of Computer Science, Tufts University.\\n  * Deng, L.; Yu, D. (2014). [\"Deep Learning: Methods and Applications\"](http://research.microsoft.com/pubs/209355/DeepLearning-NowPublishing-Vol7-SIG-039.pdf) (PDF). _Foundations and Trends in Signal Processing_. **7** (3–4): 197–387. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1561/2000000039](https://doi.org/10.1561%2F2000000039). [Archived](https://web.archive.org/web/20160314152112/http://research.microsoft.com/pubs/209355/DeepLearning-NowPublishing-Vol7-SIG-039.pdf) (PDF) from the original on 14 March 2016. Retrieved 18 October 2014.\\n  * [Dennett, Daniel](/wiki/Daniel_Dennett \"Daniel Dennett\") (1991). [_Consciousness Explained_](/wiki/Consciousness_Explained \"Consciousness Explained\"). The Penguin Press. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-0-7139-9037-9](/wiki/Special:BookSources/978-0-7139-9037-9 \"Special:BookSources/978-0-7139-9037-9\").\\n  * DiFeliciantonio, Chase (3 April 2023). [\"AI has already changed the world. This report shows how\"](https://www.sfchronicle.com/tech/article/ai-artificial-intelligence-report-stanford-17869558.php). _San Francisco Chronicle_. [Archived](https://web.archive.org/web/20230619015309/https://www.sfchronicle.com/tech/article/ai-artificial-intelligence-report-stanford-17869558.php) from the original on 19 June 2023. Retrieved 19 June 2023.\\n  * Dickson, Ben (2 May 2022). [\"Machine learning: What is the transformer architecture?\"](https://bdtechtalks.com/2022/05/02/what-is-the-transformer). _TechTalks_. [Archived](https://web.archive.org/web/20231122142948/https://bdtechtalks.com/2022/05/02/what-is-the-transformer/) from the original on 22 November 2023. 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[_What Computers Can\\'t Do_](/wiki/What_Computers_Can%27t_Do \"What Computers Can\\'t Do\"). New York: MIT Press. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-0-0601-1082-6](/wiki/Special:BookSources/978-0-0601-1082-6 \"Special:BookSources/978-0-0601-1082-6\").\\n  * [Dreyfus, Hubert](/wiki/Hubert_Dreyfus \"Hubert Dreyfus\"); Dreyfus, Stuart (1986). [_Mind over Machine: The Power of Human Intuition and Expertise in the Era of the Computer_](https://archive.org/details/mindovermachinep00drey). Oxford: Blackwell. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-0-0290-8060-3](/wiki/Special:BookSources/978-0-0290-8060-3 \"Special:BookSources/978-0-0290-8060-3\"). [Archived](https://web.archive.org/web/20200726131414/https://archive.org/details/mindovermachinep00drey) from the original on 26 July 2020. 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[ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-3-5402-9621-8](/wiki/Special:BookSources/978-3-5402-9621-8 \"Special:BookSources/978-3-5402-9621-8\").\\n  * Taylor, Josh; Hern, Alex (2 May 2023). [\"\\'Godfather of AI\\' Geoffrey Hinton quits Google and warns over dangers of misinformation\"](https://www.theguardian.com/technology/2023/may/02/geoffrey-hinton-godfather-of-ai-quits-google-warns-dangers-of-machine-learning). _[The Guardian](/wiki/The_Guardian \"The Guardian\")_. [Archived](https://web.archive.org/web/20241005171343/https://www.theguardian.com/technology/2023/may/02/geoffrey-hinton-godfather-of-ai-quits-google-warns-dangers-of-machine-learning) from the original on 5 October 2024. Retrieved 5 October 2024.\\n  * Thompson, Derek (23 January 2014). [\"What Jobs Will the Robots Take?\"](https://www.theatlantic.com/business/archive/2014/01/what-jobs-will-the-robots-take/283239). _The Atlantic_. 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[\"OpenAI has published the text-generating AI it said was too dangerous to share\"](https://www.theverge.com/2019/11/7/20953040/openai-text-generation-ai-gpt-2-full-model-release-1-5b-parameters). _The Verge_. [Archived](https://web.archive.org/web/20200611054114/https://www.theverge.com/2019/11/7/20953040/openai-text-generation-ai-gpt-2-full-model-release-1-5b-parameters) from the original on 11 June 2020. Retrieved 11 June 2020.\\n  * Vincent, James (15 November 2022). [\"The scary truth about AI copyright is nobody knows what will happen next\"](https://www.theverge.com/23444685/generative-ai-copyright-infringement-legal-fair-use-training-data). _The Verge_. [Archived](https://web.archive.org/web/20230619055201/https://www.theverge.com/23444685/generative-ai-copyright-infringement-legal-fair-use-training-data) from the original on 19 June 2023. Retrieved 19 June 2023.\\n  * Vincent, James (3 April 2023). 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Retrieved 14 November 2011.\\n  * Waddell, Kaveh (2018). [\"Chatbots Have Entered the Uncanny Valley\"](https://www.theatlantic.com/technology/archive/2017/04/uncanny-valley-digital-assistants/523806). _The Atlantic_. [Archived](https://web.archive.org/web/20180424202350/https://www.theatlantic.com/technology/archive/2017/04/uncanny-valley-digital-assistants/523806) from the original on 24 April 2018. Retrieved 24 April 2018.\\n  * Wallach, Wendell (2010). _Moral Machines_. Oxford University Press.\\n  * [Wason, P. C.](/wiki/Peter_Cathcart_Wason \"Peter Cathcart Wason\"); Shapiro, D. (1966). [\"Reasoning\"](https://archive.org/details/newhorizonsinpsy0000foss). In Foss, B. M. (ed.). _New horizons in psychology_. Harmondsworth: Penguin. [Archived](https://web.archive.org/web/20200726131518/https://archive.org/details/newhorizonsinpsy0000foss) from the original on 26 July 2020. Retrieved 18 November 2019.\\n  * Weng, J.; McClelland; Pentland, A.; Sporns, O.; Stockman, I.; Sur, M.; Thelen, E. (2001). [\"Autonomous mental development by robots and animals\"](http://www.cse.msu.edu/dl/SciencePaper.pdf) (PDF). _Science_. **291** (5504): 599–600. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1126/science.291.5504.599](https://doi.org/10.1126%2Fscience.291.5504.599). [PMID](/wiki/PMID_\\\\(identifier\\\\) \"PMID \\\\(identifier\\\\)\") [11229402](https://pubmed.ncbi.nlm.nih.gov/11229402). [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [54131797](https://api.semanticscholar.org/CorpusID:54131797). [Archived](https://web.archive.org/web/20130904235242/http://www.cse.msu.edu/dl/SciencePaper.pdf) (PDF) from the original on 4 September 2013. Retrieved 4 June 2013 – via msu.edu.\\n  * [\"What is \\'fuzzy logic\\'? Are there computers that are inherently fuzzy and do not apply the usual binary logic?\"](https://www.scientificamerican.com/article/what-is-fuzzy-logic-are-t). _Scientific American_. 21 October 1999. [Archived](https://web.archive.org/web/20180506035133/https://www.scientificamerican.com/article/what-is-fuzzy-logic-are-t) from the original on 6 May 2018. Retrieved 5 May 2018.\\n  * Williams, Rhiannon (28 June 2023), [\"Humans may be more likely to believe disinformation generated by AI\"](https://www.technologyreview.com/2023/06/28/1075683/humans-may-be-more-likely-to-believe-disinformation-generated-by-ai/), _[MIT Technology Review](/wiki/MIT_Technology_Review \"MIT Technology Review\")_ , [archived](https://web.archive.org/web/20240916014613/https://www.technologyreview.com/2023/06/28/1075683/humans-may-be-more-likely-to-believe-disinformation-generated-by-ai/) from the original on 16 September 2024, retrieved 5 October 2024\\n  * Wirtz, Bernd W.; Weyerer, Jan C.; Geyer, Carolin (24 July 2018). [\"Artificial Intelligence and the Public Sector – Applications and Challenges\"](https://zenodo.org/record/3569435). _International Journal of Public Administration_. **42** (7): 596–615. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1080/01900692.2018.1498103](https://doi.org/10.1080%2F01900692.2018.1498103). [ISSN](/wiki/ISSN_\\\\(identifier\\\\) \"ISSN \\\\(identifier\\\\)\") [0190-0692](https://search.worldcat.org/issn/0190-0692). [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [158829602](https://api.semanticscholar.org/CorpusID:158829602). [Archived](https://web.archive.org/web/20200818131415/https://zenodo.org/record/3569435) from the original on 18 August 2020. Retrieved 22 August 2020.\\n  * Wong, Matteo (19 May 2023), [\"ChatGPT Is Already Obsolete\"](https://www.theatlantic.com/technology/archive/2023/05/ai-advancements-multimodal-models/674113/), _The Atlantic_ , [archived](https://web.archive.org/web/20240918022529/https://www.theatlantic.com/technology/archive/2023/05/ai-advancements-multimodal-models/674113/) from the original on 18 September 2024, retrieved 5 October 2024\\n  * Yudkowsky, E (2008), [\"Artificial Intelligence as a Positive and Negative Factor in Global Risk\"](http://intelligence.org/files/AIPosNegFactor.pdf) (PDF), _Global Catastrophic Risks_ , Oxford University Press, 2008, [Bibcode](/wiki/Bibcode_\\\\(identifier\\\\) \"Bibcode \\\\(identifier\\\\)\"):[2008gcr..book..303Y](https://ui.adsabs.harvard.edu/abs/2008gcr..book..303Y), [archived](https://web.archive.org/web/20131019182403/http://intelligence.org/files/AIPosNegFactor.pdf) (PDF) from the original on 19 October 2013, retrieved 24 September 2021\\n\\n## Further reading\\n\\n  * [Autor, David H.](/wiki/David_Autor \"David Autor\"), \"Why Are There Still So Many Jobs? The History and Future of Workplace Automation\" (2015) 29(3) _Journal of Economic Perspectives_ 3.\\n  * [Berlinski, David](/wiki/David_Berlinski \"David Berlinski\") (2000). [_The Advent of the Algorithm_](https://archive.org/details/adventofalgorith0000berl). Harcourt Books. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-0-1560-1391-8](/wiki/Special:BookSources/978-0-1560-1391-8 \"Special:BookSources/978-0-1560-1391-8\"). [OCLC](/wiki/OCLC_\\\\(identifier\\\\) \"OCLC \\\\(identifier\\\\)\") [46890682](https://search.worldcat.org/oclc/46890682). [Archived](https://web.archive.org/web/20200726215744/https://archive.org/details/adventofalgorith0000berl) from the original on 26 July 2020. Retrieved 22 August 2020.\\n  * [Boden, Margaret](/wiki/Margaret_Boden \"Margaret Boden\"), _Mind As Machine_ , [Oxford University Press](/wiki/Oxford_University_Press \"Oxford University Press\"), 2006.\\n  * [Cukier, Kenneth](/wiki/Kenneth_Cukier \"Kenneth Cukier\"), \"Ready for Robots? How to Think about the Future of AI\", _[Foreign Affairs](/wiki/Foreign_Affairs \"Foreign Affairs\")_ , vol. 98, no. 4 (July/August 2019), pp. 192–198. [George Dyson](/wiki/George_Dyson_\\\\(science_historian\\\\) \"George Dyson \\\\(science historian\\\\)\"), historian of computing, writes (in what might be called \"Dyson\\'s Law\") that \"Any system simple enough to be understandable will not be complicated enough to behave intelligently, while any system complicated enough to behave intelligently will be too complicated to understand.\" (p. 197.) Computer scientist [Alex Pentland](/wiki/Alex_Pentland \"Alex Pentland\") writes: \"Current [AI machine-learning](/wiki/Machine_learning \"Machine learning\") [algorithms](/wiki/Algorithm \"Algorithm\") are, at their core, dead simple stupid. They work, but they work by brute force.\" (p. 198.)\\n  * [Evans, Woody](/wiki/Woody_Evans \"Woody Evans\") (2015). [\"Posthuman Rights: Dimensions of Transhuman Worlds\"](https://doi.org/10.5209%2Frev_TK.2015.v12.n2.49072). _Teknokultura_. **12** (2). [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.5209/rev_TK.2015.v12.n2.49072](https://doi.org/10.5209%2Frev_TK.2015.v12.n2.49072). [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [147612763](https://api.semanticscholar.org/CorpusID:147612763).\\n  * Frank, Michael (22 September 2023). [\"US Leadership in Artificial Intelligence Can Shape the 21st Century Global Order\"](https://thediplomat.com/2023/09/us-leadership-in-artificial-intelligence-can-shape-the-21st-century-global-order). _[The Diplomat](/wiki/The_Diplomat \"The Diplomat\")_. [Archived](https://web.archive.org/web/20240916014433/https://thediplomat.com/2023/09/us-leadership-in-artificial-intelligence-can-shape-the-21st-century-global-order/) from the original on 16 September 2024. Retrieved 8 December 2023. \"Instead, the United States has developed a new area of dominance that the rest of the world views with a mixture of awe, envy, and resentment: artificial intelligence... From AI models and research to cloud computing and venture capital, U.S. companies, universities, and research labs – and their affiliates in allied countries – appear to have an enormous lead in both developing cutting-edge AI and commercializing it. The value of U.S. venture capital investments in AI start-ups exceeds that of the rest of the world combined.\"\\n  * Gertner, Jon. (2023) \"Wikipedia\\'s Moment of Truth: Can the online encyclopedia help teach A.I. chatbots to get their facts right — without destroying itself in the process?\" _New York Times Magazine_ (July 18, 2023) [online](https://www.nytimes.com/2023/07/18/magazine/wikipedia-ai-chatgpt.html) [Archived](https://web.archive.org/web/20230720125400/https://www.nytimes.com/2023/07/18/magazine/wikipedia-ai-chatgpt.html) 20 July 2023 at the [Wayback Machine](/wiki/Wayback_Machine \"Wayback Machine\")\\n  * [Gleick, James](/wiki/Gleick,_James \"Gleick, James\"), \"The Fate of Free Will\" (review of Kevin J. Mitchell, _Free Agents: How Evolution Gave Us Free Will_ , Princeton University Press, 2023, 333 pp.), _[The New York Review of Books](/wiki/The_New_York_Review_of_Books \"The New York Review of Books\")_ , vol. LXXI, no. 1 (18 January 2024), pp. 27–28, 30. \"[Agency](/wiki/Agency_\\\\(philosophy\\\\) \"Agency \\\\(philosophy\\\\)\") is what distinguishes us from machines. For biological creatures, [reason](/wiki/Reason \"Reason\") and [purpose](/wiki/Motivation \"Motivation\") come from acting in the world and experiencing the consequences. Artificial intelligences – disembodied, strangers to blood, sweat, and tears – have no occasion for that.\" (p. 30.)\\n  * Halpern, Sue, \"The Coming Tech Autocracy\" (review of [Verity Harding](/wiki/Verity_Harding \"Verity Harding\"), _AI Needs You: How We Can Change AI\\'s Future and Save Our Own_ , Princeton University Press, 274 pp.; [Gary Marcus](/wiki/Gary_Marcus \"Gary Marcus\"), _Taming Silicon Valley: How We Can Ensure That AI Works for Us_ , MIT Press, 235 pp.; [Daniela Rus](/wiki/Daniela_Rus \"Daniela Rus\") and [Gregory Mone](/w/index.php?title=Gregory_Mone&action=edit&redlink=1 \"Gregory Mone \\\\(page does not exist\\\\)\"), _The Mind\\'s Mirror: Risk and Reward in the Age of AI_ , Norton, 280 pp.; [Madhumita Murgia](/wiki/Madhumita_Murgia \"Madhumita Murgia\"), _Code Dependent: Living in the Shadow of AI_ , Henry Holt, 311 pp.), _[The New York Review of Books](/wiki/The_New_York_Review_of_Books \"The New York Review of Books\")_ , vol. LXXI, no. 17 (7 November 2024), pp. 44–46. \"\\'We can\\'t realistically expect that those who hope to get rich from AI are going to have the interests of the rest of us close at heart,\\' ... writes [Gary Marcus]. \\'We can\\'t count on [governments](/wiki/Government \"Government\") driven by [campaign finance](/wiki/Campaign_finance \"Campaign finance\") contributions [from tech companies] to push back.\\'... Marcus details the demands that citizens should make of their governments and the [tech companies](/wiki/Tech_company \"Tech company\"). They include [transparency](/wiki/Transparency_\\\\(behavior\\\\) \"Transparency \\\\(behavior\\\\)\") on how AI systems work; compensation for individuals if their data [are] used to train LLMs ([large language model](/wiki/Large_language_model \"Large language model\"))s and the right to consent to this use; and the ability to hold tech companies liable for the harms they cause by eliminating [Section 230](/wiki/Section_230 \"Section 230\"), imposing cash penalties, and passing stricter [product liability](/wiki/Product_liability \"Product liability\") laws... Marcus also suggests... that a new, AI-specific federal agency, akin to the [FDA](/wiki/FDA \"FDA\"), the [FCC](/wiki/FCC \"FCC\"), or the [FTC](/wiki/Federal_Trade_Commission \"Federal Trade Commission\"), might provide the most robust oversight.... [T]he [Fordham](/wiki/Fordham_University \"Fordham University\") law professor [Chinmayi Sharma](/w/index.php?title=Chinmayi_Sharma&action=edit&redlink=1 \"Chinmayi Sharma \\\\(page does not exist\\\\)\")... suggests... establish[ing] a professional licensing regime for engineers that would function in a similar way to [medical licenses](/wiki/Medical_license \"Medical license\"), [malpractice](/wiki/Malpractice \"Malpractice\") suits, and the [Hippocratic oath](/wiki/Hippocratic_oath \"Hippocratic oath\") in medicine. \\'What if, like doctors,\\' she asks..., \\'AI engineers also vowed to [do no harm](/wiki/Primum_non_nocere \"Primum non nocere\")?\\'\" (p. 46.)\\n  * Henderson, Mark (24 April 2007). [\"Human rights for robots? We\\'re getting carried away\"](http://www.thetimes.co.uk/tto/technology/article1966391.ece). _The Times Online_. London. [Archived](https://web.archive.org/web/20140531104850/http://www.thetimes.co.uk/tto/technology/article1966391.ece) from the original on 31 May 2014. Retrieved 31 May 2014.\\n  * Hughes-Castleberry, Kenna, \"A Murder Mystery Puzzle: The literary puzzle _[Cain\\'s Jawbone](/wiki/Cain%27s_Jawbone \"Cain\\'s Jawbone\")_ , which has stumped humans for decades, reveals the limitations of natural-language-processing algorithms\", _[Scientific American](/wiki/Scientific_American \"Scientific American\")_ , vol. 329, no. 4 (November 2023), pp. 81–82. \"This murder mystery competition has revealed that although NLP ([natural-language processing](/wiki/Natural-language_processing \"Natural-language processing\")) models are capable of incredible feats, their abilities are very much limited by the amount of [context](/wiki/Context_\\\\(linguistics\\\\) \"Context \\\\(linguistics\\\\)\") they receive. This [...] could cause [difficulties] for researchers who hope to use them to do things such as analyze [ancient languages](/wiki/Ancient_language \"Ancient language\"). In some cases, there are few historical records on long-gone [civilizations](/wiki/Civilization \"Civilization\") to serve as [training data](/wiki/Training_data \"Training data\") for such a purpose.\" (p. 82.)\\n  * [Immerwahr, Daniel](/wiki/Immerwahr,_Daniel \"Immerwahr, Daniel\"), \"Your Lying Eyes: People now use A.I. to generate fake videos indistinguishable from real ones. How much does it matter?\", _[The New Yorker](/wiki/The_New_Yorker \"The New Yorker\")_ , 20 November 2023, pp. 54–59. \"If by \\'[deepfakes](/wiki/Deepfakes \"Deepfakes\")\\' we mean realistic videos produced using artificial intelligence that actually deceive people, then they barely exist. The fakes aren\\'t deep, and the deeps aren\\'t fake. [...] A.I.-generated videos are not, in general, operating in our media as counterfeited evidence. Their role better resembles that of [cartoons](/wiki/Cartoon \"Cartoon\"), especially smutty ones.\" (p. 59.)\\n  * Johnston, John (2008) _The Allure of Machinic Life: Cybernetics, Artificial Life, and the New AI_ , MIT Press.\\n  * Jumper, John; Evans, Richard; Pritzel, Alexander; et al. (26 August 2021). [\"Highly accurate protein structure prediction with AlphaFold\"](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371605). _Nature_. **596** (7873): 583–589. [Bibcode](/wiki/Bibcode_\\\\(identifier\\\\) \"Bibcode \\\\(identifier\\\\)\"):[2021Natur.596..583J](https://ui.adsabs.harvard.edu/abs/2021Natur.596..583J). [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1038/s41586-021-03819-2](https://doi.org/10.1038%2Fs41586-021-03819-2). [PMC](/wiki/PMC_\\\\(identifier\\\\) \"PMC \\\\(identifier\\\\)\") [8371605](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371605). [PMID](/wiki/PMID_\\\\(identifier\\\\) \"PMID \\\\(identifier\\\\)\") [34265844](https://pubmed.ncbi.nlm.nih.gov/34265844). [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [235959867](https://api.semanticscholar.org/CorpusID:235959867).\\n  * LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey (28 May 2015). [\"Deep learning\"](https://www.nature.com/articles/nature14539). _Nature_. **521** (7553): 436–444. [Bibcode](/wiki/Bibcode_\\\\(identifier\\\\) \"Bibcode \\\\(identifier\\\\)\"):[2015Natur.521..436L](https://ui.adsabs.harvard.edu/abs/2015Natur.521..436L). [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1038/nature14539](https://doi.org/10.1038%2Fnature14539). [PMID](/wiki/PMID_\\\\(identifier\\\\) \"PMID \\\\(identifier\\\\)\") [26017442](https://pubmed.ncbi.nlm.nih.gov/26017442). [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [3074096](https://api.semanticscholar.org/CorpusID:3074096). [Archived](https://web.archive.org/web/20230605235832/https://www.nature.com/articles/nature14539) from the original on 5 June 2023. Retrieved 19 June 2023.\\n  * Leffer, Lauren, \"The Risks of Trusting AI: We must avoid humanizing machine-learning models used in scientific research\", _[Scientific American](/wiki/Scientific_American \"Scientific American\")_ , vol. 330, no. 6 (June 2024), pp. 80–81.\\n  * [Lepore, Jill](/wiki/Jill_Lepore \"Jill Lepore\"), \"The Chit-Chatbot: Is talking with a machine a conversation?\", _[The New Yorker](/wiki/The_New_Yorker \"The New Yorker\")_ , 7 October 2024, pp. 12–16.\\n  * Maschafilm (2010). [\"Content: Plug & Pray Film – Artificial Intelligence – Robots\"](http://www.plugandpray-film.de/en/content.html). _plugandpray-film.de_. [Archived](https://web.archive.org/web/20160212040134/http://www.plugandpray-film.de/en/content.html) from the original on 12 February 2016.\\n  * [Marcus, Gary](/wiki/Marcus,_Gary \"Marcus, Gary\"), \"Artificial Confidence: Even the newest, buzziest systems of artificial general intelligence are stymmied by the same old problems\", _[Scientific American](/wiki/Scientific_American \"Scientific American\")_ , vol. 327, no. 4 (October 2022), pp. 42–45.\\n  * Mitchell, Melanie (2019). _Artificial intelligence: a guide for thinking humans_. New York: Farrar, Straus and Giroux. [ISBN](/wiki/ISBN_\\\\(identifier\\\\) \"ISBN \\\\(identifier\\\\)\") [978-0-3742-5783-5](/wiki/Special:BookSources/978-0-3742-5783-5 \"Special:BookSources/978-0-3742-5783-5\").\\n  * Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; et al. (26 February 2015). [\"Human-level control through deep reinforcement learning\"](https://www.nature.com/articles/nature14236). _Nature_. **518** (7540): 529–533. [Bibcode](/wiki/Bibcode_\\\\(identifier\\\\) \"Bibcode \\\\(identifier\\\\)\"):[2015Natur.518..529M](https://ui.adsabs.harvard.edu/abs/2015Natur.518..529M). [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1038/nature14236](https://doi.org/10.1038%2Fnature14236). [PMID](/wiki/PMID_\\\\(identifier\\\\) \"PMID \\\\(identifier\\\\)\") [25719670](https://pubmed.ncbi.nlm.nih.gov/25719670). [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [205242740](https://api.semanticscholar.org/CorpusID:205242740). [Archived](https://web.archive.org/web/20230619055525/https://www.nature.com/articles/nature14236) from the original on 19 June 2023. Retrieved 19 June 2023. Introduced [DQN](/wiki/Deep_Q-learning \"Deep Q-learning\"), which produced human-level performance on some Atari games.\\n  * [Press, Eyal](/wiki/Eyal_Press \"Eyal Press\"), \"In Front of Their Faces: Does facial-recognition technology lead police to ignore contradictory evidence?\", _[The New Yorker](/wiki/The_New_Yorker \"The New Yorker\")_ , 20 November 2023, pp. 20–26.\\n  * [\"Robots could demand legal rights\"](http://news.bbc.co.uk/2/hi/technology/6200005.stm). _BBC News_. 21 December 2006. [Archived](https://web.archive.org/web/20191015042628/http://news.bbc.co.uk/2/hi/technology/6200005.stm) from the original on 15 October 2019. Retrieved 3 February 2011.\\n  * Roivainen, Eka, \"AI\\'s IQ: [ChatGPT](/wiki/ChatGPT \"ChatGPT\") aced a [standard intelligence] test but showed that [intelligence](/wiki/Intelligence \"Intelligence\") cannot be measured by [IQ](/wiki/IQ \"IQ\") alone\", _[Scientific American](/wiki/Scientific_American \"Scientific American\")_ , vol. 329, no. 1 (July/August 2023), p. 7. \"Despite its high IQ, [ChatGPT](/wiki/ChatGPT \"ChatGPT\") fails at tasks that require real humanlike reasoning or an understanding of the physical and social world.... ChatGPT seemed unable to reason logically and tried to rely on its vast database of... facts derived from online texts.\"\\n  * Scharre, Paul, \"Killer Apps: The Real Dangers of an AI Arms Race\", _[Foreign Affairs](/wiki/Foreign_Affairs \"Foreign Affairs\")_ , vol. 98, no. 3 (May/June 2019), pp. 135–144. \"Today\\'s AI technologies are powerful but unreliable. Rules-based systems cannot deal with circumstances their programmers did not anticipate. Learning systems are limited by the data on which they were trained. AI failures have already led to tragedy. Advanced autopilot features in cars, although they perform well in some circumstances, have driven cars without warning into trucks, concrete barriers, and parked cars. In the wrong situation, AI systems go from supersmart to superdumb in an instant. When an enemy is trying to manipulate and hack an AI system, the risks are even greater.\" (p. 140.)\\n  * Schulz, Hannes; Behnke, Sven (1 November 2012). [\"Deep Learning\"](https://www.researchgate.net/publication/230690795). _KI – Künstliche Intelligenz_. **26** (4): 357–363. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1007/s13218-012-0198-z](https://doi.org/10.1007%2Fs13218-012-0198-z). [ISSN](/wiki/ISSN_\\\\(identifier\\\\) \"ISSN \\\\(identifier\\\\)\") [1610-1987](https://search.worldcat.org/issn/1610-1987). [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [220523562](https://api.semanticscholar.org/CorpusID:220523562).\\n  * Serenko, Alexander; Michael Dohan (2011). [\"Comparing the expert survey and citation impact journal ranking methods: Example from the field of Artificial Intelligence\"](http://www.aserenko.com/papers/JOI_AI_Journal_Ranking_Serenko.pdf) (PDF). _Journal of Informetrics_. **5** (4): 629–649. [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1016/j.joi.2011.06.002](https://doi.org/10.1016%2Fj.joi.2011.06.002). [Archived](https://web.archive.org/web/20131004212839/http://www.aserenko.com/papers/JOI_AI_Journal_Ranking_Serenko.pdf) (PDF) from the original on 4 October 2013. Retrieved 12 September 2013.\\n  * Silver, David; Huang, Aja; Maddison, Chris J.; et al. (28 January 2016). [\"Mastering the game of Go with deep neural networks and tree search\"](https://www.nature.com/articles/nature16961). _Nature_. **529** (7587): 484–489. [Bibcode](/wiki/Bibcode_\\\\(identifier\\\\) \"Bibcode \\\\(identifier\\\\)\"):[2016Natur.529..484S](https://ui.adsabs.harvard.edu/abs/2016Natur.529..484S). [doi](/wiki/Doi_\\\\(identifier\\\\) \"Doi \\\\(identifier\\\\)\"):[10.1038/nature16961](https://doi.org/10.1038%2Fnature16961). [PMID](/wiki/PMID_\\\\(identifier\\\\) \"PMID \\\\(identifier\\\\)\") [26819042](https://pubmed.ncbi.nlm.nih.gov/26819042). [S2CID](/wiki/S2CID_\\\\(identifier\\\\) \"S2CID \\\\(identifier\\\\)\") [515925](https://api.semanticscholar.org/CorpusID:515925). [Archived](https://web.archive.org/web/20230618213059/https://www.nature.com/articles/nature16961) from the original on 18 June 2023. Retrieved 19 June 2023.\\n  * [Vaswani, Ashish](/wiki/Ashish_Vaswani \"Ashish Vaswani\"), Noam Shazeer, Niki Parmar et al. \"[Attention is all you need](/wiki/Attention_is_all_you_need \"Attention is all you need\").\" Advances in neural information processing systems 30 (2017). Seminal paper on [transformers](/wiki/Transformer_\\\\(machine_learning_model\\\\) \"Transformer \\\\(machine learning model\\\\)\").\\n  * Vincent, James, \"Horny Robot Baby Voice: James Vincent on AI chatbots\", _[London Review of Books](/wiki/London_Review_of_Books \"London Review of Books\")_ , vol. 46, no. 19 (10 October 2024), pp. 29–32. \"[AI chatbot] programs are made possible by new technologies but rely on the timelelss human tendency to [anthropomorphise](/wiki/Anthropomorphise \"Anthropomorphise\").\" (p. 29.)\\n  * [_White Paper: On Artificial Intelligence – A European approach to excellence and trust_](https://ec.europa.eu/info/sites/info/files/commission-white-paper-artificial-intelligence-feb2020_en.pdf) (PDF). Brussels: European Commission. 2020. [Archived](https://web.archive.org/web/20200220173419/https://ec.europa.eu/info/sites/info/files/commission-white-paper-artificial-intelligence-feb2020_en.pdf) (PDF) from the original on 20 February 2020. Retrieved 20 February 2020.\\n\\n## External links\\n\\n**Artificial intelligence** at Wikipedia\\'s [sister\\nprojects](/wiki/Wikipedia:Wikimedia_sister_projects \"Wikipedia:Wikimedia\\nsister projects\")\\n\\n  * ![](//upload.wikimedia.org/wikipedia/en/thumb/0/06/Wiktionary-logo-v2.svg/27px-Wiktionary-logo-v2.svg.png)[Definitions](https://en.wiktionary.org/wiki/artificial_intelligence \"wikt:artificial intelligence\") from Wiktionary\\n  * ![](//upload.wikimedia.org/wikipedia/en/thumb/4/4a/Commons-logo.svg/20px-Commons-logo.svg.png)[Media](https://commons.wikimedia.org/wiki/Category:Artificial_intelligence \"c:Category:Artificial intelligence\") from Commons\\n  * ![](//upload.wikimedia.org/wikipedia/commons/thumb/f/fa/Wikiquote-logo.svg/23px-Wikiquote-logo.svg.png)[Quotations](https://en.wikiquote.org/wiki/Artificial_intelligence \"q:Artificial intelligence\") from Wikiquote\\n  * ![](//upload.wikimedia.org/wikipedia/commons/thumb/f/fa/Wikibooks-logo.svg/27px-Wikibooks-logo.svg.png)[Textbooks](https://en.wikibooks.org/wiki/Artificial_Intelligence \"b:Artificial Intelligence\") from Wikibooks\\n  * ![](//upload.wikimedia.org/wikipedia/commons/thumb/0/0b/Wikiversity_logo_2017.svg/27px-Wikiversity_logo_2017.svg.png)[Resources](https://en.wikiversity.org/wiki/Portal:Artificial_intelligence \"v:Portal:Artificial intelligence\") from Wikiversity\\n  * ![](//upload.wikimedia.org/wikipedia/commons/thumb/f/ff/Wikidata-logo.svg/27px-Wikidata-logo.svg.png)[Data](https://www.wikidata.org/wiki/Q11660 \"d:Q11660\") from Wikidata\\n\\n![](//upload.wikimedia.org/wikipedia/commons/thumb/3/32/Scholia_logo.svg/40px-\\nScholia_logo.svg.png)\\n\\n[Scholia](https://www.wikidata.org/wiki/Wikidata:Scholia \"d:Wikidata:Scholia\")\\nhas a _topic_ profile for _**[Artificial\\nintelligence](https://iw.toolforge.org/scholia/topic/Q11660\\n\"toolforge:scholia/topic/Q11660\")**_.\\n\\n  * [\"Artificial Intelligence\"](http://www.iep.utm.edu/art-inte). _[Internet Encyclopedia of Philosophy](/wiki/Internet_Encyclopedia_of_Philosophy \"Internet Encyclopedia of Philosophy\")_.\\n  * Thomason, Richmond. [\"Logic and Artificial Intelligence\"](https://plato.stanford.edu/entries/logic-ai/). In [Zalta, Edward N.](/wiki/Edward_N._Zalta \"Edward N. Zalta\") (ed.). _[Stanford Encyclopedia of Philosophy](/wiki/Stanford_Encyclopedia_of_Philosophy \"Stanford Encyclopedia of Philosophy\")_.\\n  * [Artificial Intelligence](https://www.bbc.co.uk/programmes/p003k9fc). BBC Radio 4 discussion with John Agar, Alison Adam & Igor Aleksander (_In Our Time_ , 8 December 2005).\\n\\nshowArticles related to Artificial intelligence  \\n---  \\n| show\\n\\n  * [v](/wiki/Template:John_McCarthy \"Template:John McCarthy\")\\n  * [t](/wiki/Template_talk:John_McCarthy \"Template talk:John McCarthy\")\\n  * [e](/wiki/Special:EditPage/Template:John_McCarthy \"Special:EditPage/Template:John McCarthy\")\\n\\n[John McCarthy](/wiki/John_McCarthy_\\\\(computer_scientist\\\\) \"John McCarthy\\n\\\\(computer scientist\\\\)\")  \\n---  \\n  \\n  * Artificial intelligence\\n  * [Circumscription](/wiki/Circumscription_\\\\(logic\\\\) \"Circumscription \\\\(logic\\\\)\")\\n  * [Dartmouth workshop](/wiki/Dartmouth_workshop \"Dartmouth workshop\")\\n  * [Frame problem](/wiki/Frame_problem \"Frame problem\")\\n  * [Garbage collection](/wiki/Garbage_collection_\\\\(computer_science\\\\) \"Garbage collection \\\\(computer science\\\\)\")\\n  * [Lisp](/wiki/Lisp_\\\\(programming_language\\\\) \"Lisp \\\\(programming language\\\\)\")\\n  * [ALGOL 60](/wiki/ALGOL_60 \"ALGOL 60\")\\n  * [McCarthy evaluation](/wiki/Short-circuit_evaluation \"Short-circuit evaluation\")\\n  * [McCarthy Formalism](/wiki/McCarthy_Formalism \"McCarthy Formalism\")\\n  * [McCarthy 91 function](/wiki/McCarthy_91_function \"McCarthy 91 function\")\\n  * [Situation calculus](/wiki/Situation_calculus \"Situation calculus\")\\n  * [Space fountain](/wiki/Space_fountain \"Space fountain\")\\n\\n  \\n  \\nshow\\n\\n  * [v](/wiki/Template:Philosophy_of_mind \"Template:Philosophy of mind\")\\n  * [t](/wiki/Template_talk:Philosophy_of_mind \"Template talk:Philosophy of mind\")\\n  * [e](/wiki/Special:EditPage/Template:Philosophy_of_mind \"Special:EditPage/Template:Philosophy of mind\")\\n\\n[Philosophy of mind](/wiki/Philosophy_of_mind \"Philosophy of mind\")  \\n---  \\n[Philosophers](/wiki/Category:Philosophers_of_mind \"Category:Philosophers of\\nmind\")|\\n\\n  * [G. E. M. Anscombe](/wiki/G._E._M._Anscombe \"G. E. M. Anscombe\")\\n  * [Aristotle](/wiki/Aristotle \"Aristotle\")\\n  * [Armstrong](/wiki/David_Malet_Armstrong \"David Malet Armstrong\")\\n  * [Thomas Aquinas](/wiki/Thomas_Aquinas \"Thomas Aquinas\")\\n  * [J. L. Austin](/wiki/J._L._Austin \"J. L. Austin\")\\n  * [Alexander Bain](/wiki/Alexander_Bain_\\\\(philosopher\\\\) \"Alexander Bain \\\\(philosopher\\\\)\")\\n  * [George Berkeley](/wiki/George_Berkeley \"George Berkeley\")\\n  * [Henri Bergson](/wiki/Henri_Bergson \"Henri Bergson\")\\n  * [Ned Block](/wiki/Ned_Block \"Ned Block\")\\n  * [Franz Brentano](/wiki/Franz_Brentano \"Franz Brentano\")\\n  * [C. D. Broad](/wiki/C._D._Broad \"C. D. Broad\")\\n  * [Tyler Burge](/wiki/Tyler_Burge \"Tyler Burge\")\\n  * [David Chalmers](/wiki/David_Chalmers \"David Chalmers\")\\n  * [Patricia Churchland](/wiki/Patricia_Churchland \"Patricia Churchland\")\\n  * [Paul Churchland](/wiki/Paul_Churchland \"Paul Churchland\")\\n  * [Andy Clark](/wiki/Andy_Clark \"Andy Clark\")\\n  * [Dharmakirti](/wiki/Dharmakirti \"Dharmakirti\")\\n  * [Donald Davidson](/wiki/Donald_Davidson_\\\\(philosopher\\\\) \"Donald Davidson \\\\(philosopher\\\\)\")\\n  * [Daniel Dennett](/wiki/Daniel_Dennett \"Daniel Dennett\")\\n  * [René Descartes](/wiki/Ren%C3%A9_Descartes \"René Descartes\")\\n  * [Fred Dretske](/wiki/Fred_Dretske \"Fred Dretske\")\\n  * [Fodor](/wiki/Jerry_Fodor \"Jerry Fodor\")\\n  * [Goldman](/wiki/Alvin_Goldman \"Alvin Goldman\")\\n  * [Martin Heidegger](/wiki/Martin_Heidegger \"Martin Heidegger\")\\n  * [David Hume](/wiki/David_Hume \"David Hume\")\\n  * [Edmund Husserl](/wiki/Edmund_Husserl \"Edmund Husserl\")\\n  * [William James](/wiki/William_James \"William James\")\\n  * [Frank Cameron Jackson](/wiki/Frank_Cameron_Jackson \"Frank Cameron Jackson\")\\n  * [Immanuel Kant](/wiki/Immanuel_Kant \"Immanuel Kant\")\\n  * [David Lewis (philosopher)](/wiki/David_Lewis_\\\\(philosopher\\\\) \"David Lewis \\\\(philosopher\\\\)\")\\n  * [John Locke](/wiki/John_Locke \"John Locke\")\\n  * [Gottfried Wilhelm Leibniz](/wiki/Gottfried_Wilhelm_Leibniz \"Gottfried Wilhelm Leibniz\")\\n  * [Maurice Merleau-Ponty](/wiki/Maurice_Merleau-Ponty \"Maurice Merleau-Ponty\")\\n  * [Marvin Minsky](/wiki/Marvin_Minsky \"Marvin Minsky\")\\n  * [Thomas Nagel](/wiki/Thomas_Nagel \"Thomas Nagel\")\\n  * [Alva Noë](/wiki/Alva_No%C3%AB \"Alva Noë\")\\n  * [Derek Parfit](/wiki/Derek_Parfit \"Derek Parfit\")\\n  * [Plato](/wiki/Plato \"Plato\")\\n  * [Hilary Putnam](/wiki/Hilary_Putnam \"Hilary Putnam\")\\n  * [Richard Rorty](/wiki/Richard_Rorty \"Richard Rorty\")\\n  * [Gilbert Ryle](/wiki/Gilbert_Ryle \"Gilbert Ryle\")\\n  * [John Searle](/wiki/John_Searle \"John Searle\")\\n  * [Wilfrid Sellars](/wiki/Wilfrid_Sellars \"Wilfrid Sellars\")\\n  * [Baruch Spinoza](/wiki/Baruch_Spinoza \"Baruch Spinoza\")\\n  * [Alan Turing](/wiki/Alan_Turing \"Alan Turing\")\\n  * [Michael Tye](/wiki/Michael_Tye_\\\\(philosopher\\\\) \"Michael Tye \\\\(philosopher\\\\)\")\\n  * [Vasubandhu](/wiki/Vasubandhu \"Vasubandhu\")\\n  * [Ludwig Wittgenstein](/wiki/Ludwig_Wittgenstein \"Ludwig Wittgenstein\")\\n  * [Stephen Yablo](/wiki/Stephen_Yablo \"Stephen Yablo\")\\n  * [Zhuangzi](/wiki/Zhuang_Zhou \"Zhuang Zhou\")\\n  * _[more...](/wiki/List_of_philosophers_of_mind \"List of philosophers of mind\")_\\n\\n  \\nTheories|\\n\\n  * [Behaviorism](/wiki/Behaviorism \"Behaviorism\")\\n  * [Biological naturalism](/wiki/Biological_naturalism \"Biological naturalism\")\\n  * [Dualism](/wiki/Mind%E2%80%93body_dualism \"Mind–body dualism\")\\n  * [Eliminative materialism](/wiki/Eliminative_materialism \"Eliminative materialism\")\\n  * [Emergent materialism](/wiki/Emergent_materialism \"Emergent materialism\")\\n  * [Epiphenomenalism](/wiki/Epiphenomenalism \"Epiphenomenalism\")\\n  * [Functionalism](/wiki/Functionalism_\\\\(philosophy_of_mind\\\\) \"Functionalism \\\\(philosophy of mind\\\\)\")\\n  * [Interactionism](/wiki/Interactionism_\\\\(philosophy_of_mind\\\\) \"Interactionism \\\\(philosophy of mind\\\\)\")\\n  * [Naïve realism](/wiki/Na%C3%AFve_realism \"Naïve realism\")\\n    * [Neurophenomenology](/wiki/Neurophenomenology \"Neurophenomenology\")\\n  * [Neutral monism](/wiki/Neutral_monism \"Neutral monism\")\\n  * [New mysterianism](/wiki/New_mysterianism \"New mysterianism\")\\n  * [Nondualism](/wiki/Nondualism \"Nondualism\")\\n  * [Occasionalism](/wiki/Occasionalism \"Occasionalism\")\\n  * [Parallelism](/wiki/Psychophysical_parallelism \"Psychophysical parallelism\")\\n  * [Phenomenalism](/wiki/Phenomenalism \"Phenomenalism\")\\n  * [Phenomenology](/wiki/Phenomenology_\\\\(philosophy\\\\) \"Phenomenology \\\\(philosophy\\\\)\")\\n  * [Physicalism](/wiki/Physicalism \"Physicalism\")\\n    * [Type physicalism](/wiki/Type_physicalism \"Type physicalism\")\\n  * [Property dualism](/wiki/Property_dualism \"Property dualism\")\\n  * [Representational](/wiki/Mental_representation \"Mental representation\")\\n  * [Solipsism](/wiki/Solipsism \"Solipsism\")\\n  * [Substance dualism](/wiki/Substance_dualism \"Substance dualism\")\\n\\n  \\nConcepts|\\n\\n  * [Abstract object](/wiki/Abstract_and_concrete \"Abstract and concrete\")\\n  * [Chinese room](/wiki/Chinese_room \"Chinese room\")\\n  * [Creativity](/wiki/Creativity \"Creativity\")\\n  * [Cognition](/wiki/Cognition \"Cognition\")\\n  * [Cognitive closure](/wiki/Cognitive_closure_\\\\(philosophy\\\\) \"Cognitive closure \\\\(philosophy\\\\)\")\\n  * [Concept](/wiki/Concept \"Concept\")\\n  * [Consciousness](/wiki/Consciousness \"Consciousness\")\\n  * [Hard problem of consciousness](/wiki/Hard_problem_of_consciousness \"Hard problem of consciousness\")\\n  * [Hypostatic abstraction](/wiki/Hypostatic_abstraction \"Hypostatic abstraction\")\\n  * [Idea](/wiki/Idea \"Idea\")\\n  * [Identity](/wiki/Identity_\\\\(philosophy\\\\) \"Identity \\\\(philosophy\\\\)\")\\n  * [Intelligence](/wiki/Intelligence \"Intelligence\")\\n    * Artificial\\n    * [Human](/wiki/Human_intelligence \"Human intelligence\")\\n  * [Intentionality](/wiki/Intentionality \"Intentionality\")\\n  * [Introspection](/wiki/Introspection \"Introspection\")\\n  * [Intuition](/wiki/Intuition \"Intuition\")\\n  * [Language of thought](/wiki/Language_of_thought_hypothesis \"Language of thought hypothesis\")\\n  * [Mental event](/wiki/Mental_event \"Mental event\")\\n  * [Mental image](/wiki/Mental_image \"Mental image\")\\n  * [Mental process](/wiki/Template:Mental_processes \"Template:Mental processes\")\\n  * [Mental property](/wiki/Mental_state \"Mental state\")\\n  * [Mental representation](/wiki/Mental_representation \"Mental representation\")\\n  * [Mind](/wiki/Mind \"Mind\")\\n  * [Mind–body problem](/wiki/Mind%E2%80%93body_problem \"Mind–body problem\")\\n  * [Pain](/wiki/Pain_\\\\(philosophy\\\\) \"Pain \\\\(philosophy\\\\)\")\\n  * [Problem of other minds](/wiki/Problem_of_other_minds \"Problem of other minds\")\\n  * [Propositional attitude](/wiki/Propositional_attitude \"Propositional attitude\")\\n  * [Qualia](/wiki/Qualia \"Qualia\")\\n  * [Tabula rasa](/wiki/Tabula_rasa \"Tabula rasa\")\\n  * [Understanding](/wiki/Understanding \"Understanding\")\\n  * [Zombie](/wiki/Philosophical_zombie \"Philosophical zombie\")\\n\\n  \\nRelated|\\n\\n  * [Metaphysics](/wiki/Metaphysics \"Metaphysics\")\\n  * [Philosophy of artificial intelligence](/wiki/Philosophy_of_artificial_intelligence \"Philosophy of artificial intelligence\") / [information](/wiki/Philosophy_of_information \"Philosophy of information\") / [perception](/wiki/Philosophy_of_perception \"Philosophy of perception\") / [self](/wiki/Philosophy_of_self \"Philosophy of self\")\\n\\n  \\n  \\n  * [Category](/wiki/Category:Philosophy_of_mind \"Category:Philosophy of mind\")\\n  * [Philosophers category](/wiki/Category:Philosophers_of_mind \"Category:Philosophers of mind\")\\n  * [Project](/wiki/Wikipedia:WikiProject_Philosophy \"Wikipedia:WikiProject Philosophy\")\\n  * [Task Force](/wiki/Wikipedia:WikiProject_Philosophy/Mind \"Wikipedia:WikiProject Philosophy/Mind\")\\n\\n  \\n  \\nshow\\n\\n  * [v](/wiki/Template:Philosophy_of_science \"Template:Philosophy of science\")\\n  * [t](/wiki/Template_talk:Philosophy_of_science \"Template talk:Philosophy of science\")\\n  * [e](/wiki/Special:EditPage/Template:Philosophy_of_science \"Special:EditPage/Template:Philosophy of science\")\\n\\n[Philosophy of science](/wiki/Philosophy_of_science \"Philosophy of science\")  \\n---  \\nConcepts|\\n\\n  * [Analysis](/wiki/Philosophical_analysis \"Philosophical analysis\")\\n  * [Analytic–synthetic distinction](/wiki/Analytic%E2%80%93synthetic_distinction \"Analytic–synthetic distinction\")\\n  * [_A priori_ and _a posteriori_](/wiki/A_priori_and_a_posteriori \"A priori and a posteriori\")\\n  * [Causality](/wiki/Causality \"Causality\")\\n    * [Mill\\'s Methods](/wiki/Mill%27s_Methods \"Mill\\'s Methods\")\\n  * [Commensurability](/wiki/Commensurability_\\\\(philosophy_of_science\\\\) \"Commensurability \\\\(philosophy of science\\\\)\")\\n  * [Consilience](/wiki/Consilience \"Consilience\")\\n  * [Construct](/wiki/Construct_\\\\(philosophy\\\\) \"Construct \\\\(philosophy\\\\)\")\\n  * [Correlation](/wiki/Correlation \"Correlation\")\\n    * [function](/wiki/Correlation_function \"Correlation function\")\\n  * [Creative synthesis](/wiki/Creative_synthesis \"Creative synthesis\")\\n  * [Demarcation problem](/wiki/Demarcation_problem \"Demarcation problem\")\\n  * [Empirical evidence](/wiki/Empirical_evidence \"Empirical evidence\")\\n  * [Experiment](/wiki/Experiment \"Experiment\")\\n    * [design](/wiki/Design_of_experiments \"Design of experiments\")\\n  * [Explanatory power](/wiki/Explanatory_power \"Explanatory power\")\\n  * [Fact](/wiki/Fact \"Fact\")\\n  * [Falsifiability](/wiki/Falsifiability \"Falsifiability\")\\n  * [Feminist method](/wiki/Feminist_method \"Feminist method\")\\n  * [Functional contextualism](/wiki/Functional_contextualism \"Functional contextualism\")\\n  * [Hypothesis](/wiki/Hypothesis \"Hypothesis\")\\n    * [alternative](/wiki/Alternative_hypothesis \"Alternative hypothesis\")\\n    * [null](/wiki/Null_hypothesis \"Null hypothesis\")\\n  * _[Ignoramus et ignorabimus](/wiki/Ignoramus_et_ignorabimus \"Ignoramus et ignorabimus\")_\\n  * [Inductive reasoning](/wiki/Inductive_reasoning \"Inductive reasoning\")\\n  * [Intertheoretic reduction](/wiki/Intertheoretic_reduction \"Intertheoretic reduction\")\\n  * [Inquiry](/wiki/Inquiry \"Inquiry\")\\n  * [Nature](/wiki/Nature_\\\\(philosophy\\\\) \"Nature \\\\(philosophy\\\\)\")\\n  * [Objectivity](/wiki/Objectivity_\\\\(philosophy\\\\) \"Objectivity \\\\(philosophy\\\\)\")\\n  * [Observation](/wiki/Observation \"Observation\")\\n  * [Paradigm](/wiki/Paradigm \"Paradigm\")\\n  * [Problem of induction](/wiki/Problem_of_induction \"Problem of induction\")\\n  * [Scientific evidence](/wiki/Scientific_evidence \"Scientific evidence\")\\n    * [Evidence-based practice](/wiki/Evidence-based_practice \"Evidence-based practice\")\\n  * [Scientific law](/wiki/Scientific_law \"Scientific law\")\\n  * [Scientific method](/wiki/Scientific_method \"Scientific method\")\\n  * [Scientific pluralism](/wiki/Scientific_pluralism \"Scientific pluralism\")\\n  * [Scientific Revolution](/wiki/Scientific_Revolution \"Scientific Revolution\")\\n  * [Testability](/wiki/Testability \"Testability\")\\n  * [Theory](/wiki/Theory \"Theory\")\\n    * [choice](/wiki/Theory_choice \"Theory choice\")\\n    * [ladenness](/wiki/Theory-ladenness \"Theory-ladenness\")\\n    * [scientific](/wiki/Scientific_theory \"Scientific theory\")\\n  * [Underdetermination](/wiki/Underdetermination \"Underdetermination\")\\n  * [Unity of science](/wiki/Unity_of_science \"Unity of science\")\\n  * [Variable](/wiki/Variable_and_attribute_\\\\(research\\\\) \"Variable and attribute \\\\(research\\\\)\")\\n    * [control](/wiki/Control_variable \"Control variable\")\\n    * [dependent and independent](/wiki/Dependent_and_independent_variables \"Dependent and independent variables\")\\n  * [more...](/wiki/Index_of_philosophy_of_science_articles \"Index of philosophy of science articles\")\\n\\n  \\nTheories|\\n\\n  * [Coherentism](/wiki/Coherentism \"Coherentism\")\\n  * [Confirmation holism](/wiki/Confirmation_holism \"Confirmation holism\")\\n  * [Constructive empiricism](/wiki/Constructive_empiricism \"Constructive empiricism\")\\n  * [Constructive realism](/wiki/Constructive_realism \"Constructive realism\")\\n  * [Constructivist epistemology](/wiki/Constructivist_epistemology \"Constructivist epistemology\")\\n  * [Contextualism](/wiki/Contextualism \"Contextualism\")\\n  * [Conventionalism](/wiki/Conventionalism \"Conventionalism\")\\n  * [Deductive-nomological model](/wiki/Deductive-nomological_model \"Deductive-nomological model\")\\n  * [Epistemological anarchism](/wiki/Epistemological_anarchism \"Epistemological anarchism\")\\n  * [Evolutionism](/wiki/Evolutionism \"Evolutionism\")\\n  * [Fallibilism](/wiki/Fallibilism \"Fallibilism\")\\n  * [Foundationalism](/wiki/Foundationalism \"Foundationalism\")\\n  * [Hypothetico-deductive model](/wiki/Hypothetico-deductive_model \"Hypothetico-deductive model\")\\n  * [Inductionism](/wiki/Inductionism \"Inductionism\")\\n  * [Instrumentalism](/wiki/Instrumentalism \"Instrumentalism\")\\n  * [Model-dependent realism](/wiki/Model-dependent_realism \"Model-dependent realism\")\\n  * [Naturalism](/wiki/Naturalism_\\\\(philosophy\\\\) \"Naturalism \\\\(philosophy\\\\)\")\\n  * [Physicalism](/wiki/Physicalism \"Physicalism\")\\n  * [Positivism](/wiki/Positivism \"Positivism\") / [Reductionism](/wiki/Reductionism \"Reductionism\") / [Determinism](/wiki/Determinism \"Determinism\")\\n  * [Pragmatism](/wiki/Pragmatism \"Pragmatism\")\\n  * [Rationalism](/wiki/Rationalism \"Rationalism\") / [Empiricism](/wiki/Empiricism \"Empiricism\")\\n  * [Received view](/wiki/Received_view_of_theories \"Received view of theories\") / [Semantic view of theories](/wiki/Semantic_view_of_theories \"Semantic view of theories\")\\n  * [Scientific essentialism](/wiki/Scientific_essentialism \"Scientific essentialism\")\\n  * [Scientific formalism](/wiki/Scientific_formalism \"Scientific formalism\")\\n  * [Scientific realism](/wiki/Scientific_realism \"Scientific realism\") / [Anti-realism](/wiki/Anti-realism \"Anti-realism\")\\n  * [Scientific skepticism](/wiki/Scientific_skepticism \"Scientific skepticism\")\\n  * [Scientism](/wiki/Scientism \"Scientism\")\\n  * [Structuralism](/wiki/Structuralism_\\\\(philosophy_of_science\\\\) \"Structuralism \\\\(philosophy of science\\\\)\")\\n  * [Uniformitarianism](/wiki/Uniformitarianism \"Uniformitarianism\")\\n  * [Verificationism](/wiki/Verificationism \"Verificationism\")\\n  * [Vitalism](/wiki/Vitalism \"Vitalism\")\\n\\n  \\nPhilosophy of...|\\n\\n  * [Biology](/wiki/Philosophy_of_biology \"Philosophy of biology\")\\n  * [Chemistry](/wiki/Philosophy_of_chemistry \"Philosophy of chemistry\")\\n  * [Physics](/wiki/Philosophy_of_physics \"Philosophy of physics\")\\n    * [Space and time](/wiki/Philosophy_of_space_and_time \"Philosophy of space and time\")\\n  * [Social science](/wiki/Philosophy_of_social_science \"Philosophy of social science\")\\n    * [Archaeology](/wiki/Philosophy_of_archaeology \"Philosophy of archaeology\")\\n    * [Economics\\u200e](/wiki/Philosophy_of_economics \"Philosophy of economics\")\\n    * [Geography](/wiki/Philosophy_of_geography \"Philosophy of geography\")\\n    * [History](/wiki/Philosophy_of_history \"Philosophy of history\")\\n    * [Linguistics](/wiki/Philosophy_of_linguistics \"Philosophy of linguistics\")\\n    * [Psychology](/wiki/Philosophy_of_psychology \"Philosophy of psychology\")\\n\\n  \\nRelated topics|\\n\\n  * [Criticism of science](/wiki/Criticism_of_science \"Criticism of science\")\\n  * [Descriptive science](/wiki/Descriptive_research \"Descriptive research\")\\n  * [Epistemology](/wiki/Epistemology \"Epistemology\")\\n  * [Exact sciences](/wiki/Exact_sciences \"Exact sciences\")\\n  * [Faith and rationality](/wiki/Faith_and_rationality \"Faith and rationality\")\\n  * [Hard and soft science](/wiki/Hard_and_soft_science \"Hard and soft science\")\\n  * [History and philosophy of science](/wiki/History_and_philosophy_of_science \"History and philosophy of science\")\\n  * [Non-science](/wiki/Non-science \"Non-science\")\\n    * [Pseudoscience](/wiki/Pseudoscience \"Pseudoscience\")\\n  * [Normative science](/wiki/Normative_science \"Normative science\")\\n  * [Protoscience](/wiki/Protoscience \"Protoscience\")\\n  * [Questionable cause](/wiki/Questionable_cause \"Questionable cause\")\\n  * [Relationship between religion and science](/wiki/Relationship_between_religion_and_science \"Relationship between religion and science\")\\n  * [Rhetoric of science](/wiki/Rhetoric_of_science \"Rhetoric of science\")\\n  * [Science studies](/wiki/Science_studies \"Science studies\")\\n  * [Sociology of scientific ignorance](/wiki/Sociology_of_scientific_ignorance \"Sociology of scientific ignorance\")\\n  * [Sociology of scientific knowledge](/wiki/Sociology_of_scientific_knowledge \"Sociology of scientific knowledge\")\\n\\n  \\n[Philosophers of science](/wiki/List_of_philosophers_of_science \"List of philosophers of science\")| | Precursors| \\n\\n  * [Roger Bacon](/wiki/Roger_Bacon \"Roger Bacon\")\\n  * [Francis Bacon](/wiki/Francis_Bacon \"Francis Bacon\")\\n  * [Galileo Galilei](/wiki/Galileo_Galilei \"Galileo Galilei\")\\n  * [Isaac Newton](/wiki/Isaac_Newton \"Isaac Newton\")\\n  * [David Hume](/wiki/David_Hume \"David Hume\")\\n\\n  \\n---|---  \\n  \\n  * [Auguste Comte](/wiki/Auguste_Comte \"Auguste Comte\")\\n  * [Henri Poincaré](/wiki/Henri_Poincar%C3%A9 \"Henri Poincaré\")\\n  * [Pierre Duhem](/wiki/Pierre_Duhem \"Pierre Duhem\")\\n  * [Rudolf Steiner](/wiki/Rudolf_Steiner \"Rudolf Steiner\")\\n  * [Karl Pearson](/wiki/Karl_Pearson \"Karl Pearson\")\\n  * [Charles Sanders Peirce](/wiki/Charles_Sanders_Peirce \"Charles Sanders Peirce\")\\n  * [Wilhelm Windelband](/wiki/Wilhelm_Windelband \"Wilhelm Windelband\")\\n  * [Alfred North Whitehead](/wiki/Alfred_North_Whitehead \"Alfred North Whitehead\")\\n  * [Bertrand Russell](/wiki/Bertrand_Russell \"Bertrand Russell\")\\n  * [Otto Neurath](/wiki/Otto_Neurath \"Otto Neurath\")\\n  * [C. D. Broad](/wiki/C._D._Broad \"C. D. Broad\")\\n  * [Michael Polanyi](/wiki/Michael_Polanyi \"Michael Polanyi\")\\n  * [Hans Reichenbach](/wiki/Hans_Reichenbach \"Hans Reichenbach\")\\n  * [Rudolf Carnap](/wiki/Rudolf_Carnap \"Rudolf Carnap\")\\n  * [Karl Popper](/wiki/Karl_Popper \"Karl Popper\")\\n  * [Carl Gustav Hempel](/wiki/Carl_Gustav_Hempel \"Carl Gustav Hempel\")\\n  * [W. V. O. Quine](/wiki/Willard_Van_Orman_Quine \"Willard Van Orman Quine\")\\n  * [Thomas Kuhn](/wiki/Thomas_Kuhn \"Thomas Kuhn\")\\n  * [Imre Lakatos](/wiki/Imre_Lakatos \"Imre Lakatos\")\\n  * [Paul Feyerabend](/wiki/Paul_Feyerabend \"Paul Feyerabend\")\\n  * [Ian Hacking](/wiki/Ian_Hacking \"Ian Hacking\")\\n  * [Bas van Fraassen](/wiki/Bas_van_Fraassen \"Bas van Fraassen\")\\n  * [Larry Laudan](/wiki/Larry_Laudan \"Larry Laudan\")\\n\\n  \\n  \\n* [Category](/wiki/Category:Philosophy_of_science \"Category:Philosophy of science\")\\n* ![](//upload.wikimedia.org/wikipedia/commons/thumb/c/cd/Socrates.png/18px-Socrates.png) [Philosophy portal](/wiki/Portal:Philosophy \"Portal:Philosophy\")\\n* [![icon](//upload.wikimedia.org/wikipedia/commons/thumb/8/8b/Nuvola_apps_kalzium.svg/28px-Nuvola_apps_kalzium.svg.png)](/wiki/File:Nuvola_apps_kalzium.svg) [Science portal](/wiki/Portal:Science \"Portal:Science\")  \\n  \\nshow\\n\\n  * [v](/wiki/Template:Evolutionary_computation \"Template:Evolutionary computation\")\\n  * [t](/wiki/Template_talk:Evolutionary_computation \"Template talk:Evolutionary computation\")\\n  * [e](/wiki/Special:EditPage/Template:Evolutionary_computation \"Special:EditPage/Template:Evolutionary computation\")\\n\\n[Evolutionary computation](/wiki/Evolutionary_computation \"Evolutionary\\ncomputation\")  \\n---  \\nMain Topics|\\n\\n  * [Evolutionary algorithm](/wiki/Evolutionary_algorithm \"Evolutionary algorithm\")\\n  * [Evolutionary data mining](/wiki/Evolutionary_data_mining \"Evolutionary data mining\")\\n  * [Evolutionary multimodal optimization](/wiki/Evolutionary_multimodal_optimization \"Evolutionary multimodal optimization\")\\n  * [Human-based evolutionary computation](/wiki/Human-based_evolutionary_computation \"Human-based evolutionary computation\")\\n  * [Interactive evolutionary computation](/wiki/Interactive_evolutionary_computation \"Interactive evolutionary computation\")\\n\\n  \\n[Algorithms](/wiki/Algorithm \"Algorithm\")|\\n\\n  * [Cellular evolutionary algorithm](/wiki/Cellular_evolutionary_algorithm \"Cellular evolutionary algorithm\")\\n  * [Covariance Matrix Adaptation Evolution Strategy (CMA-ES)](/wiki/CMA-ES \"CMA-ES\")\\n  * [Cultural algorithm](/wiki/Cultural_algorithm \"Cultural algorithm\")\\n  * [Differential evolution](/wiki/Differential_evolution \"Differential evolution\")\\n  * [Evolutionary programming](/wiki/Evolutionary_programming \"Evolutionary programming\")\\n  * [Genetic algorithm](/wiki/Genetic_algorithm \"Genetic algorithm\")\\n  * [Genetic programming](/wiki/Genetic_programming \"Genetic programming\")\\n  * [Gene expression programming](/wiki/Gene_expression_programming \"Gene expression programming\")\\n  * [Evolution strategy](/wiki/Evolution_strategy \"Evolution strategy\")\\n  * [Natural evolution strategy](/wiki/Natural_evolution_strategy \"Natural evolution strategy\")\\n  * [Neuroevolution](/wiki/Neuroevolution \"Neuroevolution\")\\n  * [Learning classifier system](/wiki/Learning_classifier_system \"Learning classifier system\")\\n\\n  \\nRelated techniques|\\n\\n  * [Swarm intelligence](/wiki/Swarm_intelligence \"Swarm intelligence\")\\n  * [Ant colony optimization](/wiki/Ant_colony_optimization \"Ant colony optimization\")\\n  * [Bees algorithm](/wiki/Bees_algorithm \"Bees algorithm\")\\n  * [Cuckoo search](/wiki/Cuckoo_search \"Cuckoo search\")\\n  * [Particle swarm optimization](/wiki/Particle_swarm_optimization \"Particle swarm optimization\")\\n  * [Bacterial Colony Optimization](/wiki/Bacterial_Colony_Optimization \"Bacterial Colony Optimization\")\\n\\n  \\n[Metaheuristic methods](/wiki/Metaheuristic \"Metaheuristic\")|\\n\\n  * [Firefly algorithm](/wiki/Firefly_algorithm \"Firefly algorithm\")\\n  * [Harmony search](/wiki/Harmony_search \"Harmony search\")\\n  * [Gaussian adaptation](/wiki/Gaussian_adaptation \"Gaussian adaptation\")\\n  * [Memetic algorithm](/wiki/Memetic_algorithm \"Memetic algorithm\")\\n\\n  \\nRelated topics|\\n\\n  * [Artificial development](/wiki/Artificial_development \"Artificial development\")\\n  * Artificial intelligence\\n  * [Artificial life](/wiki/Artificial_life \"Artificial life\")\\n  * [Digital organism](/wiki/Digital_organism \"Digital organism\")\\n  * [Evolutionary robotics](/wiki/Evolutionary_robotics \"Evolutionary robotics\")\\n  * [Fitness function](/wiki/Fitness_function \"Fitness function\")\\n  * [Fitness landscape](/wiki/Fitness_landscape \"Fitness landscape\")\\n  * [Fitness approximation](/wiki/Fitness_approximation \"Fitness approximation\")\\n  * [Genetic operators](/wiki/Genetic_operators \"Genetic operators\")\\n  * [Interactive evolutionary computation](/wiki/Interactive_evolutionary_computation \"Interactive evolutionary computation\")\\n  * [No free lunch in search and optimization](/wiki/No_free_lunch_in_search_and_optimization \"No free lunch in search and optimization\")\\n  * [Machine learning](/wiki/Machine_learning \"Machine learning\")\\n  * [Mating pool](/wiki/Mating_pool \"Mating pool\")\\n  * [Program synthesis](/wiki/Program_synthesis \"Program synthesis\")\\n\\n  \\n[Journals](/wiki/Academic_journal \"Academic journal\")|\\n\\n  * [Evolutionary Computation (journal)](/wiki/Evolutionary_Computation_\\\\(journal\\\\) \"Evolutionary Computation \\\\(journal\\\\)\")\\n\\n  \\n  \\nshow\\n\\n  * [v](/wiki/Template:Differentiable_computing \"Template:Differentiable computing\")\\n  * [t](/wiki/Template_talk:Differentiable_computing \"Template talk:Differentiable computing\")\\n  * [e](/wiki/Special:EditPage/Template:Differentiable_computing \"Special:EditPage/Template:Differentiable computing\")\\n\\nDifferentiable computing  \\n---  \\n[General](/wiki/Differentiable_function \"Differentiable function\")|\\n\\n  * **[Differentiable programming](/wiki/Differentiable_programming \"Differentiable programming\")**\\n  * [Information geometry](/wiki/Information_geometry \"Information geometry\")\\n  * [Statistical manifold](/wiki/Statistical_manifold \"Statistical manifold\")\\n  * [Automatic differentiation](/wiki/Automatic_differentiation \"Automatic differentiation\")\\n  * [Neuromorphic engineering](/wiki/Neuromorphic_engineering \"Neuromorphic engineering\")\\n  * [Pattern recognition](/wiki/Pattern_recognition \"Pattern recognition\")\\n  * [Tensor calculus](/wiki/Tensor_calculus \"Tensor calculus\")\\n  * [Computational learning theory](/wiki/Computational_learning_theory \"Computational learning theory\")\\n  * [Inductive bias](/wiki/Inductive_bias \"Inductive bias\")\\n\\n  \\nConcepts|\\n\\n  * [Parameter](/wiki/Parameter \"Parameter\")\\n    * [Hyperparameter](/wiki/Hyperparameter_\\\\(machine_learning\\\\) \"Hyperparameter \\\\(machine learning\\\\)\")\\n  * [Loss functions](/wiki/Loss_functions_for_classification \"Loss functions for classification\")\\n  * [Regression](/wiki/Regression_analysis \"Regression analysis\")\\n    * [Bias–variance tradeoff](/wiki/Bias%E2%80%93variance_tradeoff \"Bias–variance tradeoff\")\\n    * [Double descent](/wiki/Double_descent \"Double descent\")\\n    * [Overfitting](/wiki/Overfitting \"Overfitting\")\\n  * [Clustering](/wiki/Cluster_analysis \"Cluster analysis\")\\n  * [Gradient descent](/wiki/Gradient_descent \"Gradient descent\")\\n    * [SGD](/wiki/Stochastic_gradient_descent \"Stochastic gradient descent\")\\n    * [Quasi-Newton method](/wiki/Quasi-Newton_method \"Quasi-Newton method\")\\n    * [Conjugate gradient descent](/wiki/Conjugate_gradient_descent \"Conjugate gradient descent\")\\n  * [Backpropagation](/wiki/Backpropagation \"Backpropagation\")\\n  * [Attention](/wiki/Attention_\\\\(machine_learning\\\\) \"Attention \\\\(machine learning\\\\)\")\\n  * [Convolution](/wiki/Convolution \"Convolution\")\\n  * [Normalization](/wiki/Normalization_\\\\(machine_learning\\\\) \"Normalization \\\\(machine learning\\\\)\")\\n    * [Batchnorm](/wiki/Batch_normalization \"Batch normalization\")\\n  * [Activation](/wiki/Activation_function \"Activation function\")\\n    * [Softmax](/wiki/Softmax_function \"Softmax function\")\\n    * [Sigmoid](/wiki/Sigmoid_function \"Sigmoid function\")\\n    * [Rectifier](/wiki/Rectifier_\\\\(neural_networks\\\\) \"Rectifier \\\\(neural networks\\\\)\")\\n  * [Gating](/wiki/Gating_mechanism \"Gating mechanism\")\\n  * [Weight initialization](/wiki/Weight_initialization \"Weight initialization\")\\n  * [Regularization](/wiki/Regularization_\\\\(mathematics\\\\) \"Regularization \\\\(mathematics\\\\)\")\\n  * [Datasets](/wiki/Training,_validation,_and_test_sets \"Training, validation, and test sets\")\\n    * [Augmentation](/wiki/Data_augmentation \"Data augmentation\")\\n  * [Reinforcement learning](/wiki/Reinforcement_learning \"Reinforcement learning\")\\n    * [Q-learning](/wiki/Q-learning \"Q-learning\")\\n    * [SARSA](/wiki/State%E2%80%93action%E2%80%93reward%E2%80%93state%E2%80%93action \"State–action–reward–state–action\")\\n    * [Imitation](/wiki/Imitation_learning \"Imitation learning\")\\n  * [Diffusion](/wiki/Diffusion_process \"Diffusion process\")\\n  * [Autoregression](/wiki/Autoregressive_model \"Autoregressive model\")\\n  * [Adversary](/wiki/Adversarial_machine_learning \"Adversarial machine learning\")\\n  * [Hallucination](/wiki/Hallucination_\\\\(artificial_intelligence\\\\) \"Hallucination \\\\(artificial intelligence\\\\)\")\\n\\n  \\nApplications|\\n\\n  * [Machine learning](/wiki/Machine_learning \"Machine learning\")\\n    * [In-context learning](/wiki/Prompt_engineering#In-context_learning \"Prompt engineering\")\\n  * [Artificial neural network](/wiki/Artificial_neural_network \"Artificial neural network\")\\n    * [Deep learning](/wiki/Deep_learning \"Deep learning\")\\n  * [Scientific computing](/wiki/Computational_science \"Computational science\")\\n  * Artificial Intelligence\\n  * [Language model](/wiki/Language_model \"Language model\")\\n    * [Large language model](/wiki/Large_language_model \"Large language model\")\\n    * [NMT](/wiki/Neural_machine_translation \"Neural machine translation\")\\n\\n  \\nHardware|\\n\\n  * [IPU](/wiki/Graphcore \"Graphcore\")\\n  * [TPU](/wiki/Tensor_Processing_Unit \"Tensor Processing Unit\")\\n  * [VPU](/wiki/Vision_processing_unit \"Vision processing unit\")\\n  * [Memristor](/wiki/Memristor \"Memristor\")\\n  * [SpiNNaker](/wiki/SpiNNaker \"SpiNNaker\")\\n\\n  \\nSoftware libraries|\\n\\n  * [TensorFlow](/wiki/TensorFlow \"TensorFlow\")\\n  * [PyTorch](/wiki/PyTorch \"PyTorch\")\\n  * [Keras](/wiki/Keras \"Keras\")\\n  * [scikit-learn](/wiki/Scikit-learn \"Scikit-learn\")\\n  * [Theano](/wiki/Theano_\\\\(software\\\\) \"Theano \\\\(software\\\\)\")\\n  * [JAX](/wiki/Google_JAX \"Google JAX\")\\n  * [Flux.jl](/wiki/Flux_\\\\(machine-learning_framework\\\\) \"Flux \\\\(machine-learning framework\\\\)\")\\n  * [MindSpore](/wiki/MindSpore \"MindSpore\")\\n\\n  \\nImplementations| | Audio–visual| \\n\\n  * [AlexNet](/wiki/AlexNet \"AlexNet\")\\n  * [WaveNet](/wiki/WaveNet \"WaveNet\")\\n  * [Human image synthesis](/wiki/Human_image_synthesis \"Human image synthesis\")\\n  * [HWR](/wiki/Handwriting_recognition \"Handwriting recognition\")\\n  * [OCR](/wiki/Optical_character_recognition \"Optical character recognition\")\\n  * [Speech synthesis](/wiki/Deep_learning_speech_synthesis \"Deep learning speech synthesis\")\\n  * [Speech recognition](/wiki/Speech_recognition \"Speech recognition\")\\n  * [Facial recognition](/wiki/Facial_recognition_system \"Facial recognition system\")\\n  * [AlphaFold](/wiki/AlphaFold \"AlphaFold\")\\n  * [Text-to-image models](/wiki/Text-to-image_model \"Text-to-image model\")\\n    * [Latent diffusion model](/wiki/Latent_diffusion_model \"Latent diffusion model\")\\n    * [DALL-E](/wiki/DALL-E \"DALL-E\")\\n    * [Midjourney](/wiki/Midjourney \"Midjourney\")\\n    * [Stable Diffusion](/wiki/Stable_Diffusion \"Stable Diffusion\")\\n  * [Text-to-video models](/wiki/Text-to-video_model \"Text-to-video model\")\\n    * [Sora](/wiki/Sora_\\\\(text-to-video_model\\\\) \"Sora \\\\(text-to-video model\\\\)\")\\n    * [VideoPoet](/wiki/VideoPoet \"VideoPoet\")\\n  * [Whisper](/wiki/Whisper_\\\\(speech_recognition_system\\\\) \"Whisper \\\\(speech recognition system\\\\)\")\\n\\n  \\n---|---  \\nText|\\n\\n  * [Word2vec](/wiki/Word2vec \"Word2vec\")\\n  * [Seq2seq](/wiki/Seq2seq \"Seq2seq\")\\n  * [GloVe](/wiki/GloVe \"GloVe\")\\n  * [BERT](/wiki/BERT_\\\\(language_model\\\\) \"BERT \\\\(language model\\\\)\")\\n  * [T5](/wiki/T5_\\\\(language_model\\\\) \"T5 \\\\(language model\\\\)\")\\n  * [Llama](/wiki/Llama_\\\\(language_model\\\\) \"Llama \\\\(language model\\\\)\")\\n  * [Chinchilla AI](/wiki/Chinchilla_AI \"Chinchilla AI\")\\n  * [PaLM](/wiki/PaLM \"PaLM\")\\n  * [GPT](/wiki/Generative_Pre-trained_Transformer \"Generative Pre-trained Transformer\")\\n    * [1](/wiki/GPT-1 \"GPT-1\")\\n    * [J](/wiki/GPT-J \"GPT-J\")\\n    * [2](/wiki/GPT-2 \"GPT-2\")\\n    * [3](/wiki/GPT-3 \"GPT-3\")\\n    * [ChatGPT](/wiki/ChatGPT \"ChatGPT\")\\n    * [4](/wiki/GPT-4 \"GPT-4\")\\n  * [Claude](/wiki/Claude_\\\\(language_model\\\\) \"Claude \\\\(language model\\\\)\")\\n  * [Gemini](/wiki/Gemini_\\\\(language_model\\\\) \"Gemini \\\\(language model\\\\)\")\\n  * [LaMDA](/wiki/LaMDA \"LaMDA\")\\n    * [Bard](/wiki/Bard_\\\\(chatbot\\\\) \"Bard \\\\(chatbot\\\\)\")\\n  * [BLOOM](/wiki/BLOOM_\\\\(language_model\\\\) \"BLOOM \\\\(language model\\\\)\")\\n  * [Project Debater](/wiki/Project_Debater \"Project Debater\")\\n  * [IBM Watson](/wiki/IBM_Watson \"IBM Watson\")\\n  * [IBM Watsonx](/wiki/IBM_Watsonx \"IBM Watsonx\")\\n  * [Granite](/wiki/IBM_Granite \"IBM Granite\")\\n  * [PanGu-Σ](/wiki/Huawei_PanGu \"Huawei PanGu\")\\n\\n  \\nDecisional|\\n\\n  * [AlphaGo](/wiki/AlphaGo \"AlphaGo\")\\n  * [AlphaZero](/wiki/AlphaZero \"AlphaZero\")\\n  * [OpenAI Five](/wiki/OpenAI_Five \"OpenAI Five\")\\n  * [Self-driving car](/wiki/Self-driving_car \"Self-driving car\")\\n  * [MuZero](/wiki/MuZero \"MuZero\")\\n  * [Action selection](/wiki/Action_selection \"Action selection\")\\n    * [Auto-GPT](/wiki/Auto-GPT \"Auto-GPT\")\\n  * [Robot control](/wiki/Robot_control \"Robot control\")\\n\\n  \\n  \\nPeople|\\n\\n  * [Frank Rosenblatt](/wiki/Frank_Rosenblatt \"Frank Rosenblatt\")\\n  * [Bernard Widrow](/wiki/Bernard_Widrow \"Bernard Widrow\")\\n  * [Paul Werbos](/wiki/Paul_Werbos \"Paul Werbos\")\\n  * [Yoshua Bengio](/wiki/Yoshua_Bengio \"Yoshua Bengio\")\\n  * [Alex Graves](/wiki/Alex_Graves_\\\\(computer_scientist\\\\) \"Alex Graves \\\\(computer scientist\\\\)\")\\n  * [Ian Goodfellow](/wiki/Ian_Goodfellow \"Ian Goodfellow\")\\n  * [Stephen Grossberg](/wiki/Stephen_Grossberg \"Stephen Grossberg\")\\n  * [Demis Hassabis](/wiki/Demis_Hassabis \"Demis Hassabis\")\\n  * [Geoffrey Hinton](/wiki/Geoffrey_Hinton \"Geoffrey Hinton\")\\n  * [Yann LeCun](/wiki/Yann_LeCun \"Yann LeCun\")\\n  * [Fei-Fei Li](/wiki/Fei-Fei_Li \"Fei-Fei Li\")\\n  * [Andrew Ng](/wiki/Andrew_Ng \"Andrew Ng\")\\n  * [Jürgen Schmidhuber](/wiki/J%C3%BCrgen_Schmidhuber \"Jürgen Schmidhuber\")\\n  * [David Silver](/wiki/David_Silver_\\\\(computer_scientist\\\\) \"David Silver \\\\(computer scientist\\\\)\")\\n  * [Ilya Sutskever](/wiki/Ilya_Sutskever \"Ilya Sutskever\")\\n\\n  \\nOrganizations|\\n\\n  * [Anthropic](/wiki/Anthropic \"Anthropic\")\\n  * [EleutherAI](/wiki/EleutherAI \"EleutherAI\")\\n  * [Google DeepMind](/wiki/Google_DeepMind \"Google DeepMind\")\\n  * [Hugging Face](/wiki/Hugging_Face \"Hugging Face\")\\n  * [OpenAI](/wiki/OpenAI \"OpenAI\")\\n  * [Meta AI](/wiki/Meta_AI \"Meta AI\")\\n  * [Mila](/wiki/Mila_\\\\(research_institute\\\\) \"Mila \\\\(research institute\\\\)\")\\n  * [MIT CSAIL](/wiki/MIT_Computer_Science_and_Artificial_Intelligence_Laboratory \"MIT Computer Science and Artificial Intelligence Laboratory\")\\n  * [Huawei](/wiki/Huawei \"Huawei\")\\n\\n  \\nArchitectures|\\n\\n  * [Neural Turing machine](/wiki/Neural_Turing_machine \"Neural Turing machine\")\\n  * [Differentiable neural computer](/wiki/Differentiable_neural_computer \"Differentiable neural computer\")\\n  * [Transformer](/wiki/Transformer_\\\\(machine_learning_model\\\\) \"Transformer \\\\(machine learning model\\\\)\")\\n    * [Vision transformer (ViT)](/wiki/Vision_transformer \"Vision transformer\")\\n  * [Recurrent neural network (RNN)](/wiki/Recurrent_neural_network \"Recurrent neural network\")\\n  * [Long short-term memory (LSTM)](/wiki/Long_short-term_memory \"Long short-term memory\")\\n  * [Gated recurrent unit (GRU)](/wiki/Gated_recurrent_unit \"Gated recurrent unit\")\\n  * [Echo state network](/wiki/Echo_state_network \"Echo state network\")\\n  * [Multilayer perceptron (MLP)](/wiki/Multilayer_perceptron \"Multilayer perceptron\")\\n  * [Convolutional neural network (CNN)](/wiki/Convolutional_neural_network \"Convolutional neural network\")\\n  * [Residual neural network (RNN)](/wiki/Residual_neural_network \"Residual neural network\")\\n  * [Highway network](/wiki/Highway_network \"Highway network\")\\n  * [Mamba](/wiki/Mamba_\\\\(deep_learning\\\\) \"Mamba \\\\(deep learning\\\\)\")\\n  * [Autoencoder](/wiki/Autoencoder \"Autoencoder\")\\n  * [Variational autoencoder (VAE)](/wiki/Variational_autoencoder \"Variational autoencoder\")\\n  * [Generative adversarial network (GAN)](/wiki/Generative_adversarial_network \"Generative adversarial network\")\\n  * [Graph neural network (GNN)](/wiki/Graph_neural_network \"Graph neural network\")\\n\\n  \\n  \\n  * [![](//upload.wikimedia.org/wikipedia/en/thumb/e/e2/Symbol_portal_class.svg/16px-Symbol_portal_class.svg.png)](/wiki/File:Symbol_portal_class.svg \"Portal\") Portals \\n    * [Computer programming](/wiki/Portal:Computer_programming \"Portal:Computer programming\")\\n    * [Technology](/wiki/Portal:Technology \"Portal:Technology\")\\n  * ![](//upload.wikimedia.org/wikipedia/en/thumb/9/96/Symbol_category_class.svg/16px-Symbol_category_class.svg.png) Categories \\n    * [Artificial neural networks](/wiki/Category:Artificial_neural_networks \"Category:Artificial neural networks\")\\n    * [Machine learning](/wiki/Category:Machine_learning \"Category:Machine learning\")\\n\\n  \\n  \\nshow\\n\\n  * [v](/wiki/Template:Computer_science \"Template:Computer science\")\\n  * [t](/wiki/Template_talk:Computer_science \"Template talk:Computer science\")\\n  * [e](/wiki/Special:EditPage/Template:Computer_science \"Special:EditPage/Template:Computer science\")\\n\\n[Computer science](/wiki/Computer_science \"Computer science\")  \\n---  \\nNote: This template roughly follows the 2012 [ACM Computing Classification\\nSystem](/wiki/ACM_Computing_Classification_System \"ACM Computing\\nClassification System\").  \\n[Hardware](/wiki/Computer_hardware \"Computer hardware\")|\\n\\n  * [Printed circuit board](/wiki/Printed_circuit_board \"Printed circuit board\")\\n  * [Peripheral](/wiki/Peripheral \"Peripheral\")\\n  * [Integrated circuit](/wiki/Integrated_circuit \"Integrated circuit\")\\n  * [Very Large Scale Integration](/wiki/Very_Large_Scale_Integration \"Very Large Scale Integration\")\\n  * [Systems on Chip (SoCs)](/wiki/System_on_a_chip \"System on a chip\")\\n  * [Energy consumption (Green computing)](/wiki/Green_computing \"Green computing\")\\n  * [Electronic design automation](/wiki/Electronic_design_automation \"Electronic design automation\")\\n  * [Hardware acceleration](/wiki/Hardware_acceleration \"Hardware acceleration\")\\n  * [Processor](/wiki/Processor_\\\\(computing\\\\) \"Processor \\\\(computing\\\\)\")\\n  * [Size](/wiki/List_of_computer_size_categories \"List of computer size categories\") / [Form](/wiki/Form_factor_\\\\(design\\\\) \"Form factor \\\\(design\\\\)\")\\n\\n  \\nComputer systems organization|\\n\\n  * [Computer architecture](/wiki/Computer_architecture \"Computer architecture\")\\n  * [Computational complexity](/wiki/Computational_complexity \"Computational complexity\")\\n  * [Dependability](/wiki/Dependability \"Dependability\")\\n  * [Embedded system](/wiki/Embedded_system \"Embedded system\")\\n  * [Real-time computing](/wiki/Real-time_computing \"Real-time computing\")\\n\\n  \\n[Networks](/wiki/Computer_network \"Computer network\")|\\n\\n  * [Network architecture](/wiki/Network_architecture \"Network architecture\")\\n  * [Network protocol](/wiki/Network_protocol \"Network protocol\")\\n  * [Network components](/wiki/Networking_hardware \"Networking hardware\")\\n  * [Network scheduler](/wiki/Network_scheduler \"Network scheduler\")\\n  * [Network performance evaluation](/wiki/Network_performance \"Network performance\")\\n  * [Network service](/wiki/Network_service \"Network service\")\\n\\n  \\nSoftware organization|\\n\\n  * [Interpreter](/wiki/Interpreter_\\\\(computing\\\\) \"Interpreter \\\\(computing\\\\)\")\\n  * [Middleware](/wiki/Middleware \"Middleware\")\\n  * [Virtual machine](/wiki/Virtual_machine \"Virtual machine\")\\n  * [Operating system](/wiki/Operating_system \"Operating system\")\\n  * [Software quality](/wiki/Software_quality \"Software quality\")\\n\\n  \\n[Software notations](/wiki/Programming_language_theory \"Programming language\\ntheory\") and [tools](/wiki/Programming_tool \"Programming tool\")|\\n\\n  * [Programming paradigm](/wiki/Programming_paradigm \"Programming paradigm\")\\n  * [Programming language](/wiki/Programming_language \"Programming language\")\\n  * [Compiler](/wiki/Compiler_construction \"Compiler construction\")\\n  * [Domain-specific language](/wiki/Domain-specific_language \"Domain-specific language\")\\n  * [Modeling language](/wiki/Modeling_language \"Modeling language\")\\n  * [Software framework](/wiki/Software_framework \"Software framework\")\\n  * [Integrated development environment](/wiki/Integrated_development_environment \"Integrated 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\"Software engineering\")\\n  * [Software maintenance](/wiki/Software_maintenance \"Software maintenance\")\\n  * [Programming team](/wiki/Programming_team \"Programming team\")\\n  * [Open-source model](/wiki/Open-source_software \"Open-source software\")\\n\\n  \\n[Theory of computation](/wiki/Theory_of_computation \"Theory of computation\")|\\n\\n  * [Model of computation](/wiki/Model_of_computation \"Model of computation\")\\n    * [Stochastic](/wiki/Stochastic_computing \"Stochastic computing\")\\n  * [Formal language](/wiki/Formal_language \"Formal language\")\\n  * [Automata theory](/wiki/Automata_theory \"Automata theory\")\\n  * [Computability theory](/wiki/Computability_theory \"Computability theory\")\\n  * [Computational complexity theory](/wiki/Computational_complexity_theory \"Computational complexity theory\")\\n  * [Logic](/wiki/Logic_in_computer_science \"Logic in computer science\")\\n  * [Semantics](/wiki/Semantics_\\\\(computer_science\\\\) \"Semantics \\\\(computer science\\\\)\")\\n\\n  \\n[Algorithms](/wiki/Algorithm \"Algorithm\")|\\n\\n  * [Algorithm design](/wiki/Algorithm_design \"Algorithm design\")\\n  * [Analysis of algorithms](/wiki/Analysis_of_algorithms \"Analysis of algorithms\")\\n  * [Algorithmic efficiency](/wiki/Algorithmic_efficiency \"Algorithmic efficiency\")\\n  * [Randomized algorithm](/wiki/Randomized_algorithm \"Randomized algorithm\")\\n  * [Computational geometry](/wiki/Computational_geometry \"Computational geometry\")\\n\\n  \\nMathematics of [computing](/wiki/Computing \"Computing\")|\\n\\n  * [Discrete mathematics](/wiki/Discrete_mathematics \"Discrete mathematics\")\\n  * [Probability](/wiki/Probability \"Probability\")\\n  * [Statistics](/wiki/Statistics \"Statistics\")\\n  * [Mathematical software](/wiki/Mathematical_software \"Mathematical software\")\\n  * [Information theory](/wiki/Information_theory \"Information theory\")\\n  * [Mathematical analysis](/wiki/Mathematical_analysis \"Mathematical analysis\")\\n  * [Numerical analysis](/wiki/Numerical_analysis \"Numerical analysis\")\\n  * [Theoretical computer science](/wiki/Theoretical_computer_science \"Theoretical computer science\")\\n\\n  \\n[Information systems](/wiki/Information_system \"Information system\")|\\n\\n  * [Database management system](/wiki/Database \"Database\")\\n  * [Information storage systems](/wiki/Computer_data_storage \"Computer data storage\")\\n  * [Enterprise information system](/wiki/Enterprise_information_system \"Enterprise information system\")\\n  * [Social information systems](/wiki/Social_software \"Social software\")\\n  * [Geographic information system](/wiki/Geographic_information_system \"Geographic information system\")\\n  * [Decision support system](/wiki/Decision_support_system \"Decision support system\")\\n  * [Process control system](/wiki/Process_control \"Process control\")\\n  * [Multimedia information system](/wiki/Multimedia_database \"Multimedia database\")\\n  * [Data mining](/wiki/Data_mining \"Data mining\")\\n  * [Digital library](/wiki/Digital_library \"Digital library\")\\n  * [Computing platform](/wiki/Computing_platform \"Computing platform\")\\n  * [Digital marketing](/wiki/Digital_marketing \"Digital marketing\")\\n  * [World Wide Web](/wiki/World_Wide_Web \"World Wide Web\")\\n  * [Information retrieval](/wiki/Information_retrieval \"Information retrieval\")\\n\\n  \\n[Security](/wiki/Computer_security \"Computer security\")|\\n\\n  * [Cryptography](/wiki/Cryptography \"Cryptography\")\\n  * [Formal methods](/wiki/Formal_methods \"Formal methods\")\\n  * [Security hacker](/wiki/Security_hacker \"Security hacker\")\\n  * [Security services](/wiki/Security_service_\\\\(telecommunication\\\\) \"Security service \\\\(telecommunication\\\\)\")\\n  * [Intrusion detection system](/wiki/Intrusion_detection_system \"Intrusion detection system\")\\n  * [Hardware security](/wiki/Hardware_security \"Hardware security\")\\n  * [Network security](/wiki/Network_security \"Network security\")\\n  * [Information security](/wiki/Information_security \"Information security\")\\n  * [Application security](/wiki/Application_security \"Application security\")\\n\\n  \\n[Human–computer interaction](/wiki/Human%E2%80%93computer_interaction\\n\"Human–computer interaction\")|\\n\\n  * [Interaction design](/wiki/Interaction_design \"Interaction design\")\\n  * [Social computing](/wiki/Social_computing \"Social computing\")\\n  * [Ubiquitous computing](/wiki/Ubiquitous_computing \"Ubiquitous computing\")\\n  * [Visualization](/wiki/Visualization_\\\\(graphics\\\\) \"Visualization \\\\(graphics\\\\)\")\\n  * [Accessibility](/wiki/Computer_accessibility \"Computer accessibility\")\\n\\n  \\n[Concurrency](/wiki/Concurrency_\\\\(computer_science\\\\) \"Concurrency \\\\(computer\\nscience\\\\)\")|\\n\\n  * [Concurrent computing](/wiki/Concurrent_computing \"Concurrent computing\")\\n  * [Parallel computing](/wiki/Parallel_computing \"Parallel computing\")\\n  * [Distributed computing](/wiki/Distributed_computing \"Distributed computing\")\\n  * [Multithreading](/wiki/Multithreading_\\\\(computer_architecture\\\\) \"Multithreading \\\\(computer architecture\\\\)\")\\n  * [Multiprocessing](/wiki/Multiprocessing \"Multiprocessing\")\\n\\n  \\nArtificial intelligence|\\n\\n  * [Natural language processing](/wiki/Natural_language_processing \"Natural language processing\")\\n  * [Knowledge representation and reasoning](/wiki/Knowledge_representation_and_reasoning \"Knowledge representation and reasoning\")\\n  * [Computer vision](/wiki/Computer_vision \"Computer vision\")\\n  * [Automated planning and scheduling](/wiki/Automated_planning_and_scheduling \"Automated planning and scheduling\")\\n  * [Search methodology](/wiki/Mathematical_optimization \"Mathematical optimization\")\\n  * [Control method](/wiki/Control_theory \"Control theory\")\\n  * [Philosophy of artificial intelligence](/wiki/Philosophy_of_artificial_intelligence \"Philosophy of artificial intelligence\")\\n  * [Distributed artificial intelligence](/wiki/Distributed_artificial_intelligence \"Distributed artificial intelligence\")\\n\\n  \\n[Machine learning](/wiki/Machine_learning \"Machine learning\")|\\n\\n  * [Supervised learning](/wiki/Supervised_learning \"Supervised learning\")\\n  * [Unsupervised learning](/wiki/Unsupervised_learning \"Unsupervised learning\")\\n  * [Reinforcement learning](/wiki/Reinforcement_learning \"Reinforcement learning\")\\n  * [Multi-task learning](/wiki/Multi-task_learning \"Multi-task learning\")\\n  * [Cross-validation](/wiki/Cross-validation_\\\\(statistics\\\\) \"Cross-validation \\\\(statistics\\\\)\")\\n\\n  \\n[Graphics](/wiki/Computer_graphics \"Computer graphics\")|\\n\\n  * [Animation](/wiki/Computer_animation \"Computer animation\")\\n  * [Rendering](/wiki/Rendering_\\\\(computer_graphics\\\\) \"Rendering \\\\(computer graphics\\\\)\")\\n  * [Photograph manipulation](/wiki/Photograph_manipulation \"Photograph manipulation\")\\n  * [Graphics processing unit](/wiki/Graphics_processing_unit \"Graphics processing unit\")\\n  * [Mixed reality](/wiki/Mixed_reality \"Mixed reality\")\\n  * [Virtual reality](/wiki/Virtual_reality \"Virtual reality\")\\n  * [Image compression](/wiki/Image_compression \"Image compression\")\\n  * [Solid modeling](/wiki/Solid_modeling \"Solid modeling\")\\n\\n  \\nApplied computing|\\n\\n  * [Quantum Computing](/wiki/Quantum_Computing \"Quantum Computing\")\\n  * [E-commerce](/wiki/E-commerce \"E-commerce\")\\n  * [Enterprise software](/wiki/Enterprise_software \"Enterprise software\")\\n  * [Computational mathematics](/wiki/Computational_mathematics \"Computational mathematics\")\\n  * [Computational physics](/wiki/Computational_physics \"Computational physics\")\\n  * [Computational chemistry](/wiki/Computational_chemistry \"Computational chemistry\")\\n  * [Computational biology](/wiki/Computational_biology \"Computational biology\")\\n  * [Computational social science](/wiki/Computational_social_science \"Computational social science\")\\n  * [Computational engineering](/wiki/Computational_engineering \"Computational engineering\")\\n  * [Differentiable computing](/wiki/Template:Differentiable_computing \"Template:Differentiable computing\")\\n  * [Computational healthcare](/wiki/Health_informatics \"Health informatics\")\\n  * [Digital art](/wiki/Digital_art \"Digital art\")\\n  * [Electronic publishing](/wiki/Electronic_publishing \"Electronic publishing\")\\n  * [Cyberwarfare](/wiki/Cyberwarfare \"Cyberwarfare\")\\n  * [Electronic voting](/wiki/Electronic_voting \"Electronic voting\")\\n  * [Video games](/wiki/Video_game \"Video game\")\\n  * [Word processing](/wiki/Word_processor \"Word processor\")\\n  * [Operations research](/wiki/Operations_research \"Operations research\")\\n  * [Educational technology](/wiki/Educational_technology \"Educational technology\")\\n  * [Document management](/wiki/Document_management_system \"Document management system\")\\n\\n  \\n  \\n  * ![](//upload.wikimedia.org/wikipedia/en/thumb/9/96/Symbol_category_class.svg/16px-Symbol_category_class.svg.png) [Category](/wiki/Category:Computer_science \"Category:Computer science\")\\n  * ![](//upload.wikimedia.org/wikipedia/commons/thumb/4/41/Global_thinking.svg/10px-Global_thinking.svg.png) [Outline](/wiki/Outline_of_computer_science \"Outline of computer science\")\\n  * ![](//upload.wikimedia.org/wikipedia/en/thumb/e/e0/Symbol_question.svg/16px-Symbol_question.svg.png) [Glossaries](/wiki/Template:Glossaries_of_computers \"Template:Glossaries of computers\")\\n\\n  \\n  \\nshow\\n\\n  * [v](/wiki/Template:Emerging_technologies \"Template:Emerging technologies\")\\n  * [t](/wiki/Template_talk:Emerging_technologies \"Template talk:Emerging technologies\")\\n  * [e](/wiki/Special:EditPage/Template:Emerging_technologies \"Special:EditPage/Template:Emerging technologies\")\\n\\n[Emerging technologies](/wiki/Emerging_technologies \"Emerging technologies\")  \\n---  \\nFields| | [Information and  \\ncommunications](/wiki/Information_and_communications_technology \"Information\\nand communications technology\")|\\n\\n  * [Ambient intelligence](/wiki/Ambient_intelligence \"Ambient intelligence\")\\n    * [Internet of things](/wiki/Internet_of_things \"Internet of things\")\\n  * Artificial intelligence\\n    * [Applications of artificial intelligence](/wiki/Applications_of_artificial_intelligence \"Applications of artificial intelligence\")\\n    * [Machine translation](/wiki/Machine_translation \"Machine translation\")\\n    * [Machine vision](/wiki/Machine_vision \"Machine vision\")\\n    * [Mobile translation](/wiki/Mobile_translation \"Mobile translation\")\\n    * [Progress in artificial intelligence](/wiki/Progress_in_artificial_intelligence \"Progress in artificial intelligence\")\\n    * [Semantic Web](/wiki/Semantic_Web \"Semantic Web\")\\n    * [Speech recognition](/wiki/Speech_recognition \"Speech recognition\")\\n  * [Atomtronics](/wiki/Atomtronics \"Atomtronics\")\\n  * [Carbon nanotube field-effect transistor](/wiki/Carbon_nanotube_field-effect_transistor \"Carbon nanotube field-effect transistor\")\\n  * [Cybermethodology](/wiki/Cybermethodology \"Cybermethodology\")\\n  * [Extended reality](/wiki/Extended_reality \"Extended reality\")\\n  * [Fourth-generation optical discs](/wiki/Optical_disc#Fourth-generation \"Optical disc\")\\n    * [3D optical data storage](/wiki/3D_optical_data_storage \"3D optical data storage\")\\n    * [Holographic data storage](/wiki/Holographic_data_storage \"Holographic data storage\")\\n  * [GPGPU](/wiki/General-purpose_computing_on_graphics_processing_units \"General-purpose computing on graphics processing units\")\\n  * Memory \\n    * [CBRAM](/wiki/Programmable_metallization_cell \"Programmable metallization cell\")\\n    * [ECRAM](/wiki/Electrochemical_RAM \"Electrochemical RAM\")\\n    * [FRAM](/wiki/Ferroelectric_RAM \"Ferroelectric RAM\")\\n    * [Millipede](/wiki/Millipede_memory \"Millipede memory\")\\n    * [MRAM](/wiki/Magnetoresistive_RAM \"Magnetoresistive RAM\")\\n    * [NRAM](/wiki/Nano-RAM \"Nano-RAM\")\\n    * [PRAM](/wiki/Phase-change_memory \"Phase-change memory\")\\n    * [Racetrack memory](/wiki/Racetrack_memory \"Racetrack memory\")\\n    * [RRAM](/wiki/Resistive_random-access_memory \"Resistive random-access memory\")\\n    * [SONOS](/wiki/SONOS \"SONOS\")\\n    * [UltraRAM](/wiki/UltraRAM \"UltraRAM\")\\n  * [Optical computing](/wiki/Optical_computing \"Optical computing\")\\n  * [RFID](/wiki/Radio-frequency_identification \"Radio-frequency identification\")\\n    * [Chipless RFID](/wiki/Chipless_RFID \"Chipless RFID\")\\n  * [Software-defined radio](/wiki/Software-defined_radio \"Software-defined radio\")\\n  * [Three-dimensional integrated circuit](/wiki/Three-dimensional_integrated_circuit \"Three-dimensional integrated circuit\")\\n\\n  \\n---|---  \\n  \\nTopics|\\n\\n  * [Automation](/wiki/Automation \"Automation\")\\n  * [Collingridge dilemma](/wiki/Collingridge_dilemma \"Collingridge dilemma\")\\n  * [Differential technological development](/wiki/Differential_technological_development \"Differential technological development\")\\n  * [Disruptive innovation](/wiki/Disruptive_innovation \"Disruptive innovation\")\\n  * [Ephemeralization](/wiki/Ephemeralization \"Ephemeralization\")\\n  * [Ethics](/wiki/Ethics_of_technology \"Ethics of technology\")\\n    * [Bioethics](/wiki/Bioethics \"Bioethics\")\\n    * [Cyberethics](/wiki/Cyberethics \"Cyberethics\")\\n    * [Neuroethics](/wiki/Neuroethics \"Neuroethics\")\\n    * [Robot ethics](/wiki/Robot_ethics \"Robot ethics\")\\n  * [Exploratory engineering](/wiki/Exploratory_engineering \"Exploratory engineering\")\\n  * [Proactionary principle](/wiki/Proactionary_principle \"Proactionary principle\")\\n  * [Technological change](/wiki/Technological_change \"Technological change\")\\n    * [Technological unemployment](/wiki/Technological_unemployment \"Technological unemployment\")\\n  * [Technological convergence](/wiki/Technological_convergence \"Technological convergence\")\\n  * [Technological evolution](/wiki/Technological_evolution \"Technological evolution\")\\n  * [Technological paradigm](/wiki/Technological_paradigm \"Technological paradigm\")\\n  * [Technology forecasting](/wiki/Technology_forecasting \"Technology forecasting\")\\n    * [Accelerating change](/wiki/Accelerating_change \"Accelerating change\")\\n    * [Future-oriented technology analysis](/wiki/Future-oriented_technology_analysis \"Future-oriented technology analysis\")\\n    * [Horizon scanning](/wiki/Horizon_scanning \"Horizon scanning\")\\n    * [Moore\\'s law](/wiki/Moore%27s_law \"Moore\\'s law\")\\n    * [Technological singularity](/wiki/Technological_singularity \"Technological singularity\")\\n    * [Technology scouting](/wiki/Technology_scouting \"Technology scouting\")\\n  * [Technology in science fiction](/wiki/Technology_in_science_fiction \"Technology in science fiction\")\\n  * [Technology readiness level](/wiki/Technology_readiness_level \"Technology readiness level\")\\n  * [Technology roadmap](/wiki/Technology_roadmap \"Technology roadmap\")\\n  * [Transhumanism](/wiki/Transhumanism \"Transhumanism\")\\n\\n  \\n  \\n  * ![](//upload.wikimedia.org/wikipedia/en/thumb/d/db/Symbol_list_class.svg/16px-Symbol_list_class.svg.png) **[List](/wiki/List_of_emerging_technologies \"List of emerging technologies\")**\\n\\n  \\n  \\nshow\\n\\n  * [v](/wiki/Template:Robotics \"Template:Robotics\")\\n  * [t](/wiki/Template_talk:Robotics \"Template talk:Robotics\")\\n  * [e](/wiki/Special:EditPage/Template:Robotics \"Special:EditPage/Template:Robotics\")\\n\\n[Robotics](/wiki/Robotics \"Robotics\")  \\n---  \\nMain articles|\\n\\n  * [Outline](/wiki/Outline_of_robotics \"Outline of robotics\")\\n  * [Glossary](/wiki/Glossary_of_robotics \"Glossary of robotics\")\\n  * [Index](/wiki/Index_of_robotics_articles \"Index of robotics articles\")\\n  * [History](/wiki/History_of_robots \"History of robots\")\\n  * [Geography](/wiki/Geography_of_robotics \"Geography of robotics\")\\n  * [Hall of Fame](/wiki/Robot_Hall_of_Fame \"Robot Hall of Fame\")\\n  * [Ethics](/wiki/Robot_ethics \"Robot ethics\")\\n  * [Laws](/wiki/Laws_of_robotics \"Laws of robotics\")\\n  * [Competitions](/wiki/Robot_competition \"Robot competition\")\\n  * [AI competitions](/wiki/Competitions_and_prizes_in_artificial_intelligence \"Competitions and prizes in artificial intelligence\")\\n\\n|\\n[![](//upload.wikimedia.org/wikipedia/commons/thumb/c/c5/Shadow_Hand_Bulb_large.jpg/100px-\\nShadow_Hand_Bulb_large.jpg)](/wiki/File:Shadow_Hand_Bulb_large.jpg)  \\n[Types](/wiki/Robot \"Robot\")|\\n\\n  * [Aerobot](/wiki/Aerobot \"Aerobot\")\\n  * [Anthropomorphic](/wiki/Anthropomorphic \"Anthropomorphic\")\\n    * [Humanoid](/wiki/Humanoid_robot \"Humanoid robot\")\\n    * [Android](/wiki/Android_\\\\(robot\\\\) \"Android \\\\(robot\\\\)\")\\n    * [Cyborg](/wiki/Cyborg \"Cyborg\")\\n    * [Gynoid](/wiki/Gynoid \"Gynoid\")\\n  * [Claytronics](/wiki/Claytronics \"Claytronics\")\\n  * [Companion](/wiki/Companion_robot \"Companion robot\")\\n  * [Automaton](/wiki/Automaton \"Automaton\")\\n    * [Animatronic](/wiki/Animatronics \"Animatronics\")\\n      * [Audio-Animatronics](/wiki/Audio-Animatronics \"Audio-Animatronics\")\\n  * [Industrial](/wiki/Industrial_robot \"Industrial robot\")\\n  * [Articulated](/wiki/Articulated_robot \"Articulated robot\")\\n    * [arm](/wiki/Robotic_arm \"Robotic arm\")\\n  * [Domestic](/wiki/Domestic_robot \"Domestic robot\")\\n  * [Educational](/wiki/Educational_robotics \"Educational robotics\")\\n  * [Entertainment](/wiki/Entertainment_robot \"Entertainment robot\")\\n  * [Juggling](/wiki/Juggling_robot \"Juggling robot\")\\n  * [Military](/wiki/Military_robot \"Military robot\")\\n  * [Medical](/wiki/Medical_robot \"Medical robot\")\\n  * [Service](/wiki/Service_robot \"Service robot\")\\n  * [Disability](/wiki/Disability_robot \"Disability robot\")\\n  * [Agricultural](/wiki/Agricultural_robot \"Agricultural robot\")\\n  * [Food service](/wiki/Automated_restaurant \"Automated restaurant\")\\n  * [Retail](/wiki/Automated_retail \"Automated retail\")\\n  * [BEAM robotics](/wiki/BEAM_robotics \"BEAM robotics\")\\n  * [Soft robotics](/wiki/Soft_robotics \"Soft robotics\")\\n\\n  \\nClassifications|\\n\\n  * [Biorobotics](/wiki/Biorobotics \"Biorobotics\")\\n  * [Cloud robotics](/wiki/Cloud_robotics \"Cloud robotics\")\\n  * [Continuum robot](/wiki/Continuum_robot \"Continuum robot\")\\n  * [Unmanned vehicle](/wiki/Unmanned_vehicle \"Unmanned vehicle\")\\n    * [aerial](/wiki/Unmanned_aerial_vehicle \"Unmanned aerial vehicle\")\\n    * [ground](/wiki/Unmanned_ground_vehicle \"Unmanned ground vehicle\")\\n  * [Mobile robot](/wiki/Mobile_robot \"Mobile robot\")\\n  * [Microbotics](/wiki/Microbotics \"Microbotics\")\\n  * [Nanorobotics](/wiki/Nanorobotics \"Nanorobotics\")\\n  * [Necrobotics](/wiki/Necrobotics \"Necrobotics\")\\n  * [Robotic spacecraft](/wiki/Robotic_spacecraft \"Robotic spacecraft\")\\n    * [Space probe](/wiki/Space_probe \"Space probe\")\\n  * [Swarm](/wiki/Swarm_robotics \"Swarm robotics\")\\n  * [Telerobotics](/wiki/Telerobotics \"Telerobotics\")\\n  * [Underwater](/wiki/Autonomous_underwater_vehicle \"Autonomous underwater vehicle\")\\n    * [remotely-operated](/wiki/Remotely_operated_underwater_vehicle \"Remotely operated underwater vehicle\")\\n    * [Robotic fish](/wiki/Robotic_fish \"Robotic fish\")\\n\\n  \\n[Locomotion](/wiki/Robot_locomotion \"Robot locomotion\")|\\n\\n  * [Tracks](/wiki/Continuous_track \"Continuous track\")\\n  * [Walking](/wiki/Legged_robot \"Legged robot\")\\n    * [Hexapod](/wiki/Hexapod_\\\\(robotics\\\\) \"Hexapod \\\\(robotics\\\\)\")\\n  * [Climbing](/wiki/Climber_\\\\(BEAM\\\\) \"Climber \\\\(BEAM\\\\)\")\\n  * [Electric unicycle](/wiki/Electric_unicycle \"Electric unicycle\")\\n  * [Robotic fins](/wiki/Robotic_fin \"Robotic fin\")\\n\\n  \\n[Navigation](/wiki/Robotic_navigation \"Robotic navigation\") and\\n[mapping](/wiki/Robotic_mapping \"Robotic mapping\")|\\n\\n  * [Motion planning](/wiki/Motion_planning \"Motion planning\")\\n  * [Simultaneous localization and mapping](/wiki/Simultaneous_localization_and_mapping \"Simultaneous localization and mapping\")\\n  * [Visual odometry](/wiki/Visual_odometry \"Visual odometry\")\\n  * [Vision-guided robot systems](/wiki/Vision-guided_robot_systems \"Vision-guided robot systems\")\\n\\n  \\nResearch|\\n\\n  * [Evolutionary](/wiki/Evolutionary_robotics \"Evolutionary robotics\")\\n  * [Kits](/wiki/Robot_kit \"Robot kit\")\\n  * [Simulator](/wiki/Robotics_simulator \"Robotics simulator\")\\n  * [Suite](/wiki/Robotics_suite \"Robotics suite\")\\n  * [Open-source](/wiki/Open-source_robotics \"Open-source robotics\")\\n  * [Software](/wiki/Robot_software \"Robot software\")\\n  * [Adaptable](/wiki/Adaptable_robotics \"Adaptable robotics\")\\n  * [Developmental](/wiki/Developmental_robotics \"Developmental robotics\")\\n  * [Human–robot interaction](/wiki/Human%E2%80%93robot_interaction \"Human–robot interaction\")\\n  * [Paradigms](/wiki/Robotic_paradigm \"Robotic paradigm\")\\n  * [Perceptual](/wiki/Perceptual_robotics \"Perceptual robotics\")\\n  * [Situated](/wiki/Situated_robotics \"Situated robotics\")\\n  * [Ubiquitous](/wiki/Ubiquitous_robot \"Ubiquitous robot\")\\n\\n  \\nCompanies|\\n\\n  * [Amazon Robotics](/wiki/Amazon_Robotics \"Amazon Robotics\")\\n  * [Anybots](/wiki/Anybots \"Anybots\")\\n  * [Barrett Technology](/wiki/Barrett_Technology \"Barrett Technology\")\\n  * [Boston Dynamics](/wiki/Boston_Dynamics \"Boston Dynamics\")\\n  * [Energid Technologies](/wiki/Energid_Technologies \"Energid Technologies\")\\n  * [FarmWise](/wiki/FarmWise \"FarmWise\")\\n  * [FANUC](/wiki/FANUC \"FANUC\")\\n  * [Figure AI](/wiki/Figure_AI \"Figure AI\")\\n  * [Foster-Miller](/wiki/Foster-Miller \"Foster-Miller\")\\n  * [Harvest Automation](/wiki/Harvest_Automation \"Harvest Automation\")\\n  * [Honeybee Robotics](/wiki/Honeybee_Robotics \"Honeybee Robotics\")\\n  * [Intuitive Surgical](/wiki/Intuitive_Surgical \"Intuitive Surgical\")\\n  * [IRobot](/wiki/IRobot \"IRobot\")\\n  * [KUKA](/wiki/KUKA \"KUKA\")\\n  * [Starship Technologies](/wiki/Starship_Technologies \"Starship Technologies\")\\n  * [Symbotic](/wiki/Symbotic \"Symbotic\")\\n  * [Universal Robotics](/wiki/Universal_Robotics \"Universal Robotics\")\\n  * [Wolf Robotics](/wiki/Wolf_Robotics \"Wolf Robotics\")\\n  * [Yaskawa](/wiki/Yaskawa_Electric_Corporation \"Yaskawa Electric Corporation\")\\n\\n  \\nRelated|\\n\\n  * [Critique of work](/wiki/Critique_of_work \"Critique of work\")\\n  * [Powered exoskeleton](/wiki/Powered_exoskeleton \"Powered exoskeleton\")\\n  * [Workplace robotics safety](/wiki/Workplace_robotics_safety \"Workplace robotics safety\")\\n    * [Robotic tech vest](/wiki/Robotic_tech_vest \"Robotic tech vest\")\\n  * [Technological unemployment](/wiki/Technological_unemployment \"Technological unemployment\")\\n  * [Terrainability](/wiki/Terrainability \"Terrainability\")\\n  * [Fictional robots](/wiki/List_of_fictional_robots_and_androids \"List of fictional robots and androids\")\\n\\n  \\n  \\n  * ![](//upload.wikimedia.org/wikipedia/en/thumb/9/96/Symbol_category_class.svg/16px-Symbol_category_class.svg.png) **[Category](/wiki/Category:Robotics \"Category:Robotics\")**\\n  * ![](//upload.wikimedia.org/wikipedia/commons/thumb/4/41/Global_thinking.svg/10px-Global_thinking.svg.png) **[Outline](/wiki/Outline_of_robotics \"Outline of robotics\")**\\n\\n  \\n  \\nshow\\n\\n  * [v](/wiki/Template:Existential_risk_from_artificial_intelligence \"Template:Existential risk from artificial intelligence\")\\n  * [t](/wiki/Template_talk:Existential_risk_from_artificial_intelligence \"Template talk:Existential risk from artificial intelligence\")\\n  * [e](/wiki/Special:EditPage/Template:Existential_risk_from_artificial_intelligence \"Special:EditPage/Template:Existential risk from artificial intelligence\")\\n\\n[Existential risk](/wiki/Existential_risk_from_artificial_general_intelligence\\n\"Existential risk from artificial general intelligence\") from artificial\\nintelligence  \\n---  \\nConcepts|\\n\\n  * [AGI](/wiki/Artificial_general_intelligence \"Artificial general intelligence\")\\n  * [AI alignment](/wiki/AI_alignment \"AI alignment\")\\n  * [AI capability control](/wiki/AI_capability_control \"AI capability control\")\\n  * [AI safety](/wiki/AI_safety \"AI safety\")\\n  * [AI takeover](/wiki/AI_takeover \"AI takeover\")\\n  * [Consequentialism](/wiki/Consequentialism \"Consequentialism\")\\n  * [Effective accelerationism](/wiki/Effective_accelerationism \"Effective accelerationism\")\\n  * [Ethics of artificial intelligence](/wiki/Ethics_of_artificial_intelligence \"Ethics of artificial intelligence\")\\n  * [Existential risk from artificial general intelligence](/wiki/Existential_risk_from_artificial_general_intelligence \"Existential risk from artificial general intelligence\")\\n  * [Friendly artificial intelligence](/wiki/Friendly_artificial_intelligence \"Friendly artificial intelligence\")\\n  * [Instrumental convergence](/wiki/Instrumental_convergence \"Instrumental convergence\")\\n  * [Intelligence explosion](/wiki/Intelligence_explosion \"Intelligence explosion\")\\n  * [Longtermism](/wiki/Longtermism \"Longtermism\")\\n  * [Machine ethics](/wiki/Machine_ethics \"Machine ethics\")\\n  * [Suffering risks](/wiki/Suffering_risks \"Suffering risks\")\\n  * [Superintelligence](/wiki/Superintelligence \"Superintelligence\")\\n  * [Technological singularity](/wiki/Technological_singularity \"Technological singularity\")\\n\\n  \\nOrganizations|\\n\\n  * [Alignment Research Center](/wiki/Alignment_Research_Center \"Alignment Research Center\")\\n  * [Center for AI Safety](/wiki/Center_for_AI_Safety \"Center for AI Safety\")\\n  * [Center for Applied Rationality](/wiki/Center_for_Applied_Rationality \"Center for Applied Rationality\")\\n  * [Center for Human-Compatible Artificial Intelligence](/wiki/Center_for_Human-Compatible_Artificial_Intelligence \"Center for Human-Compatible Artificial Intelligence\")\\n  * [Centre for the Study of Existential Risk](/wiki/Centre_for_the_Study_of_Existential_Risk \"Centre for the Study of Existential Risk\")\\n  * [EleutherAI](/wiki/EleutherAI \"EleutherAI\")\\n  * [Future of Humanity Institute](/wiki/Future_of_Humanity_Institute \"Future of Humanity Institute\")\\n  * [Future of Life Institute](/wiki/Future_of_Life_Institute \"Future of Life Institute\")\\n  * [Google DeepMind](/wiki/Google_DeepMind \"Google DeepMind\")\\n  * [Humanity+](/wiki/Humanity%2B \"Humanity+\")\\n  * [Institute for Ethics and Emerging Technologies](/wiki/Institute_for_Ethics_and_Emerging_Technologies \"Institute for Ethics and Emerging Technologies\")\\n  * [Leverhulme Centre for the Future of Intelligence](/wiki/Leverhulme_Centre_for_the_Future_of_Intelligence \"Leverhulme Centre for the Future of Intelligence\")\\n  * [Machine Intelligence Research Institute](/wiki/Machine_Intelligence_Research_Institute \"Machine Intelligence Research Institute\")\\n  * [OpenAI](/wiki/OpenAI \"OpenAI\")\\n\\n  \\nPeople|\\n\\n  * [Scott Alexander](/wiki/Slate_Star_Codex \"Slate Star Codex\")\\n  * [Sam Altman](/wiki/Sam_Altman \"Sam Altman\")\\n  * [Yoshua Bengio](/wiki/Yoshua_Bengio \"Yoshua Bengio\")\\n  * [Nick Bostrom](/wiki/Nick_Bostrom \"Nick Bostrom\")\\n  * [Paul Christiano](/wiki/Paul_Christiano_\\\\(researcher\\\\) \"Paul Christiano \\\\(researcher\\\\)\")\\n  * [Eric Drexler](/wiki/K._Eric_Drexler \"K. Eric Drexler\")\\n  * [Sam Harris](/wiki/Sam_Harris \"Sam Harris\")\\n  * [Stephen Hawking](/wiki/Stephen_Hawking \"Stephen Hawking\")\\n  * [Dan Hendrycks](/wiki/Dan_Hendrycks \"Dan Hendrycks\")\\n  * [Geoffrey Hinton](/wiki/Geoffrey_Hinton \"Geoffrey Hinton\")\\n  * [Bill Joy](/wiki/Bill_Joy \"Bill Joy\")\\n  * [Shane Legg](/wiki/Shane_Legg \"Shane Legg\")\\n  * [Elon Musk](/wiki/Elon_Musk \"Elon Musk\")\\n  * [Steve Omohundro](/wiki/Steve_Omohundro \"Steve Omohundro\")\\n  * [Huw Price](/wiki/Huw_Price \"Huw Price\")\\n  * [Martin Rees](/wiki/Martin_Rees \"Martin Rees\")\\n  * [Stuart J. Russell](/wiki/Stuart_J._Russell \"Stuart J. Russell\")\\n  * [Jaan Tallinn](/wiki/Jaan_Tallinn \"Jaan Tallinn\")\\n  * [Max Tegmark](/wiki/Max_Tegmark \"Max Tegmark\")\\n  * [Frank Wilczek](/wiki/Frank_Wilczek \"Frank Wilczek\")\\n  * [Roman Yampolskiy](/wiki/Roman_Yampolskiy \"Roman Yampolskiy\")\\n  * [Eliezer Yudkowsky](/wiki/Eliezer_Yudkowsky \"Eliezer Yudkowsky\")\\n\\n  \\nOther|\\n\\n  * [Statement on AI risk of extinction](/wiki/Statement_on_AI_risk_of_extinction \"Statement on AI risk of extinction\")\\n  * _[Human Compatible](/wiki/Human_Compatible \"Human Compatible\")_\\n  * [Open letter on artificial intelligence (2015)](/wiki/Open_letter_on_artificial_intelligence_\\\\(2015\\\\) \"Open letter on artificial intelligence \\\\(2015\\\\)\")\\n  * _[Our Final Invention](/wiki/Our_Final_Invention \"Our Final Invention\")_\\n  * _[The Precipice](/wiki/The_Precipice:_Existential_Risk_and_the_Future_of_Humanity \"The Precipice: Existential Risk and the Future of Humanity\")_\\n  * _[Superintelligence: Paths, Dangers, Strategies](/wiki/Superintelligence:_Paths,_Dangers,_Strategies \"Superintelligence: Paths, Dangers, Strategies\")_\\n  * _[Do You Trust This Computer?](/wiki/Do_You_Trust_This_Computer%3F \"Do You Trust This Computer?\")_\\n  * [Artificial Intelligence Act](/wiki/Artificial_Intelligence_Act \"Artificial Intelligence Act\")\\n\\n  \\n![](//upload.wikimedia.org/wikipedia/en/thumb/9/96/Symbol_category_class.svg/16px-\\nSymbol_category_class.svg.png)\\n[Category](/wiki/Category:Existential_risk_from_artificial_general_intelligence\\n\"Category:Existential risk from artificial general intelligence\")  \\n  \\nshow\\n\\n  * [v](/wiki/Template:Cybernetics \"Template:Cybernetics\")\\n  * [t](/wiki/Template_talk:Cybernetics \"Template talk:Cybernetics\")\\n  * [e](/wiki/Special:EditPage/Template:Cybernetics \"Special:EditPage/Template:Cybernetics\")\\n\\nSubfields of and cyberneticians involved in [cybernetics](/wiki/Cybernetics\\n\"Cybernetics\")  \\n---  \\nSubfields|\\n\\n  * Artificial intelligence\\n  * [Biological cybernetics](/wiki/Biocybernetics \"Biocybernetics\")\\n  * [Biomedical cybernetics](/wiki/Biomedical_cybernetics \"Biomedical cybernetics\")\\n  * [Biorobotics](/wiki/Biorobotics \"Biorobotics\")\\n  * [Biosemiotics](/wiki/Biosemiotics \"Biosemiotics\")\\n  * [Neurocybernetics](/wiki/Brain%E2%80%93computer_interface \"Brain–computer interface\")\\n  * [Catastrophe theory](/wiki/Catastrophe_theory \"Catastrophe theory\")\\n  * [Computational neuroscience](/wiki/Computational_neuroscience \"Computational neuroscience\")\\n  * [Connectionism](/wiki/Connectionism \"Connectionism\")\\n  * [Control theory](/wiki/Control_theory \"Control theory\")\\n  * [Conversation theory](/wiki/Conversation_theory \"Conversation theory\")\\n  * [Cybernetics in the Soviet Union](/wiki/Cybernetics_in_the_Soviet_Union \"Cybernetics in the Soviet Union\")\\n  * [Decision theory](/wiki/Decision_theory \"Decision theory\")\\n  * [Emergence](/wiki/Emergence \"Emergence\")\\n  * [Engineering cybernetics](/wiki/Engineering_cybernetics \"Engineering cybernetics\")\\n  * [Homeostasis](/wiki/Homeostasis \"Homeostasis\")\\n  * [Information theory](/wiki/Information_theory \"Information theory\")\\n  * [Management cybernetics](/wiki/Management_cybernetics \"Management cybernetics\")\\n  * [Medical cybernetics](/wiki/Medical_cybernetics \"Medical cybernetics\")\\n  * [Second-order cybernetics](/wiki/Second-order_cybernetics \"Second-order cybernetics\")\\n  * [Cybersemiotics](/wiki/Cybersemiotics \"Cybersemiotics\")\\n  * [Sociocybernetics](/wiki/Sociocybernetics \"Sociocybernetics\")\\n  * [Synergetics](/wiki/Synergetics_\\\\(Haken\\\\) \"Synergetics \\\\(Haken\\\\)\")\\n\\n  \\n[Cyberneticians](/wiki/Cyberneticist \"Cyberneticist\")|\\n\\n  * [Alexander Lerner](/wiki/Alexander_Lerner \"Alexander Lerner\")\\n  * [Alexey Lyapunov](/wiki/Alexey_Lyapunov \"Alexey Lyapunov\")\\n  * [Alfred Radcliffe-Brown](/wiki/Alfred_Radcliffe-Brown \"Alfred Radcliffe-Brown\")\\n  * [Allenna Leonard](/wiki/Allenna_Leonard \"Allenna Leonard\")\\n  * [Anthony Wilden](/wiki/Anthony_Wilden \"Anthony Wilden\")\\n  * [Buckminster Fuller](/wiki/Buckminster_Fuller \"Buckminster Fuller\")\\n  * [Charles François](/wiki/Charles_Fran%C3%A7ois_\\\\(systems_scientist\\\\) \"Charles François \\\\(systems scientist\\\\)\")\\n  * [Genevieve Bell](/wiki/Genevieve_Bell \"Genevieve Bell\")\\n  * [Margaret Boden](/wiki/Margaret_Boden \"Margaret Boden\")\\n  * [Claude Bernard](/wiki/Claude_Bernard \"Claude Bernard\")\\n  * [Cliff Joslyn](/wiki/Cliff_Joslyn \"Cliff Joslyn\")\\n  * [Erich von Holst](/wiki/Erich_von_Holst \"Erich von Holst\")\\n  * [Ernst von Glasersfeld](/wiki/Ernst_von_Glasersfeld \"Ernst von Glasersfeld\")\\n  * [Francis Heylighen](/wiki/Francis_Heylighen \"Francis Heylighen\")\\n  * [Francisco Varela](/wiki/Francisco_Varela \"Francisco Varela\")\\n  * [Frederic Vester](/wiki/Frederic_Vester \"Frederic Vester\")\\n  * [Charles Geoffrey Vickers](/wiki/Geoffrey_Vickers \"Geoffrey Vickers\")\\n  * [Gordon Pask](/wiki/Gordon_Pask \"Gordon Pask\")\\n  * [Gordon S. Brown](/wiki/Gordon_S._Brown \"Gordon S. Brown\")\\n  * [Gregory Bateson](/wiki/Gregory_Bateson \"Gregory Bateson\")\\n  * [Heinz von Foerster](/wiki/Heinz_von_Foerster \"Heinz von Foerster\")\\n  * [Humberto Maturana](/wiki/Humberto_Maturana \"Humberto Maturana\")\\n  * [I. A. Richards](/wiki/I._A._Richards \"I. A. Richards\")\\n  * [Igor Aleksander](/wiki/Igor_Aleksander \"Igor Aleksander\")\\n  * [Jacque Fresco](/wiki/Jacque_Fresco \"Jacque Fresco\")\\n  * [Jakob von Uexküll](/wiki/Jakob_Johann_von_Uexk%C3%BCll \"Jakob Johann von Uexküll\")\\n  * [Jason Jixuan Hu](/wiki/Jason_Jixuan_Hu \"Jason Jixuan Hu\")\\n  * [Jay Wright Forrester](/wiki/Jay_Wright_Forrester \"Jay Wright Forrester\")\\n  * [Jennifer Wilby](/wiki/Jennifer_Wilby \"Jennifer Wilby\")\\n  * [John N. Warfield](/wiki/John_N._Warfield \"John N. Warfield\")\\n  * [Kevin Warwick](/wiki/Kevin_Warwick \"Kevin Warwick\")\\n  * [Ludwig von Bertalanffy](/wiki/Ludwig_von_Bertalanffy \"Ludwig von Bertalanffy\")\\n  * [Maleyka Abbaszadeh](/wiki/Maleyka_Abbaszadeh \"Maleyka Abbaszadeh\")\\n  * [Manfred Clynes](/wiki/Manfred_Clynes \"Manfred Clynes\")\\n  * [Margaret Mead](/wiki/Margaret_Mead \"Margaret Mead\")\\n  * [Marian Mazur](/wiki/Marian_Mazur \"Marian Mazur\")\\n  * [N. Katherine Hayles](/wiki/N._Katherine_Hayles \"N. Katherine Hayles\")\\n  * [Natalia Bekhtereva](/wiki/Natalia_Bekhtereva \"Natalia Bekhtereva\")\\n  * [Niklas Luhmann](/wiki/Niklas_Luhmann \"Niklas Luhmann\")\\n  * [Norbert Wiener](/wiki/Norbert_Wiener \"Norbert Wiener\")\\n  * [Pyotr Grigorenko](/wiki/Petro_Grigorenko \"Petro Grigorenko\")\\n  * [Qian Xuesen](/wiki/Qian_Xuesen \"Qian Xuesen\")\\n  * [Ranulph Glanville](/wiki/Ranulph_Glanville \"Ranulph Glanville\")\\n  * [Robert Trappl](/wiki/Robert_Trappl \"Robert Trappl\")\\n  * [Sergei P. 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     ]
    }
   ],
   "source": [
    "# Run the agent step by step\n",
    "\n",
    "max_steps = 50\n",
    "for i in range(max_steps):\n",
    "\tprint(f'\\n📍 Step {i+1}')\n",
    "\taction, result = await agent.step()\n",
    "\n",
    "\tprint('Action:', action)\n",
    "\tprint('Result:', result)\n",
    "\n",
    "\tif result.done:\n",
    "\t\tprint('\\n✅ Task completed successfully!')\n",
    "\t\tprint('Extracted content:', result.extracted_content)\n",
    "\t\tbreak\n"
   ]
  }
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