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Artificial intelligence - Wikipedia

# Artificial intelligence Artificial intelligence "AI" redirects here. For other uses, see [AI (disambiguation)](https://en.wikipedia.org/wiki/AI_(disambiguation)) and [Artificial intelligence (disambiguation)](https://en.wikipedia.org/wiki/Artificial_intelligence_(disambiguation)). **Artificial intelligence** ( **AI**) is the capability of [computational systems](https://en.wikipedia.org/wiki/Computer) to perform tasks typically associated with [human intelligence](https://en.wikipedia.org/wiki/Human_intelligence), such as [learning](https://en.wikipedia.org/wiki/Learning), [reasoning](https://en.wikipedia.org/wiki/Reason), [problem-solving](https://en.wikipedia.org/wiki/Problem-solving), [perception](https://en.wikipedia.org/wiki/Perception), and [decision-making](https://en.wikipedia.org/wiki/Decision-making). High-profile [applications of AI](https://en.wikipedia.org/wiki/Applications_of_artificial_intelligence) include advanced [web search engines](https://en.wikipedia.org/wiki/Web_search_engine), [chatbots](https://en.wikipedia.org/wiki/Chatbot), [virtual assistants](https://en.wikipedia.org/wiki/Virtual_assistant), [autonomous vehicles](https://en.wikipedia.org/wiki/Autonomous_vehicles), play and analysis in [strategy games](https://en.wikipedia.org/wiki/Strategy_game) (e.g., [chess](https://en.wikipedia.org/wiki/Chess) and [Go](https://en.wikipedia.org/wiki/Go_(game))), and [content generation](https://en.wikipedia.org/wiki/Generative_AI) (e.g., text, images, audio, and videos). The traditional goals of AI research include learning, [reasoning](https://en.wikipedia.org/wiki/Automated_reasoning), [knowledge representation](https://en.wikipedia.org/wiki/Knowledge_representation), [planning](https://en.wikipedia.org/wiki/Automated_planning_and_scheduling), [natural language processing](https://en.wikipedia.org/wiki/Natural_language_processing), and [perception](https://en.wikipedia.org/wiki/Machine_perception), as well as support for [robotics](https://en.wikipedia.org/wiki/Robotics). [[a]](https://en.wikipedia.org/wiki/Artificial_intelligence#cite_note-Problems_of_AI-2) To reach these goals, AI researchers use techniques including [state space search](https://en.wikipedia.org/wiki/State_space_search) and [mathematical optimisation](https://en.wikipedia.org/wiki/Mathematical_optimization), [formal logic](https://en.wikipedia.org/wiki/Formal_logic), [artificial neural networks](https://en.wikipedia.org/wiki/Artificial_neural_network), and methods based on [statistics](https://en.wikipedia.org/wiki/Statistics), [operations research](https://en.wikipedia.org/wiki/Operations_research), and [economics](https://en.wikipedia.org/wiki/Economics). [[b]](https://en.wikipedia.org/wiki/Artificial_intelligence#cite_note-Tools_of_AI-3) AI also draws upon [psychology](https://en.wikipedia.org/wiki/Psychology), [linguistics](https://en.wikipedia.org/wiki/Linguistics), [philosophy](https://en.wikipedia.org/wiki/Philosophy_of_artificial_intelligence), [neuroscience](https://en.wikipedia.org/wiki/Neuroscience), and other fields. [[2]](https://en.wikipedia.org/wiki/Artificial_intelligence#cite_note-4) Some companies, such as [OpenAI](https://en.wikipedia.org/wiki/OpenAI), [Google DeepMind](https://en.wikipedia.org/wiki/Google_DeepMind), and [Meta](https://en.wikipedia.org/wiki/Meta_Platforms), aim to create [artificial general intelligence](https://en.wikipedia.org/wiki/Artificial_general_intelligence) (AGI)—AI that can complete nearly any [cognitive](https://en.wikipedia.org/wiki/Cognition) task at least as well as a human. In addition to [AI safety](https://en.wikipedia.org/wiki/AI_safety) and [unintended consequences and harms](https://en.wikipedia.org/wiki/Generative_AI#Concerns) from the use of AI, [ethical concerns](https://en.wikipedia.org/wiki/Ethics_of_artificial_intelligence), [AI's long-term effects](https://en.wikipedia.org/wiki/AI_aftermath_scenarios), [environmental effects](https://en.wikipedia.org/wiki/Environmental_impacts_of_artificial_intelligence),[[11]](https://en.wikipedia.org/wiki/Artificial_intelligence#cite_note-UN-13) and [potential existential risks](https://en.wikipedia.org/wiki/Existential_risk_from_artificial_intelligence) have prompted discussions of [AI regulation](https://en.wikipedia.org/wiki/Regulation_of_artificial_intelligence). ## Notes 51. [↑](https://en.wikipedia.org/wiki/Artificial_intelligence#cite_ref-58)["Artificial Intelligence (AI): What Is AI and How Does It Work?"](https://builtin.com/artificial-intelligence). _Built In_. Retrieved 30 October 2023. 398. [↑](https://en.wikipedia.org/wiki/Artificial_intelligence#cite_ref-422)AI widely used in the late 1990s: [Kurzweil (2005](https://en.wikipedia.org/wiki/Artificial_intelligence#CITEREFKurzweil2005), p.265), [NRC (1999](https://en.wikipedia.org/wiki/Artificial_intelligence#CITEREFNRC1999), pp.216–222), [Newquist (1994](https://en.wikipedia.org/wiki/Artificial_intelligence#CITEREFNewquist1994), pp.189–201) ## External links | [Artificial intelligence](https://en.wikipedia.org/wiki/Artificial_intelligence) (AI) | |-| | - [History](https://en.wikipedia.org/wiki/History_of_artificial_intelligence) <br> - [timeline](https://en.wikipedia.org/wiki/Timeline_of_artificial_intelligence)<br>- [Glossary](https://en.wikipedia.org/wiki/Glossary_of_artificial_intelligence)<br>- Lists<br> - [Algorithms](https://en.wikipedia.org/wiki/List_of_artificial_intelligence_algorithms)<br> - [Companies](https://en.wikipedia.org/wiki/List_of_artificial_intelligence_companies)<br> - [Institutions](https://en.wikipedia.org/wiki/List_of_artificial_intelligence_institutions)<br> - [Projects](https://en.wikipedia.org/wiki/List_of_artificial_intelligence_projects)<br> - Software<br> - [Open-source](https://en.wikipedia.org/wiki/Lists_of_open-source_artificial_intelligence_software)<br> - [Proprietary](https://en.wikipedia.org/wiki/List_of_proprietary_artificial_intelligence_software) | | Concepts | - [Automated reasoning](https://en.wikipedia.org/wiki/Automated_reasoning)<br>- [Automated planning](https://en.wikipedia.org/wiki/Automated_planning_and_scheduling)<br>- [Constraint satisfaction](https://en.wikipedia.org/wiki/Constraint_satisfaction_problem)<br>- [Knowledge representation](https://en.wikipedia.org/wiki/Knowledge_representation_and_reasoning)<br>- [Parameter](https://en.wikipedia.org/wiki/Parameter) <br> - [Hyperparameter](https://en.wikipedia.org/wiki/Hyperparameter_(machine_learning))<br>- [Loss functions](https://en.wikipedia.org/wiki/Loss_functions_for_classification)<br>- [Regression](https://en.wikipedia.org/wiki/Regression_analysis) <br> - [Bias–variance tradeoff](https://en.wikipedia.org/wiki/Bias%E2%80%93variance_tradeoff)<br> - [Double descent](https://en.wikipedia.org/wiki/Double_descent)<br> - [Overfitting](https://en.wikipedia.org/wiki/Overfitting)<br>- [Clustering](https://en.wikipedia.org/wiki/Cluster_analysis)<br>- [Gradient descent](https://en.wikipedia.org/wiki/Gradient_descent) <br> - [SGD](https://en.wikipedia.org/wiki/Stochastic_gradient_descent)<br> - [Quasi-Newton method](https://en.wikipedia.org/wiki/Quasi-Newton_method)<br> - [Conjugate gradient method](https://en.wikipedia.org/wiki/Conjugate_gradient_method)<br>- [Backpropagation](https://en.wikipedia.org/wiki/Backpropagation)<br>- [Attention](https://en.wikipedia.org/wiki/Attention_(machine_learning))<br>- [Convolution](https://en.wikipedia.org/wiki/Convolution)<br>- [Normalization](https://en.wikipedia.org/wiki/Normalization_(machine_learning)) <br> - [Batchnorm](https://en.wikipedia.org/wiki/Batch_normalization)<br>- [Activation](https://en.wikipedia.org/wiki/Activation_function) <br> - [Softmax](https://en.wikipedia.org/wiki/Softmax_function)<br> - [Sigmoid](https://en.wikipedia.org/wiki/Sigmoid_function)<br> - [Rectifier](https://en.wikipedia.org/wiki/Rectifier_(neural_networks))<br>- [Gating](https://en.wikipedia.org/wiki/Gating_mechanism)<br>- [Weight initialization](https://en.wikipedia.org/wiki/Weight_initialization)<br>- [Regularization](https://en.wikipedia.org/wiki/Regularization_(mathematics))<br>- [Datasets](https://en.wikipedia.org/wiki/Training,_validation,_and_test_data_sets) <br> - [Augmentation](https://en.wikipedia.org/wiki/Data_augmentation)<br>- [Prompt engineering](https://en.wikipedia.org/wiki/Prompt_engineering)<br>- [Reinforcement learning](https://en.wikipedia.org/wiki/Reinforcement_learning) <br> - [Q-learning](https://en.wikipedia.org/wiki/Q-learning)<br> - [SARSA](https://en.wikipedia.org/wiki/State%E2%80%93action%E2%80%93reward%E2%80%93state%E2%80%93action)<br> - [Imitation](https://en.wikipedia.org/wiki/Imitation_learning)<br> - [Policy gradient](https://en.wikipedia.org/wiki/Policy_gradient_method)<br>- [Diffusion](https://en.wikipedia.org/wiki/Diffusion_process)<br>- [Latent diffusion model](https://en.wikipedia.org/wiki/Latent_diffusion_model)<br>- [Autoregression](https://en.wikipedia.org/wiki/Autoregressive_model)<br>- [Adversary](https://en.wikipedia.org/wiki/Adversarial_machine_learning)<br>- [RAG](https://en.wikipedia.org/wiki/Retrieval-augmented_generation)<br>- [Uncanny valley](https://en.wikipedia.org/wiki/Uncanny_valley)<br>- [LLM post-training](https://en.wikipedia.org/wiki/Post-training_of_large_language_models)<br>- [RLHF](https://en.wikipedia.org/wiki/Reinforcement_learning_from_human_feedback)<br>- [Self-supervised learning](https://en.wikipedia.org/wiki/Self-supervised_learning)<br>- [Reflection](https://en.wikipedia.org/wiki/Reflection_(artificial_intelligence))<br>- [Recursive self-improvement](https://en.wikipedia.org/wiki/Recursive_self-improvement)<br>- [Hallucination](https://en.wikipedia.org/wiki/Hallucination_(artificial_intelligence))<br>- [Word embedding](https://en.wikipedia.org/wiki/Word_embedding)<br>- [Vibe coding](https://en.wikipedia.org/wiki/Vibe_coding)<br>- [Blended AI](https://en.wikipedia.org/wiki/Blended_artificial_intelligence)<br>- [Open-source AI](https://en.wikipedia.org/wiki/Open-source_artificial_intelligence)<br>- [Sovereign AI](https://en.wikipedia.org/wiki/Sovereign_AI)<br>- [Symbolic AI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)<br>- [Neuro-symbolic AI](https://en.wikipedia.org/wiki/Neuro-symbolic_AI)<br>- [Situated approach](https://en.wikipedia.org/wiki/Situated_approach_(artificial_intelligence))<br>- [Actor-critic algorithm](https://en.wikipedia.org/wiki/Actor-critic_algorithm) | | [Applications](https://en.wikipedia.org/wiki/Applications_of_artificial_intelligence) | - [Automated theorem proving](https://en.wikipedia.org/wiki/Automated_theorem_proving)<br>- [General game playing](https://en.wikipedia.org/wiki/General_game_playing)<br>- [Machine learning](https://en.wikipedia.org/wiki/Machine_learning) <br> - [In-context learning](https://en.wikipedia.org/wiki/Prompt_engineering#In-context_learning)<br>- [Artificial neural network](https://en.wikipedia.org/wiki/Neural_network_(machine_learning)) <br> - [Deep learning](https://en.wikipedia.org/wiki/Deep_learning)<br>- [Language model](https://en.wikipedia.org/wiki/Language_model) <br> - [Large](https://en.wikipedia.org/wiki/Large_language_model)<br> - [NMT](https://en.wikipedia.org/wiki/Neural_machine_translation)<br> - [Reasoning](https://en.wikipedia.org/wiki/Reasoning_model)<br>- [Model Context Protocol](https://en.wikipedia.org/wiki/Model_Context_Protocol)<br>- [Intelligent agent](https://en.wikipedia.org/wiki/Intelligent_agent) <br> - [AI agent](https://en.wikipedia.org/wiki/AI_agent)<br>- [Artificial human companion](https://en.wikipedia.org/wiki/Artificial_human_companion)<br>- [Humanity's Last Exam](https://en.wikipedia.org/wiki/Humanity's_Last_Exam)<br>- [Lethal autonomous weapons (LAWs)](https://en.wikipedia.org/wiki/Lethal_autonomous_weapon)<br>- [Generative AI](https://en.wikipedia.org/wiki/Generative_AI)<br>- [Weak AI](https://en.wikipedia.org/wiki/Weak_artificial_intelligence)<br>- Hypothetical<br> - [Artificial general intelligence (AGI)](https://en.wikipedia.org/wiki/Artificial_general_intelligence)<br> - [Artificial superintelligence (ASI)](https://en.wikipedia.org/wiki/Superintelligence)<br>- [Agent2Agent protocol](https://en.wikipedia.org/wiki/Agent2Agent)<br>- [Physical AI](https://en.wikipedia.org/wiki/Physical_AI) | | Implementations | | Audio–visual | - [AlexNet](https://en.wikipedia.org/wiki/AlexNet)<br>- [WaveNet](https://en.wikipedia.org/wiki/WaveNet)<br>- [Human image synthesis](https://en.wikipedia.org/wiki/Human_image_synthesis)<br>- [HWR](https://en.wikipedia.org/wiki/Handwriting_recognition)<br>- [OCR](https://en.wikipedia.org/wiki/Optical_character_recognition)<br>- [Computer vision](https://en.wikipedia.org/wiki/Computer_vision)<br>- [Speech synthesis](https://en.wikipedia.org/wiki/Deep_learning_speech_synthesis) <br> - [15.ai](https://en.wikipedia.org/wiki/15.ai)<br> - [ElevenLabs](https://en.wikipedia.org/wiki/ElevenLabs)<br>- [Speech recognition](https://en.wikipedia.org/wiki/Speech_recognition) <br> - [Whisper](https://en.wikipedia.org/wiki/Whisper_(speech_recognition_system))<br>- [Facial recognition](https://en.wikipedia.org/wiki/Facial_recognition_system)<br>- [AlphaFold](https://en.wikipedia.org/wiki/AlphaFold)<br>- [Text-to-image models](https://en.wikipedia.org/wiki/Text-to-image_model) <br> - [Aurora](https://en.wikipedia.org/wiki/Aurora_(text-to-image_model))<br> - [DALL-E](https://en.wikipedia.org/wiki/DALL-E)<br> - [Firefly](https://en.wikipedia.org/wiki/Adobe_Firefly)<br> - [Flux](https://en.wikipedia.org/wiki/Flux_(text-to-image_model))<br> - [GPT Image](https://en.wikipedia.org/wiki/GPT_Image)<br> - [Ideogram](https://en.wikipedia.org/wiki/Ideogram_(text-to-image_model))<br> - [Imagen](https://en.wikipedia.org/wiki/Imagen_(text-to-image_model))<br> - [Midjourney](https://en.wikipedia.org/wiki/Midjourney)<br> - [Recraft](https://en.wikipedia.org/wiki/Recraft)<br> - [Stable Diffusion](https://en.wikipedia.org/wiki/Stable_Diffusion)<br>- [Text-to-video models](https://en.wikipedia.org/wiki/Text-to-video_model) <br> - [Dream Machine](https://en.wikipedia.org/wiki/Dream_Machine_(text-to-video_model))<br> - [Runway Gen](https://en.wikipedia.org/wiki/Runway_(company)#Services_and_technologies)<br> - [Hailuo AI](https://en.wikipedia.org/wiki/MiniMax_(company)#Hailuo_AI)<br> - [Kling](https://en.wikipedia.org/wiki/Kling_AI)<br> - [Sora](https://en.wikipedia.org/wiki/Sora_(text-to-video_model))<br> - [Seedance](https://en.wikipedia.org/wiki/Seedance)<br> - [Veo](https://en.wikipedia.org/wiki/Veo_(text-to-video_model))<br>- [Music generation](https://en.wikipedia.org/wiki/Artificial_intelligence_in_music) <br> - [Riffusion](https://en.wikipedia.org/wiki/Riffusion)<br> - [Suno](https://en.wikipedia.org/wiki/Suno_(platform))<br> - [Udio](https://en.wikipedia.org/wiki/Udio)<br>- [World models](https://en.wikipedia.org/wiki/World_model_(artificial_intelligence)) <br> - [Genie](https://en.wikipedia.org/wiki/Genie_(world_model))<br> - [_Oasis_](https://en.wikipedia.org/wiki/Oasis_(Minecraft_clone)) | | Text | - [List of large language models](https://en.wikipedia.org/wiki/List_of_large_language_models)<br>- [Project Debater](https://en.wikipedia.org/wiki/Project_Debater)<br>- [IBM Watson](https://en.wikipedia.org/wiki/IBM_Watson) <br> - [IBM Watsonx](https://en.wikipedia.org/wiki/IBM_Watsonx) | | Decisional | - [AlphaGo](https://en.wikipedia.org/wiki/AlphaGo)<br>- [AlphaZero](https://en.wikipedia.org/wiki/AlphaZero)<br>- [OpenAI Five](https://en.wikipedia.org/wiki/OpenAI_Five)<br>- [Self-driving car](https://en.wikipedia.org/wiki/Self-driving_car)<br>- [MuZero](https://en.wikipedia.org/wiki/MuZero)<br>- [Action selection](https://en.wikipedia.org/wiki/Action_selection) <br> - [AutoGPT](https://en.wikipedia.org/wiki/AutoGPT)<br>- [Robot control](https://en.wikipedia.org/wiki/Robot_control) | | [Reasoning systems](https://en.wikipedia.org/wiki/Reasoning_system) | - [Deductive classifiers](https://en.wikipedia.org/wiki/Deductive_classifier)<br>- [Expert systems](https://en.wikipedia.org/wiki/Expert_system)<br>- [Inference engines](https://en.wikipedia.org/wiki/Inference_engine)<br>- [Knowledge-based systems](https://en.wikipedia.org/wiki/Knowledge-based_system)<br>- [Logic programs](https://en.wikipedia.org/wiki/Logic_program)<br>- [Procedural reasoning systems](https://en.wikipedia.org/wiki/Procedural_reasoning_system)<br>- [Semantic reasoners](https://en.wikipedia.org/wiki/Semantic_reasoner)<br>- [Rule-based systems](https://en.wikipedia.org/wiki/Rule-based_system) | | People | - [Alan Turing](https://en.wikipedia.org/wiki/Alan_Turing)<br>- [Warren Sturgis McCulloch](https://en.wikipedia.org/wiki/Warren_Sturgis_McCulloch)<br>- [Walter Pitts](https://en.wikipedia.org/wiki/Walter_Pitts)<br>- [John von Neumann](https://en.wikipedia.org/wiki/John_von_Neumann)<br>- [Christopher D. Manning](https://en.wikipedia.org/wiki/Christopher_D._Manning)<br>- [Claude Shannon](https://en.wikipedia.org/wiki/Claude_Shannon)<br>- [Shun'ichi Amari](https://en.wikipedia.org/wiki/Shun'ichi_Amari)<br>- [Kunihiko Fukushima](https://en.wikipedia.org/wiki/Kunihiko_Fukushima)<br>- [Takeo Kanade](https://en.wikipedia.org/wiki/Takeo_Kanade)<br>- [Marvin Minsky](https://en.wikipedia.org/wiki/Marvin_Minsky)<br>- [John McCarthy](https://en.wikipedia.org/wiki/John_McCarthy_(computer_scientist))<br>- [Nathaniel Rochester](https://en.wikipedia.org/wiki/Nathaniel_Rochester_(computer_scientist))<br>- [Allen Newell](https://en.wikipedia.org/wiki/Allen_Newell)<br>- [Cliff Shaw](https://en.wikipedia.org/wiki/Cliff_Shaw)<br>- [Herbert A. Simon](https://en.wikipedia.org/wiki/Herbert_A._Simon)<br>- [Oliver Selfridge](https://en.wikipedia.org/wiki/Oliver_Selfridge)<br>- [Frank Rosenblatt](https://en.wikipedia.org/wiki/Frank_Rosenblatt)<br>- [Bernard Widrow](https://en.wikipedia.org/wiki/Bernard_Widrow)<br>- [Joseph Weizenbaum](https://en.wikipedia.org/wiki/Joseph_Weizenbaum)<br>- [Seymour Papert](https://en.wikipedia.org/wiki/Seymour_Papert)<br>- [Seppo Linnainmaa](https://en.wikipedia.org/wiki/Seppo_Linnainmaa)<br>- [Paul Werbos](https://en.wikipedia.org/wiki/Paul_Werbos)<br>- [Geoffrey Hinton](https://en.wikipedia.org/wiki/Geoffrey_Hinton)<br>- [John Hopfield](https://en.wikipedia.org/wiki/John_Hopfield)<br>- [Jürgen Schmidhuber](https://en.wikipedia.org/wiki/J%C3%BCrgen_Schmidhuber)<br>- [Yann LeCun](https://en.wikipedia.org/wiki/Yann_LeCun)<br>- [Yoshua Bengio](https://en.wikipedia.org/wiki/Yoshua_Bengio)<br>- [Lotfi A. Zadeh](https://en.wikipedia.org/wiki/Lotfi_A._Zadeh)<br>- [Stephen Grossberg](https://en.wikipedia.org/wiki/Stephen_Grossberg)<br>- [Alex Graves](https://en.wikipedia.org/wiki/Alex_Graves_(computer_scientist))<br>- [James Goodnight](https://en.wikipedia.org/wiki/James_Goodnight)<br>- [Andrew Ng](https://en.wikipedia.org/wiki/Andrew_Ng)<br>- [Fei-Fei Li](https://en.wikipedia.org/wiki/Fei-Fei_Li)<br>- [Alex Krizhevsky](https://en.wikipedia.org/wiki/Alex_Krizhevsky)<br>- [Ilya Sutskever](https://en.wikipedia.org/wiki/Ilya_Sutskever)<br>- [Oriol Vinyals](https://en.wikipedia.org/wiki/Oriol_Vinyals)<br>- [Quoc V. Le](https://en.wikipedia.org/wiki/Quoc_V._Le)<br>- [Ian Goodfellow](https://en.wikipedia.org/wiki/Ian_Goodfellow)<br>- [Demis Hassabis](https://en.wikipedia.org/wiki/Demis_Hassabis)<br>- [David Silver](https://en.wikipedia.org/wiki/David_Silver_(computer_scientist))<br>- [Andrej Karpathy](https://en.wikipedia.org/wiki/Andrej_Karpathy)<br>- [Ashish Vaswani](https://en.wikipedia.org/wiki/Ashish_Vaswani)<br>- [Noam Shazeer](https://en.wikipedia.org/wiki/Noam_Shazeer)<br>- [Aidan Gomez](https://en.wikipedia.org/wiki/Aidan_Gomez)<br>- [John Schulman](https://en.wikipedia.org/wiki/John_Schulman)<br>- [Mustafa Suleyman](https://en.wikipedia.org/wiki/Mustafa_Suleyman)<br>- [Jan Leike](https://en.wikipedia.org/wiki/Jan_Leike)<br>- [Daniel Kokotajlo](https://en.wikipedia.org/wiki/Daniel_Kokotajlo_(researcher))<br>- [François Chollet](https://en.wikipedia.org/wiki/Fran%C3%A7ois_Chollet) | | Neural network<br>architectures | - [Neural Turing machine](https://en.wikipedia.org/wiki/Neural_Turing_machine)<br>- [Differentiable neural computer](https://en.wikipedia.org/wiki/Differentiable_neural_computer)<br>- [Transformer](https://en.wikipedia.org/wiki/Transformer_(deep_learning)) <br> - [Vision transformer (ViT)](https://en.wikipedia.org/wiki/Vision_transformer)<br>- [Recurrent neural network (RNN)](https://en.wikipedia.org/wiki/Recurrent_neural_network)<br>- [Long short-term memory (LSTM)](https://en.wikipedia.org/wiki/Long_short-term_memory)<br>- [Gated recurrent unit (GRU)](https://en.wikipedia.org/wiki/Gated_recurrent_unit)<br>- [Echo state network](https://en.wikipedia.org/wiki/Echo_state_network)<br>- [Multilayer perceptron (MLP)](https://en.wikipedia.org/wiki/Multilayer_perceptron)<br>- [Convolutional neural network (CNN)](https://en.wikipedia.org/wiki/Convolutional_neural_network)<br>- [Residual neural network (RNN)](https://en.wikipedia.org/wiki/Residual_neural_network)<br>- [Highway network](https://en.wikipedia.org/wiki/Highway_network)<br>- [Mamba](https://en.wikipedia.org/wiki/Mamba_(deep_learning_architecture))<br>- [Autoencoder](https://en.wikipedia.org/wiki/Autoencoder)<br>- [Variational autoencoder (VAE)](https://en.wikipedia.org/wiki/Variational_autoencoder)<br>- [Generative adversarial network (GAN)](https://en.wikipedia.org/wiki/Generative_adversarial_network)<br>- [Graph neural network (GNN)](https://en.wikipedia.org/wiki/Graph_neural_network) | | Political | - [AI Cold War](https://en.wikipedia.org/wiki/Artificial_Intelligence_Cold_War)<br>- [AI in government](https://en.wikipedia.org/wiki/Artificial_intelligence_in_government)<br>- [AI safety](https://en.wikipedia.org/wiki/AI_safety) ( [Alignment](https://en.wikipedia.org/wiki/AI_alignment))<br>- [AI takeover](https://en.wikipedia.org/wiki/AI_takeover)<br>- [Elections](https://en.wikipedia.org/wiki/Artificial_intelligence_and_elections)<br>- [Ethics of AI](https://en.wikipedia.org/wiki/Ethics_of_artificial_intelligence)<br>- EU [AI Act](https://en.wikipedia.org/wiki/Artificial_Intelligence_Act)<br>- [Nationalism](https://en.wikipedia.org/wiki/AI_nationalism)<br>- [Precautionary principle](https://en.wikipedia.org/wiki/Precautionary_principle)<br>- [Regulation of AI](https://en.wikipedia.org/wiki/Regulation_of_artificial_intelligence) <br> - [US](https://en.wikipedia.org/wiki/Regulation_of_artificial_intelligence_in_the_United_States)<br>- [Virtual politician](https://en.wikipedia.org/wiki/Virtual_politician)<br>- [Propaganda](https://en.wikipedia.org/wiki/Computational_propaganda)<br>- [Opposition to AI data centers](https://en.wikipedia.org/wiki/Opposition_to_AI_data_centers) | | Social<br>and economic | - [AI boom](https://en.wikipedia.org/wiki/AI_boom)<br>- [AI bubble](https://en.wikipedia.org/wiki/AI_bubble)<br>- [AI data center](https://en.wikipedia.org/wiki/AI_data_center)<br>- [AI effect](https://en.wikipedia.org/wiki/AI_effect)<br>- [AI infrastructure](https://en.wikipedia.org/wiki/AI_infrastructure)<br>- [AI literacy](https://en.wikipedia.org/wiki/AI_literacy)<br>- [AI slop](https://en.wikipedia.org/wiki/AI_slop)<br>- [AI winter](https://en.wikipedia.org/wiki/AI_winter)<br>- [Anthropomorphism](https://en.wikipedia.org/wiki/AI_anthropomorphism)<br>- [Arms race](https://en.wikipedia.org/wiki/Artificial_intelligence_arms_race)<br>- [Competition](https://en.wikipedia.org/wiki/Competition_in_artificial_intelligence)<br>- [Environmental impact](https://en.wikipedia.org/wiki/Environmental_impact_of_artificial_intelligence)<br>- [Explainable AI](https://en.wikipedia.org/wiki/Explainable_artificial_intelligence)<br>- [Generative engine optimization](https://en.wikipedia.org/wiki/Generative_engine_optimization)<br>- [In architecture](https://en.wikipedia.org/wiki/Artificial_intelligence_in_architecture)<br>- [In education](https://en.wikipedia.org/wiki/Artificial_intelligence_in_education)<br>- [In fiction](https://en.wikipedia.org/wiki/Artificial_intelligence_in_fiction)<br>- [In healthcare](https://en.wikipedia.org/wiki/Artificial_intelligence_in_healthcare) <br> - [Chatbot psychosis](https://en.wikipedia.org/wiki/Chatbot_psychosis)<br>- [In marketing](https://en.wikipedia.org/wiki/Artificial_intelligence_in_marketing)<br>- [In video games](https://en.wikipedia.org/wiki/Artificial_intelligence_in_video_games)<br>- [In visual art](https://en.wikipedia.org/wiki/Artificial_intelligence_visual_art)<br>- [Military applications](https://en.wikipedia.org/wiki/Military_applications_of_artificial_intelligence) <br> - [AI warfare](https://en.wikipedia.org/wiki/AI_warfare)<br>- [Workplace impact](https://en.wikipedia.org/wiki/Workplace_impact_of_artificial_intelligence) | | - ![](https://thumb.wikimedia.org/wikipedia/en/thumb/9/96/Symbol_category_class.svg/40px-Symbol_category_class.svg.png?utm_source=en.wikipedia.org&utm_campaign=parser&utm_content=thumbnail)[Category](https://en.wikipedia.org/wiki/Category:Artificial_intelligence) | | [Large language models](https://en.wikipedia.org/wiki/Large_language_model) (LLMs) | |-| | Training, prompting,<br>and alignment | - [Self-supervised learning](https://en.wikipedia.org/wiki/Self-supervised_learning)<br>- [Supervised learning](https://en.wikipedia.org/wiki/Supervised_learning)<br>- [Fine-tuning](https://en.wikipedia.org/wiki/Fine-tuning_(machine_learning)) <br> - [Instruction tuning](https://en.wikipedia.org/wiki/Instruction_tuning)<br>- [RLHF](https://en.wikipedia.org/wiki/Reinforcement_learning_from_human_feedback)<br>- [Constitutional AI](https://en.wikipedia.org/wiki/Constitutional_AI)<br>- [AI alignment](https://en.wikipedia.org/wiki/AI_alignment)<br>- [AI safety](https://en.wikipedia.org/wiki/AI_safety)<br>- [Mechanistic interpretability](https://en.wikipedia.org/wiki/Mechanistic_interpretability)<br>- [Prompt engineering](https://en.wikipedia.org/wiki/Prompt_engineering) <br> - [In-context learning](https://en.wikipedia.org/wiki/In-context_learning)<br> - [Chain-of-thought prompting](https://en.wikipedia.org/wiki/Chain-of-thought_prompting)<br>- [RAG](https://en.wikipedia.org/wiki/Retrieval-augmented_generation)<br>- [Prompt injection](https://en.wikipedia.org/wiki/Prompt_injection)<br>- [Adversarial machine learning](https://en.wikipedia.org/wiki/Adversarial_machine_learning)<br>- [Hallucination](https://en.wikipedia.org/wiki/Hallucination_(artificial_intelligence))<br>- [Stochastic parrot](https://en.wikipedia.org/wiki/Stochastic_parrot)<br>- [Glitch token](https://en.wikipedia.org/wiki/Glitch_token)<br>- [Generative engine optimization](https://en.wikipedia.org/wiki/Generative_engine_optimization) | | Models | - [Apertus](https://en.wikipedia.org/wiki/Apertus_(LLM))<br>- [BERT](https://en.wikipedia.org/wiki/BERT_(language_model))<br>- [BLOOM](https://en.wikipedia.org/wiki/BLOOM_(language_model))<br>- [Chinchilla](https://en.wikipedia.org/wiki/Chinchilla_(language_model))<br>- [Claude](https://en.wikipedia.org/wiki/Claude_(language_model))<br>- [DBRX](https://en.wikipedia.org/wiki/DBRX)<br>- [DeepSeek-LLM](https://en.wikipedia.org/wiki/DeepSeek#DeepSeek-LLM)<br>- [Gemini](https://en.wikipedia.org/wiki/Gemini_(language_model)) <br> - [Gemma](https://en.wikipedia.org/wiki/Gemma_(language_model))<br>- [GloVe](https://en.wikipedia.org/wiki/GloVe)<br>- [GLM](https://en.wikipedia.org/wiki/GLM_(AI))<br>- [GPT](https://en.wikipedia.org/wiki/GPT_(OpenAI_model))<br>- [GPT-J](https://en.wikipedia.org/wiki/GPT-J)<br>- [PanGu](https://en.wikipedia.org/wiki/Huawei_PanGu)<br>- [Granite](https://en.wikipedia.org/wiki/IBM_Granite)<br>- [Hy](https://en.wikipedia.org/wiki/Tencent_Hy)<br>- [Inkling](https://en.wikipedia.org/wiki/Inkling_(large_language_model))<br>- [Jais](https://en.wikipedia.org/wiki/Jais_(language_model))<br>- [LaMDA](https://en.wikipedia.org/wiki/LaMDA)<br>- [Laguna S](https://en.wikipedia.org/wiki/Poolside_AI#Models)<br>- [Llama](https://en.wikipedia.org/wiki/Llama_(language_model))<br>- [MiMo](https://en.wikipedia.org/wiki/Xiaomi_MiMo)<br>- [Minerva](https://en.wikipedia.org/wiki/Minerva_(model))<br>- [Mistral and Mixtral](https://en.wikipedia.org/wiki/Mistral_AI#Models)<br>- [Muse Spark](https://en.wikipedia.org/wiki/Muse_Spark) <br> - [Muse Glimmer](https://en.wikipedia.org/wiki/Muse_Spark#Muse_Glimmer)<br>- [Nemotron](https://en.wikipedia.org/wiki/Nemotron)<br>- [PaLM](https://en.wikipedia.org/wiki/PaLM)<br>- [Phi](https://en.wikipedia.org/wiki/Phi_(language_model))<br>- [Qwen](https://en.wikipedia.org/wiki/Qwen)<br>- [Seq2seq](https://en.wikipedia.org/wiki/Seq2seq)<br>- [T5](https://en.wikipedia.org/wiki/T5_(language_model))<br>- [Vicuna](https://en.wikipedia.org/wiki/Vicuna_LLM)<br>- [Word2vec](https://en.wikipedia.org/wiki/Word2vec)<br>- [XLNet](https://en.wikipedia.org/wiki/XLNet) | | Chatbots and assistants | - [Amazon Q](https://en.wikipedia.org/wiki/Amazon_Q)<br>- [ChatGPT](https://en.wikipedia.org/wiki/ChatGPT)<br>- [Character.ai](https://en.wikipedia.org/wiki/Character.ai)<br>- [Claude](https://en.wikipedia.org/wiki/Claude_(language_model)) <br> - [Claude Code](https://en.wikipedia.org/wiki/Claude_(language_model)#Claude_Code)<br>- [DeepSeek](https://en.wikipedia.org/wiki/DeepSeek_(chatbot))<br>- [Doubao](https://en.wikipedia.org/wiki/Doubao)<br>- [Ernie Bot](https://en.wikipedia.org/wiki/Ernie_Bot)<br>- [Gemini](https://en.wikipedia.org/wiki/Google_Gemini)<br>- [Grok](https://en.wikipedia.org/wiki/Grok_(chatbot))<br>- [Kimi](https://en.wikipedia.org/wiki/Kimi_(AI)) <br> - [Kimi Code](https://en.wikipedia.org/wiki/Kimi_(AI))<br>- [Lumo](https://en.wikipedia.org/wiki/Lumo_(AI_assistant))<br>- [Microsoft Copilot](https://en.wikipedia.org/wiki/Microsoft_Copilot)<br>- [Meta AI](https://en.wikipedia.org/wiki/Meta_AI)<br>- [Perplexity AI](https://en.wikipedia.org/wiki/Perplexity_AI)<br>- [Sparrow](https://en.wikipedia.org/wiki/Sparrow_(chatbot))<br>- [You.com](https://en.wikipedia.org/wiki/You.com) | | Agents, coding,<br>and applications | - [AI agent](https://en.wikipedia.org/wiki/AI_agent)<br>- [Intelligent agent](https://en.wikipedia.org/wiki/Intelligent_agent)<br>- [AutoGPT](https://en.wikipedia.org/wiki/AutoGPT)<br>- [CrewAI](https://en.wikipedia.org/wiki/CrewAI)<br>- [LangChain](https://en.wikipedia.org/wiki/LangChain)<br>- [Manus](https://en.wikipedia.org/wiki/Manus_(AI_agent))<br>- [Model Context Protocol](https://en.wikipedia.org/wiki/Model_Context_Protocol)<br>- [Agent2Agent](https://en.wikipedia.org/wiki/Agent2Agent)<br>- [OpenAI Codex](https://en.wikipedia.org/wiki/OpenAI_Codex)<br>- [Vibe coding](https://en.wikipedia.org/wiki/Vibe_coding)<br>- [Code generation](https://en.wikipedia.org/wiki/AI-assisted_software_development)<br>- [Question answering](https://en.wikipedia.org/wiki/Question_answering)<br>- [Machine translation](https://en.wikipedia.org/wiki/Machine_translation)<br>- [Text summarization](https://en.wikipedia.org/wiki/Text_summarization)<br>- [Chatbot](https://en.wikipedia.org/wiki/Chatbot)<br>- [Virtual assistant](https://en.wikipedia.org/wiki/Virtual_assistant) | | Social, economic,<br>and governance | - [AI boom](https://en.wikipedia.org/wiki/AI_boom)<br>- [AI bubble](https://en.wikipedia.org/wiki/AI_bubble)<br>- [AI slop](https://en.wikipedia.org/wiki/AI_slop)<br>- [AI anthropomorphism](https://en.wikipedia.org/wiki/AI_anthropomorphism)<br>- [AI arms race](https://en.wikipedia.org/wiki/Artificial_intelligence_arms_race)<br>- [Chatbot psychosis](https://en.wikipedia.org/wiki/Chatbot_psychosis)<br>- [Competition](https://en.wikipedia.org/wiki/Competition_in_artificial_intelligence)<br>- [Copyright](https://en.wikipedia.org/wiki/Artificial_intelligence_and_copyright)<br>- [Deaths linked to chatbots](https://en.wikipedia.org/wiki/Deaths_linked_to_chatbots)<br>- [Dependency (GAID)](https://en.wikipedia.org/wiki/Generative_artificial_intelligence_dependency)<br>- [Environmental impact](https://en.wikipedia.org/wiki/Environmental_impact_of_artificial_intelligence)<br>- [Regulation](https://en.wikipedia.org/wiki/Regulation_of_artificial_intelligence)<br>- [Ethics](https://en.wikipedia.org/wiki/Ethics_of_artificial_intelligence)<br>- [Existential risk](https://en.wikipedia.org/wiki/Existential_risk_from_artificial_intelligence)<br>- [In education](https://en.wikipedia.org/wiki/Artificial_intelligence_in_education)<br>- [In healthcare](https://en.wikipedia.org/wiki/Artificial_intelligence_in_healthcare)<br>- [Workplace impact](https://en.wikipedia.org/wiki/Workplace_impact_of_artificial_intelligence) |

https://en.wikipedia.org/wiki/Artificial_intelligence
ENcloud.google.comfirecrawl

What is Artificial Intelligence (AI)? | Google Cloud

# Artificial intelligence (AI): a simple-to-understand guide Ever wonder how your phone can recognize your face, a streaming service knows exactly what movie you’ll love next, or how a car can drive itself? The answer is artificial intelligence (AI). Far from being science fiction, or limited to just the chatbots we know and enjoy, AI is part of our daily lives in countless ways. It's one of the most transformative technologies of our time, acting as the engine behind modern innovation. But what does "Artificial Intelligence" actually mean? Learn how to innovate with AI [Learn how to innovate with AI ](https://www.skills.google/course_templates/946/?utm_source=cgc-site&utm_medium=et&utm_campaign=referral-what-is-ai&utm_content=-&utm_term=-) Stay informed [Stay informed](https://cloud.google.com/newsletter) # Key takeaways ## The history of AI ### Solve your business challenges with Google Cloud #### The cutting edge: generative AI, LLMs, and the rise of AI agents - [**Generative AI**](https://cloud.google.com/use-cases/generative-ai): This is a type of AI that doesn't just analyze data; it creates new content. Think of it as an AI artist, writer, or even coder. Generative AI learns the patterns and structures within vast amounts of data (text, images, code, and more.) and then uses that knowledge to produce entirely new, original content based on prompts. Tools like DALL-E for images and ChatGPT for text are prime examples. - [**Large Language Models (LLMs)**](https://cloud.google.com/ai/llms): These are the engines powering many of today's most sophisticated AI applications, especially in text-based tasks. LLMs are large AI models trained on massive datasets of text and code. They excel at understanding, generating, and manipulating human language. Because they've processed so much information, they can answer complex questions, summarize documents, translate languages, write creative content, and even generate computer code. These models are becoming increasingly capable, even developing "emergent abilities" like solving math problems and writing code, though it's always wise for developers to review and validate AI-generated code. LLMs are also becoming multimodal, meaning they can understand and process not just text, but also images, audio, and video.

https://cloud.google.com/learn/what-is-artificial-intelligence
ENai.googlefirecrawl

Google AI - How we're making AI helpful for everyone

## Get started with Google AI ### Create and edit images with Nano Banana [Try in Gemini](https://gemini.google.com/?utm_source=ai.google&utm_medium=referral) ## For creativity ### Try ready-made AI templates in Google Photos to help you create images based on popular edits ![](https://lh3.googleusercontent.com/hKRdqCpHk-yzgOsZ7V2FRLU02TEsxlc6YJ1-ytp9CPwIeI4wjiGRYznaKm34-1xbpH2yJ03nqqWt4uvjzx3SBStZYXk1B3WmZ3uKMt1PZkGgSVlHv3k=w1440)![](https://lh3.googleusercontent.com/Rjk9pXRIT2hy54RaxySmn3Gdc12-i0-ubM90PDAQ2ZhxdiwNKKO8Vi4tWjK4qcZYQpBhGUy5MFuDhD0aispuXiTw3QCNVs4CInFdZZn4ff29oX8=w1440)

https://ai.google/
ENwww.britannica.comfirecrawl

Artificial intelligence (AI) | Definition, Examples, Types, Applications ...

- [Methods and goals in AI](https://www.britannica.com/technology/artificial-intelligence/Methods-and-goals-in-AI) - [Artificial general intelligence (AGI), applied AI, and cognitive simulation](https://www.britannica.com/technology/artificial-intelligence/Methods-and-goals-in-AI#ref219086) - [AI technology](https://www.britannica.com/technology/artificial-intelligence/Methods-and-goals-in-AI#ref380007) - [Machine learning](https://www.britannica.com/technology/artificial-intelligence/Methods-and-goals-in-AI#ref380008) - [Large language models and natural language processing (NLP)](https://www.britannica.com/technology/artificial-intelligence/Methods-and-goals-in-AI#ref380009) - [Autonomous vehicles](https://www.britannica.com/technology/artificial-intelligence/Methods-and-goals-in-AI#ref380010) - [Virtual assistants](https://www.britannica.com/technology/artificial-intelligence/Methods-and-goals-in-AI#ref380011) Related Topics: [history of artificial intelligence (AI)](https://www.britannica.com/science/history-of-artificial-intelligence)[Vibe coding](https://www.britannica.com/technology/vibe-coding)[frame](https://www.britannica.com/technology/frame-computing)[generative AI](https://www.britannica.com/technology/generative-AI)[General Problem Solver](https://www.britannica.com/science/General-Problem-Solver)_(Show more)_ [![Artificial intelligence](https://cdn.britannica.com/47/246247-050-F1021DE9/AI-text-to-image-photo-robot-with-computer.jpg?w=400&h=300&c=crop)](https://cdn.britannica.com/47/246247-050-F1021DE9/AI-text-to-image-photo-robot-with-computer.jpg) [Artificial intelligence](https://cdn.britannica.com/47/246247-050-F1021DE9/AI-text-to-image-photo-robot-with-computer.jpg) Image generated by the Stable Diffusion model from the prompt “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings,” which is the definition of artificial intelligence in the _Encyclopædia Britannica_ article on the subject. # artificial intelligence ## News • **artificial intelligence (AI)**, the ability of a digital [computer](https://www.britannica.com/technology/computer) or computer-controlled [robot](https://www.britannica.com/technology/robot-technology) to perform tasks commonly associated with intelligent beings. # Reasoning ## [Language](https://www.britannica.com/topic/language) - Methods and goals in AI - AI technology

https://www.britannica.com/technology/artificial-intelligence
ENwww.ibm.comfirecrawl

What Is Artificial Intelligence (AI)? - IBM

## Additional learning - [What is AI?](https://www.ibm.com/think/topics/artificial-intelligence#What+is+AI%3F%C2%A0) # What is artificial intelligence (AI)? Published 09 August 2024 Updated 02 October 2026 ![Illustration of a brain interconnected with several neural pathways](https://assets.ibm.com/is/image/ibm/adobestock_273431842:2x1?dpr=on%2C1&fit=fit%2C1&wid=320&hei=160) By [Cole Stryker](https://www.ibm.com/think/author/cole-stryker.html) and [Eda Kavlakoglu](https://www.ibm.com/think/author/eda-kavlakoglu.html) ## Deep learning ![AI vs Machine Learning](https://cfvod.kaltura.com/p/1773841/sp/177384100/thumbnail/entry_id/1_mpwgg1y4/height/0/width/1180) AI vs Machine Learning (5:49 min) ## Generative AI ![Outside view of a commercial building](https://www.ibm.com/adobe/dynamicmedia/deliver/dm-aid--3d4105bc-8250-45e4-9ac4-1bfcddb0e066/agents-hiu-dach-975x861.png?preferwebp=true&width=320) ### 2026 Buyer's Guide for IBM's AI agents and assistants Adopting AI tools like assistants and agents is a critical first step. [Get started](https://www.ibm.com/forms/mkt-53811) ## Benefits of AI ### Automation of repetitive tasks AI can automate routine, repetitive and often tedious tasks including digital tasks such as data collection, entering and preprocessing, and physical tasks such as warehouse stock-picking and manufacturing processes. This automation frees to work on higher value, more creative work. ## History of AI The idea of "a machine that thinks" dates back to ancient Greece. **1950** Alan Turing publishes [Computing Machinery and Intelligence](https://courses.cs.umbc.edu/471/papers/turing.pdf). In this paper, Turing famous for breaking the German ENIGMA code during WWII and often referred to as the "father of computer science" asks the following question: "Can machines think?" From there, he offers a test, now famously known as the "Turing Test," where a human interrogator would try to distinguish between a computer and human text response. While this test has undergone much scrutiny since it was published, it remains an important part of the history of AI, and an ongoing concept within philosophy as it uses ideas around linguistics. **1956** John McCarthy coins the term "artificial intelligence" at the first-ever AI conference at Dartmouth College. (McCarthy went on to invent the Lisp language.) Later that year, Allen Newell, J.C. Shaw and Herbert Simon create the Logic Theorist, the first-ever running AI computer program. **1967** Frank Rosenblatt builds the Mark 1 Perceptron, the first computer based on a neural network that "learned" through trial and error. Just a year later, Marvin Minsky and Seymour Papert publish a book titled Perceptrons, which becomes both the landmark work on neural networks and, at least for a while, an argument against future neural network research initiatives. **1980** Neural networks, which use a backpropagation algorithm to train itself, became widely used in AI applications. **1995** Stuart Russell and Peter Norvig publish [Artificial Intelligence: A Modern Approach](https://aima.cs.berkeley.edu/), which becomes one of the leading textbooks in the study of AI. In it, they delve into four potential goals or definitions of AI, which differentiates computer systems based on rationality and thinking versus acting. **1997** IBM's Deep Blue beats then world chess champion Garry Kasparov, in a chess match (and rematch). **2004** John McCarthy writes a paper, [What Is Artificial Intelligence?](https://www-formal.stanford.edu/jmc/whatisai.pdf), and proposes an often-cited definition of AI. By this time, the era of big data and cloud computing is underway, enabling organizations to manage ever-larger data estates, which will one day be used to train AI models. **2011** IBM Watson® beats champions Ken Jennings and Brad Rutter at Jeopardy! Also, around this time, data science begins to emerge as a popular discipline. **2015** Baidu's Minwa supercomputer uses a special deep neural network called a convolutional neural network to identify and categorize images with a higher rate of accuracy than the average human. **2016** DeepMind's AlphaGo program, powered by a deep neural network, beats Lee Sodol, the world champion Go player, in a five-game match. The victory is significant given the huge number of possible moves as the game progresses (over 14.5 trillion after just four moves). Later, Google purchased DeepMind for a reported USD 400 million. **2022** A rise in [large language models](https://www.ibm.com/think/topics/large-language-models) or LLMs, such as OpenAI’s ChatGPT, creates an enormous change in performance of AI and its potential to drive enterprise value. With these new generative AI practices, deep-learning models can be pretrained on large amounts of data. **2024** The latest [AI trends](https://www.ibm.com/think/insights/artificial-intelligence-trends) point to a continuing AI renaissance. Multimodal models that can take multiple types of data as input are providing richer, more robust experiences. These models bring together [computer vision](https://www.ibm.com/think/topics/computer-vision) image recognition and NLP speech recognition capabilities. Smaller models are also making strides in an age of diminishing returns with massive models with large parameter counts. Authors ![Cole](https://www.ibm.com/adobe/dynamicmedia/deliver/dm-aid--6ffe6fc8-d405-4a89-ad05-780d6960d862/cole-stryker-2x.jpg?preferwebp=true&width=128) [Cole Stryker](https://www.ibm.com/think/author/cole-stryker.html) Staff Editor, AI Models IBM Think ![ Eda](https://assets.ibm.com/is/image/ibm/eda-kavlakoglu?wid=128) [Eda Kavlakoglu](https://www.ibm.com/think/author/eda-kavlakoglu.html) Business Development + Partnerships IBM Research Link copied Next step in your AI journey See watsonx Orchestrate in action Start your free trial ## Resources Carousel Slide 1 of 3. Showing 4 items. [Cost of a Data Breach report 2026\ \ Attackers are weaponing AI\ \ \ AI-driven attacks increased 56%, led by deepfake impersonations and AI-enabled malware. Discover what’s driving the surge.](https://www.ibm.com/reports/data-breach) Get the report [Case study\ \ Designing an AI native airline at enterprise scale\ \ \ When margins are thin, every inefficiency matters. While legacy systems continue to constrain AI’s potential across aviation, Riyadh Air chose a different path. In partnership with IBM, Riyadh Air built the world’s first AI‑native airline, redefining a smarter, faster, more intuitive way to travel.](https://www.ibm.com/case-studies/riyadh-air) Read the story [AI models\ \ Explore IBM Granite\ \ \ IBM Granite® is a family of open, high performance and trusted AI models designed for business and optimized to scale your AI applications. Explore options across language, code, time series and guardrails.](https://www.ibm.com/granite) Meet Granite Related solutions Related solutions ## Related solutions Loading START END START END [![close icon](https://consent.trustarc.com/get?name=ibm_close_icon.svg)](https://www.ibm.com/think/topics/artificial-intelligence#) IBM web domains ibm.com, ibm.org, ibm-zcouncil.com, insights-on-business.com, jazz.net, mobilebusinessinsights.com, promontory.com, proveit.com, ptech.org, s81c.com, securityintelligence.com, skillsbuild.org, softlayer.com, storagecommunity.org, think-exchange.com, thoughtsoncloud.com, alphaevents.webcasts.com, ibm-cloud.github.io, ibmbigdatahub.com, bluemix.net, mybluemix.net, ibm.net, ibmcloud.com, galasa.dev, blueworkslive.com, swiss-quantum.ch, blueworkslive.com, cloudant.com, ibm.ie, ibm.fr, ibm.com.br, ibm.co, ibm.ca, community.watsonanalytics.com, datapower.com, skills.yourlearning.ibm.com, bluewolf.com, carbondesignsystem.com, openliberty.io ![close icon](https://consent.trustarc.com/get?name=ibm_close_icon.svg) By visiting our website, you agree to our processing of information as described in IBM’s [privacy statement](https://www.ibm.com/privacy). Accept AllMore options Something went wrong watsonx isn't available right now. Problems with a related system are preventing the data from being supplied. Retry The chat is loading. Return to conversation Return to conversation Return to conversation Restart conversationClose the chat window Options Contact IBM Chat History AI Chat history begin. Select this button to focus the first message then use the arrow keys to move between messages. Press escape to exit the message list. Press F6 to toggle between the message list and the input field. Chat history end. Select this button to focus the last message then use the arrow keys to move between messages. Press escape to exit the message list. Press F6 to toggle between the message list and the input field. 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https://www.ibm.com/think/topics/artificial-intelligence
ENwww.ibm.comfirecrawl

What Is Artificial Intelligence (AI)?

## Additional learning - [What is AI?](https://www.ibm.com/think/topics/artificial-intelligence#What+is+AI%3F%C2%A0) # What is artificial intelligence (AI)? Published 09 August 2024 Updated 02 October 2026 ![Illustration of a brain interconnected with several neural pathways](https://assets.ibm.com/is/image/ibm/adobestock_273431842:2x1?dpr=on%2C1&fit=fit%2C1&wid=320&hei=160) By [Cole Stryker](https://www.ibm.com/think/author/cole-stryker.html) and [Eda Kavlakoglu](https://www.ibm.com/think/author/eda-kavlakoglu.html) ## Deep learning ![AI vs Machine Learning](https://cfvod.kaltura.com/p/1773841/sp/177384100/thumbnail/entry_id/1_mpwgg1y4/height/0/width/1180) AI vs Machine Learning (5:49 min) ## Generative AI ![Outside view of a commercial building](https://www.ibm.com/adobe/dynamicmedia/deliver/dm-aid--3d4105bc-8250-45e4-9ac4-1bfcddb0e066/agents-hiu-dach-975x861.png?preferwebp=true&width=320) ### 2026 Buyer's Guide for IBM's AI agents and assistants Adopting AI tools like assistants and agents is a critical first step. [Get started](https://www.ibm.com/forms/mkt-53811) ## Benefits of AI ### Automation of repetitive tasks AI can automate routine, repetitive and often tedious tasks including digital tasks such as data collection, entering and preprocessing, and physical tasks such as warehouse stock-picking and manufacturing processes. This automation frees to work on higher value, more creative work. ## History of AI The idea of "a machine that thinks" dates back to ancient Greece. **1950** Alan Turing publishes [Computing Machinery and Intelligence](https://courses.cs.umbc.edu/471/papers/turing.pdf). In this paper, Turing famous for breaking the German ENIGMA code during WWII and often referred to as the "father of computer science" asks the following question: "Can machines think?" From there, he offers a test, now famously known as the "Turing Test," where a human interrogator would try to distinguish between a computer and human text response. While this test has undergone much scrutiny since it was published, it remains an important part of the history of AI, and an ongoing concept within philosophy as it uses ideas around linguistics. **1956** John McCarthy coins the term "artificial intelligence" at the first-ever AI conference at Dartmouth College. (McCarthy went on to invent the Lisp language.) Later that year, Allen Newell, J.C. Shaw and Herbert Simon create the Logic Theorist, the first-ever running AI computer program. **1967** Frank Rosenblatt builds the Mark 1 Perceptron, the first computer based on a neural network that "learned" through trial and error. Just a year later, Marvin Minsky and Seymour Papert publish a book titled Perceptrons, which becomes both the landmark work on neural networks and, at least for a while, an argument against future neural network research initiatives. **1980** Neural networks, which use a backpropagation algorithm to train itself, became widely used in AI applications. **1995** Stuart Russell and Peter Norvig publish [Artificial Intelligence: A Modern Approach](https://aima.cs.berkeley.edu/), which becomes one of the leading textbooks in the study of AI. In it, they delve into four potential goals or definitions of AI, which differentiates computer systems based on rationality and thinking versus acting. **1997** IBM's Deep Blue beats then world chess champion Garry Kasparov, in a chess match (and rematch). **2004** John McCarthy writes a paper, [What Is Artificial Intelligence?](https://www-formal.stanford.edu/jmc/whatisai.pdf), and proposes an often-cited definition of AI. By this time, the era of big data and cloud computing is underway, enabling organizations to manage ever-larger data estates, which will one day be used to train AI models. **2011** IBM Watson® beats champions Ken Jennings and Brad Rutter at Jeopardy! Also, around this time, data science begins to emerge as a popular discipline. **2015** Baidu's Minwa supercomputer uses a special deep neural network called a convolutional neural network to identify and categorize images with a higher rate of accuracy than the average human. **2016** DeepMind's AlphaGo program, powered by a deep neural network, beats Lee Sodol, the world champion Go player, in a five-game match. The victory is significant given the huge number of possible moves as the game progresses (over 14.5 trillion after just four moves). Later, Google purchased DeepMind for a reported USD 400 million. **2022** A rise in [large language models](https://www.ibm.com/think/topics/large-language-models) or LLMs, such as OpenAI’s ChatGPT, creates an enormous change in performance of AI and its potential to drive enterprise value. With these new generative AI practices, deep-learning models can be pretrained on large amounts of data. **2024** The latest [AI trends](https://www.ibm.com/think/insights/artificial-intelligence-trends) point to a continuing AI renaissance. Multimodal models that can take multiple types of data as input are providing richer, more robust experiences. These models bring together [computer vision](https://www.ibm.com/think/topics/computer-vision) image recognition and NLP speech recognition capabilities. Smaller models are also making strides in an age of diminishing returns with massive models with large parameter counts. Authors ![Cole](https://www.ibm.com/adobe/dynamicmedia/deliver/dm-aid--6ffe6fc8-d405-4a89-ad05-780d6960d862/cole-stryker-2x.jpg?preferwebp=true&width=128) [Cole Stryker](https://www.ibm.com/think/author/cole-stryker.html) Staff Editor, AI Models IBM Think ![ Eda](https://assets.ibm.com/is/image/ibm/eda-kavlakoglu?wid=128) [Eda Kavlakoglu](https://www.ibm.com/think/author/eda-kavlakoglu.html) Business Development + Partnerships IBM Research Link copied Next step in your AI journey See watsonx Orchestrate in action Start your free trial ## Resources Carousel Slide 1 of 3. Showing 4 items. [Cost of a Data Breach report 2026\ \ Attackers are weaponing AI\ \ \ AI-driven attacks increased 56%, led by deepfake impersonations and AI-enabled malware. Discover what’s driving the surge.](https://www.ibm.com/reports/data-breach) Get the report [Case study\ \ Designing an AI native airline at enterprise scale\ \ \ When margins are thin, every inefficiency matters. 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