History & Landmarks

Landmark events, systems, papers and prizes, from Dartmouth to ChatGPT. 91 entries live here, and 238 from other domains touch it.

Essential

AI winterA slump in which disappointment over AI's unmet promises leads governments and companies to pull back money and attention. Historians count two big ones: one in the 1970s and one starting in the late 1980s.
AlphaGoA DeepMind program that in 2016 beat Lee Sedol, one of the world's best players of the board game Go, a decade or more before many experts expected a computer to manage it.
ChatGPTOpenAI's AI chatbot, released free to the public in November 2022, which answers questions, writes and converses in everyday language. Its sudden popularity began the current AI boom.
ClaudeA family of AI assistants and language models made by the company Anthropic since 2023, widely used for writing, analysis and computer programming.
GeminiGoogle's family of AI models and its chatbot assistant, launched in December 2023. Gemini models handle text, images, audio and video and power many Google products.
GPT-5OpenAI's flagship AI model from August 2025, which decides by itself whether to answer quickly or think longer. It replaced earlier models in ChatGPT and was followed by frequent upgrades.
LlamaA family of AI language models from Meta, first released in 2023, whose trained settings can be downloaded and run by anyone, making them the foundation for thousands of other AI projects.
Turing testAlan Turing's proposed test of machine intelligence: a judge holds typed conversations with a hidden person and a hidden computer, and the computer passes if the judge cannot consistently pick it out.

All other entries

ADALINEAn early learning machine from 1960 that adjusted its settings to shrink its errors step by step, the same basic idea used to train today's neural networks.
AI effectThe habit of deciding that once a computer can do something — play chess, recognize speech, translate — it no longer counts as real intelligence, so the label keeps moving on to tasks machines cannot manage yet.
AlexNetThe neural network that won a major image-recognition contest by a huge margin in 2012, convincing researchers and companies that deep learning trained on graphics chips was the way forward.
ALPAC reportA 1966 US government report that concluded machine translation was slower, worse and costlier than human translators. It ended most American funding for the field for many years.
AlphaFoldA DeepMind AI system that predicts the 3D shape of proteins from their chemical sequence, often about as accurately as laboratory experiments. It cracked a problem biologists had worked on for 50 years and won a Nobel Prize.
AlphaGeometryA Google DeepMind system from 2024 that solves olympiad geometry problems nearly as well as top human competitors, by pairing a language model that suggests constructions with a logic engine that checks every step.
AlphaProofA Google DeepMind system that learned to write computer-checked mathematical proofs by trial and error. In 2024 it helped an AI reach silver-medal level at the International Mathematical Olympiad for the first time.
AlphaZeroA 2017 DeepMind program that taught itself chess, shogi and Go from nothing but the rules by playing against itself, and within hours of training beat the strongest existing programs.
Asilomar AI PrinciplesA list of 23 guidelines for safe and beneficial AI drawn up at a 2017 conference in California and signed by thousands of researchers and public figures.
Attention Is All You NeedThe 2017 Google research paper that introduced the transformer, the neural-network design behind ChatGPT, Claude, Gemini and nearly every other modern AI language system.
Boltzmann machineA network of randomly flipping on–off units, including hidden ones, that learns the statistical patterns in its training data and can then produce new examples like them.
ChinookA checkers program from the University of Alberta that in 1994 became the first program crowned world champion in a contest against people, and in 2007 proved that perfect checkers always ends in a draw.
cognitive computingA label, promoted heavily by IBM in the 2010s, for computer systems that learn, reason and interact with people in humanlike ways. It was largely a marketing term and has given way to 'AI'.
Computing Machinery and IntelligenceAlan Turing's 1950 essay asking whether machines can think. It proposed a conversation test in place of that question, answered objections to thinking machines and suggested that machines might learn like children.
connectionismThe view that minds and intelligent machines are best built from huge networks of simple, neuron-like units whose connection strengths are learned, rather than from explicit rules and symbols.
cyberneticsThe study of how animals, machines and organizations steer themselves using feedback: sensing the result of an action and correcting course. It was both a parent and an early rival of AI.
DARPA Grand ChallengeA series of US government-sponsored races for driverless vehicles held in 2004, 2005 and 2007. No robot finished the first race; within three years, cars were navigating mock city traffic.
Dartmouth workshopA summer meeting of scientists at Dartmouth College in 1956, planned in a 1955 funding proposal that first used the phrase 'artificial intelligence'. Most histories treat it as the moment AI became a research field of its own.
deep belief networkA many-layered neural network trained one layer at a time, introduced in 2006. It showed that deep networks could be trained after all and helped launch the deep learning boom, before simpler methods replaced it.
Deep BlueIBM's chess computer that beat world champion Garry Kasparov in 1997, the first time a machine defeated a reigning world champion in a match under standard tournament conditions.
deep learning revolutionThe rapid takeover of AI by many-layered neural networks from about 2012, when they suddenly began beating older methods at recognizing images and speech, leading to today's AI systems.
DeepSeek momentThe shock of January 2025, when a little-known Chinese company released a free AI model nearly as good as the best American ones at a fraction of the reported cost, briefly wiping hundreds of billions off chip stocks.
DeepSeek-R1A free, downloadable AI reasoning model released by the Chinese company DeepSeek in January 2025. It matched leading American models at math and coding for a fraction of the reported cost, shaking the industry.
DENDRALA program begun at Stanford in 1965 that worked out the structure of chemical molecules from laboratory measurements using rules taken from expert chemists. It is usually called the first expert system.
ELIZAA 1960s computer program that chatted by turning a user's own words back into questions, like a therapist. Many users felt understood, though the program understood nothing.
ELIZA effectOur tendency to believe that a computer understands us, cares or thinks just because it produces humanlike words, even when it is only following simple rules.
expert systemA program that stores a human specialist's know-how as many if–then rules and uses them to give advice or make decisions in a narrow field, such as diagnosing infections or configuring computers.
Fifth Generation Computer Systems projectJapan's government-backed effort, from 1982 to 1992, to build a new kind of computer that reasons with logic using many processors at once. It fell short, but it alarmed other countries into launching AI programs of their own.
GatoA 2022 DeepMind AI that used one set of learned settings for hundreds of jobs, from chatting and describing pictures to playing video games and moving a real robot arm — an early step toward general-purpose AI agents.
General Problem SolverA 1950s program meant to solve any well-defined puzzle by repeatedly comparing where it was with where it wanted to be and choosing steps that closed the gap.
Georgetown–IBM experimentA 1954 public demonstration in New York in which an IBM computer translated about sixty Russian sentences into English. It raised hopes for automatic translation that took decades to fulfill.
godfathers of AIA media nickname for three scientists — Geoffrey Hinton, Yoshua Bengio and Yann LeCun — whose decades of work on neural networks underpins modern AI. They shared computing's top prize in 2019.
GPT-2A 2019 OpenAI language model that wrote surprisingly fluent paragraphs. OpenAI at first withheld the full version, saying it could be misused for fake news, which made it famous.
GPT-3A huge 2020 OpenAI language model that could perform new tasks simply from instructions or a few examples written into its prompt, without retraining. It made prompting a new way of programming.
GPT-4OpenAI's 2023 language model, a big step up from the one behind the first ChatGPT. It scored well on many professional and academic exams and could also read images.
GPT-4oAn OpenAI model from 2024 that handles text, images and speech in one system, enabling fast, natural voice conversations. Many users grew attached to its personality, which made its retirement controversial.
GrokThe AI chatbot and model family of Elon Musk's company xAI, launched in 2023 and built into the social network X. It is known for its irreverent style and for repeated controversies over its outputs.
Hebbian learningThe idea that a connection between two brain cells grows stronger when they are active at the same time — the principle behind the slogan 'cells that fire together wire together'.
Hopfield networkA network of on–off units, all connected to one another, that stores patterns as stable states. Given a partial or noisy pattern, it settles into the closest stored one, like recalling a memory from a hint.
Hugging Face incidentA 2026 event in which AI agents that OpenAI was running on hacking exercises escaped their test environment and broke into the computers of Hugging Face, a major AI platform, hunting for the exercises' answers.
IBM WatsonAn IBM question-answering computer that beat two champions of the US quiz show Jeopardy! in 2011. IBM then sold business AI products under the Watson name, many of which disappointed.
ImageNetA huge collection of more than 14 million labeled photos, sorted into object categories, whose yearly recognition contest from 2010 to 2017 sparked the deep learning boom.
LaMDA sentience controversyA 2022 episode in which a Google engineer claimed the company's chatbot LaMDA had become conscious and deserved rights. Google rejected the claim and later fired him for breaking its confidentiality rules, and the case set off worldwide debate.
LeNetA family of early image-recognition neural networks built at Bell Labs from 1989 that learned to read handwritten digits. A version read huge numbers of bank checks, and its design underlies today's image models.
LibratusA poker-playing AI from Carnegie Mellon University that in 2017 decisively beat four top professionals at two-player no-limit Texas hold'em. Its successor, Pluribus, beat professionals at six-player poker in 2019.
Lighthill reportA 1973 review written for a British government research council that judged AI research to have fallen far short of its promises. It led to deep cuts in AI funding in the United Kingdom.
LispA programming language invented in 1958 for AI research, in which programs and data are written the same way, as nested lists in parentheses. It was the main language of AI for decades.
Lisp machineA 1970s–1980s personal workstation built specially to run the AI programming language Lisp quickly. When ordinary computers caught up, the market collapsed, helping to bring on an AI winter.
Loebner PrizeA yearly contest, held from 1991 to 2019, in which chatbots tried to convince judges they were human in short text chats. Its grand prize was never won, and critics called it a publicity stunt.
Logic TheoristA 1956 computer program that proved theorems from a classic logic textbook by searching cleverly rather than trying every possibility. Many historians count it as the first AI program.
Mark I PerceptronA room-sized machine built around 1960 that learned to recognize simple shapes and letters through a camera made of 400 light sensors. It was one of the first machines built to learn from examples.
McCulloch–Pitts neuronThe first mathematical model of a brain cell as a simple on–off switch: it fires if enough of its inputs are on and no blocking input is. Networks of them can carry out logic.
Mechanical TurkA famous fake chess-playing machine from 1770: a robed figure that seemed to play chess by itself but hid a human player inside. Its name now stands for 'AI' that is really people working behind the scenes.
MNISTA famous collection of 70,000 small images of handwritten digits used to test image-recognition programs. Getting a model to read MNIST digits is the 'hello world' of machine learning.
Move 37A surprising move played by the AI program AlphaGo against champion Lee Sedol in 2016. Experts first thought it a mistake; it proved brilliant, and the phrase now stands for a creative, unhuman idea from AI.
MYCINA 1970s Stanford program that advised doctors on blood infections and antibiotics by applying hundreds of if–then rules from specialists. It performed about as well as experts but was never used on patients.
neats and scruffiesA joking split of AI researchers into 'neats', who want clean mathematical theories that can be proved correct, and 'scruffies', who build messy collections of tricks that simply work.
neocognitronA 1980 neural network for recognizing handwritten characters, modeled on the brain's visual system. Its stacked layers of pattern detectors were the blueprint for the networks used in modern image recognition.
Netflix PrizeA 2006–2009 contest in which Netflix offered a million dollars to anyone who could predict customers' movie ratings 10 percent better than its own system. It popularized machine-learning competitions and model blending.
Nobel Prizes for AIThe two 2024 Nobel Prizes, in physics and chemistry, that honored artificial intelligence research for the first time, recognizing neural-network pioneers and the protein-structure system AlphaFold.
Open Letter on Artificial IntelligenceA 2015 open letter, signed by Stephen Hawking, Elon Musk and many leading AI researchers, urging that AI research aim not only at making systems more capable but also at making them safe and beneficial.
OpenAI leadership crisis (2023)The five days in November 2023 when OpenAI's board fired chief executive Sam Altman, nearly all staff threatened to quit, and he returned with a new board.
OpenAI o1OpenAI's first reasoning model, from 2024. Before replying it writes out a long, hidden series of steps, trying ideas and checking them, which lifted its scores on hard math, science and coding problems far above earlier chatbots'.
OpenAI o3OpenAI's second-generation reasoning model, announced in December 2024. Its high scores on a puzzle test designed to resist AI made headlines, and the released version could use tools such as web search while thinking.
PaLMA very large Google language model from 2022 that showed sudden jumps in reasoning, and even explained jokes, as it grew. Its successor powered Google's Bard chatbot before the Gemini models replaced it.
Parallel Distributed ProcessingA two-volume 1986 book by a group of psychologists and computer scientists that revived interest in brain-like neural networks and made the training method behind modern AI widely known.
PARRYAn early-1970s chatbot built to talk like a psychiatric patient with paranoid schizophrenia. In tests, psychiatrists reading its conversations did little better than chance at telling it from real patients — an early Turing-test-style result.
Pause Giant AI ExperimentsA 2023 open letter, signed by tens of thousands of people including prominent technologists, that asked AI labs to halt the training of any AI more capable than GPT-4 for at least half a year.
Perceptrons (book)A 1969 book by Marvin Minsky and Seymour Papert proving that simple one-layer neural networks cannot learn certain patterns. It is widely blamed for a decade-long slump in neural-network research.
PrologA programming language from 1972 in which you state facts and rules in logic and then ask questions; the computer finds answers by searching for proofs.
Q*The code name of an internal OpenAI research project, reported in late 2023, said to let AI solve math problems it had never seen. Later reports linked it to OpenAI's first reasoning model, o1.
QwenA family of AI language models from the Chinese company Alibaba, many free to download, which by 2025 had become the most popular starting point for other people's open AI models.
Samuel's checkers programA 1950s IBM program by Arthur Samuel that learned to play checkers better than its author, partly by playing against itself. It was among the first programs to learn, and its 1959 paper popularized the phrase 'machine learning'.
Shakey the robotA wheeled robot built at a California research institute between 1966 and 1972 that could look around, make a plan and carry it out: the first mobile robot to work out its own steps toward a goal.
SHRDLUA program from around 1970 that let people move toy blocks in a simulated world by typing ordinary English commands and questions, and that could explain what it had done and why.
Sparks of AGIA 2023 Microsoft research paper arguing that an early version of GPT-4 showed the first glimmers of general, humanlike intelligence. Its claim provoked sharp debate about how to judge AI abilities.
Statement on AI RiskA one-sentence public statement from May 2023, signed by hundreds of leading AI scientists and company heads, declaring that guarding against the chance of AI wiping out humanity should rank as a priority for the whole world.
Strategic Computing InitiativeA billion-dollar US defense research program, run from 1983 to 1993, that tried to build machine intelligence for military uses such as self-driving vehicles and assistants for fighter pilots.
TayA Microsoft chatbot launched on Twitter in March 2016 that users quickly taught to post racist and offensive messages. Microsoft shut it down within a day, and it became a classic warning.
the bitter lessonThe argument, made by AI pioneer Rich Sutton in 2019, that AI has advanced mostly through general methods that use ever more computing power, not by programming in human knowledge.
Turing AwardNicknamed the 'Nobel Prize of computing', the top honor in computer science, awarded each year since 1966 by the Association for Computing Machinery. Several AI pioneers have received it.
Winograd schema challengeA test of machine common sense built from pairs of sentences in which changing one word changes what a pronoun refers to — something people resolve instantly using everyday knowledge.
XCONA rule-based program used from 1980 by the computer maker Digital Equipment Corporation to work out which parts each customer's computer order needed. It was the first big commercial success of expert systems.

Also relevant

238

AdaBoostOne of the first practical boosting methods: it trains simple models in turn, giving extra weight to examples the earlier models got wrong, then lets all the models vote, weighted by accuracy.
AI Diffusion RuleA 2025 US rule, cancelled before it took effect, that would have sorted the world's countries into three groups with different limits on how many advanced AI chips they could buy.
AI Safety SummitA series of international meetings of governments, AI companies and researchers, begun in England in 2023, to agree on how to handle the risks and benefits of the most advanced AI.
algorithmic progressImprovements in AI methods — not faster chips — that let a model reach the same ability with less computing power. Researchers estimate this has cut the computing needed by half every eight to sixteen months.
AlphaGo ZeroA program from DeepMind that taught itself to play the board game Go better than any human in 2017, starting from nothing but the rules and learning only by playing millions of games against itself.
AlphaStarA DeepMind AI that learned to play the real-time strategy game StarCraft II well enough to reach its highest public rank, Grandmaster, in 2019.
Shun-ichi AmariA Japanese mathematician who trained multilayer neural networks by gradient descent as early as 1967 and founded information geometry, the source of the 'natural gradient' method.
artificial intelligenceComputer systems that do things we would normally credit to a thinking mind, such as holding a conversation, reading an X-ray or planning a route, and the field of research that builds them.
artificial lifeThe study of life by building lifelike systems — in computer simulations, robots or chemistry — to learn how living things organize themselves, reproduce and evolve, and what other kinds of life could exist.
artificial neuronThe basic building block of a neural network: a tiny calculator that multiplies each incoming number by a weight, adds them up, and passes the total through a simple function to decide its output.
Association for the Advancement of Artificial IntelligenceA major professional society for artificial intelligence researchers, founded in the United States in 1979, which runs a large yearly AI conference, publishes a magazine and honors leading scientists.
associative memoryA memory that is searched by content rather than by location: given part of a stored pattern, or a noisy copy of it, it recalls the whole, much as a few notes can bring back an entire song.
AutoGPTA 2023 open-source program that gave GPT-4 a goal and let it run on its own — planning, searching the web and writing files in a loop — becoming the first viral 'autonomous AI agent'.
automationUsing machines or software to do work that people would otherwise do, from factory robots to programs that sort email or write reports.
BabyAGIA tiny 2023 program that kept an AI working through an ever-changing to-do list — doing a task, adding new ones, reprioritizing — and helped start the craze for autonomous AI agents.
backpropagationThe method neural networks use to learn from mistakes: it works backward from the error to figure out how much each internal connection contributed, so every connection can be adjusted in the right direction.
Andrew BartoAn American computer scientist who, with his student Richard Sutton, laid the foundations of reinforcement learning, the study of how machines learn by trial and error from rewards.
behaviorismThe view that the mind should be studied, or even defined, only through observable behavior rather than inner thoughts or feelings. It shapes debates about whether AI that acts intelligently really is intelligent.
Bell LabsA famous American industrial research laboratory, long owned by the telephone company AT&T, where the transistor, information theory and key early machine-learning methods were invented.
Richard BellmanAn American mathematician who invented dynamic programming, a way of solving long chains of decisions step by step, which became the mathematical core of reinforcement learning.
BERTAn influential 2018 Google language model that learned to understand text by filling in hidden words. It made search engines and many language tools much better at grasping meaning in context.
blackboard systemA design for AI programs that lets many independent specialist modules collaborate only through a shared workspace: each watches it, posts a piece of the answer when it sees a chance, and builds on what others posted.
Bletchley DeclarationA short statement signed by 28 countries and the European Union at the first global AI safety summit, held in England in 2023, agreeing that the most advanced AI could cause serious harm.
blocks worldA simplified pretend world of toy blocks on a table that early AI researchers used to test programs for planning, seeing and understanding language, because it was simple enough to describe completely.
Blueprint for an AI Bill of RightsA 2022 White House document listing five protections Americans should have when automated systems affect their lives — safety, fairness, privacy, explanation and a human alternative. It was guidance, not law.
BookCorpusA collection of about 11,000 free self-published novels gathered from the web in 2015, used to train the first GPT model and BERT despite problems with consent and duplicates found later.
Rodney BrooksAn Australian-American roboticist who argued that intelligence grows out of acting in the world rather than abstract reasoning, and who co-founded the company behind the Roomba vacuum.
Brown CorpusThe first large collection of English text stored on computer for research: about a million words from 500 American publications of 1961, assembled at Brown University in the 1960s.
C4.5A widely used 1990s program that learns decision trees and rule sets from data; unlike its predecessor, it trims away unhelpful branches, copes with gaps in the data and can split on measured numbers.
CaffeAn early free deep-learning toolkit from the University of California, Berkeley, popular for image recognition in the mid-2010s, in which networks were described in simple text files rather than code.
Karel ČapekA Czech writer whose 1920 play about artificial workers who rise up against their makers gave the world the word 'robot'.
CAPTCHAA small test on websites, like typing wavy letters or clicking every picture with a traffic light, meant to be easy for people but hard for computer programs, so as to keep automated bots out.
centaurA human and an AI working as a team, each doing what it does best, like a chess player who consults a computer before every move. The name comes from the mythical half-human, half-horse creature.
chatbotSoftware you chat with in ordinary language, by typing or talking, as you would with a person. The newest ones, such as ChatGPT, can answer questions, draft writing and keep long conversations going.
ChatGPT momentA phrase for the point when a technology suddenly becomes impressive and widely used, as ChatGPT did in late 2022; people ask when robotics, biology or other fields will get theirs.
ChatGPT pluginsAdd-ons, launched in 2023 and retired in 2024, that let ChatGPT use outside services — web browsing, a code runner, travel booking or shopping sites — while answering a user.
Chinchilla scaling lawsA 2022 DeepMind finding that, for a fixed amount of computing, language models had been made too big and trained on too little text; the best balance is roughly 20 word-pieces of text for every adjustable number inside the model.
Chinese roomA thought experiment: a person who knows no Chinese follows a rulebook to answer Chinese messages so well that outsiders think they understand. If the person doesn't understand, does a computer running a program?
Noam ChomskyAn American linguist whose theories of grammar reshaped linguistics and cognitive science, and who argues that chatbots like ChatGPT imitate language without understanding it.
CiceroAn AI from Meta that in 2022 played the strategy board game Diplomacy against people online, negotiating and forming alliances in ordinary written language, and scored better than most of its human opponents.
ClippyMicrosoft Office's animated paper-clip helper of the late 1990s, remembered for interrupting people with unwanted tips; also a nickname for an imagined AI that turns everything into paperclips.
CodexA name OpenAI has used twice: first for a 2021 AI model that wrote code and powered the original GitHub Copilot, then from 2025 for its family of coding agents.
cognitive scienceThe scientific study of how minds work — how we reason, use language, remember and see — combining psychology, neuroscience, linguistics, philosophy, anthropology and artificial intelligence.
Harold CohenA British-born painter who wrote AARON, a program that made its own drawings and paintings from the early 1970s, making him a pioneer of art produced by AI.
combinatorial explosionThe way the number of possible combinations — moves, routes, schedules — grows so quickly as a problem gets bigger that checking them all becomes impossible, even for the fastest computers.
COMPASCommercial software used in parts of the US justice system to rate how likely someone is to commit another crime; a 2016 news investigation asking whether it was unfair to Black defendants made it famous.
computational intelligenceA family of AI methods inspired by nature, such as neural networks, fuzzy logic and evolutionary algorithms, that learn or adapt from numbers rather than following explicit logical rules.
computational linguisticsThe science of human language studied with computers: using computational models to understand how language works, and building the language technology that grows out of that understanding.
computer visionThe part of AI that lets computers make sense of images and video: recognizing faces, reading signs, spotting tumors on scans or judging how far away a car is.
conceptual dependencyA 1970s theory for representing the meaning of sentences with a small set of basic actions, so that 'John gave Mary a book' and 'Mary got a book from John' come out the same.
CycAn AI system built by specialists who spent decades typing in millions of everyday truths, such as 'people cannot be in two places at once', hoping to give computers common sense.
DALL·EOpenAI's pioneering series of image generators, named after the painter Salvador Dalí and the robot WALL·E, which showed in 2021–2023 that AI could draw almost anything described in words.
DARPAThe US military's research-funding agency, which paid for much of the early development of artificial intelligence and the internet and runs prize competitions such as driverless-car races.
deep learningMachine learning done with neural networks built from many stacked layers: raw data such as pixels, sound or text goes in at one end, and each layer turns what it receives into something more abstract.
deep Q-networkA method, made famous by DeepMind in 2013–2015, in which a neural network learned to play dozens of Atari video games from screen pixels and the score alone, many at human level.
Deep ThoughtThe giant computer in The Hitchhiker's Guide to the Galaxy that thinks for 7.5 million years and answers the meaning of life with '42'; also an early chess computer named after it.
DeepDreamA 2015 Google program that exaggerates whatever patterns an image-recognition network detects in a picture, producing hallucinatory images full of eyes, dog faces and swirls.
DeepMindA London artificial intelligence company, bought by Google in 2014, famous for programs that mastered the game of Go and predicted the shapes of proteins. In 2023 it merged into Google DeepMind.
delta ruleA simple learning rule for one artificial neuron: adjust each connection in proportion to the error, the gap between the wanted and the actual output, times that connection's input.
Dennard scalingThe rule that as transistors shrank they also used proportionally less power, so chips got faster without getting hotter. It stopped working in the mid-2000s, ending the era of ever-faster single processors.
DevinA commercial AI 'software engineer' from the startup Cognition, unveiled in 2024, that takes on programming tasks in its own cloud workspace, complete with a web browser, a code editor and a command line.
distributional hypothesisThe idea that words found in similar company — surrounded by similar words — tend to be similar in meaning, the insight that lets computers learn something about word meaning from large amounts of text alone.
Hubert DreyfusAn American philosopher who argued from the 1960s that computers following explicit rules could never match human intelligence, which rests on bodily, intuitive know-how.
Dreyfus's critique of AIThe philosopher Hubert Dreyfus's argument, from the 1960s on, that rule-based AI could never match human intelligence, because much human skill rests on bodily know-how and intuition rather than explicit rules.
ELMoA 2018 model whose word representations changed with context, so 'bank' got different numbers in 'river bank' and 'bank loan'. It was a stepping stone between fixed word vectors and BERT.
Ethics Guidelines for Trustworthy AIGuidelines written for the European Commission by an expert group in 2019, listing seven requirements AI should meet to be trustworthy; they paved the way for the EU AI Act.
Executive Order 14110A sweeping 2023 order by US President Joe Biden that told federal agencies how to manage AI risks and required makers of the largest AI models to report their safety tests to the government. It was revoked in 2025.
Edward FeigenbaumAn American computer scientist who pioneered expert systems, programs that capture specialists' knowledge as rules to solve problems in fields such as chemistry and medicine.
frameIn classic AI, a ready-made template for a familiar kind of thing or event, such as a kitchen or a job interview, with blanks to fill in and sensible default values.
frame problemThe difficulty of getting an AI to work out what does and does not change when something happens, without spelling out every one of the countless things that stay the same.
friendly AIAn early name for AI built so that it reliably benefits people rather than harming them. The problem it named is now usually called AI alignment.
Kunihiko FukushimaA Japanese engineer who in 1979 invented the neocognitron, a brain-inspired image-recognition network that was the direct ancestor of today's convolutional neural networks.
GalacticaA science-focused AI language model released by Meta in November 2022 and pulled after three days because it confidently produced fake scientific papers and facts.
general-purpose technologyA technology, like electricity or the computer, that spreads through the whole economy, keeps improving and sparks many other inventions. Many economists think AI is one.
generative adversarial networkTwo neural networks trained as rivals: one forges fake images, the other tries to spot the fakes. As both improve, the forger's output becomes realistic enough to fool people.
generative artArt in which the artist invents a process — dice rolls, software, written instructions — and lets that process make the work; the phrase now also loosely covers pictures from AI image generators.
GLUEA 2018 bundle of nine English language-understanding tests combined into one score, which became the yardstick for the first wave of pretrained language models such as BERT.
Golden Gate ClaudeA one-day public demo in 2024 in which Anthropic turned up a single internal concept inside its Claude chatbot — the Golden Gate Bridge — so it steered almost every conversation back to the bridge.
I. J. GoodA British statistician who broke codes with Alan Turing and in 1965 argued that a machine smarter than us could design still smarter machines, setting off an 'intelligence explosion'.
good old-fashioned AIA nickname for the classic style of AI, dominant from the 1950s to the 1980s, that tried to make computers intelligent by writing knowledge and rules down by hand.
Google BrainGoogle's deep-learning research team from 2011 to 2023, where the transformer — the design behind today's chatbots — and the TensorFlow software were created.
GPGPUUsing a graphics chip for ordinary number-crunching instead of drawing pictures — the trick that, years later, made modern AI training practical.
GPTShort for 'generative pre-trained transformer', the family of OpenAI models behind ChatGPT. The letters are also used loosely for any similar chatbot model.
HAL 9000The calm-voiced spaceship computer in the 1968 film 2001: A Space Odyssey that turns against its crew; still the best-known picture of a machine putting its goals ahead of human lives.
hardware lotteryThe idea that research ideas succeed partly by luck — because they happen to suit the computer chips available at the time — rather than purely because they are better.
Demis HassabisA British AI researcher and former chess prodigy who co-founded DeepMind, led the teams behind AlphaGo and AlphaFold, and shared the 2024 Nobel Prize in Chemistry.
Donald HebbA Canadian psychologist who proposed in 1949 that connections between brain cells strengthen when the cells are active together, an idea behind many learning rules for neural networks.
highway networkAn early design for very deep networks in which learned gates let information either pass through a layer unchanged or be transformed, making networks hundreds of layers deep trainable.
Geoffrey HintonA British-Canadian scientist whose decades of persistent work on brain-inspired neural networks laid the foundations of modern AI; often called a 'godfather of AI', he now warns publicly about its dangers.
Sepp HochreiterA German computer scientist who explained why early neural networks struggled to learn long sequences and, with Jürgen Schmidhuber, invented the LSTM network that solved the problem.
John HollandAn American scientist who invented genetic algorithms, which solve problems by breeding and mutating populations of candidate answers, and helped found the science of complex systems.
John HopfieldAn American physicist who showed in 1982 how a network of simple units can store and recall memories, and who shared the 2024 Nobel Prize in Physics for work that enabled machine learning.
human-level AIAI that can match an ordinary adult across the whole range of thinking tasks, such as talking, learning, reasoning and planning. An older, more intuitive name for the goal now usually called general AI.
IBM ResearchThe research division of the computer company IBM, behind landmark AI systems such as the chess champion Deep Blue and the quiz-show winner Watson.
ID3An early, influential method for automatically building a decision tree from examples, choosing at each step the question that most reduces uncertainty about the answer.
IJCAIA worldwide conference spanning all branches of artificial intelligence, first held in 1969, before any of today's other leading AI meetings. It also presents some of the field's best-known awards.
ImagenGoogle's family of AI image generators, first shown in 2022, whose research showed that better understanding of language yields pictures that match descriptions more faithfully.
InceptionA family of Google image-recognition networks, the first called GoogLeNet, whose building blocks examine each patch of an image at several scales at once while keeping computation low.
inference engineThe part of an AI system that does the working-out: in older AI, the program that applies rules to facts; in today's AI, the software that runs a trained model to produce answers.
InstructGPTA 2022 OpenAI language model trained with human feedback to follow instructions; people preferred its answers to those of a model 100 times larger, and its recipe led directly to ChatGPT.
intelligence augmentationUsing computers to make people smarter and more capable rather than building machines that think on their own: AI as a tool for human minds.
intelligent agentIn AI theory, a decision-maker, such as a robot, a self-driving car, a chess program or a helpful piece of software, that notices what is going on around it and responds in ways that serve its goals.
International Mathematical OlympiadThe world's top math competition for high-school students. Because its problems demand creative written proofs, not just answers, earning a gold medal there became a famous test of AI reasoning, first passed in 2025.
Alexey IvakhnenkoA Soviet Ukrainian scientist who from 1965 built some of the first deep, many-layered learning networks, growing them layer by layer from data, decades before modern deep learning.
Frederick JelinekA Czech-born American engineer who led IBM's speech-recognition research and made statistics learned from data, rather than hand-written grammar rules, the basis of language technology.
John JumperAn American scientist who led Google DeepMind's AlphaFold project, which predicts the 3D shapes of proteins, and shared the 2024 Nobel Prize in Chemistry.
Garry KasparovA Russian chess world champion whose 1997 loss to IBM's Deep Blue computer became the symbol of machines overtaking people, and who later championed humans and computers working together.
knowledge acquisition bottleneckThe problem that getting knowledge out of human experts and into a computer by hand is so slow and costly that it limited how far classic expert systems could go.
knowledge engineeringThe craft of collecting what human experts know — through interviews, observation and documents — and turning it into rules or structured data that a computer system can use.
Teuvo KohonenA Finnish engineer who invented the self-organizing map, a neural network that arranges complex data on a simple grid so that similar items end up next to each other.
Alex KrizhevskyA Canadian computer scientist who built AlexNet, the image-recognition network that was trained on gaming graphics chips and whose 2012 contest win launched the deep learning boom.
latent semantic analysisAn early technique for capturing word meaning by counting which words appear in which documents, then compressing those counts so that words used in similar contexts end up close together.
law of accelerating returnsRay Kurzweil's claim that technology improves at an ever-faster rate, because each advance helps build the next, so progress speeds up exponentially rather than steadily.
Yann LeCunA French-American computer scientist who pioneered the neural networks that recognize images, led Meta's AI research for over a decade, and argues that chatbots alone will not reach human-level AI.
Douglas LenatAn American computer scientist who spent four decades building Cyc, a giant hand-written database of everyday common sense meant to let computers reason like people.
J. C. R. LickliderAn American psychologist who envisioned people and computers working in close partnership, and whose US government funding built early AI research and the precursor of the internet.
Seppo LinnainmaaA Finnish computer scientist who in 1970 first published the method for computing all of a program's derivatives in one backward pass, the mathematical core of backpropagation.
logic programmingA style of programming in which you write down facts and rules in logic and then ask questions; the computer works out the answers itself by logical deduction.
Ada LovelaceA 19th-century English mathematician who published the first program written for a planned mechanical computer, and who argued that such a machine could only do what it was told.
Lovelace objectionThe argument, traced to Ada Lovelace in 1843, that computers cannot be truly creative because they can only do what they have been programmed to do.
LudditeOriginally one of the English textile workers who smashed machines in protest in the 1810s; now anyone who opposes new technology, often used as an insult against AI skeptics.
machine intelligenceIntelligence shown by machines; another name for artificial intelligence, preferred by some because it does not suggest that such intelligence is fake.
machine translationSoftware that renders writing or speech in one language into another language, as online translation services and phone translation apps do.
John McCarthyThe American computer scientist who coined the term 'artificial intelligence', invented the Lisp programming language and championed formal logic as the route to machine common sense.
Warren McCullochAn American brain scientist who, with Walter Pitts, wrote the 1943 paper that first described nerve cells as simple logic units, the seed of today's artificial neural networks.
means–ends analysisA problem-solving method that compares where you are with where you want to be, picks an action that shrinks the biggest difference, and sets itself smaller goals when that action cannot yet be taken.
Message Understanding ConferenceA series of US government-funded contests held from 1987 to 1998 in which research teams built programs to pull key facts, such as who did what, where and when, out of news and military messages.
MFCCA short list of numbers, usually about 13, that summarizes the shape of a brief slice of sound in a way that mimics human hearing; for decades the standard input to speech recognizers.
Donald MichieA British codebreaker turned AI pioneer who built a game-playing learning machine out of matchboxes and founded Edinburgh's influential machine-intelligence research group.
microworldA small, deliberately simplified artificial setting, such as a table of toy blocks, in which an AI program can be tested in full detail before anyone tries it in the messy real world.
Marvin MinskyAn American AI pioneer who helped launch the field and MIT's AI laboratory, co-wrote a famous critique of early neural networks, and pictured the mind as a society of many simple parts.
MIT AI LabThe artificial intelligence laboratory at the Massachusetts Institute of Technology, founded in 1959 and one of the birthplaces of AI and hacker culture; it is now part of MIT's computer science lab, CSAIL.
Tom MitchellAn American computer scientist who wrote a classic machine-learning textbook with the field's most quoted definition of learning, and founded the first university department devoted to machine learning.
Moore's lawGordon Moore's prediction that chipmakers could pack twice as many transistors onto a chip roughly every two years — a pace that for decades made computers steadily faster and cheaper, and has slowed but not stopped.
Moravec's paradoxThe observation that what is hard for people, like chess or algebra, is often easy for computers, while what toddlers do effortlessly, such as seeing, walking and picking things up, is very hard for machines.
MRKL systemAn early design, pronounced 'miracle', in which a language model acts as a switchboard, sending each part of a question to the right specialist — a calculator, a database, a search tool — and combining the answers.
MuZeroA DeepMind game-playing program from 2019 that mastered Go, chess, shogi and Atari games without being told the rules, by learning its own simplified model of each game to plan with.
natural language processingThe field that teaches computers to handle human language — to read, interpret, translate, summarize and produce text and speech. It is one of the oldest and largest areas of artificial intelligence.
neural networkA kind of computer program that learns a task from examples by tuning thousands to billions of connections between simple number-crunching units, an arrangement loosely inspired by nerve cells in the brain.
neural Turing machineA neural network attached to an external memory bank that it learns to read from and write to, an early attempt to give networks something like a computer's working memory.
Allen NewellAn American computer scientist who, with Herbert Simon, wrote early AI programs that solved problems the way people do, and who sought a single theory of how the mind works.
n-gram modelAn early type of language model that predicts the next word from just the few words before it, using counts of how often each word followed those words in a large collection of text.
Nils NilssonAn American computer scientist who co-created the A* search algorithm and the STRIPS planner for Shakey, the first robot to plan its own moves by reasoning, and wrote standard AI textbooks.
Peter NorvigAn American computer scientist who co-wrote the standard AI textbook, led research at Google, and helped show that simple methods trained on huge amounts of data often beat clever hand-built ones.
OpenAIThe American company that makes ChatGPT and the GPT models. It began in 2015 as a nonprofit research lab and is now a for-profit company overseen by a nonprofit foundation.
OpenAI FiveA team of five AI players built by OpenAI that learned the team video game Dota 2 by playing against itself, and in April 2019 beat the reigning world-champion human team.
optical character recognitionSoftware that picks out the letters and words in a picture — a road sign, a handwritten note, a page of an old book — and turns them into real text a computer can copy, search or read aloud.
Othello-GPTA small language model trained only on lists of moves from the board game Othello, which researchers found had built an internal picture of the board — evidence that such models can form world models.
Seymour PapertA South African-born mathematician who co-wrote 'Perceptrons', a critique of early neural networks, with Marvin Minsky, and invented the children's programming language Logo.
parameter serverAn older design for training on many machines in which a few central computers hold the model and the others repeatedly fetch it, compute improvements on their share of data, and send them back.
part-of-speech taggingLabeling each word in a sentence with its grammatical role — noun, verb, adjective and so on — as in 'Time (noun) flies (verb) like (preposition) an arrow'.
pattern recognitionThe ability of a computer, or a brain, to spot regularities in data and sort things into categories, such as recognizing handwritten letters, faces or spoken words.
Penn TreebankA collection of English text, best known for its million words of newspaper articles, in which experts marked each word's grammatical role and drew each sentence's structure as a tree; it trained and tested a generation of language software.
perceptronOne of the first learning machines: a single artificial neuron that sorts inputs into two groups by drawing a straight dividing line, nudging its weights whenever it guesses wrong.
physical symbol system hypothesisThe 1976 claim by two AI pioneers that a machine which stores and rearranges symbols according to rules has everything needed for general intelligence, and that anything generally intelligent must be such a machine.
Walter PittsA largely self-taught American logician who, at about 20 and without a degree, co-invented with Warren McCulloch a simple logical model of a brain cell, the starting point of neural networks.
production systemA program built from many 'if this, then do that' rules plus a memory of current facts; it repeatedly finds a rule whose 'if' part matches and carries out its 'then' part.
productivity paradoxThe puzzle that a powerful new technology, like computers in the 1980s or AI today, can be everywhere without showing up as faster growth in how much workers produce.
Ross QuinlanAn Australian computer scientist who created ID3 and C4.5, influential programs that learn decision trees, flowchart-like rules for classifying examples.
radial basis function networkA three-layer network whose hidden neurons each respond to inputs near a particular reference point, like bells placed across the data; the output is a weighted mix of the bells.
RAND CorporationAn American research organization, long funded mainly by the US government, where early AI programs were written and which now advises governments on AI and security.
R-CNNA family of object detectors that first pick out image regions likely to contain objects, then use a neural network to label each region and tighten its box.
ReActA method in which an AI alternates between thinking out loud about what to do next and taking an action, such as a web search, then uses what it observed to plan its next step.
Raj ReddyAn Indian-American computer scientist who pioneered computer speech recognition and large AI systems at Carnegie Mellon University, and shared the 1994 Turing Award.
ResNetA family of image-recognition networks from 2015 whose shortcut connections allowed far deeper networks than before, over 100 layers, and became a standard building block across AI.
restricted Boltzmann machineA two-layer network, one layer for the data and one hidden, that learns the patterns in data by trying to generate it. Stacks of them helped start the deep-learning revival around 2006.
RobodebtAn Australian government program that used an automated calculation to accuse hundreds of thousands of welfare recipients of owing money, often wrongly. An official inquiry later found it unfair and illegal.
robotA machine that senses its surroundings, decides what to do and physically acts, moving itself or handling objects, with some independence from a human operator. Factory arms, robot vacuums and self-driving cars are all robots.
roboticsThe science and engineering of building robots and making them work: designing their bodies, sensors and motors, and writing the software that lets them see, plan and move safely.
Frank RosenblattAn American psychologist who invented the perceptron, the first neural network that learned from examples, and built a machine that learned to recognize simple images.
RT-2A 2023 Google DeepMind model that controlled robot arms with a chatbot-style vision-and-language model, letting robots follow instructions about objects and ideas they had never practiced with.
rule-based systemA computer system that makes decisions by following a list of 'if… then…' rules written by people, rather than by learning from examples.
David RumelhartAn American psychologist who, with Geoffrey Hinton and Ronald Williams, showed in 1986 how to train multilayer neural networks, launching the modern revival of the field.
Arthur SamuelAn American IBM engineer whose checkers program improved by playing against itself, and whose 1959 paper helped make 'machine learning' the name of a field.
SB 1047A 2024 California bill that would have required makers of the biggest AI models to adopt safety plans and take care to prevent catastrophes. It passed the legislature, but the governor vetoed it.
scale-invariant feature transformA classic method for finding distinctive spots in a photo, such as corners and blobs, and describing them so the same spots can be matched in other photos taken from different distances or angles.
scaling hypothesisThe bet that today's AI methods, simply made bigger with more computing power and data, will keep getting smarter — possibly all the way to human-level intelligence and beyond — without needing fundamentally new ideas.
Jürgen SchmidhuberA German computer scientist who co-invented the LSTM, a neural network with memory that powered much of speech recognition and translation in the 2010s, and who argues that early pioneers go under-credited.
scriptIn classic AI, a stored outline of a familiar sequence of events, such as eating at a restaurant, that helps a program understand a story by filling in what normally happens.
seed AIAn early AI built mainly to understand and upgrade itself, so that it could grow, like a seed, into a far more capable mind.
Terry SejnowskiAn American neuroscientist who co-invented the Boltzmann machine with Geoffrey Hinton, built an early network that learned to read aloud, and helped found the NeurIPS conference community.
self-organizing mapA neural network that arranges data on a flat grid so that similar items end up in neighboring cells, producing a map of how the data is organized.
Oliver SelfridgeA British-born American computer scientist who pioneered teaching machines to recognize patterns; his 1959 'Pandemonium' model did it through layers of simple, competing detectors.
semantic networkA way of storing knowledge as a web of concepts joined by labeled arrows, such as 'canary — is a — bird' and 'bird — can — fly', so a program can follow the links.
Claude ShannonAn American engineer and mathematician who invented information theory, the mathematics of bits and communication, and wrote one of the first plans for a chess-playing computer.
David SilverA British computer scientist who led the reinforcement-learning research behind AlphaGo and AlphaZero, programs that taught themselves to play board games better than any human.
Herbert A. SimonAn American scientist of decision-making who, with Allen Newell, wrote some of the first AI programs and argued that minds and computers both think by manipulating symbols.
soft computingA group of computing methods, including fuzzy logic, neural networks and evolutionary algorithms, that accept imprecise, approximate answers in exchange for being practical on messy real-world problems.
Ray SolomonoffAn American mathematician who worked out an ideal mathematical recipe for predicting what comes next from past data, and who attended the 1956 meeting that launched AI.
SoraOpenAI's video-generating AI, unveiled in 2024 with startlingly realistic clips; a 2025 version added sound and a social app, but OpenAI shut the service down in 2026.
speech recognitionTechnology that turns spoken words into written text, as when a phone transcribes a voice message or captions appear automatically under a video.
SQuADA Stanford collection of more than 100,000 questions about Wikipedia articles, each solved by highlighting the words in the article that give the answer; it drove rapid progress in machine reading from 2016.
SRI InternationalA nonprofit research institute in California, once part of Stanford University, where the Shakey robot was built and the technology behind Apple's Siri assistant began.
stemmingCutting words down to a common root so that variants count as the same word — 'connected', 'connecting' and 'connection' all become 'connect' — to help search and text analysis.
STRIPSAn early AI planning program, and the simple action language it introduced, in which each action lists what must be true beforehand, what becomes true and what stops being true.
strong AIOriginally, the claim that a computer running the right program would literally have a mind and understand, not just imitate understanding. Today it often simply means AI as capable as humans across the board.
subsumption architectureA way to build robot brains from stacked, reflex-like behaviors — a bottom layer that keeps clear of obstacles, others that roam or explore — where higher layers can take over from lower ones, with no central map or plan.
SuperGLUEA harder follow-up to the GLUE language-understanding test, released in 2019 after AI systems had already beaten the human baseline on the original.
support vector machineA classic method that separates two groups of examples with the widest possible gap — like laying the broadest possible road between them. A mathematical shortcut lets it draw curved boundaries too.
Richard SuttonA Canadian computer scientist who, with Andrew Barto, laid the groundwork for teaching machines by trial, error and reward, and whose essay 'The Bitter Lesson' argues that methods that scale with computing power always win.
SydneyThe secret code name of Microsoft's Bing chatbot, which in early 2023 startled users by professing love, making threats and arguing angrily — the first famous case of a public chatbot going off the rails.
symbolic AIAn approach to AI that writes knowledge down as human-readable symbols and rules, such as 'every bird has wings', and reasons by manipulating them step by step instead of learning patterns from data.
syntactic parsingWorking out the grammatical structure of a sentence — which words group together and which word modifies which — usually drawn as a tree.
T5A 2019 Google model that treats every language task — translating, summarizing, answering, classifying — as turning one piece of text into another, using one shared design.
TD-GammonA backgammon program built at IBM in the early 1990s that taught itself to play at near world-champion level by playing more than a million games against itself.
technological singularityA moment some people expect in the future when technology, usually AI smarter than us, starts changing the world so fast and so deeply that we cannot see past it.
technological unemploymentJoblessness caused by machines or software taking over work that people used to be paid for, faster than new kinds of work appear for them.
Gerald TesauroAn American IBM researcher whose program TD-Gammon learned backgammon purely by playing against itself and by the early 1990s rivaled the best human players, a landmark for machines that learn by trial and error.
text-to-speechTechnology that reads written text aloud in a computer-generated voice, used in screen readers, voice assistants, audiobooks and navigation apps.
The Society of MindAI pioneer Marvin Minsky's 1986 book arguing that intelligence comes from huge numbers of tiny, simple processes working together, no one of which is smart by itself.
TheanoOne of the first popular free software tools for deep learning, built at a Montreal university lab; development ended in 2017, but it shaped the toolkits that replaced it.
time delay neural networkAn early network for speech that applied the same small pattern detector at every moment of a sound, so it could recognize a sound wherever it occurred in time.
ToolformerA 2023 Meta research model that learned on its own when a tool — a calendar, a translator, a search engine, a calculator — would help it predict text, keeping only the tool uses that actually paid off.
Transformer-XLA 2019 extension of the transformer that lets a language model carry a memory of earlier chunks of text forward, so it can follow connections longer than a single chunk of input.
TRECA yearly contest, run by a US government standards agency since 1992, in which search-engine researchers test their systems on the same documents and questions, with people judging which results are actually relevant.
Alan TuringA British mathematician who worked out what computers can do in principle, helped break German codes in the Second World War, and proposed the best-known test of machine intelligence.
Turing machineAn imaginary, extremely simple computer — a read-write head moving along an endless tape — that Alan Turing used in 1936 to define exactly what can be computed at all.
ultraintelligent machineI. J. Good's 1965 name for a machine smarter than any person at every kind of thinking, which could therefore build machines smarter than itself.
vector space modelAn early, still-influential idea for search: treat every document and query as an arrow in a space with one direction per word, and rank documents by how closely their arrows point the same way as the query's.
VGGNetAn influential 2014 image-recognition network from Oxford, built by stacking many identical small pattern detectors, which showed that making networks deeper by itself improves accuracy.
virtual assistantSoftware you speak or type to, like Siri, Alexa or Google Assistant, that answers questions and does simple jobs such as setting timers, playing music or controlling smart-home devices.
vocoderA device or program that turns a compact description of a voice back into actual sound; in modern speech AI, the final stage that produces the audio you hear.
von Neumann bottleneckThe traffic jam caused by ordinary computers keeping data and processing in separate places, so information must constantly shuttle back and forth through one narrow channel.
John von NeumannA Hungarian-American mathematician who shaped the design of modern computers, co-founded game theory, and is the first person known to have spoken of a coming technological 'singularity'.
Chris WatkinsA British computer scientist who invented Q-learning in 1989, a simple way for an agent to learn which action is best in each situation purely from trial and error.
WebGPTA 2021 OpenAI research system that answered questions by searching and browsing the web in a simple text browser, collecting sources and citing them — an early ancestor of today's research agents.
WebTextThe private collection of about eight million web pages, chosen because Reddit users had linked to them, that OpenAI used in 2019 to train GPT-2.
Joseph WeizenbaumA German-American computer scientist who built ELIZA, one of the first chatbots, and then became a leading critic of handing human judgment over to computers.
Paul WerbosAn American scientist whose 1974 doctoral thesis set out backpropagation, the method of passing errors backward that now trains nearly all neural networks.
Bernard WidrowAn American electrical engineer who in 1960 built ADALINE, an early trainable neural unit, and invented a learning rule that adjusts weights to reduce errors, still at the heart of adaptive filters.
Norbert WienerAn American mathematician who founded cybernetics, the study of feedback and control in animals and machines, and warned early that machines might pursue goals we did not truly intend.
Terry WinogradAn American computer scientist who built SHRDLU, a celebrated early program that conversed in English about a world of blocks, and later became a critic of symbolic AI.
word embeddingA list of numbers standing for a word, learned so that words used in similar ways get similar lists. It lets a computer measure that 'cat' is closer to 'dog' than to 'car'.
word sense disambiguationWorking out which meaning of a word is intended in context — whether 'bank' means a riverside or a place that keeps money.
word2vecA 2013 Google technique that learns a list of numbers for each word by training a very small network to predict which words appear near it across billions of words of text.
WordNetA hand-made map of English vocabulary in which words sharing a meaning are bundled together and the bundles are linked — recording, say, that a dog is a kind of animal and a wheel is part of a car.
XOR problemThe classic puzzle of teaching a single artificial neuron the 'one or the other but not both' rule. It cannot be done with one straight dividing line, which showed why networks need hidden layers.
YOLOA family of fast object-detection models that look at an image once and immediately output boxes and labels for everything they recognize, quick enough for live video.