Science

Mathematician Norbert Wiener is widely considered the founder of cybernetics, the study of regulatory systems. His 1948 book Cybernetics treated feedback formally and framed control and communication as one problem for animals and machines.

American mathematician and electrical engineer whose 1948 paper "A Mathematical Theory of Communication" gave communication engineering a mathematical foundation.

C. E. Shannon's 1948 paper set out a mathematical framework for communication, defining information in bits, channel capacity, and entropy, and treating messages statistically while setting aside semantic meaning.

A framework that treats information as a measurable quantity to be encoded and transmitted, founded in Shannon's 1948 paper; it gave the field the bit, entropy and channel capacity.

Marc Raibert (born 1949) is a robotics researcher who built the first self-balancing hopping robots, founded Boston Dynamics, and is now executive director of the Boston Dynamics AI Institute.

The Turing test is Alan Turing's 1950 proposal for replacing the question "Can machines think?" with a game: a machine passes if an interrogator cannot tell its written answers apart from a human's.

A. L. Samuel's 1959 paper reporting experiments in which a checkers program, given only the rules of the game and an imperfect set of parameters, learned in 8 to 10 hours of playing time to beat the person who wrote it.

DENDRAL was a Stanford artificial intelligence project begun in 1964 that identified unknown organic molecules from mass spectra using chemical knowledge. It is widely described as the first expert system and the ancestor of later systems such as MYCIN and PROSPECTOR.

A 1969 book by Marvin Minsky and Seymour Papert that proved mathematical limits on what single-layer perceptrons can compute — notably that they cannot compute parity or connectedness — and has long been credited with steering research away from neural networks.

AI winter is a period of sharply reduced funding and interest in artificial intelligence research. The field's hype cycles have produced two such downturns, usually dated to about 1974–1980 and 1987–2000.

A recurrent neural network introduced by John Hopfield in 1982 that stores patterns as minima of an energy function and recalls them from partial or distorted input, bringing statistical mechanics into the study of neural networks.

A 1982 paper by John J. Hopfield arguing that useful computation can emerge as a collective property of many simple, equivalent units, and describing a model whose collective behaviour gives content-addressable memory, generalisation and error correction.

A 1982 paper by John J. Hopfield showing that large networks of simple neuron-like units can collectively store and recall memories. It became known as the Hopfield network, and the work was recognised by the 2024 Nobel Prize in Physics.

A two-volume MIT Press work by Rumelhart, McClelland and the PDP Research Group, published in 1986, that set out the parallel distributed processing framework — networks of simple units with hidden layers and sigmoid activation — and became a landmark of connectionism.

In a 1986 Nature paper, Rumelhart, Hinton and Williams showed that backpropagation lets hidden units in a multilayer network learn useful internal features of a task. The method is standard in most neural networks today.

Imitation learning trains an agent by supervised learning on expert demonstrations rather than by trial and error. Its simplest form is behaviour cloning, and its best-known weakness is distribution shift.

Richard Sutton's 1988 paper introduced temporal-difference learning, a family of incremental prediction methods that assign credit from changes between successive predictions and are shown to be more economical and accurate than conventional supervised approaches on most prediction problems.

Rodney Brooks's 1990 paper argued for building artificial intelligence from the ground up, with ongoing physical interaction with the environment as the main constraint on design, rather than through the abstract manipulation of symbols that had dominated the field for roughly thirty years.

Published in 1992, this paper by Boser, Guyon and Vapnik presents a training algorithm that maximizes the margin between training patterns and the decision boundary, with experiments on optical character recognition.[^1]

A small NASA rover that landed on Mars on July 4, 1997 with the Mars Pathfinder lander and became the first wheeled vehicle operated on another planet.

A 1998 conference paper by Sergey Brin and Lawrence Page describing PageRank, an algorithm that ranks web pages by the number and quality of links pointing to them, and the search engine built on that algorithm.

A generative probabilistic model that represents each document as a finite mixture over topics, fitted with variational approximate inference and EM, and evaluated on document modelling, text classification and collaborative filtering.

Stanley is the Stanford University robotic vehicle that won DARPA's 2005 Grand Challenge, completing a 132-mile desert course autonomously in 6 hours 53 minutes and claiming the $2 million prize.

A 2010 paper by Xavier Glorot and Yoshua Bengio on why deep feedforward networks are hard to train: sigmoid saturation under random initialization and layer Jacobians whose singular values sit far from 1, plus a new initialization scheme that converges substantially faster.

A London-headquartered AI research organisation formed in 2023 by merging DeepMind with Google's Brain team, known for AlphaGo, AlphaFold and the Gemini model family.

A CVPR 2011 Best Paper that recovers 3D body joint positions from a single depth image without temporal information, by classifying pixels into body parts, and runs at 200 frames per second on consumer hardware.

A 2011 paper by Glorot, Bordes and Bengio reporting that deep networks built from rectifying neurons match or beat tanh networks and reach their best performance without unsupervised pre-training on large labelled supervised tasks.

A free online version of Stanford's artificial intelligence course, taught by Sebastian Thrun and Peter Norvig, which started on October 10, 2011 and drew 160,000 students from over 190 countries.

Adam is a stochastic optimisation algorithm from a 2014 paper by Diederik P. Kingma and Jimmy Ba that sets per-parameter step sizes from running estimates of the gradient's first and second moments, needing little memory and little hyper-parameter tuning.

A 2015 Nature review by Yann LeCun, Yoshua Bengio and Geoffrey Hinton explaining deep learning: models of multiple processing layers that learn layered representations of data, and the results this produced in speech, vision and other fields.

AlphaGo Zero learned Go only by playing against itself, starting from random play, and beat the earlier champion-defeating AlphaGo 100 games to 0 after three days of training. The Nature paper appeared in October 2017.

Isomorphic Labs is an AI drug discovery company launched out of DeepMind and dated to 2021, building the IsoDDE platform and working with Novartis, Eli Lilly and Johnson & Johnson.

RoseTTAFold is a three-track neural network for protein structure prediction, published by the Baker lab in 2021; its accuracy approached AlphaFold2's at CASP14, it models protein–protein complexes from sequence alone, and it is distributed as open code with a public web server.

The Nature paper described AlphaFold's methods, system design, and evaluation for protein-structure prediction.

AlphaFold 3, published in Nature in May 2024, extends structure prediction to biomolecular interactions, reporting greater accuracy than docking tools for protein–ligand binding and than AlphaFold-Multimer v.2.3 for antibody–antigen complexes.

AlphaFold 3 is a structure-prediction model from Google DeepMind and Isomorphic Labs, announced on 8 May 2024. It predicts the structures and interactions of proteins, DNA, RNA, ligands and chemical modifications, extending structure prediction beyond proteins alone.[^1]

ESM3 is a protein generative model announced by EvolutionaryScale in June 2024 that reasons over sequence, structure and function together, and generated a fluorescent protein estimated to sit over 500 million years of evolution away from known ones.

OpenAI o1 is the first reasoning model series from OpenAI, introduced in September 2024. It thinks through a long internal chain of thought before answering, and it was the base for later reasoning models such as o3.

OpenAI's second-generation reasoning model, announced in December 2024 and released in April 2025, which posted large gains over o1 on science, software-engineering and competitive-programming benchmarks before being succeeded by GPT-5.

Claude Fable 5 is Anthropic's Mythos-class model for general use, released on 9 June 2026. Its sibling Claude Mythos 5 is the same model with some safeguards lifted for vetted users.

Reinforcement learning is the branch of machine learning and optimal control in which an agent learns, by trial and error, which actions in a dynamic environment maximise a reward signal.

Andrew Chi-Chih Yao is a computer scientist born in Shanghai who won the 2000 ACM A.M. Turing Award for fundamental contributions to the theory of computation, and later founded Tsinghua University's Yao Class and IIIS.

ImageNet is a large, hierarchical image database built on the WordNet conceptual model and released at Princeton University in 2009. It holds more than 14 million images in 21,841 categories, with bounding-box annotations, and a 1,000-class subset used by the ILSVRC challenge.

A US public university founded in 1861, with campuses in Seattle, Bothell and Tacoma and a medical centre serving its state and region; it says it receives more federal research funding than any other US public university.

Berlin-born American computer scientist who wrote ELIZA, an early program that held a written conversation with a user, and later published an influential critique of artificial intelligence.

American physicist born in 1933 who invented the Hopfield network in 1982, a model that stores and recalls patterns using ideas from spin physics, and who received half of the 2024 Nobel Prize in Physics.

David Rumelhart (1942–2011) was an American cognitive psychologist. His 1986 work with colleagues helped bring back-propagation and neural-network models to a wide audience.

Rodney Brooks (born 1954) is an Australian-born roboticist who promoted behaviour-based robotics and the subsumption architecture, directed MIT's AI Laboratory and CSAIL, and co-founded iRobot, Rethink Robotics and Robust.AI.

DARPA is the research agency of the United States Department of Defense, created in 1958 in response to Sputnik. It states its mission as creating and preventing technological surprise, and its Grand Challenges brought autonomous vehicle work to a wider community.

Protein scientist at the University of Washington in Seattle, known for computational protein design: he designed a protein unlike any in nature in 2003 and received one half of the 2024 Nobel Prize in Chemistry.

The Association for Computational Linguistics (ACL) is the main scientific and professional society for natural language processing. Founded in 1962, it runs one of the field's two leading conferences and publishes the journal Computational Linguistics.

A January 1966 paper by Joseph Weizenbaum presenting ELIZA, a program on MIT's MAC time-sharing system that used keyword-triggered decomposition and reassembly rules to enable certain natural-language conversations between people and computers.

IJCAI is a non-profit corporation founded in California in 1969 for scientific and educational purposes; it runs the IJCAI conference series (biennial in odd years from 1969, annual since 2015) and publishes a journal and proceedings.

Demis Hassabis is a British AI researcher and entrepreneur who co-founded DeepMind and was the last author of the 2016 AlphaGo paper. He shared the 2024 Nobel Prize in Chemistry for work on predicting protein structures.

ICML is the annual International Conference on Machine Learning, held every year since 1980 and organized by the International Machine Learning Society. It is the oldest of the field's main conferences and one of its three most influential venues.

A Boltzmann machine is a neural network whose configurations are scored by a global energy and trained by a stochastic learning algorithm. Introduced by Geoffrey Hinton and Terry Sejnowski, it brought energy-based models into cognitive science and machine learning.

A 1985 Cognitive Science paper by Ackley, Hinton and Sejnowski that presents a general learning rule for connectionist networks and reports simple examples of efficient internal representations.

American scientist (born 1985) who worked on AlphaFold at Google DeepMind and shared half of the 2024 Nobel Prize in Chemistry with Demis Hassabis for protein structure prediction.

NETtalk is an artificial neural network built by Terrence Sejnowski and Charles Rosenberg that learns to convert written English into phonemes and audible speech, showing that a network trained on examples can generalize to unseen words.

NeurIPS is an annual December conference on machine learning and computational neuroscience, founded in 1987 and counted among the most influential meetings in AI research.

PC Therapist was Joseph Weintraub's conversational program; a modified version won the first annual Loebner Prize Competition in 1991, fooling five of 10 judges into thinking it was human.

Gerald Tesauro's 1992 paper tested whether temporal difference learning could master a complex real-world task, using self-play backgammon as the case study.

Chelsea Finn is a computer scientist and assistant professor at Stanford University whose research spans meta-learning, deep reinforcement learning and robot learning; she is a co-founder of Physical Intelligence.

C4.5 is a machine learning system that builds decision trees or if-then rules from cases with known classes. J. Ross Quinlan's 1993 book documents its C/UNIX implementation, source code, and use.

NASA's Mars Pathfinder lander touched down on July 4, 1997, deployed the small Sojourner rover, used an airbag landing system for the first time, and returned thousands of images of the Martian surface.

Brin and Page's PageRank technical report treats hyperlinks as citations to rank web pages and was used to build Google's search engine; it is one of the heavily cited papers on their early work.

Topic models represent documents as mixtures of latent topics, giving a compact statistical description of text collections. The 2003 Latent Dirichlet Allocation paper formalized this idea as a hierarchical Bayesian model.

An independent, non-profit research institute in Cambridge, Massachusetts, founded in 2004 with support from Eli and Edythe Broad, working to understand the roots of disease and turn biological insights into impact for patients.

Connectionist temporal classification (CTC) is a method for training recurrent neural networks to label unsegmented sequences, such as speech or handwriting, without frame-by-frame alignment. Introduced in 2006, it let CTC-trained LSTMs win the first international contests for recurrent networks.

Deep neural network acoustic modeling uses multilayer networks to map speech to units such as phones. A 2010 NIPS paper used Deep Belief Nets and a mean-covariance RBM to extract speech features, reaching 20.5% phone error on TIMIT.

Xavier (Glorot) initialization is a weight-initialization scheme from Glorot and Bengio's 2010 paper that sets each layer's starting weight scale so signals stay stable across layers, giving substantially faster convergence in deep feedforward networks.

A 2010 NIPS paper by Dahl, Ranzato, Mohamed and Hinton applies Deep Belief Nets and a mean-covariance RBM to acoustic modeling, reaching 20.5% phone error on speaker-independent TIMIT phone recognition.

A 2011 Journal of Machine Learning Research paper by Collobert, Weston, Bottou, Karlen, Kavukcuoglu and Kuksa, presenting one neural network architecture and learning algorithm for part-of-speech tagging, chunking, named entity recognition and semantic role labeling, trained on mostly unlabeled data with little task-specific engineering.

Robonaut 2 is a humanoid robot built jointly by NASA and General Motors that flew to the International Space Station in 2011 to show how dexterous robots behave in orbit, and later gained legs to move around inside the station.

ICLR is an annual machine learning conference held in late April or early May, founded in 2012 by Yann LeCun and Yoshua Bengio, and known for its open peer review process.

A research institute at the University of Washington, founded in 2012 and led by David Baker, that designs new proteins for medicine and technology; its labs produced RoseTTAFold and, it says, the first computationally designed vaccine.

Curiosity is NASA's Mars rover, which landed in Gale Crater in August 2012 carrying a science payload far larger than earlier rovers, and which used a sky-crane descent to set down on its wheels.

A 2012 article in IEEE Signal Processing Magazine in which four research groups argued that deep neural networks, replacing Gaussian mixture models, gave better acoustic models for speech recognition.

A 2013 paper by Mikolov, Sutskever, Chen, Corrado and Dean presents continuous Skip-gram as an efficient method for learning distributed word and phrase representations, with extensions that improve vector quality and training speed.

Recursion is a drug discovery company that pairs automated laboratory experiments with computation; its Recursion OS platform spans target identification to clinical trial enrolment. It listed on Nasdaq in 2021 and combined with Exscientia in 2024.

Insilico Medicine is a drug discovery company founded in the United States in 2014 that pairs an AI software platform, Pharma.AI, with its own pipeline of drug programmes and automated laboratory work.

Nonprofit AI research institute founded by Paul Allen in 2014 and based in Seattle, known for Semantic Scholar and for the openly released OLMo family of language models, whose training data, code and checkpoints are published alongside the weights.

A 2014 paper by Srivastava, Hinton, Krizhevsky, Sutskever and Salakhutdinov introducing dropout, a training trick that randomly removes units so large neural networks overfit less.

A 2014 paper presenting an end-to-end deep-learning speech recognition system that removes hand-engineered noise modules and the phoneme dictionary, relying instead on recurrent networks trained across multiple GPUs and synthesized data.

A 2015 paper by Sergey Ioffe and Christian Szegedy that proposed normalising each layer's inputs per training mini-batch, which allowed higher learning rates, looser initialisation and much faster training of deep networks.

A 2016 analysis of residual networks arguing that with identity skip connections and the activation placed after addition, signals travel directly between blocks; a new residual unit built on this eases training, and a 1001-layer network reaches 4.62% error on CIFAR-10.

mixup is a training principle from a 2017 paper by Zhang, Cisse, Dauphin and Lopez-Paz that trains networks on convex combinations of pairs of examples and their labels, improving generalisation on image, speech and tabular benchmarks.

A 2017 arXiv paper, later published in Science, reporting that a single self-play reinforcement learning algorithm, AlphaZero, mastered chess, shogi and Go and beat strong specialised programs in each.

A 2018 paper by Chen, Rubanova, Bettencourt and Duvenaud that replaces a fixed sequence of hidden layers with a neural network describing the derivative of the hidden state, so outputs are computed by an ODE solver — yielding continuous-depth models with constant memory cost.[^1]

DeepMind's first protein-structure prediction system, which placed first overall in the 2018 CASP13 blind assessment by estimating probability distributions of distances between residues.

MBZUAI, the Mohamed bin Zayed University of Artificial Intelligence, is a graduate AI university in Abu Dhabi, founded in 2019. It hosts the Institute of Foundation Models, which builds the K2, Jais and PAN model lines.

MuZero is a DeepMind reinforcement-learning algorithm that learns a model of its environment and plans inside that model, mastering Atari, Go, chess and shogi without being given the rules of those games.

AlphaFold2 is DeepMind's protein structure prediction system, announced in 2020. It reached accuracy competitive with experimental methods in many cases, and work in this area received half of the 2024 Nobel Prize in Chemistry.

AMD's data-center GPU accelerator launched on 8 November 2021, built on the CDNA 2 architecture with 220 compute units, 128 GB of HBM2e memory, and strong double-precision throughput alongside low-precision AI formats.

A 2022 Nature paper by Degrave, Felici and colleagues showing that a deep reinforcement learning controller can learn on its own to command all of a tokamak's magnetic control coils, producing and holding a range of plasma shapes.

GraphCast is a graph neural network trained on four decades of reanalysis data that produces 10-day global weather forecasts at 0.25 degree resolution in under a minute, outperforming the leading operational deterministic systems on most verification targets.

Pangu-Weather is a three-dimensional deep-learning model for medium-range global weather forecasting, published in Nature in 2023; on reanalysis data it produced stronger forecasts than ECMWF's operational system across all tested variables.

GPQA is a benchmark of 448 expert-written multiple-choice questions in biology, physics and chemistry, built so that skilled non-experts cannot look the answers up, and hard enough that the strongest GPT-4 baseline scored 39% while domain experts reached 65%.

A 2023 Nature paper from researchers at Google DeepMind presenting a scaled-up deep-learning approach to predicting stable crystal structures, screening 2.2 million candidates and reporting a large jump in stability-prediction accuracy.

METR is a Berkeley-based nonprofit that evaluates frontier AI models on long-horizon agentic tasks, publishes capability metrics and incident investigations, and works with AI developers on pre-deployment assessments and safeguards.

FunSearch is a method that uses a pretrained large language model inside an evolutionary loop to search for programs that solve mathematical and computational problems, rather than for answers directly. It produced new results on the cap set problem and on online bin packing.

A public benefit AI company that introduced itself alongside its ESM3 model in June 2024 and whose team joined Biohub in November 2025.

FrontierMath is a benchmark of hundreds of original, unpublished mathematics problems written and vetted by expert mathematicians, introduced by Epoch AI to test advanced mathematical reasoning in AI. At release, state-of-the-art models solved under 2% of the problems.[^1][^2]

Deep research is a research agent in ChatGPT, released by OpenAI on 2 February 2025 and built on a version of o3, that searches the web and turns many sources into a written report.

AlphaEvolve is a Google DeepMind coding agent announced on 14 May 2025 that pairs Gemini models with automated evaluators to evolve algorithms, yielding a Borg scheduling heuristic, faster kernels and new mathematical results.

Aurora is a foundation model for the Earth system, trained on more than a million hours of geophysical data. It outperforms operational forecasts for weather, air quality, ocean waves and tropical cyclone tracks at far lower computational cost.

An enhanced reasoning mode for Gemini 2.5 Pro that weighs multiple hypotheses in parallel before answering, announced experimentally in 2025 and known for reaching gold-medal standard at the International Mathematical Olympiad.

DeepSeekMath-V2, released on 27 November 2025, is a mathematical reasoning model trained to verify its own proofs. DeepSeek reported gold-level scores on IMO 2025 and CMO 2024 problems, and 118 of 120 on Putnam 2024.

Gemini 3 Deep Think is Google's enhanced reasoning mode for Gemini 3, announced with Gemini 3 Pro on 18 November 2025 and released to Google AI Ultra subscribers on 3 December 2025, with an upgraded version following in February 2026.

Claude Opus 5, released on 24 July 2026 at $5 and $25 per million tokens, is Anthropic's most aligned model to date and its most capable generally available model for scientific research.

Claude Fable 5.1, released on 1 September 2026, keeps the $10 and $50 per million token price of Fable 5, with cache reads 75% cheaper. Its sibling Claude Mythos 5.1 is limited to trusted-access programmes.

Ian Goodfellow is a machine learning researcher and first author of the 2014 paper that introduced generative adversarial networks, which train a generator and a discriminator against each other. He has worked at OpenAI, Google Brain, Apple and Google DeepMind.

A four-wheeled planetary rover prototype built at Carnegie Mellon's Robotics Institute with NASA funding, Nomad tested autonomous driving and rock analysis in Antarctica, hunting meteorites on the ice without step-by-step human control.

Chinook is a checkers-playing computer program built by Jonathan Schaeffer and colleagues [^1]. It became the first computer program to win a human world championship in any game, and its completed form cannot be beaten [^1].

The RoboCup Federation runs an international robot-soccer initiative and competition whose stated aim is to develop robotic players able to beat a human World Cup champion team.

Epoch AI's Benchmarking Hub collects benchmark results for leading AI models, including Epoch-run evaluations, and combines many scores into the Epoch Capabilities Index, a single general capability scale.

American electrical engineer who built one of the first checkers-playing programs and, in a 1959 paper, helped name the field now called machine learning.

The Technology Innovation Institute is a research centre of Abu Dhabi's Advanced Technology Research Council that works across ten technology fields and develops the Falcon family of language models, releasing model weights, technical reports and its own licence.

The University of Alberta's Department of Computing Science is the institutional home of the Chinook checkers project, and the university has trained a long line of researchers who use games to test ideas in artificial intelligence.

Sergey Levine is a computer scientist who studies how robots can learn control behaviour from data. He is a professor at UC Berkeley and a co-founder of Physical Intelligence.

University College London (UCL) is a public research university in central London. Geoffrey Hinton led its Gatsby Computational Neuroscience Unit, and Demis Hassabis, a Gatsby postdoctoral researcher, later co-founded DeepMind.

EPFL, the École Polytechnique Fédérale de Lausanne, is a technical university founded in 1853 and renamed in 1969; it organizes its work around three missions: teaching, research and innovation.

A society for computing educators, researchers and professionals, founded in 1947 at Columbia University and headquartered in New York, with nearly 110,000 members and the Turing Award among its recognitions.

HHMI is a private biomedical research institution founded in 1953 that funds scientists at all career stages and runs the Janelia Research Campus.

The International Energy Agency is a Paris-based intergovernmental organisation founded in 1974 to respond to oil supply disruptions. It publishes the annual World Energy Outlook and, since 2024, has run work on energy and AI.

AAAI is an international nonprofit scientific society for artificial intelligence, founded in 1979, which runs a flagship annual conference and has published a quarterly magazine since 1980.

The UCI Letter Recognition dataset is an archive of 20,000 distorted capital-letter images, each reduced to 16 integer attributes, used to benchmark classification algorithms on a 26-class recognition task.

Founded in 2000 as the Singularity Institute, MIRI is a Berkeley nonprofit that was among the first to treat artificial intelligence risk as a technical research problem, and now advocates halting work on smarter-than-human AI.

Graph neural networks are neural networks built for graph-structured data, in which nodes repeatedly exchange messages with their neighbours. Since the model was formulated in 2009, they have become a standard way of learning on graphs.

A 2013 paper by Goodfellow, Warde-Farley, Mirza, Courville and Bengio introduces maxout units, whose output is the maximum of a set of inputs, designed to work with dropout, and reports state-of-the-art results on four benchmarks.

A 2013 paper by Graves, Mohamed and Hinton that examines deep recurrent neural networks for speech recognition, arguing for end-to-end sequence training with methods such as connectionist temporal classification.

Group Normalization is a 2018 paper by Yuxin Wu and Kaiming He that proposes normalizing channels in groups, independent of batch size, to address batch normalization's weakness when batches are small.

Epoch AI is a data-first research nonprofit studying the future of artificial intelligence, known for tracking AI training-compute trends, hosting databases on hardware and compute, and running independent model evaluations and its FrontierMath benchmark.

A San Francisco nonprofit founded in 2022 that researches technical AI safety, builds the field of safety researchers, and advocates for safety standards — known for a 2023 statement on AI extinction risk signed by industry leaders.

Galactica is a large language model for science, unveiled by Meta AI and Papers with Code in November 2022. Its public demo was taken down about three days later, after users found it produced fake papers.

A pair of medical question-answering language models described in arXiv papers of 26 December 2022 and 16 May 2023; the first introduced the MultiMedQA benchmark, and Med-PaLM 2 reached up to 86.5% on MedQA.

Pythia is a suite of 16 open language models from EleutherAI, ranging from 70 million to 12 billion parameters, all trained on the same data in the same order, with 154 public checkpoints from each training run.

GraphCast is a Google DeepMind machine-learning model that makes global weather forecasts up to 10 days ahead, producing a 10-day forecast in under a minute on a single TPU and outperforming ECMWF's HRES on most tested variables.

GNoME is a Google DeepMind deep-learning tool, announced on 29 November 2023, that predicts new inorganic crystals; it produced 2.2 million candidate structures, of which 380,000 were predicted to be stable.

AlphaGeometry is a Google DeepMind system that pairs a neural language model with a symbolic deduction engine to solve olympiad geometry problems, reaching near gold-medal level on a benchmark of 30 problems.

DeepSeekMath is a 7B-parameter open language model built for mathematical reasoning and released in 2024. It reached 51.7% on the competition-level MATH benchmark without external tools, and introduced GRPO, a reinforcement-learning algorithm that uses less memory than PPO.

AlphaProof is a Google DeepMind reinforcement-learning system that proves mathematical statements in the formal language Lean. At the 2024 International Mathematical Olympiad it solved three problems, and together with AlphaGeometry 2 reached silver-medal level.

A version of OpenAI's o1 that spends more compute before answering, launched on 5 December 2024 inside the $200-a-month ChatGPT Pro plan and added to the API on 19 March 2025.

DeepSeek's open-source model for formal theorem proving in Lean 4, trained with a subgoal-decomposition pipeline; it reached an 88.9% pass ratio on MiniF2F-test and introduced the ProverBench benchmark.

OpenAI o3-pro is a version of the o3 model released on 10 June 2025, which OpenAI described as its most capable model at the time and recommended for hard questions where reliability matters more than speed.

Karol Hausman is a roboticist working on robot learning, sim-to-real transfer and embodied AI. He was a senior research scientist at Google Brain and Google DeepMind, is an adjunct professor at Stanford, and co-founded Physical Intelligence.

An AI drug-discovery company with sites in London and Oxford that focused on computational molecule design; in November 2024 it became a wholly-owned subsidiary of Recursion, with a combined pipeline of more than 10 clinical and preclinical programmes.

Shun-ichi Amari (born 1936) is a Japanese mathematical engineer who founded information geometry and built theoretical foundations for machine learning and neural networks; he received the 2025 Kyoto Prize in Advanced Technology.

Redwood Research is an AI safety research group that has co-authored, with Anthropic, studies of deceptive behaviour in language models — sleeper-agent backdoors and alignment faking — as well as work on AI control protocols.

Apollo Research is a research organization focused on the risk of scheming: advanced AI systems covertly pursuing misaligned objectives. It evaluates frontier models for this behavior and advises policymakers.

Amnon Shashua is the founder of Mobileye, which grew out of his Hebrew University research into single-camera vehicle detection; he has led the company as chief executive since Intel acquired it in 2017.

XRCE's computer-vision team competed in the ImageNet challenge and won the 2011 classification task using high-dimensional image signatures, product quantization and linear SVMs; its Fisher-vector methods performed strongly across the 2010–2014 challenges.

A 7-billion-parameter model released by Mistral AI on 16 July 2024 for mathematical and STEM reasoning, built on Mistral 7B, openly licensed, and now listed as deprecated.