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Foundation, generative, multimodal and specialised models.
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2022
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Apr 4, 2022
PaLM
PaLM is a 540-billion-parameter dense Transformer language model announced by Google Research in April 2022, trained with the Pathways system across 6,144 TPU v4 chips; it set strong few-shot results on many benchmarks.
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Mar 15, 2022
GPT-3.5 (text-davinci-002/003)
GPT-3.5 is the family of OpenAI language models between GPT-3 and GPT-4, released through API models such as text-davinci-002 and text-davinci-003 and underlying the first version of ChatGPT.
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Feb 2, 2022
AlphaCode
AlphaCode is a DeepMind code-generation system for competitive programming, announced in February 2022. On Codeforces contests held after its training data, it reached an estimated rank around the median participant. A Gemini-based AlphaCode 2 followed in December 2023.
2021
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Dec 8, 2021
Gopher
Gopher is DeepMind's 280-billion-parameter language model, announced in December 2021 alongside a study of what scale does to language models and a companion taxonomy of their risks.
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Oct 11, 2021
Megatron-Turing NLG 530B
Megatron-Turing NLG 530B is a 530-billion-parameter language model announced by NVIDIA and Microsoft on 11 October 2021, then the largest monolithic transformer language model, trained on NVIDIA's Selene supercomputer with Megatron-LM and DeepSpeed combined.
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Jul 15, 2021
RoseTTAFold
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.
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Jul 7, 2021
OpenAI Codex (2021 model)
OpenAI Codex is a 2021 GPT language model fine-tuned on public code from GitHub. It translates natural language into code, and was introduced alongside the HumanEval benchmark for testing code correctness.
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Jul 5, 2021
ERNIE 3.0
ERNIE 3.0 is a 10-billion-parameter pre-trained language model from 2021 that trains on plain text plus a large-scale knowledge graph and fuses auto-encoding and auto-regressive networks, so one model handles both language understanding and generation.
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May 18, 2021
LaMDA
LaMDA is a family of conversational language models that Google announced in 2021 and described in a 2022 paper, notable for its work on safety and factual grounding in dialogue and for later powering Bard.
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Jan 5, 2021
CLIP
An image-text model from OpenAI that learns to match pictures with their captions. Trained on about 400 million image-caption pairs, it can classify images by comparing them against written prompts, with no task-specific training.
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Jan 5, 2021
DALL·E
DALL·E is OpenAI's text-to-image model unveiled on 5 January 2021: a 12-billion-parameter transformer trained on 250 million text-image pairs that generates a picture token by token from a caption.
2020
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Nov 30, 2020
AlphaFold2
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.
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May 28, 2020
GPT-3
GPT-3 is an autoregressive language model with 175 billion parameters, described in a May 2020 paper. It could perform new tasks from a few examples in the prompt, without any gradient updates, and it was first offered through OpenAI's API.
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Jan 28, 2020
Meena
Meena is a 2.6-billion-parameter open-domain chatbot from Google, trained end-to-end on filtered social media conversations. Its 2020 paper introduced the SSA human-evaluation metric and linked next-token perplexity to human-judged chat quality. The work was later renamed LaMDA.
2019
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Nov 19, 2019
MuZero
MuZero is a DeepMind reinforcement-learning algorithm that pairs tree-based search with a learned model. It reached superhuman play in Atari, Go, chess and shogi without being given the environment's rules.
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Oct 23, 2019
T5 (Text-to-Text Transfer Transformer)
T5 is a family of Google Transformer models that recasts every language task as text in, text out. Its 11-billion-parameter version set state of the art on several benchmarks, and the code, models and C4 dataset were released openly.
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Jul 29, 2019
ERNIE 2.0
ERNIE 2.0 is Baidu's pre-trained language model framework, published in 2019, which builds pre-training tasks incrementally through continual multi-task learning and reported results above BERT and XLNet on English and Chinese benchmarks.
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Mar 2019
ERNIE 1.0
Baidu's first ERNIE pre-trained language model, released in March 2019, added entity- and phrase-level masking to BERT-style pre-training and reported state-of-the-art results on five Chinese NLP tasks.
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Feb 14, 2019
GPT-2
GPT-2 is a large language model that OpenAI announced in February 2019. Its largest version has 1.5 billion parameters. OpenAI first withheld the full model, then released it in stages through November 2019.
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Jan 2019
AlphaStar
AlphaStar is a DeepMind system that plays StarCraft II. In 2019 it reached Grandmaster level with all three races, ranking above 99.8% of active players on Battle.net.
2018
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Dec 2018
AlphaFold (first version)
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.
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Oct 11, 2018
BERT
BERT is a language model from Google that reads text in both directions and is pre-trained by filling in masked words. Fine-tuned per task, it set new records on question answering and language-understanding benchmarks and later went into Google Search.
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Jun 11, 2018
GPT-1
GPT-1 was OpenAI's first generative pre-trained transformer, published in June 2018. It showed that one language model, pre-trained on unlabelled text and then fine-tuned, could improve results on many language tasks.
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Jun 2018
OpenAI Five
OpenAI Five was a team of five reinforcement-learning bots that played the video game Dota 2; in April 2019 it beat OG, the reigning world champions, in a best-of-three series.
2017
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Dec 5, 2017
AlphaZero
AlphaZero is a general game-playing system from DeepMind, described in a preprint in December 2017, that reached a superhuman level in chess, shogi and Go within 24 hours starting from random play, using only the rules of each game.
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Oct 18, 2017
AlphaGo Zero
A DeepMind Go program that learned the game from scratch by playing against itself, using no human game records, and beat earlier versions of AlphaGo within days.
2016
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Sep 8, 2016
WaveNet
A DeepMind generative model that predicts raw audio one sample at a time, bringing neural text-to-speech close to human quality and later powering Google Assistant and Cloud Text-to-Speech voices.
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Jan 27, 2016
AlphaGo
AlphaGo is a Go-playing program from DeepMind that combined deep neural networks with Monte Carlo tree search. In 2016 it beat top professional Lee Sedol in a widely watched match, a landmark for learned systems.
2013
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Dec 19, 2013
Deep Q-Network (DQN)
A DeepMind reinforcement-learning agent that combined Q-learning with a convolutional neural network to play Atari 2600 games straight from raw pixels, reaching human-level performance on many titles without being told the rules.
2012
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2012
AlexNet
AlexNet is the eight-layer convolutional network that won the ILSVRC2012 image classification task by a wide margin, showing that a large network trained on a large labelled dataset with GPUs could beat hand-designed features.