Models

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.

Large language modelsResearch historyEurope

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.

Large language modelsFoundation modelsHardware & compute

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.

Large language modelsResearch historyChina

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.

Large language modelsResearch historyConsumer apps

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.

Open sourceFoundation modelsMultimodal

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.

Large language modelsResearch historyConsumer apps

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.

Research historyDeep learningReasoning

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.

Large language modelsOpen sourceFoundation models

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.

Large language modelsResearch historyOpen source

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.

Large language modelsResearch historyOpen source

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.

Research historyDeep learningReasoning

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.

Research historyDeep learningReasoning

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.

Research historyDeep learningComputer vision

IBM Watson is a question-answering computer system built by an IBM research team led by David Ferrucci; in February 2011 it defeated the two foremost all-time champions of the televised quiz show Jeopardy!

Research historyEnterpriseReasoning