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Foundation, generative, multimodal and specialised models.

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2023

  • Dec 14, 2023 FunSearch

    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.

    Deep learningReasoningScience

  • Dec 12, 2023 Phi-2

    Phi-2 is a 2.7-billion-parameter base language model from Microsoft Research, announced on 12 December 2023. Microsoft reported that it matched or beat models up to 25 times larger on complex benchmarks, making it a reference point for small-model training.

    Large language modelsOpen sourceReasoning

  • Nov 29, 2023 GNoME (Graph Networks for Materials Exploration)

    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.

    Deep learningData & datasetsScience

  • Nov 14, 2023 GraphCast

    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.

    Open sourceDeep learningScience

  • Nov 3, 2023 Grok-1

    Grok-1 is xAI's first large language model, announced on 3 November 2023 as the engine of the Grok chatbot. Its 314-billion-parameter weights were released openly in March 2024.

    Large language modelsOpen sourceFoundation models

  • Nov 2, 2023 DeepSeek Coder

    DeepSeek's first model release: a family of open-source code models from 1.3B to 33B parameters, trained from scratch on 2 trillion tokens and reported to beat Codex and GPT-3.5 on several benchmarks.

    Large language modelsOpen sourceChina

  • Sep 27, 2023 Mistral 7B

    Mistral AI's first model: a 7.3-billion-parameter language model released in September 2023 under the Apache 2.0 license, built to match much larger models on standard benchmarks.

    Large language modelsOpen sourceFoundation models

  • Sep 11, 2023 Phi-1.5

    Phi-1.5 is a 1.3-billion-parameter language model from Microsoft Research, trained on curated synthetic "textbook" text rather than web crawls; its report claims natural-language performance comparable to models five times larger.

    Large language modelsOpen sourceReasoning

  • Aug 24, 2023 Code Llama

    Code Llama is a family of coding models that Meta released in August 2023 by further training Llama 2 on code. It ranges from 7 billion to 70 billion parameters and uses the Llama 2 community license.

    Large language modelsOpen sourceDeveloper tools

  • Aug 15, 2023 iFlytek Spark V2.0

    SparkDesk V2.0 is the second version of iFlytek's large language model, launched on 15 August 2023 with upgraded coding and multimodal abilities, and released alongside the iFlyCode 1.0 programming assistant.

    Large language modelsChinaFoundation models

  • Jul 28, 2023 RT-2 (Robotic Transformer 2)

    RT-2 is a vision-language-action model from Google DeepMind, announced on 28 July 2023, that turns images and text instructions into robot actions written as text tokens. In over 6,000 trials it reached 62% on unseen scenarios, up from 32% for RT-1.

    MultimodalRoboticsComputer vision

  • Jul 5, 2023 Pangu-Weather

    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.

    ChinaDeep learningScience

  • Jun 20, 2023 Phi-1

    Phi-1 is a 1.3-billion-parameter Transformer language model for Python from Microsoft Research, which showed that filtered and synthetic "textbook quality" training data can partly substitute for model and data scale.

    Large language modelsOpen sourceData & datasets

  • May 10, 2023 PaLM 2

    PaLM 2 is Google's second-generation Pathways language model, announced on 10 May 2023 in four sizes and used across more than 25 Google products, including Bard.

    Large language modelsEnterpriseConsumer apps

  • May 4, 2023 StarCoder

    StarCoder is an open-access code language model of about 15.5 billion parameters, released on 4 May 2023 by the BigCode project led by Hugging Face and ServiceNow.

    Large language modelsOpen sourceData & datasets

  • Apr 19, 2023 Stable LM

    Stable LM is Stability AI's family of open language models, first released in April 2023 as 3B- and 7B-parameter alpha versions under licenses that allow commercial use of the base models and research-only use of the instruction-tuned ones.

    Large language modelsOpen sourceFoundation models

  • Apr 5, 2023 Segment Anything Model (SAM)

    The Segment Anything Model (SAM) is a promptable image segmentation model Meta AI released in April 2023. Given a point, a box or a mask, it outlines the object the prompt refers to.

    Open sourceDeep learningFoundation models

  • Feb 24, 2023 LLaMA

    A family of foundation language models from Meta AI, released in 7B to 65B parameter sizes and trained on public data; its 13B model was reported to beat GPT-3 on most benchmarks.

    Large language modelsOpen sourceFoundation models

2022

2021

  • 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.

    Large language modelsResearch historyEurope

  • 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.

    Large language modelsFoundation modelsHardware & compute

  • 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.

    Large language modelsResearch historyDeveloper tools

  • 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.

    Large language modelsResearch historyChina

  • 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.

    Large language modelsResearch historyConsumer apps

  • 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.

    Open sourceFoundation modelsMultimodal

  • 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.

    MultimodalGenerative modelsCreative tools

2020

  • 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.

    Large language modelsResearch historyFoundation models

  • 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.

    Large language modelsResearch historyConsumer apps

2019

2018

  • 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.

    Large language modelsResearch historyOpen source

  • 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.

    Large language modelsResearch historyOpen source

  • 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.

    Research historyDeep learningAgents & tool use

2013

  • 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.

    Research historyDeep learningEurope

2011

  • Feb 2011 IBM Watson

    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