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Foundation, generative, multimodal and specialised models.

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2023

  • 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

  • Oct 17, 2023 Fuyu-8B

    Fuyu-8B is a decoder-only multimodal model that Adept open-sourced in October 2023; it drops the image encoder, accepts arbitrary resolutions, and reads screens and charts.

    Open sourceAgents & tool useMultimodal

  • Sep 25, 2023 GPT-4V (GPT-4 with vision)

    GPT-4V is a version of GPT-4 that accepts image input alongside text, documented in OpenAI's system card of 25 September 2023 and released to developers through preview API models; image understanding later became native in GPT-4o.

    Large language modelsMultimodalSafety & governance

  • 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 Qwen-VL

    Qwen-VL is a family of vision-language models released in August 2023 that builds on the Qwen language model to caption images, answer questions about them, locate objects and read text, with open Base and Chat versions.

    Open sourceChinaMultimodal

  • 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 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 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

  • 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

2019

2018

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

2012

  • 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.

    Research historyDeep learningComputer vision

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