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In June 2025 Nature Medicine published a phase 2a trial of rentosertib, a TNIK inhibitor for idiopathic pulmonary fibrosis that was discovered by an AI platform, together with early signs of a lung-function effect.
Aurora is a foundation model for the Earth system whose Nature paper, published on 21 May 2025 and promoted by Microsoft Research the same month, reports better than operational forecasts across four domains at far lower compute.
FunSearch, published in Nature in December 2023, used large language models for program search rather than direct solution search, and found results better than the previous best on the cap set problem and online bin packing.
On 14 November 2023, Google DeepMind announced GraphCast; its Science paper reported beating ECMWF HRES on most test variables, and a live version forecast Hurricane Lee's landfall earlier.
On 5 July 2023 Nature published Pangu-Weather, a deep-learning global weather model that reported better deterministic forecasts than ECMWF's operational system on every variable it tested, in the same issue as a deep-learning precipitation nowcasting paper.
On 23 May 2022, Google Research presented Imagen, a text-to-image diffusion model built on a large frozen T5-XXL text encoder, which beat DALL-E 2 in human ratings on the new DrawBench benchmark but was never released publicly.
On 30 October 2019, DeepMind announced that AlphaStar reached Grandmaster level in StarCraft II for all three races, ranking above 99.8% of active players and playing under human-like interface limits.
On 8 September 2016, DeepMind announced WaveNet, a deep neural network that generates raw audio one sample at a time. In blind listening tests it beat Google's existing text-to-speech systems and narrowed the gap to human speech.
Goodfellow, Bengio, and co-authors proposed a generative-model framework with adversarially trained generator and discriminator.
On 19 December 2013, DeepMind researchers posted a paper showing that one convolutional network, trained with a variant of Q-learning, could learn Atari 2600 control policies directly from raw pixels and outperform prior methods on six of seven games.
