DeepMind released three papers that push the boundaries — and examine the issues — of large language models.

New research shows that drastically increasing the number of layers in a graph neural networks improves its performance on large datasets.

Isomorphic aims to build its business on AlphaFold 2, an ensemble of neural networks that finds the shapes of protein molecules.

Playing a team sport involves a fluid blend of individual and group skills. Researchers integrated both types of action into realistic humanoid agents that play football (known as soccer in the U.S.).

Machine learning researchers tend to trust international organizations, distrust military forces, and disagree on how much disclosure is necessary when describing new models, a new study found.

The previous state-of-the-art model for playing vintage Atari games took advantage of a number of advances in reinforcement learning (RL). The new champion is a basic RL architecture plus a trick borrowed from image generation.

DeepMind opened access to AlphaFold, a model that finds the shapes of proteins, and to its output so far — a potential cornucopia for biomedical research. The research lab, a division of Google’s parent company Alphabet, made AlphaFold freely available.

To reconstruct the 3D world behind a set of 2D images, machine learning systems usually require a dedicated neural network for each scene. New research enables a single trained network to generate 3D reconstructions of multiple scenes.

Language models are starting to take on programming work. SourceAI uses GPT-3 to translate plain-English requests into computer code in 40 programming languages. The French startup is one of several companies that use AI to ease coding.

Bayes-optimal algorithms always make the best decisions given their training and input, if certain assumptions hold true. New work shows that some neural networks can approach this kind of performance.

AI has humbled human chess masters. Now it’s helping them take the game to the next level. DeepMind and retired chess champion Vladimir Kramnik trained AlphaZero, a reinforcement learning model that bested human experts in chess, Go, and Shogi, to play-test changes in the rules.

If the world changes every second and you take a picture every 10 seconds, you won’t have enough pictures to observe the changes clearly, and storing a series of pictures won’t help. On the other hand, if you take a picture every tenth of a second, then storing a history will help model the world.

A protein’s biological function depends largely on its three-dimensional shape, but deducing its shape from its sequence of amino acids has been a longstanding problem. Researchers at DeepMind reveal how they used deep learning to solve the puzzle.

AlphaGo Zero demonstrates superhuman performance playing Go, chess, and shogi. Models like R2D2 do the same playing classic Atari titles. A new approach to deep reinforcement learning is the first to achieve state-of-the-art results playing both board and video games.

Computer vision has potential to spot cancer earlier and more accurately than human experts. A new system surpassed human accuracy in trials, but critics aren’t convinced.