Reinforcement Learning

Online sorting algorithms run trillions of times a day to organize lists according to users’ interests. New work found faster alternatives. Daniel J. Mankowitz and colleagues at Google developed AlphaDev, a system that learned to generate algorithms that sort three...

Reinforcement learning agents have mastered games like Go that provide complete information about the state of the game to players. They’ve also excelled at Texas Hold ’Em poker, which provides incomplete information, as few cards are revealed.

One challenge to making online education available worldwide is evaluating an immense volume of student work. Especially difficult is evaluating interactive computer programming assignments such as coding a game.

A new coding framework lets you pipe your own data into large language models. LlamaIndex streamlines the coding involved in enabling developers to summarize, reason over, and otherwise manipulate data from documents, databases, and apps using models like GPT-4.

Matrix multiplication is executed so often in deep learning, video games, and scientific computing that even a slight acceleration can save substantial amounts of processing time. New work finds ways to speed up this crucial operation.

Both transformers and reinforcement learning models are notoriously data-hungry. They may be less so when they work together. Vincent Micheli and colleagues at the University of Geneva trained a transformer-based system to simulate Atari games using a small amount of gameplay.

Roboticists often train their machines in simulation, where the controller model can learn from millions of hours of experience. A new method trained robots in the real world in 20 minutes.

Autonomous robots trained to navigate in a simulation often struggle in the real world. New work helps bridge the gap in a counterintuitive way.

Reinforcement learning is powering a new generation of video game cheaters. Players of Rocket League, a video game that ranks among the world’s most popular esports, are getting trounced by cheaters who use AI models originally developed to train contestants.

Amid speculation about the threat posed by OpenAI’s ChatGPT chatbot to Google’s search business, a paper shows how the search giant might address the tendency of such models to produce offensive, incoherent, or untruthful dialog.

Recent advances in deep learning largely have come by brute force: taking the latest architectures and scaling up compute power, data, and engineering. Do we have the architectures we need, and all that remains is to develop better hardware and datasets so we can keep...

A new algorithm defeated a championship-winning Go model using moves that even a middling human player could counter. Researchers trained a model to defeat KataGo, an open source Go-playing system that has beaten top human players.

A new method enables robots to respond helpfully to verbal commands by pairing a natural language model with a repertoire of existing skills.

Robots trained via reinforcement learning usually study videos of robots performing the task at hand. A new approach used videos of humans to pre-train robotic arms.

A dog doesn’t think twice about fetching a tennis ball, but an autonomous robot typically suffers from delays between perception and action. A new machine-learning model helped a quadruped robot coordinate its sensors and actuators.