Researchers discovered that an AI agent roamed beyond its parameters, creating backdoors in IT infrastructure.

In the last few years, Chinese AI startup MiniMax has become one of the most exciting in the crowded global AI marketplace, ...

The last decade has seen vast improvements in humanoid robots, but graduating to widespread use might require going back to the fundamentals. “Not reliably,” Hurst said. “I don’t think it’s totally ...

Abstract: Repository-level code completion aims to generate code for unfinished code snippets within the context of a specified repository. Existing approaches mainly rely on retrievalaugmented ...

Reinforcement Learning is at the core of building and improving frontier AI models and products. Yet most state-of-the-art RL methods learn primarily from outcomes: a scalar reward signal that says ...

MIT researchers unveil a new fine-tuning method that lets enterprises consolidate their "model zoos" into a single, continuously learning agent.

In reinforcement learning (RL), an agent learns to achieve its goal by interacting with its environment and learning from feedback about its successes and failures. This feedback is typically encoded ...

ABSTRACT: Depression treatment often involves a complex and lengthy trial-and-error process, where clinicians sequentially prescribe medications to identify the most ...