The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...

Training standard AI models against a diverse pool of opponents — rather than building complex hardcoded coordination rules — is enough to produce cooperative multi-agent systems that adapt to each ...

Today's AI agents don't meet the definition of true agents. Key missing elements are reinforcement learning and complex memory. It will take at least five years to get AI agents where they need to be.

Researchers at Meta, the University of Chicago, and UC Berkeley have developed a new framework that addresses the high costs, infrastructure complexity, and unreliable feedback associated with using ...

Researchers have developed a new artificial intelligence approach that exposes critical weaknesses in multi-agent reinforcement learning systems, enabling stronger coordinated attacks with broad ...

Chinese AI company MiniMax has released the weights for MiniMax M2.7, a 229-billion-parameter Mixture-of-Experts model that participated in its own development cycle – marking what the company calls ...

Large Language Models (LLMs) and models cross-trained on natural language are a major growth area for edge applications of neural networks and Artificial Intelligence (AI). Within the spectrum of ...