Cellular automata (CA) have become essential for exploring complex phenomena like emergence and self-organization across fields such as neuroscience, artificial life, and theoretical physics. Yet, the ...

Tools designed for rewriting, refactoring, and optimizing code should prioritize both speed and accuracy. Large language models (LLMs), however, often lack these critical attributes. Despite these ...

The rise of large language models (LLMs) has equipped AI agents with the ability to interact with users through natural, human-like conversations. As a result, these agents now face dual ...

To bring the vision of robot manipulators assisting with everyday activities in cluttered environments like living rooms, offices, and kitchens closer to reality, it's essential to create robot ...

Sparse Mixture of Experts (MoE) models are gaining traction due to their ability to enhance accuracy without proportionally increasing computational demands. Traditionally, significant computational ...

In a new paper Upcycling Large Language Models into Mixture of Experts, an NVIDIA research team introduces a new “virtual group” initialization technique to facilitate the transition of dense models ...

In a new paper Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning, a research team from the University of Oxford and Google DeepMind introduces methods to achieve ...

“Global Vision, Ideas in Collision, Leading Cutting-Edge Innovations” – The 6th annual BAAI Conference successfully concluded on June 15. Over 200 AI scholars and industry leaders gathered to discuss ...

The development and evaluation of Large Language Models (LLMs) have primarily focused on assessing individual abilities, overlooking the importance of how these capabilities intersect to handle ...