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 ...

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

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 ...

Reinforcement Learning from Human Feedback (RLHF) has become the go-to technique for refining large language models (LLMs), but it faces significant challenges in multi-task learning (MTL), ...

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 ...

In the new paper Learning Robust Real-Time Cultural Transmission Without Human Data, a DeepMind research team proposes a procedure for training artificially intelligent agents capable of flexible, ...

“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 ...

On October 13, ICCV 2021 announced its Best Paper Awards, honourable mentions, and Best Student Paper. The ICCV (IEEE International Conference on Computer Vision) is one of the top international ...