Reinforcement Learning from Human Feedback (RLHF) has emerged as a crucial technique for enhancing the performance and alignment of AI systems, particularly large language models (LLMs). By ...

Ever since researchers began noticing a slowdown in improvements to large language models using traditional training methods, ...

Scientists at the University of California, Berkeley have developed a novel machine learning (ML) method, termed “reinforcement learning via intervention feedback” (RLIF), that can make it ...

OpenAI must uphold its charitable mission and prioritize the public good, argues former OpenAI researcher Jacob Hilton.

One way to incorporate humans into the process is with reinforcement learning with human feedback (RLHF), a process for machine learning in which traditional reinforcement learning (RL) is ...

Reinforcement learning (RL) plays an important role in training AI, as it can improve machines' ability to learn, but its success hinges on the quality of the feedback it receives.

The new agent, called Asimov, was developed by Reflection, a small but ambitious startup cofounded by top AI researchers from ...

Learning from the past is critical for shaping the future, especially when it comes to economic policymaking. Building upon the current methods in the application of Reinforcement Learning (RL) to the ...