⚡️Open Questions in Agentic RL — Will Brown (Prime Intellect)
AI Summary
In this lightning talk, Will Brown discusses the advancements and challenges in open-source agent reinforcement learning (RL). He outlines the roadmap for developing general-purpose agents capable of long-horizon tasks, like web browsing and code writing. Brown emphasizes the importance of multi-turn tool usage, rewards based on intermediate steps, and the integration of reinforcement learning into model training. He highlights the significance of scalability in using multiple tool calls and managing context efficiently. The talk also touches on leveraging decentralized model training and the merging of specialized models to enhance capabilities. Overall, the discussion provides a framework for addressing the challenges in agentic RL and developing more effective models for complex tasks.