Will Brown

Will Brown, a researcher at Prime Intellect and creator of the Verifiers library, shares his insights on reinforcement learning environments and his humorous takes on AI discussions online. He highlights the importance of structured formats in model training and discusses scaling laws and their implications on cost-quality tradeoffs. Will also delves into the concept of optimizing thinking length for AI models, and how verification functions can improve outputs. He explores unique examples from the AI Engineer conference and the value of community in advancing AI research.

Join Will Brown, a researcher at Prime Intellect, as he unveils their new Environment Hub for reinforcement learning. Josh Reeves, CEO of Gusto, dives into his company's acquisition of Guideline to streamline small business retirement solutions. Keller Cliffton, co-founder of Zipline, shares stunning growth in drone deliveries, revealing a commitment to safety. Julia Steinberg, GM at Arena Magazine, contrasts California's infrastructure woes with China’s development prowess. Lastly, Olivia Moore from Andreessen Horowitz discusses the Consumer AI Top 100 and its insights on innovative companies.

In this conversation with Will Brown, research lead at Prime Intellect specializing in reinforcement learning (RL) and multi-agent systems, they explore the foundations and practical applications of RL. Will shares insights into the challenges RL faces in LLMs, emphasizing the importance of online sampling and reward models. He discusses multi-agent dynamics, optimization techniques, and the role of game theory in AI development. The discussion also highlights the significance of intermediate results and the future directions for RL in various applications.