As AI systems grow more capable, aligning them becomes increasingly challenging—especially when their behavior outpaces human understanding. This talk explores weak-to-strong generalization: can weak models effectively supervise stronger ones? Through experiments in NLP, chess, and reward modeling, the talk shows how even limited supervision can unlock surprising performance gains—and why alignment techniques like RLHF may not scale without new approaches.

As AI transforms enterprise data center infrastructure, product managers face a critical challenge: driving innovation while upholding ethical standards. This session explores how Responsible AI is shaping the future of system offerings—ensuring data privacy, fairness, and transparency in environments where operational data is central. Through real-world examples, attendees will learn how to apply ethical AI frameworks to build scalable, innovative, and socially responsible solutions that meet both technical and societal needs.