Presentation Abstract: As large language models evolve into agents capable of complex reasoning, in this talk we will explore how modern models are taught not just to respond, but to reason and think -- orchestrating plans, decomposing problems, using tools, and understanding multimodal inputs like images and diagrams. Through visual walkthroughs and code examples, we will reveal how these capabilities are reshaping AI's ability to reason about the world, and glimpse the future of models that are truly general problem-solvers. We will also consider the implications for alignment: how to encourage helpful, honest, and harmless behavior when models are increasingly agentic.

Speaker Bio: Hongyu Ren is a Member of Technical Staff at OpenAI, working on reasoning algorithms for large language models. He led the development of the o-mini series of models. Previously he received a PhD degree in CS at Stanford.