Lab Notes

On episode 2 of Lab Notes, Amir Zohrenejad sits down with Hanchen Li to explore the systems that make modern AI agents faster, more efficient, and better at learning from experience. They discuss KV Cache optimization, long-context inference, prompt learning, continual learning, and why better benchmarks may be just as important as larger models in advancing AI research.

On this debut episode of Lab Notes, Amir Zohrenejad is joined by Ren Wang, a researcher and PhD student at UC Berkeley, to explore the state of physical AI and why robotics has progressed differently from large language models. They discuss data scarcity, world models, simulation, dexterity, and the challenges of building robots that can reliably operate in the real world.