Kevin Black
Kevin Black is a researcher at Physical Intelligence and a PhD candidate in artificial intelligence at the University of California, Berkeley. He has contributed to the development of Physical Intelligence's generalist robot policies, including π0 and π0.5, as well as research on real-time action chunking for vision-language-action models. His broader research spans reinforcement learning for diffusion models, robotic manipulation, and foundation models for visual navigation.
“K. Black: Developer of π0, π0.5, and the RTC (Real-Time Chunking) methods that πR² directly builds upon and outperforms. Black's work on action chunking flow policies and their real-time execution represents the state-of-the-art baseline that πR² improves upon.”
Source→AI-extracted from podcast / newsletter / paper summaries. May contain errors.