Physical AI's ChatGPT Moment

The internet taught machines to read, write, and reason. It cannot teach them to move.

In 2026, robot foundation models are having their "ChatGPT moment," vision-language-action systems that fold laundry and assemble boxes, billions in funding, a real scaling curve. Yet the data these systems need most, first-person recordings of physical work, barely exist. There is no internet of experience to scrape.

This talk traces where Physical AI actually stands today, then gets to the harder truth underneath the hype: why degrees of freedom, contact, and force make the body far tougher than the brain, why simulation and teleoperation fall short, and why egocentric human data has become the field's central bottleneck. Drawing on lessons from building Black Robotics, it connects the embodied-AI frontier to what it means for anyone building in cloud, data, and applied AI.

Speaker Bio:

Siddhant Patil is the founder of Black Robotics, a data opt-in platform for physical AI focused on sourcing the egocentric data that robot foundation models need to learn.
He has worked as a founding AI engineer at two Silicon Valley AI startups, where he built and shipped agentic systems, LLM evaluation, and data infrastructure. He writes about AI and robotics across Medium and Towards AI, and holds an M.S. in Computer Science from California State University, Long Beach.

Time: 4pm

Structure:
4-4:30: Networking
4:30-5:00: Presentation
5:00-5:10: Q&A
5:10-5:30: Post-event networking

Snacks and drinks provided!