About the show
Every week, a deep-yet-accessible 15-minute briefing on what happened in Physical AI: robot foundation models, humanoids, manipulation, simulation, world models, and the research behind them. Built for researchers and curious newcomers alike — every episode gives you the background you need, then goes deep with concrete examples. Each episode ships with a long-form written deep dive.
What it covers
Every week the show works through the same beats of Physical AI: robot foundation models and vision-language-action systems, humanoids and hardware, manipulation and locomotion, simulation and world models, datasets and benchmarks, embodied perception, and the industry news that actually changes what gets built.
Who it's for
Researchers and engineers who want the week compressed without losing the technical detail — and anyone curious enough to follow along. Every episode builds the background before going deep, so you don't need to already know the field to keep up.
Every episode ships with a written deep dive
The audio is the briefing. The companion article on this site is the reference: full method details, benchmark numbers, limitations, and links to every paper discussed.
The host
Shubham Shrivastava leads AI at Kodiak, where his team builds the world foundation models and camera-lidar-radar perception behind the first 24/7 driverless freight fleet — real trucks, paying freight, no safety driver. He led perception at Ford's autonomous vehicle program before that. He reads the research here the way he reads it at work: not whether a result is impressive, but whether it survives contact with the road.
For more about his work, writing, and research, visit www.shrivastava.ai.
Subscribe
Add the RSS feed to any podcast app, or find the show wherever you already listen. New episodes land Saturday mornings.
https://physicalaipodcast.co/feed.xml
Contact
Corrections, suggestions, and papers worth covering are all welcome — especially corrections. Reach the show at shubham@shrivastava.ai.
If a paper of yours was covered and you think the reading was wrong, please say so. Corrections get read out in the following episode.