Physical AI, ML and Computer Vision Meetup: Robot Brains and Models - February 10, 2027

Join us for the Physical AI, ML and Computer Vision Meetup series focused on robotics use cases. In this session we will focus on robot brains and models.

Robot brains and models are the learned policies and foundation models that let robots perceive, reason, and act independent of any single body, focusing on the intelligence layer rather than the hardware and often aiming to control many different robots with shared models.

This virtual series runs every other Wednesday from January 13 to May 5, 2027. Register once and you are registered for every upcoming session in the series.

Building robots and autonomous systems means training on huge multimodal datasets, running simulation at scale, and iterating on models quickly. In this short session, CoreWeave's Head of Physical AI shares how teams are building their physical AI infrastructure today, where the bottlenecks are, and what is coming next to make it easier to go from data to deployed models.

Every vision model is trained on a snapshot of the world, but robots are deployed into one that keeps changing: lighting shifts, friction drifts, objects move, actuators wear. Today the fix is a slow loop of collecting new data, retraining, validating and redeploying, which can take weeks or months. In this talk, we show how Lazy Dynamics’ LazyInfer closes that gap by treating perception, parameter learning and control as one Bayesian inference problem that runs on the device, inside the control loop.