

Hebbian Robotics (YC S26)
7 posts

@hbr_pbc
Developing robots that extend what humanity can do, for the benefit of the communities they serve.





The scarce thing in a data center is not manpower, but instinct that only comes from years on the floor. @kstonekuan and I spent the past month with data center operators and industrial robotics startups. Most robotics companies are focused on robots as a productivity amplifiers: 24/7 uptime, five days of work done in two. Few are focused on the potential of robots to change how people work altogether. We want to show what it looks like to rethink human-robot collaboration, using AI so a shrinking pool of experts can meet the increasing demands of future infrastructure.

The scarce thing in a data center is not manpower, but instinct that only comes from years on the floor. @kstonekuan and I spent the past month with data center operators and industrial robotics startups. Most robotics companies are focused on robots as a productivity amplifiers: 24/7 uptime, five days of work done in two. Few are focused on the potential of robots to change how people work altogether. We want to show what it looks like to rethink human-robot collaboration, using AI so a shrinking pool of experts can meet the increasing demands of future infrastructure.


NVIDIA showcased Newton at GTC again earlier this year. If you are familiar with MuJoCo or Isaac Sim, Newton is a new open-source, GPU-accelerated physics engine aimed at robotics and contact-rich manipulation, built with DeepMind and Disney Research. It also runs as a physics backend inside the Isaac ecosystem. I finally had time to dig through the examples, and the RJ45 plug simulation (example_contacts_rj45_plug.py) caught my attention. The latch deflects and clicks, and the cable behaves like a real 1D deformable. We've been working on cables, connectors, and other contact-heavy interactions, so seeing this as a first-class example was a pleasant surprise. I extended it to test insertion and removal, with and without pressing the latch, and visualized the result in Rerun. Pull without pressing the tab, and the latch holds the plug in place; press it, and the plug comes free. It also interested me how code-first the examples feel. We've spent real time trying to drive both MuJoCo and Isaac Sim with coding agents, and the recurring friction is being able to reason spatially to modify the simulation setup. It feels like there's real potential here. I'm curious if Newton might be better suited for agent-generated robotics simulations. If you're looking for something like this too, Newton is definitely worth a try.
