Picture a robotics grad student with a working arm, a half-working policy, and no lab.
To train that policy they need environments.
A wet lab.
A factory floor.
A kitchen.
Every one modeled by hand, with physics that hold up under contact.
Months of work before the first useful training run.
This week NVIDIA's Inception program released RobotGym as a free public MCP for Physical AI simulation, built on Isaac Sim.
It launched with hundreds of fully functioning environments and thousands of SimReady assets, put together with robotics researchers from Stanford, MIT, Berkeley and Oxford, working toward the largest dataset of physics-accurate environments.
Here is what changes for a small team.
The scene building tax just dropped, and the platform hosts the simulation.
What still costs real money is compute.
The GPU hours you spend training, evaluating and retraining your own policy until it holds up outside the sim.
That is the part we sell.
RTX 3090 compute at $0.15/hr, cloud storage at $2.49/TB per month, and Buy Now Pay Later so you start at zero upfront and pay after one month.
No catch, just pricing you can plan around.
If you work in robotics, which environment do you keep rebuilding by hand that should already be public?
https://ai.bhkcloud.com/?utm_source=linkedin&utm_medium=social&utm_campaign=bhk_social_2026w40&utm_content=evening
Originally posted on linkedin_personal