World Models for Robotics
Ramesh Labs is building AI that can perceive, reason, and act in open-ended environments. We start with CS:GO, where navigation, memory, coordination, and long-horizon decision-making can be trained at scale. From there, we extend the same foundation to computer use and, eventually, robotics.
01
High-volume gameplay data, dense multimodal feedback, and fast iteration on navigation and tactical behavior.
02
Move from simulated worlds to real interfaces where agents can plan, operate tools, and recover from failure.
03
Carry the same perception and action stack into the physical world, where robust navigation matters most.
Writing
Rendering out 100K hours of multi-modal, multiplayer pro-level gameplay matches cost effectively using distributed, fault-tolerant (w/ retries) cloud infra.
Coming soon