Skild AI founder explains why robotics data needs four sources, each flawed
deepakpathak · x · 2026-09-12
Skild AI founder Deepak Pathak laid out a framework for how a $100M ARR robotics company thinks about data scale, arguing no single source can solve the robotics data problem.
- Robots collecting their own data: best-targeted, slowest to scale since the physical world can't run faster than real time
- Teleoperation: industry default, but almost zero diversity
- Simulation: far faster than real time, but every new task needs a hand-built environment
- Human video: most abundant, furthest from the robot
He evaluates data quality along three axes — scalability, diversity, and closeness to the robot — and argues only a combination of sources will solve robotics data.
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