Real-world RL for robots faces a triangle: scaling deployments, overfitting, and 100% success SLAs
paigeinsf · x · 2026-10-23
Practitioner Paige lays out the core tension in real-world RL for robot models: scaling deployments while avoiding overfitting to a few environments, all while serving paying customers who expect 100% success. The path forward requires economically sensible arrangements (who pays whom when service isn't at 100%?) and cost-effective ways for models to learn from real-world experience.
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