Physical AI equips robots with VLAs for perception-reasoning-action, uses reinforcement learning in randomized simulations, and iterates with real-world data to close the sim-to-real gap for messy environments.
Use group-relative contextual bandits to select optimal product slates for e-commerce homepages, leveraging relative quality signals for efficient RL over full prediction models.
Treat coupon decisions (when, to whom, strength) as sequential problems with reinforcement learning to balance conversion, margins, budgets, and customer fatigue—backed by field experiments.
