Embodied AI needs years of expert trade knowledge to learn real-world constraints
Exp_Mark · x · 2026-07-24
A quoted view argues that physical AI only becomes truly useful when it learns from people who have spent years mastering real-world trades.
The post says expert reasoning, combined with live work data, is the most accurate way for embodied models to learn constraints, failure modes, and decision logic — and that robots need much more of this kind of data before they can be deployed widely.
More from Embodied
- DoorDash says its robotics and drone bets started eight years ago — garrytan · 2026-07-24
- HP and AMD pitch AI workstations for local models and multi-agent workflows — gaganghotra_ · 2026-07-24
- Tesla robotaxi rider says Tampa trip felt smooth and near inflection point — downingARK · 2026-07-24
- REK Shop Pivots to Robot Combat, Liquidates Unitree and Booster Inventory — cixliv · 2026-07-24
- Sources: AI Robotics Startup Genesis AI Seeks $500M at $3B Valuation — nmasc_ · 2026-07-24
- U.S. Moves to Rebuild Domestic Robotics Supply Chain as Strategic Battleground — Rewkang · 2026-07-24