IBM and Dallara are using AI to cut aerodynamic simulation times from hours to seconds, highlighting a key trend in Physical AI. With real-world data scarce and costly, simulation is becoming the primary training ground. TheMarketAI Take: the better the simulation, the better AI performs in reality — making simulation the critical bridge between models and the physical world.

Physical AI faces hurdles digital AI never had to. Real-world data is scarce, hardware is costly, and edge computing adds complexity. Even with powerful simulators, the “sim-to-real” gap keeps autonomy out of reach — many demos still rely on human “babysitters.” TheMarketAI Take: progress will come from modular systems — robots that master walking, grasping, or vision, not everything at once.