Tag: Foundation Models

The fundamental bottleneck holding back generalized physical AI is not model architecture or computing power—it is the scarcity of high-quality physical training data. While Large Language Models (LLMs) scaled rapidly by ingesting trillions of public internet text tokens, embodied humanoid robots operate in the physical domain. In robotics, every physical training hour requires an actual […]

Historically, the robotics industry has operated in fragmented silos. Every hardware original equipment manufacturer (OEM)—from industrial articulated arm makers to early bipedal pioneers—built custom vertical software stacks from scratch. Kinematics solvers, computer vision classifiers, trajectory smoothers, and fieldbus communication protocols were hand-coded for bespoke motor drive architectures. This custom paradigm prevented the robotics industry from […]