Physical AI

Travis Kalanick's Atoms represents the emerging "physical AI" category -- applying AI to robotics and real-world automation rather than purely digital domains. After 8 years in stealth, Atoms targets industrial automation (mining, autonomous robots) where clear ROI justifies the longer R&D cycles physical AI companies require. Kalanick positions humans as AI's primary beneficiaries rather than its casualties, a narrative potentially shaped by Uber's experience with driver displacement backlash.

Physical AI's economic footprint extends beyond robots to the energy substrate that makes it run: the explosive power demand of AI data centers is reviving small modular nuclear reactors (NuScale $SMR) as a credible infrastructure bet, surfacing in 2030 "millionaire-maker" stock theses. This frames physical AI not just as the machines doing the work, but as the entire physical stack -- power generation, materials, and compute -- required to sustain large-scale AI.