The GPT Moment for Robotics Is Here

Physical Intelligence co-founder Quan Vuong details the shift toward general-purpose robotics, driven by the emergence of foundation models capable of controlling diverse hardware. By decoupling high-level semantic planning from low-level control, the industry is moving away from rigid, vertically integrated systems toward scalable, cross-embodiment models. This transition significantly lowers the barrier to entry, enabling a "Cambrian explosion" of specialized robotics startups. Key technical strategies include utilizing cloud-based inference with real-time action chunking to maintain performance and adopting mixed-autonomy systems that allow human intervention during early deployment phases. Successful implementation relies on identifying specific, high-impact workflows—such as laundry folding or logistics packaging—and prioritizing data collection over building proprietary hardware. This approach transforms robotics from an intractable engineering challenge into an operational strategy, allowing startups to achieve economic break-even and scale rapidly across various sectors.