AI is finally beginning to fulfill its massive transformative potential, as evidenced by the spate of new AI-enabled products across text, images, video, audio, and more. But as far as production-ready products go, one modality has thus far been notably less present from this ongoing Cambrian explosion of AI: physical actions. The types of physical actions generally performed by robots have largely been trapped within the confines of Moravec’s paradox and have seen nowhere near the pace of advancement as in other modalities. There are, of course, understandable reasons for this, ranging from the difficult unit economics of physical automation solutions to the challenges of delivering on correctness for the long tail of physical tasks. Over the last two years, however, there has been a meaningful acceleration in the talent, capital, and research progress in the robotics domain. Overlapping bodies of research appear to be heading in the direction of more general robots — toward the promise of generalist embodied AI agents. This research progress includes, among other things, the pursuit of scaling-laws hypotheses for robotics and the emergence of vision-language models applied to robot actions; advances in methods around co-training and cross-embodiment that increase the leverage of robotics data; and progress toward bridging neural nets to low-level controls for truly end-to-end robot learning. Moreover, leading researchers in the field are spinning up commercial research efforts and new companies, and billions of dollars in capital have been allocated towards robotics startups in 2024 alone. The confluence of talent, capital, and technology in the field suggests we are in the midst of a robotics and embodied AI upswing that could eventually enable the development of a horizontal robotics platform, thus giving more developers the opportunity to innovate in this field.

Full opinion : Toward a Horizontal Robotics Platform.