Vuong: Absorbing diverse data is easier than scaling proprietary hardware
Quan Vuong · The GPT Moment for Robotics Is Here · Y Combinator · Apr 16, 2026 · at 11:13
Physical Intelligence co-founder Quan Vuong explains why training foundation models across varied third-party hardware scales better than single-robot hardware companies.
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“And cross embodiment, there is the data collection aspect of, as well, which is to really make sure that your model and your organizations and infrastructure are set up to consume data From many different sources of robots, and that actually allows you to scale easier. For example, if I were to contrast our approach compared to, let's say, a company that have a particular hardware platform that they optimize for and they scale it's not an approach that have really allowed people to scale because it's just much harder to figure out how do you manufacture, like, A thousand units of something for now, compared to making sure that you yourself are ready to absorb data from like a thousand different types of robots that are already in there, in the community.”
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