The more I think about Physical AI, the more obvious the data problem becomes imo.
You know, an LLM can learn from literally billions of examples online, but a robot can't just READ its way into knowing how to move through a crowded store or react to something unexpected in the real world, coz it's messy.
That experience has to come from the physical world.
So for me, what
@humynlabs is building rn is kinda interesting. They're turning real human experience into usable skills for robots, so they can actually function in the messy real world.
For me, this is a very important piece of the Physical AI ecosystem that doesn't get talked about enough.
We're Humyn Labs. With us, every robot works fine.
We turn human experience into robot skills built from thousands of hours of model-ready data.
Unlike LLMs, that learnt from the entire internet, robotics data doesn't get that shortcut.
Robots need real-world experience to learn how to:
- Iron clothes with a toddler underfoot and a dog at your heels
- Restock shelves while navigating a crowded, constantly changing store
- Assemble components amid the variability of a real factory floor
That experience happens once, in the physical world, and disappears.
We’re building the data platform Physical AI learns from: four sensory modalities, real-world environments, and the human experience needed to turn moments into skills.