Karol Hausman
Co-founder & CEO, Physical Intelligence. On 1 show, 1 appearance. The Shows tab opens the full record on each.
founderexecutivescientistacademic@hausman_k ↗LinkedIn ↗karolhausman.github.io ↗
Karol Hausman is the co-founder and CEO of Physical Intelligence, a startup developing general-purpose foundation models for robotics. He previously served as a Staff Research Scientist at Google DeepMind and an adjunct professor at Stanford University.
1shows
1appearances
16statements
1resolved
1supported
0contradicted
100%fully supported
2said about them ↓ Everything Karol Hausman said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Hausman: End-to-end learning is the only viable path to solve robotics
“There's another reason to do end-to-end learning, which is, this is, I think, the only thing that has a chance of working.”
Hausman: Most future frontier AI models will train on real-world robot data
“So I think over time, it's quite likely that, that the places are gonna switch a little bit, where most of the models, including, you know, LLMs and BLMs, are gonna be using real-world data collected through robots, because that's the data that has no ceiling,…”
Hausman: Simulation fails for robotic manipulation due to real-world object diversity
“It hasn't worked nearly as well for manipulating objects or working with your hands, and I think the reason for that is then the difficulty isn't about, like, how do you move your hands? It's more about the world that you're manipulating, and that is much hard…”
Hausman: Robot models require surprisingly few environments to generalize to new ones
“So far we've been quite surprised by how few different environments you need to see to be able to generalize to a new one.”
Hausman: Physical Intelligence models give robots zero-shot intuition in new environments
“And one thing with Pi-O-V that we are really excited about is that we are now at the stage where the robots kind of get the sense of what they should be doing in that environment. So, they are no longer in this space where, you know, you just, like, arrive in …”
Hausman: Physical Intelligence's robot demonstrations are fully end-to-end
“So end-to-end robotics is already here. Everything we've shown so far is fully end-to-end where you take camera input in and view other sensors and output actions directly.”
Hausman: Physical Intelligence demonstrated previously impossible tasks like laundry folding
“The demonstrations that we, that we've shown so far here at physical intelligence are of tasks that were not possible before, like things like folding laundry. You can't really, there is no program that I've ever seen that could do that.”
Hausman: Robotics AI does not yet possess LLM-style compute scaling laws
“We are not there yet in terms of like having a full scaling law the same way as we've seen for LLM companies where you can just translate prog compute to progress to capability.”
Hausman: Robot physical actions function as another language for multimodal models
“And what we start to realize is that all of these different data sources contribute to each other. They give you just like a bigger picture of what the world is like and better understanding. And it just turns out that robot actions is just like yet another la…”
Karol Hausman: Physical Intelligence is building a universal robot foundation model
“We want to build a model that can control any robot to do any task.”
Hausman: Pi-05 model achieves 50% to 80% task success in unfamiliar homes
“And it turns out that with Pi oh five, which we just released yesterday, we can do that. And it doesn't work all the time. It's not that I can just give it to you and it will work in your kitchen every single time, but it works quite often quite well. So we br…”
Hausman: Diverse data across robotic form factors and tasks cross-transfers
“And it turns out if you collect very diverse data across many different tasks from many different form factors, they all contribute to each other. And that they contribute to a better understanding for the model of what actually is happening and how to utilize…”
Hausman: A small robot fleet generates LLM-scale model training data volumes
“I think that's one thing that, that I realized since starting the company is that robots generate a ton of data and you don't need that many to generate data that is close to the levels that LLM companies use for their models.”
Hausman: Robotics' biggest bottleneck is generalization, not dexterity
“The biggest challenge in robotics so far hasn't really been Agility or dexterity, what the robots can do. But then generalization.”
Hausman: In-home mobile manipulator data is a tiny training dataset fraction
“Interestingly, most of the data is actually not the model manipulators in many different homes. It's a very, very small percentage of it.”
The other half of the tape: Karol Hausman's own voice is left out of every number here. Other people bring the name up 2 times in 2 episodes across the shows. every mention, with the transcript →
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One line per show, most statements first. The link opens Karol's full record on that show: the calibration, argument clarity, speaking style and every statement made there.
| Show | Role there | Eps | Statements | Record | |
|---|---|---|---|---|---|
| TBPNLEDGER | Co-founder & CEO, Physical Intelligence | 1 | 16 | 100% 1/1 | full record on TBPN → |