
12 segments available
Physical Intelligence is building a foundation model that can control any robot to do any task — what the team describes as the GPT-1 moment for robotics. The company's cross-embodiment approach trains across many different robot platforms, and recent results show tasks being performed zero-shot that last year required hundreds of hours of data collection. In this episode of The Lightcone, co-founder Quan Vuong sat down with Garry, Jared, Diana, and Harj to talk about why robotics is finally ready for its scaling moment, how PI runs its models in the cloud rather than on-device, and the playbook for what Quan sees as a Cambrian explosion of vertical robotics companies. 00:00 The new robotics startup equation 00:41 Intro: GPT-1 moment for robotics 03:05 How AI unlocked robotics (RT-2, PaLM-E) 06:17 Breakthrough: multi-robot scaling (Open-X) 09:12 The real bottleneck: data 13:10 Emergence: zero-shot robot skills 16:01 Real-world demos: laundry & warehouses 22:21 Robotics becomes a data + ops problem 23:16 Cloud-controlled robots (big unlock) 29:03 How to start a robotics company today 32:33 The coming explosion of robotics startups 43:53 What’s still missing (and what comes next) Apply to Y Combinator: https://www.ycombinator.com/apply Work at a startup: https://www.ycombinator.com/jobs
"The equation I think for starting a robotic business has changed and will continue to change at an accelerating pace because the upfront cost is not that high anymore. >> Everyone's sort of spending a..."
"Welcome back to another episode of the light cone. Today we have a very special guest, Quan Vang. He's one of the co-founders of physical intelligence, which we think might be the robotics AI lab that..."
">> Yeah. So the dream to build general purpose robot like robots has been a longtime dream I think in humanity like you know we're not the first to say that our mission is to build a model that can wo..."
"the first that showed potential scaling laws that apply to robotics because now you could start training all these models across multiple kinds of hardware, not just one, which has never been done in ..."
"talking about sort of GP1, but even GP1, you know, that was sort of this moment where you can prove, you know, Alec Radford figured out that there was a neuron based on a very specific input and outpu..."
"if you start from the hypothesis that if you have many robot platform in your fleet your model is going to learn something more abstract which is how do I control a robot not any particular robot then..."
"way for us to do so is to partner really closely with company that want to get robot out there today. And the way that these relationship work is that we treat each other like we're on the same team v..."
"difficult engineering problem into a operation problems of how do I identify the use case and how do I collect the right data which is in some sense more scalable because you can build the system that..."
"you guys have done something very different. Can you tell us more about that so that this works in in in real time with large models and and really well? >> So the context here is that you know we tal..."
"of robot is a really serious consideration today and so the pace of progress has just been very pleasantly much faster than we expected. Originally, >> often on this podcast, we talk about like what a..."
"task. Um, and so it it allow company to focus on the component that will actually allow them to differentiate themselves from the rest of the space. Now that you've sort of unbundled it and you no lon..."
"really side project I would love to take on is to build a automated robotic research scientist >> um which is really one of the bottleneck we have today because this is a really difficult skill set um..."