Fei-Fei Li on Spatial Intelligence and Robotics

**Fei-Fei Li** (0:00)
We are building the next frontier of AI, which is what we call spatial intelligence.

**Yunzhu Li** (0:06)
At SceniX, we are developing what we call a real-to-sim-to-real pipeline. We can replace all the data, all the evaluation we need in the real environment by using the data that can generate at a scalable way in our digital world.

**Fei-Fei Li** (0:20)
Think about human intelligence. We do a lot of simulation in our head.
You know, why? There's a very important role simulation place that real-world data doesn't play, which is counterfactual reasoning.

**Yunzhu Li** (0:34)
What we are building is a consistent world. Consistence both over space, over time, over different viewpoints and over different type of interactions. My north star is I want the reality world.

**Fei-Fei Li** (0:45)
The world we live in can be multiverse, that we create technology to allow people, builders, developers to act within different spaces.

**Martin Casado** (0:55)
Do you believe we'll ever be able to build robots that have the power efficiency of a human being? How far away are we from this? Is this like five years or this is like never?

**Fei-Fei Li** (1:06)
The TLDR is...

**SPEAKER_4** (1:08)
Language models transformed how AI understands words. The next frontier is teaching AI to understand and act within the physical world.
Following World Labs acquisition of SceniX, Martin Casado sits down with Fei-Fei Li and Yunzhu Li to unpack the vision behind the deal. They discuss spatial intelligence, world models, simulation, and why solving robotics will require a new generation of AI, built for three-dimensional reasoning, not just language.

**Martin Casado** (1:39)
All right, well, it's great to have you both here. So Fei-Fei, for the listeners that may not have the background, maybe you can give an overview of what World Labs does.

**Fei-Fei Li** (1:49)
Yeah, well, World Labs is a two-year-old startup.
I think we should just recognize it's a frontier model lab. We are building the next frontier of AI, which is what we call spatial intelligence. And spatial intelligence is about creating AI that has the ability to generate, understand, reason with, and interact with spaces, whether it's physical or virtual. And of course, a means to an end towards spatial intelligence is building large world models. And that's what World Labs is mostly focused on.

**Martin Casado** (2:28)
Yeah. So you've been saying this since the very beginning, which is the machine's ability to perceive and reason about spaces and act on spaces. But I always had the assumption that the acting on spaces was some long-distance future thing, but now you're acquiring a robotics company. And so maybe talk a little bit about the timeliness of this and the intentions.

**Fei-Fei Li** (2:48)
Yeah. So first of all, it doesn't just take robotics to act within spaces or to interact, right? I mean, look at the creative field, whether it's VFX or gaming and or design, many use cases, you can create and act within virtual spaces.
World Labs thesis has always been that the world we live in can be multiverse, that we create technology to allow people, builders, developers to act within different spaces. Having said that, the ability to act within the physical space is one of the most exciting and most profoundly important capability of the future AI world. So robotics is very much that. So World Lab has always believed that robotics is an important application as well as use case of spatial intelligence and world modeling. So by joining force with inviting SceniX and SceniX team to World Labs is part of our long-term vision and mission. We've always committed to that.

**Martin Casado** (4:01)
Amazing. So, Yunzhu, you're the co-founder of SceniX. So maybe provide everyone with a quick overview of your background and what SceniX does.

**Yunzhu Li** (4:09)
Yeah. So I'm Yunzhu. So I'm currently co-founder of SceniX and also assistant professor at Columbia University. So my research started from my PhD at MIT and then postdoc with Fei-Fei.

**Martin Casado** (4:22)
Really?

**SPEAKER_4** (4:23)
Yes. That's great. The world is small.

**Yunzhu Li** (4:27)
Throughout my career, my goal has been very simple. Trying to help the robots better perceive and interact with the physical world. So I'm a very practical person. I want my robot to work in the real physical environments.
So for SceniX, the unique opportunity we see is that there has been a lot of bottlenecks. Right now we see faced by the developments of general purpose robots, especially around training and also around evaluations.
So at SceniX, we are developing what we call a real-to-seem-to-real pipeline. We're going to map the real environments into the digital world that has the best alignments with the real environments. By alignments, we mean that whatever happens in the digital world is also going to happen in the real environments, such that we can replace all the data, all the evaluation we need in the real environments by using the data that can generate at a scalable way in our digital world. So that is how everything started. In SceniX, we put together a very, very strong and best teams around robotics, robot learning, and also simulation and rendering, trying to build this real-to-seem-to-real stack to solve some of the key bottlenecks.