What was it like raising funds as an academic now entering this private world to be raising money? You've been in private well before, but to raise funds. Was it easy from this star-studded list? Good morning, Kahlil. It's really good to be here. Well, nothing is easy, but what's really, really hard is making spatial intelligence happen. I'm just so excited that we've brought together an incredible group of pixel talents to work on this really, really hard problem that we now call spatial intelligence. Explain to us what you mean when you say spatial intelligence and what is it that you're building exactly? Yeah. Rachel Well, look, humans have spatial intelligence. It's actually a very ancient ability. We have evolved over millions and millions of years. It's the ability to understand, to reason, to generate, and to even interact in a 3D world, whether you're looking at a beautiful flower or trying to touch a butterfly or building a city.

All of this is part of the capability of spatial intelligence. We see that with humans, and we see that with animals. How do you expect that? We'll see that with computers? Well, that's the problem we're working on. We're already starting to make tremendous progress. The past decade of A.I. has been pretty exhilarating, and people hear a lot about language recently. But truly, in the world of pixels, of vision and spatial intelligence, we've been making progress, such as understanding what's in the picture. To be able to tell a story of what's in the picture, to even prompting a sentence and get up to the image out of it. But what's really the next frontier, which is such a hard problem to crack, is to bring all this into 3-D because the real world is 3D, and human's spatial intelligence is built upon this very native capability of understanding and working with 3D.

So let's put into real-world context that working with 3D applications. Is it robotics? Is it manufacturing? Is it just us interacting with the real world when we put our AI function glasses on? You're Laurel and Carolyn. Those are such foundational technology and such foundational ability for computers that it has implications in a wide range of use cases. To start with, right creators. Creators include not only artists and VFX creators but also designers, developers, builders. And this technology has a profound implication for them. But in the long arc of this, of course, robotics manufacturing, AR, VR. This is, you know, there's a reason that Apple calls their Vision Pro spatial computing. Well, in my opinion, spatial computing needs spatial intelligence. So do many other use cases. Why does spatial computing need VC money? Private sector action. What couldn't you achieve in academia? So this is a whole ecosystem.

We've been seeing this in the air. We've been seeing this for years now. And this dates back to any technology that our society, our country is building. Right? This ecosystem needs upstream, fundamental, curiosity-driven research, which I have spent many years of my life in. But it also needs a very focused drive in the industry. We've got great big tech companies working on related problems, but we also what's beautiful about our ecosystem are startups. There has a tall dream, has the ability to call on the believers who believe in cracking such a hard problem. And we come together and focus all of our energy in solving this truly hard problem that needs to be scaled, needs to be protectionist, and needs to be delivered in the hands of users and customers. Dr. Lee, one of the things that you're most well-known for is ImageNet and a big database of millions of images that really help push forward the field of

object recognition and images. I'm curious how your work on that played into your decision to start World Labs. How are how do you see those two things as related? Yeah, thanks for asking that question, Rachel. I think they're related in into two ways at least. One is that image, and that is one of the earlier work in the field of computer vision, which is in the pixel space. Granted, in that time, you know, more than ten years ago what image that and the derivative algorithms were able to do are still in the 2D space, right. Recognizing objects in photos and eventually telling stories of pictures. But now this is a an intellectual continuation of the early work in computer vision. Now we're into the next really difficult chapter, which is spatial intelligence. So intellectually, I feel it's my life's work in continuation. And zooming out to one layer image that was my more than 15 years ago. It was my intellectual bet on a big

North Star problem, a North Star problem that had really changed the course of A.I. I do believe spatial intelligence is the next North Star for me and for my team, that it will change the course of A.I. One of the things I'm wondering about with the funding for this company is there are a number of big names in A.I. in particular that invested in this. We've got Jeff Dean and Jeffrey Hinton, Andre Carpathia, some of them you've worked with previously. I know several of you were at Google at the same time. How did you pitch them on it? Well, that's the beauty of our field. The first of all, these people have been friends and colleagues for years, or former students. I think they share my belief. I think they see this as such a big problem and they'd be leaving my team when they hear my co-founders, Ben Mildenhall, Christoph Laster, Justin Johnson, and really the entire founding

team, they recognize that while this is a tough problem, it needs people who really can have the ability and belief to crack this. And I think that's why they supported us. You've got money from big-name VCs as well, and he and Horowitz, to name just one. I'm interested more broadly about the rallying call you've had for money to go towards academia. You went to President Biden himself, saying that there needs to be more funding in the public sector as well as the private sector when it comes to R&D, ultimately, so universities can access GPU and compute. Are you still feeling that necessity that the public sector needs money, or have you just sort of given up and gone to the private sector hit a Carlyle? I actually believe even more so now that I'm traversing both the private and the public sector, that seeing the access to compute, access to support in the private sector, I believe none of us

will be here in the private sector without the public sector. You know, imagine that convolutional neural network back propagation transformer models, meaning of this seminal work in AI came from the public sector first. So, I think this ecosystem is so critical, and missing or the imbalance of any component is harmful for the ecosystem. And now, I have personally experienced to see the access we have to resources. It makes me believe even more that our country needs to invest in our public sector, academia, in this kind of moonshot mentality to support, you know, students and faculty and researchers in basic science research.

Fei-Fei Li's Startup Raises $230 Million in Funding

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