What's Beyond ChatGPT? The 'Godmother of AI' Has a Plan | The Circuit transcript

I hear you love walk and talks. Yes, because we sit too much. Yeah. And also our company is just next to this park, so it's great. Is it all AI talk all the time here? I don't know other people's talk, but I talk AI all the time. But that's the only thing I know. Fei-Fei Li is a giant in the field of computer vision, a branch of AI dedicated to teaching machines to see. She made a breakthrough with ImageNet, a visual library that sparked the modern AI revolution, earning her the title, 'Godmother of AI'.

And she's been a pioneer at AI's center ever since, as a Stanford professor, a Google executive, an advisor to US presidents, and a relentless advocate for AI that serves people. I feel the leaders of AI are not talking enough about empowering humanity. They're talking too much about replacing humanity, replacing jobs. Now she's adding startup co-founder to her star resume. What's it like running your own shop? I feel like a tiger mom.

While the rest of the AI world doubles down on large language models like ChatGPT and Claude, Li is betting on a new frontier, world models. She's building AI that aims to predict what happens next in the real world, not just the next word in a sentence. So what can world models do ultimately that LLMs will never be able to? Can words put down fires? Can words cook an omelet? Li and her startup, World Labs, is competing in a crowded field of rivals, all making the same bet that world models are the next big leap in AI.

Did you ever imagine AI would be this big? Have I imagined the entire civilization is going to be redefined by AI? The cultural shifts, the geopolitical landscape? I would not have imagined that. Before she became a leading AI scientist, Li was just a curious kid looking at the world. What was young Fei-Fei like as a kid? It was '80s and '90s in China. My city was Chengdu. My dad is quite a curious soul about nature, so I got quite a dosage of chasing after bugs and, and running after puppies and going to the mountains to, to draw and sketch with my dad.

And, you know, reading. Cutting your hair short, loving aerospace and physics. Did you see yourself as a rebel? As a kid, right? You're preteen. You almost have to be a rebel just because you want to make a statement for yourself. But the love of nature and science and physics, the love of aerospace and outer space, those are part of my identity. You emigrated from China to the US in - New Jersey. In the 90s. Yeah. What was it like coming here as a teenager back then?

That was tough. Shifting the whole thing, culture, language, life as a teenager is perhaps one of the hardest times because you're finding who you are and then suddenly you don't even know the world, right? Li learned English, finished high school, studied physics at Princeton while running the family dry cleaning business on weekends, and followed her dreams to Caltech, where she earned her PhD and became a computer scientist.

You've been studying artificial intelligence since then. It was super niche. Yes. What was the field like back then? That was a beautiful period. It was really pure curiosity because there was no money, there was no power, there was no fanfare, there was no hype. We were there just the same as scientists look into the sky, go down in the ocean. I was deeply curious. How does AI see and how is it different from how you or I see?

We use our eyes to drive the sensory system to turn that into signals in the brain, and the brain does computing. It's not that different for computers. We need to learn the pattern of the world and understand objects, colors, environments. A lot of seeing is preparing humans to act. You wake up this morning, you hug your kids, you go downstairs, prepare some breakfast, grab your key, drive to your work. Everything I've described so far, you've done that with your spatial intelligence.

So it's got to be hard to get computers to do that. Yes. Li was working on this back in 2006. She built ImageNet, a massive catalog of 14 million pictures in over 21,000 categories, the largest assembled at that time, because Li saw that algorithms needed data to get smarter. So what was the spark for ImageNet? Nobody was paying attention to data. My students and I had that epiphany that learning needs to be driven by data.

In 2010, Li turned ImageNet into a competition. Who could build the best algorithm to correctly identify the most images? In 2012, Geoffrey Hinton's University of Toronto team entered with AlexNet, an algorithm powered by NVIDIA Graphics cards. The result marked a turning point. That combination, massive amount of data, neural networks, and GPU computing power became the golden recipe for modern AI and cemented Li's legacy.

What do you feel when you look at this? It's not the eight of us. It's the entire humanity. That's really the main story here. Because this comes from the photo of, what, about a hundred years ago when industrialization was in the booming phase and big urban skylines are being built. That was a civilizational moment. It's amazing that you're being recognized here, but like, could they have centered the photo? Come on.

It's true because there's more space here. I asked you about being the godmother of AI a few years ago. You did. How do you feel about that title? You know, Emily, I would never call myself godmother of anything. Remember, Emily, when you asked me, I was like, oh. I was taken aback because I don't naturally think about myself as godmother of anything. That's not my personality. I focus on work. If I rejected that on that spot, we once again would be in a situation where women just don't get recognized the same way as men.

I want more women to be called godmother of whatever creation, innovation, discovery that they have done. So do you embrace the term now or? Embrace is a big word. I don't go around and say, "Hi, I'm Fei-Fei I'm the godmother of AI." But people have adopted that term thanks to you. Artificial intelligence had long been discussed in policy and tech circles as something perpetually right around the corner. Until ChatGPT, AI went from a niche research field to the most talked about technology on the planet.

Large language models, image generators, video generators. Suddenly it seemed like everyone was or wanted to be in the AI business. And let's be honest, things have come pretty far. Li saw an opportunity and launched her own startup in 2024. What's it like running your own shop? So here's the thing. I'm by far the most senior in the company. From my co-founders to my engineers and researchers and scientists, they're so talented, but they're also young.

I do feel like a mom. And oftentimes I feel like a tiger mom. I do run this shop as, I would say, high standard. Li is working on advancing world models. If ImageNet taught AI how to see, this technology aims to guide AI through the physical world because describing how to catch a ball and actually catching one are very different things. And super intelligence, she's betting that lies beyond chatbots. The rest of the AI industry is focusing on LLMs.

What can't LLMs do? If we want to create a world where we continue to push scientific discovery, where we want machines like robots to be a partner to us, all this language cannot do it alone. Building world model and spatial intelligence is not about anti - LLM. It's about the next frontier and the next chapter. So what exactly is a world model? World model at this point is an overloaded term. We look at spatial intelligence as three different kind of functions.

One is rendering, one is simulation, and the third one is planning. Rendering is the world model outputs beautiful pixels for humans to consume. Most likely you're thinking about [OpenAI's] Sora. The second class of world model is they do simulation, but it doesn't serve just humans. It serves machines. They are focused on capturing the actual structure of the world, the geometry structure based on physics. The third kind of world model planning helps you to know what is the next thing you need to do.

For example, if you have a cup, a world model that serves as a planner will let the robot know, pick it up and put it somewhere else. And that is a world model that is very closely coupled with robotics. Marble is World Lab's first step towards creating a world model. It's a platform that lets anyone generate an explorable, editable 3D world from a single visual or text prompt. Now, this is a showcase page of some user-generated world.

You can see they created a room, a beautiful room. Now you look at this, you're like, Fei-Fei, this is no different from a picture. But here's the thing. It actually is a world because I can navigate in it. So like a game, I can move forward. I can turn around. I can go anywhere. Here, it's a fully consistent 3D world. So who or what companies are using Marbel right now? Why is Marble useful? For example, virtual production.

In movies, people are using Marble because they can shoot actors in any environment. Game developers. Marble has completely lowered the amount of resource and time one needs. We also have robotics example. This is a collaboration with NVIDIA where they're using Marble environments to augment the training of robots. What are you training these models on that others don't have? We are training these models on two things, right?

One is specially prepared data. Pixel data are more nuanced than language data in the sense that there's more information in a picture. There's camera information. Another one is algorithmic and architectural innovation because no one has created generative world models as we have in terms of creating 3D and eventually 4D worlds. So would you say that's the secret? Yeah, I guess so. Well, the real secrets are people, as I always say.

But yes, the data and the algorithm and the, the system we have built. You've raised a billion dollars. How is the business doing? The business is still early. This phase of World Labs, we're focusing on building the technology. Building the technology isn't the only part of the job. When Li isn't heads down at World Labs, she's out making the case for the next frontier of AI. Absolutely. Please welcome to the stage.

Fei-Fei Li, co-founder and CEO at World Labs for a conversation with Bloomberg's Emily Chang. All of this rolls up into robotics, so I, I want to get your take on the field. And humanoids in particular. Funding for humanoids hit $6 billion, but you know, they still can't load my dishwasher as fast as I can. They still can't go get my Amazon packages. Will world models, world labs close the gap between hype and reality?

That's a loaded question, Emily. First of all, first of all, robotics is going to be one of the most important revolution in human industrialization. $6 billion is too small, right? If you look at self-driving cars investment, if you look at language models investment, it took way more than $6 billion. Are we going to close the gap? I do believe World Labs is working on one of the most critical technology in the spatial physical intelligence.

And obviously that's the, that's the hope. But Li isn't alone. World models are the tech industry's latest obsession with startups and tech giants alike all sprinting to build them. For anything from design to self-driving cars, robots and factories, to eventually machines that can navigate the unpredictable reality of the human home. You're competing against big players with deep pockets. How worried are you about that?

As an entrepreneur and a co-founder, CEO, I'm paranoid every day. I don't think there's a moment I would say, "Hey, I feel so relaxed." You know? So yes, I am worried, but am I paralyzed? Absolutely not. We have an incredible team. We also have the focus. You know, a lot of big companies, they have a lot on the, on the table. We have one thing on the table, and we're focusing on that thing. Emily, Nice to meet you. The war for talent is so fierce.

Why work with Fei-Fei when there are so many powerful AI companies out there? Well, I started working with Fei-Fei way before it was cool in 2012. Yeah, I did my PhD with Fei-Fei at Stanford way back in the day. You can go to a lot of big tech, but your hands can't change that trajectory in, in many instances. Here, we're 50 people. Your hands can change the trajectory of this company. That's a beautiful thing to have in your life.

World Labs may be a small team, but the investment in world models is gigantic. $3 billion and growing. Still, it's early days. The field hasn't even agreed on how to build them yet. Would you say it's like 2019 for chatbots where everyone was chasing LLMs and trying to make it happen, but they hadn't cracked the code yet? Is that where we are for world models? Yeah, that's probably a fair description. We're early. We're a lot earlier compared to LLMs.

But Will there be some sort of explosion and aha moment where we're like, "Oh, now we understand." If we do it right, yes. That's the magic of technology and science. When it hits that milestone, it becomes magical. There are skeptics in the AI and robotics world that say, "This isn't the next breakthrough. It's just the next hype cycle." What do you say to that? I think even a good science can be hyped. I believe spatial intelligence and physical intelligence are fundamental to machine intelligence.

And these are the frontier questions that I believe firmly in as a scientist, as a technologist, and also as an entrepreneur. I believe they will provide incredible market value. Building wrld models is incredibly resource intensive. Do you need more power? Do you need more capital to get to where you want to be? That we don't know yet. We're too early. We're likely to need more power and more resources. And can you get that?

I don't know. We have to do a good job to, to earn it. Getting world models out of the demo phase will take more time and money. Meanwhile, investment in generative AI has soared, and Americans have strong feelings about it. I'm sure you've seen the video of former Google CEO, Eric Schmidt, getting booed at a college graduation. So today we stand on this edge of another technological transformation. You spend a lot of time with students.

What are they saying? And if they're scared, are the fears justified? Yeah, I do spend a lot of time with students. Even Stanford students reflect some of this mixed sentiment. There is anxiety. There is sense of hope. There is also excitement. There is also confusion. There is also simultaneously a sense of dignity and agency when AI can help me do things that I couldn't do before. And a sense of loss of dignity and agency if AI is going to take my job.

AI Has Got to go. So what happens if the US loses faith in this technology while the rest of the world races ahead? US is such an important country in terms of its impact to the world that if we are not showing a positive attitude and positive path towards AI, everybody loses. And I don't wish for that because US has been a thought leader in the world when it comes to technology and science and economy. And if we can show that we can create incredible technology and incredible economic value using AI and have a positive cultural impact, the world will see it as a role model.

Li knows a thing or two about AI and its impact. Over her career, she took roles at big tech companies, venture capital firms, co-founded an AI institute at Stanford, and advised US presidents and the United Nations on AI policy. There's nothing artificial about artificial intelligence. It's inspired by people. It's created by people. And most importantly, it has an impact on people. You've advised President Biden, President Trump, the UN on technology and AI policy.

How do you approach conversations with world leaders? I don't go in hyping. I don't go in providing extreme rhetoric. Either it's total utopia or total doomsday. It's very important that whoever I talk to knows that I'm a scientist. What do they need? They need scientific facts, but I think it's important to be at their service and to speak my mind, to push back if they're wrong, because that's my responsibility. And have they been wrong?

Oh, yes, for sure. We all have been wrong. This technology moves so fast. I don't blame them. Most of our policymakers don't come from computer science background. What is the role of regulation? What should that look like? First and foremost, root that in science, not science fiction. A lot of the AI policy world conversation with people from Silicon Valley talk about the extinction of humanity, the, the, the AGI machine overlord that distracts the real policy work.

The second recommendation is ensure a healthy ecosystem, resource the public sector, resource STEM education in K-12 or K-16. Human capital at the end of the day is the most important resource of our world. And we want a thriving society of people, not a thriving society of just machines. What do you worry could go wrong with world models? Like if we're giving people even more realistic and more powerful AI, does that create even more opportunities for really bad things to happen?

World models, language models, these are powerful models that can create mis and disinformation. Empowered robots can be weaponized by bad actors and students who are not properly motivated can use technology as a lazy crutch instead of a empowering learning tool. I, I worry about that a lot. So I think a lot of things can go wrong with technology, not just AI. It could have gone wrong with electricity, with cars, with, you know, PC, with internet.

Some of the most powerful CEOs in AI right now have been accused of having God complexes because they seem to think they know what's best for humanity. What do you think of that term? I think it's dangerous for any individual to think they know better than everybody else. As a CEO, as an entrepreneur, our founding premise is we are here to contribute to the society and to empower people. It's not our position to make every single decision for people.

But isn't that the path we're on? I mean, these are really powerful people. I think it's too early to tell Emily. I'm not being naive. I know what you're talking about. I also have my concern. I don't think having God complex is constructive, and I wouldn't want to do that myself, but we have a democratic society. This is another reason I think our civil society should not give up on AI. We need the voices. We need the collective governance.

But let's now throw the baby with the bathwater. The governance shouldn't be, let's stop AI, because this is a technology that can discover cure for diseases, can empower students and teachers, can help our elderly. So that's the baby here. But right now, we are in a very messy period. This is also why I feel personal responsibility to speak the truth I believe in as a scientist and an educator. Li has spent her life teaching machines to see.

She gave AI its eyes. Now in her second act, she's trying to give it a world to live in. As the scientist who helped spark the modern AI revolution, perhaps we shouldn't put it past her. Where is this all going? Where are we in five years? This This is where I reveal I'm an optimist. The, the arc of history is long. I paraphrase Dr. King. I believe it bends towards benevolence. Now, we're not a perfect world of people and community, but 2026 today is better than 2026 BC for the majority of the population.

And I think it's because despite all of our dark underbelly, we have it in our DNA. We want our offsprings to live a better life, and we have moral compasses collectively to move the society towards benevolence. My hope is in humanity. Is it true you're obsessed with UFOs? When I was a kid. Like, Have you read the documents they're declassifying? No. I think it's part of that dreamy curiosity as a kid is what's out there.

Do you think there's aliens out there? So as a physics student, you learn Drake's equation. Drake's equation computes the probability of potential of outer space aliens. So there is a potential number. Wow. Okay. Favorite sci-fi movie? Contact. By far my favorite. There you go. Intelligence... somewhere out there. Yeah.