00:00:03Everyone is focused on LLM's, chat GPT,
00:00:06Claude, large language models, but you
00:00:07have raised a billion dollars to build
00:00:12something different. Large world models.
00:00:16Make the case for us. What is the bet
00:00:18you're making that others aren't?
00:00:22>> Right. So, um this is my uh co-founded
00:00:26startup, World Labs, and uh we are
00:00:29uh all in in spatial intelligence. And
00:00:32uh the means to spatial intelligence is
00:00:34building a large world model. So, what
00:00:37is the case for us? The case for us is a
00:00:41500 million year story. Is that animal
00:00:44intelligence starts with seeing and
00:00:48moving in a physical world. That uh
00:00:52evolution began with us as animals
00:00:54knowing what the world is, knows knowing
00:00:57who we are, knowing how to move around
00:01:01it, interact with it, and uh much of
00:01:04life, human life, human work life, human
00:01:08private life, has a lot to do with uh
00:01:11perceiving, understanding, reasoning,
00:01:14interaction with the world, including
00:01:19imaginary world of creativity, of uh of
00:01:21uh productivity, uh
00:01:25as virtual worlds. So, unlocking that
00:01:28capability in machines, unlocking the
00:01:31capability of generating
00:01:34from any 3D, 4D worlds, unlocking the
00:01:37capability of reasoning within any
00:01:41world, unlocking the capability of uh
00:01:44teaching agents or robots or or
00:01:46assisting humans to interact with the
00:01:49world is what spatial intelligence is
00:01:52about, and that's what we are focusing
00:01:52about, and that's what we are focusing on.
00:01:52on.
00:01:54>> So, what can world models do ultimately
00:02:02Can words put out fires?
00:02:05Can words cook an omelet?
00:02:08I think there's so much, right? So, we
00:02:10for example, creativity.
00:02:14People design. People
00:02:16whether we're designing interior space,
00:02:18we're designing
00:02:20machines, we're designing we're
00:02:22designing homes, we're designing
00:02:25stories. So much of that is beyond
00:02:25stories. So much of that is beyond words.
00:02:26words.
00:02:30We also use agents. Whether we use
00:02:33agents in virtual world, whether it's
00:02:36for entertainment like gaming, or for
00:02:39more serious industrial
00:02:41industrial applications, whether it's
00:02:43digital twin
00:02:47design or or inspection or or
00:02:49or what kind of
00:02:52many kind of optimization tasks. Or we
00:02:56build robots and to help us to do a lot
00:02:58of things from
00:03:02putting out fire to helping health care
00:03:06scenarios to manufacturing. All these
00:03:08are application downstream applications
00:03:12of unlocking spatial intelligence and
00:03:13building world models.
00:03:14>> So, what's the what do you think the
00:03:16chat GPT moment for world models will
00:03:18be? Like how will we know this has
00:03:18be? Like how will we know this has arrived?
00:03:20arrived?
00:03:21>> Yeah, that's a great question, Emily,
00:03:25because chat is such a consumer behavior
00:03:29that chat GPT moment tends to be used to
00:03:32describe a viral
00:03:36public consumer moment of getting so
00:03:40close to what AI can do. In a in a world
00:03:43of world models,
00:03:43of world models, um
00:03:43um
00:03:45the kind of spatial intelligence we're
00:03:51I'm still trying to figure out if there
00:03:54is a corresponding consumer moment
00:03:57because the kind of applications we are
00:03:59talking about
00:03:59talking about um
00:03:59um
00:04:02tends to be first going to the
00:04:04professionals, professional creators,
00:04:06professional designers, professional
00:04:09developers, uh professional researchers
00:04:11and engineers who will use it for
00:04:14robotics and industrial design and all
00:04:18that. So, maybe we will not
00:04:21necessarily have a consumer moment. But
00:04:23maybe we will. And you know, I I would
00:04:26love to design my home in a much easier
00:04:29way and just change the color of the
00:04:31curtain, you know, with a click.
00:04:33>> All right, that sounds pretty cool. So,
00:04:35in the last 6 months, Yann LeCun left
00:04:37Meta to work on world models, Google
00:04:39shipped Project Genie, Nvidia has its
00:04:42own world models, Cosmos. Nvidia's also
00:04:44one of your investors.
00:04:46What do you have that they don't? And
00:04:49which competitors out there worry you
00:04:50the most?
00:04:53>> Yeah, so first of all, we started World
00:04:57Labs in 2024. I still remember when when
00:04:58we were
00:05:00out talking about world models and
00:05:02spatial intelligence,
00:05:05it was just a year after ChatGPT. People
00:05:07were still totally talking about LLMs.
00:05:10So, we we really had a head start and
00:05:12understanding that this is going to be
00:05:15the next frontier of AI. I'm very
00:05:18excited by that. So, what do they have
00:05:20we don't? Well, first of all, I think we
00:05:22have an incredible team. We have the
00:05:22have an incredible team. We have the conviction.
00:05:23conviction.
00:05:24>> They don't have the godmother, that's
00:05:25for sure.
00:05:29>> Um but but the the world is big and and
00:05:32I think this is just like LLMs. I think
00:05:34there will be many companies doing
00:05:36incredible work in world models. Just as
00:05:4024 hours ago, uh I we kind of got fed up
00:05:44that the word world model has been so uh
00:05:47confusing and being used so in so many
00:05:49different ways that we actually put out
00:05:49different ways that we actually put out a
00:05:50a
00:05:55blog just explaining what a functional
00:05:59taxonomy of world model is instead of
00:06:02mushing everything together. And the way
00:06:04I see it is right now there are three
00:06:04I see it is right now there are three ways
00:06:05ways
00:06:08of calling world models when it comes to
00:06:11spatial intelligence. One is what I call
00:06:13a renderer when the model puts beautiful
00:06:16pixels on the screen. Mostly like video
00:06:18generation model. And the consumer is
00:06:22mostly human eyeballs. And while the
00:06:24model commits to beautiful pixels on the
00:06:28screen, it doesn't necessarily commit to
00:06:30physics and dynamics and geo geometric
00:06:30physics and dynamics and geo geometric correctness
00:06:32correctness
00:06:34because that's for just
00:06:36consuming human eyeball consuming not
00:06:39necessarily for computation and and
00:06:42other other tasks. Then another kind of
00:06:45world model is what we call a
00:06:48a planner. That is more for machines,
00:06:52more for robots where it outputs
00:06:54whatever the input is the state of the
00:06:57world or the action. It outputs a
00:07:00correct action to take to the next step.
00:07:02And you see that kind of world model a
00:07:05lot for robotics applications and you
00:07:07hear that in that context. The third
00:07:10kind which I think is the lynchpin of
00:07:13the the three is a simulator. Is that it
00:07:16actually is consumed by humans as well
00:07:19as machines is trying to respect the
00:07:21structure, the physics, and the dynamics
00:07:25of the world and really simulate the 3D
00:07:29and 4D information of the world as well
00:07:32as well as the semantic information. And
00:07:34a simulator could become a renderer. The
00:07:37simulator could become a planner. But
00:07:39this layer is
00:07:43a huge critical path in my opinion, to
00:07:45unlock spatial intelligence. And that's
00:07:48what World Lab is working on.
00:07:50>> All of this rolls up into robotics, so I
00:07:51want to get your take on the field and
00:07:54humanoids in particular. Funding for
00:07:57humanoids hit $6 billion, but, you know,
00:07:59they still can't load my dishwasher as
00:08:00fast as I can. They still can't go get
00:08:02my Amazon packages.
00:08:04Will world
00:08:06models, World Labs, close the gap
00:08:07between hype
00:08:09and reality?
00:08:11>> That's a loaded question, Emily. First
00:08:12of all,
00:08:14>> That is my job.
00:08:17>> I get it. First of all, robotics is
00:08:19going to be one of the most important
00:08:22revolution in human industrialization.
00:08:23$6 billion
00:08:26is too small. Right? If you look at
00:08:28self-driving cars investment, if you
00:08:31look at language models investment, it
00:08:33took way more than $6 billion.
00:08:41I think it will take time
00:08:44to invest, and it will also
00:08:47hopefully not take the hype, but take
00:08:50the thoughtfulness to invest in the
00:08:52right effort. And, for example,
00:08:54unlocking world modeling and spatial
00:08:57intelligence and simulation layer, all
00:09:00this is part of that that
00:09:04important effort. Um
00:09:06are we going to close the gap? I do
00:09:09believe World Labs is working on one of
00:09:13the most critical technology in spatial
00:09:16physical intelligence. And obviously,
00:09:19that's the that's the hope.
00:09:22>> You've been more measured on AI safety,
00:09:24skeptical of the doom narrative, but
00:09:28also of heavy-handed regulation.
00:09:31When you look across the industry, where
00:09:33do you feel real safety work versus
00:09:33do you feel real safety work versus safety
00:09:34safety
00:09:35safety theater?
00:09:36theater?
00:09:39Is anyone getting it right?
00:09:41>> So, in general, I've been just more
00:09:44measured on every every rhetoric makes
00:09:47me very boring, to be honest.
00:09:47me very boring, to be honest. Um
00:09:48Um
00:09:50I think there's just so much hype. There
00:09:53is so much hype. Um
00:09:55obviously, we need to build the right
00:09:57technology. We need to guardrail the
00:09:59technology. Whether you use the word
00:10:02responsible, you use the word safety,
00:10:04you use the word
00:10:08um um trustworthy, um building the right
00:10:12technology and product so that it can
00:10:16empower, enhance, augment humanity, and
00:10:20not harm them is the goal of any any
00:10:22work we do, whether it's AI or not. So,
00:10:25where is it doing right? I really hope
00:10:27every company, every
00:10:30um every product that's being built,
00:10:32that the people behind it are being
00:10:35mindful of that, and are thinking about,
00:10:37you know, what data are we using? What
00:10:40system are we building? What evaluations
00:10:43are we conducting? What guardrails are
00:10:45we putting in? How do we communicate
00:10:47with our with our users and customers?
00:10:50How do we work with regulators so that
00:10:53when the rubber hits the road, that we
00:10:56are um you know, being responsible. I do
00:10:59believe a lot of this work is happening.
00:11:01It's not happening in a theater, to be
00:11:03honest. For example, so many
00:11:06pharmaceutical and health care um
00:11:09industry uh companies are incorporating
00:11:09industry uh companies are incorporating AI.
00:11:10AI.
00:11:13Literally, I just came from the hospital
00:11:16to come to your to to your panel because
00:11:18I have a family member uh about to get a
00:11:22surgery in in the next 1 hour or so. And
00:11:22surgery in in the next 1 hour or so. And I
00:11:22I
00:11:25I was just in Stanford Hospital looking
00:11:27at where AI is already being used and
00:11:30where AI could be used. And it's already
00:11:34happening. Doctors are using AI to to to
00:11:37help them with charting. Radiologists
00:11:40are using AI to assist them reading the
00:11:43the MRI and the CT scans. I do hope that
00:11:46we have more AI to help our nurses, to
00:11:49help family members. I got this long
00:11:51radiology report last night and the
00:11:54first thing I did is send it to a AI so
00:11:56that it can help me to explain it. So,
00:11:59all this is happening. Um safety
00:12:02measures are happening. Um but there
00:12:05needs to be more in a right way, in a in
00:12:08a scientifically grounded way. Um and
00:12:10that's the conversation that should be
00:12:12taking place instead of what you say the
00:12:12taking place instead of what you say the theater.
00:12:13theater.
00:12:14>> Well, thank you for coming and I hope
00:12:17your person is okay. We all we all do.
00:12:17your person is okay. We all we all do. Um
00:12:19Um
00:12:21the backlash is we all it's being called
00:12:23the AI hate wave. I'm sure you've seen
00:12:25the video of former Google CEO Eric
00:12:27Schmidt getting booed at a college
00:12:30graduation. You spend a lot of time with
00:12:33students. What are they saying? And if
00:12:35they're scared,
00:12:38are the fears justified?
00:12:39>> Yeah, I do spend a lot of time with
00:12:41students. Uh
00:12:42to be fair, my students are pretty
00:12:44privileged cuz they're Stanford
00:12:46students. I think it's
00:12:48I think it's even more important and I
00:12:51try to do it myself that we spend time
00:12:53with our teachers, with our nurses, with
00:12:56our our parents, grandparents. And
00:12:59that's actually something I try to do. I
00:13:02try to talk to K-12 educators. I try to
00:13:05go to places and talk to people where
00:13:07they feel that they're not part of the
00:13:10conversation. And
00:13:12even Stanford students reflect some of
00:13:16this mixed sentiment. There is anxiety.
00:13:19There's sense of hope. There is also
00:13:22excitement. There is also confusion.
00:13:24There's also um
00:13:27simultaneously a sense of
00:13:30dignity and agency when AI can help me
00:13:32do things that I couldn't do before and
00:13:35a sense of loss of dignity and agency if
00:13:39AI is is going to take my job. So, I
00:13:39AI is is going to take my job. So, I think
00:13:40think
00:13:42I think the sentiment is mixed and I
00:13:44really want to point out a lot of this
00:13:48sentiment happens when there's a vacuum
00:13:49of thoughtful
00:13:53public discourse. Right now, the oxygen,
00:13:56the air is all sucked into the polarized
00:14:00extreme of doomerism or total utopian.
00:14:03And when hype takes all the oxygen in
00:14:04the room,
00:14:08that void brews the kind of anxiety and
00:14:11it's actually that void we really need
00:14:13to care about because that's where real
00:14:15people live. That's where real people
00:14:17are seeking answers.
00:14:19And I think it's
00:14:19And I think it's uh
00:14:20uh
00:14:23As a scientist and a educator and a
00:14:23As a scientist and a educator and a entrepreneur,
00:14:25entrepreneur,
00:14:29I'm on ground zero with students, with
00:14:29I'm on ground zero with students, with educators,
00:14:30educators,
00:14:33with entrepreneurs
00:14:35and I really do believe it's is one of
00:14:37my responsibility
00:14:39to not hype
00:14:43and try to speak with with both science
00:14:45and humility and
00:14:47and in inspire people to to recognize
00:14:50this is a technology that can truly
00:14:54empower a lot of our work and life,
00:14:57can truly help us, you know, have a
00:15:00better health care system, have better
00:15:03scientific discovery, have better uh
00:15:06uh better environment, better education
00:15:08if we do the right thing.
00:15:08if we do the right thing. >> Mhm.
00:15:09>> Mhm.
00:15:11We're both moms. We both have young
00:15:11We're both moms. We both have young teenagers.
00:15:13teenagers.
00:15:15How do you think AI will change learning
00:15:17in the college experience?
00:15:20>> AI must change learning. AI must change
00:15:24K to 16 learning. I think this is one of
00:15:27the biggest opportunity for humanity in
00:15:30the next decade to come is that
00:15:30the next decade to come is that what
00:15:36the most precious resource of our entire
00:15:39world is human capital.
00:15:43And when we have gotten a technology
00:15:45that can answer standardized tests,
00:15:49whether it's it's a common core kind of
00:15:50test all the way to
00:15:54international Olympiad math exams, when
00:15:57AI can do better than average human,
00:16:01it's not about humans are bad. It's
00:16:03about we need to change the education
00:16:05system. We need to change how we
00:16:08evaluate. We need to change the way we
00:16:12empower teachers to teach to to educate
00:16:15the next generation of students where
00:16:18they can use these tools, be empowered,
00:16:21and do things that we can never imagine.
00:16:23>> So, do you think our kids will still
00:16:23>> So, do you think our kids will still learn?
00:16:24learn?
00:16:26>> Absolutely. If we teach them right, if
00:16:29the society prepares them right, they
00:16:31should not be all of the kids today
00:16:33should not be scared of AI. They should
00:16:37feel the human agency to to lead AI, to
00:16:40use AI in the right way, and to use AI
00:16:42to make the right to make the impact
00:16:46that they want to make for the world.
00:16:49>> Anthropic CEO Dario Amodei has suggested
00:16:51AGI is 2 to 3 years out. We'll get there
00:16:53by scaling the current paradigm. Demis
00:16:56Hassabis says we're at the foothills of
00:16:58the singularity.
00:16:59You've said you don't even engage with
00:17:01the term
00:17:01the term AGI.
00:17:02AGI.
00:17:05Are they wrong, or is the disagreement
00:17:08about what we're calling the goal?
00:17:11>> I don't engage with the term AGI because
00:17:13the founding fathers of artificial
00:17:16intelligence as a scientific field had
00:17:20this dream of thinking and doing
00:17:23machines and that is a scientific quest
00:17:25and that quest has been my lifelong
00:17:29career and I'm still on that quest. Now
00:17:31I'm combining that scientific quest with
00:17:33making products that can make people's
00:17:36life better and that is the field called
00:17:39artificial intelligence and
00:17:39artificial intelligence and um
00:17:42um
00:17:44I'm okay people call it whatever they
00:17:46want they can call it
00:17:48an Apple that's fine.
00:17:48an Apple that's fine. >> [laughter]
00:17:49>> [laughter]
00:17:49>> [laughter] >> Um
00:17:50>> Um
00:17:51I'm focusing on
00:17:56building a technology can that can truly
00:17:58that can truly make a difference in
00:18:01people's lives and at work.
00:18:03>> What's the one thing you'll have shipped
00:18:04this year that we'll be talking about
00:18:06next year?
00:18:09>> I hope that we will be shipping a model
00:18:12for spatial intelligence
00:18:14that will
00:18:14that will inspire
00:18:16inspire
00:18:18incredibly exciting product
00:18:20opportunities that people haven't seen
00:18:20opportunities that people haven't seen before.
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