Zuckerberg's Secret Plan To WIN The AI Race | Meta AI Chief Reveals Future

What's it like working with Mark? What are some things that you've had a completely different experience with? I think one of the things that's really struck me in working with him is how quickly he sees the future. — Ladies and gentlemen, Mr. Alexander Wong. — Back in 2022, he became the youngest self-made billionaire in the world. — Chief AI officer at Meta. — Started a company when he was still a teenager, went through Y Combinator, and then built scale AI. Alex Wang is the most expensive aqua hire yet, $4. 3 billion. He's a fascinating character within the valley — and he now leads Meta's super intelligence labs division. — You work very closely with Mark. You're building a meta super intelligence. What is meta super intelligence? You know, the discoveries that we make over the course of the next 5 years in terms of AI are going to be some of the most monumental discoveries of human civilization has ever made. You know, I have the Meta Gen 2 Raybands, right? And I just feel like maybe you guys are running a very old version of Llama there. It just doesn't feel like modern AI yet. Do you have an estimate for when we'd have modern AI on the glass? uh very soon.

Ladies and gentlemen, I'm with somebody um who I think is very special, who I think um you know is somebody who spearheads the AI race but is slightly invisible to the public. Like you're much less public these days compared to everybody else in AI. So, thank you so much for doing this. My last interaction with you was I think at breakfast. We did breakfast at MEA uh at the campus. And you know, one of the questions I had for you at that time was you had this fidget spinner — and it was a very different fidget spinner. I don't know. I've never seen anything like it. What was it called? There's a there's this great I think it's a British company called Metmo that makes these uh very uh high-end fidgets. Uh it's a good company. It's — very cool. We're sending Metmo some sales. Uh but you know, Alex, I want to start with this question

right? Like what is it that you do now? I know you from the scale AI days, right? Uh but today I know that you work very closely with Mark. You're building a meta super intelligence. What is meta super intelligence? Uh for everybody, you know, watching. I mean first uh Mark and myself we very strongly believe that this is a very special time in human history and you know the discoveries that we make over the course of the next 5 years in terms of AI are going to be some of the most monumental discoveries of you know frankly the human civilization has ever made. And so MSL metsumer intelligence labs was entirely dedicated towards how do we build and develop the most optimal organization to be able to both deliver the breakthroughs and the scientific advancements necessary to deliver super intelligence and then also build the products that will enable this technology to be deployed to billions and millions of people worldwide. And one of the things that makes Meta such a special place for all of this is the fact that we have such incredible scale and reach through our products. You know, three and a half billion people utilize our platforms every single day. That puts us in an incredible position to actually bring this technology to the world in a way that's really different, we think, from many of the other AI labs out there. And then we also you know um we had the opportunity to seven months ago when I joined really kind of design the org um and design the team from a blank slate on what is the optimal team look like for the future of super intelligence. So you know we really embraced how do we build the best possible scientific foundations for this organization? How do we have the highest talent density? How do we bring the very best people together and build the best possible environment for breakthrough research to occur?

— Interesting. um how do you balance commercializing some of these products along with research because from my understanding um and what is available publicly it seems that you come more from a products perspective like you've done scale AI you've helped some of these product companies really grow uh how does it feel like going to research and how do you balance both at the core we need to be researchled because fundamentally um we are in such a special time and moment when it comes to frontier AI I technologies and breakthroughs that um I really think that uh you need to be very focused on the research um and the opportunity to actually push the frontier to have very real breakthroughs uh in super intelligence is just magical. And so we're frontier or we're uh research driven to be able to push the frontier, but we actually view it as like a flywheel internally for all of meta. So um by building frontier models and building models that um are uh are pushing the boundaries of super intelligence that enables to build incredible products um and it's kind of a base material that allows us to build some of the most interesting and innovative consumer products in the world. Those products as they gain scale then give us the ability to grow our infrastructure footprint and to build um you know large scale infrastructure some of the largest scale infrastructure in the entire world and then that will enable us to build even greater models and continue scaling our research efforts. So, um, it actually is like one virtuous flywheel within Meta. And I think that's a lot of what excites me as well is that we're not, um, uh, I think we view this as a very evolving, uh, and, um, and continuous discipline to continue advancing the models, products, and infrastructure all in tandem with one another.

— So, what's the team like? Like how do you structure the research team and where is handoff to products? like how does it like if you can give me like for example an example of something you're working on what's the team structure for that like and then when is handoff to product that would be very useful yeah so actually one of the things that has really struck me has been um if you look at a lot of the most successful AI products and developments that have happened they come from a um a tandem effort between research and product so um we're I think past the phase where it's just about research in you know a corner and then that hands off to product people and then they deploy that. I think if you look at a lot of the biggest breakthroughs like chatbt or cloud code or a lot of the things that we're working on it comes from um you know researchers who are thinking about the product and product people are thinking about research and then working handinhand with one another to sort of co-develop the best possible products. Some of the things that we're

really excited about are personal agents. you know, recently, um, Manis released, uh, agents that are working 247 on behalf of our users, um, and are constantly working to, uh, you know, accomplish your goals or make your life better. And we really see that as, um, this is the first of, uh, a whole series of of, um, products that we're excited to release around personal agents. It's one of the areas where we think there's some of the greatest opportunity to actually give a more powerful version of AI to every single person in the world and I think will be one of the things that we'll look back on a decade from now and view as one of the big breakthroughs in AI productization. Yeah, I really like Manis. I remember using it, you know, a few months ago. I keep going back to it again and again. It's a cool product.

Um, do you have a sense of what Meta's identity is in the AI battle? I feel like, you know, Anthropic has one. It feels a very It feels like it feels very um, you know, machines of love and grace style. Open AI has one. It's very consumer pop friendly one. But like Meta's identity is still very much on device. It at least to me as a consumer, it feels like ondevice. It's there, but the device is like up front and center. But is there an identity you're building for Meta Super Intelligence Play? Yeah, I think um I think what we really believe in are personal agents deployed globally. So, one of the things that makes us unique is that we are a global company and uh we have half of the world using our products every single day. I mean that is just um an incredible amount of reach and it means that as we deploy powerful personal agents to everybody in the world. It creates totally new opportunities I think um are very hard for any other lab to actually fully accomplish in terms of what does that mean for entire communities? countries? What does that mean for um you know the whole world as we all on board onto this technology together. Um the other thing that we're really excited about uh is the sort of continued um what does the

hardware vision look like, right? And uh this is an area that we've been investing in for many years are wearables and sort of the next form factors for consumer hardware. And we think that with personal agents um that vision has never been more real where I think you're going to want your personal agent to be on a constellation of peripherals uh in the future and you're going to um we're going to expand beyond the phone into a world where you're going to want your personal agent to be with you in a bunch of different ways. uh that um that will always be on be, you know, see what you see, hear what you hear, uh and will be able to just help you in a way that's much deeper than and then than even the devices today are able to help them. — Cool. Like a like an always on friend who's with you on all your devices. That's why cool. I think there's a lot of other companies trying to do that, but I think you have the step ahead because I've already worn the meta hardware products and I'm already comfortable with it. So it's very easy to say well here's an update which allows you to have you know this god tier intelligence on which actually brings me to a an aside point

which is you know I have the meta gen 2 ray bands right um and I just feel like maybe you guys are running a very old version of llama there um it just doesn't feel like modern AI yet. — Yeah. — Do you have an estimate for when we'd have modern AI on the glass? — Uh very soon. Um you know I think uh we've been you know when I got to Meta something like 7 months ago um the entire focus was let's set up this organization uh in the right way for the long term so that we're not just setting us setting ourselves up to cut a corner here or to optimize for some short-term outcome but mortgage the long-term opportunity. We're going to set up it with the right set it up with the right scientific foundations. We're going to set up with the incredible talent density and the focus on long-term science. We're going to remove artificial deadlines so that we're actually building the technology at the best pace. And what we've seen from that is actually over the past 7 months, we've built the foundations incredibly quickly. And now we're at a moment where I think over the coming months, you're going to see incredible velocity coming from us. And that'll continue throughout the course of the year. We think that um over the course of the full year, we will really be pushing the frontier in a very exciting way across many dimensions of the technology. Um so uh so stay tuned. I know it's been a long wait for many people, but uh we're really excited about what's coming. — Yeah, because I just feel like that's a very easy, you know, sort of upgrade for me, right? Or everybody else, which is just have those glasses be super because I just feel like they're being artificially restrained by a very old AI on it. And I just know what modern AI can do. and you already have access to the camera, audio, uh you can do wonders, right? Uh but — to your point, we've already sold millions of units and it's already a ubiquitous technology and so I think the opportunity is just immense. — Yeah, I think it's one software update away from superpowers. So, I'm very excited about that. But I think it's

incredibly mature of you to come in and first build out the AUG. And it's something that I've learned like this year uh compared to you know five or 10 years ago to build out the AG for velocity a year later. Um how do you learn all this? Like what's the difference between you as an 18-year-old entrepreneur you know starting scale AI versus today building you know what you're building today? Like what's the difference between you as an as an entrepreneur? — Yeah. I mean I' I feel like I've learned just so many different things. Um I think one thing when you're young you're very impatient, right? And uh and I think you know this as well as I do. Um you know I started my company uh right out of college, dropped out of college and um you know you you're so impatient to make things happen that and that's both a great strength and a great weakness. Like I think on the one hand you do you can make things happen faster than other people would expect but you're also um uh not necessarily setting things up to be long-term sustainable and to be um to create long-term advantages. And one of the things that um I've thought a lot about, you know, if you sort of study the history of uh of great businesses in Silicon Valley or even just broadly in the sort of like history of business, the ones with true staying power have built some sort of foundation that is actually very difficult to replicate. And it's something that is it's almost like a seed that is planted and grows over the course of of you know, in many cases decades. And so I think a lot of um a lot of how we think about how we thought about building MSL and how we think about building teams and um you know accomplishing big things going forward is how do you set something up such that uh it has durability and it has a um it has a differential point of view all the way down to the organization and that enables it to grow and expand and develop in a way that is um that will be continue to be differentiated long into the future. So I think this sort of mix of you know I think you know to put it pithily I think you can't let your impatience drive you um too far and you need to um it's important to always be thinking about what foundations are you building and what does the long-term story look like. — Yeah. You know if I had to summarize the last 10 years of my you know entrepreneurial career I would come up with the same insights. slow intentionally slow down build for the long term and then eventually and also put the right people together right because you know and they need like three or four years to bloom so I

totally get you hey what was the scale exit like I mean I don't even know if you can call it an exit right so — they're still going — yeah they're still going right like I would say what is the what was the relationship why do you go decide to work at you know Meta super intelligence like how did that conversation with Mark happen give us some insider your information. — Yeah. Well, um I mean it was incredibly non-standard. Um and I think the way it happened was even um was very surprising because it took you know Mark is obviously quite a bold and visionary leader and I think it really took um you know uh that level of vision for the whole thing to come together. Um, and I mean it was an incredible I think milestone for scale and everything that we've done. Um, and scale continues on and I think that team is continuing to execute and deliver uh on really incredible um outcomes for enterprises and governments and um continues to uh crush it. But you know the opportunity that we saw really was um you know there's it was an incredible milestone for scale and it was a way to kind of give back to all the people who have uh supported scales um you know success to date including the investors and the employees and everybody involved while also um setting scale up for the future and frankly the opportunity that I saw with Meta was just astronomical. I think that um you know sometimes in the middle of these AI races everything just feels so um pressurized so you can sort of lose sight of things and um I think at that time you know a lot of people were weren't giving meta the credit it deserved in terms of I mean it has all the ingredients for incredible success in AI. It has the distribution. It has the billions and billions of users. It has the scale, it has the business model, it has um the incredible talent, has the infrastructure. And so all the pieces were really there. And I think the opportunity to really um kind of lock everything in a way that allows us to allows Meta to really um succeed and thrive in the long term was very exciting. — Very cool. You know, I have this question that I ask almost everybody

you know, in the AI race, right? which is uh you know I'm sure you have some ideas and thoughts about AI that your peers don't agree with right some way it's going to go in the future or some you know method of training or whatever it could be right uh do you have an insight that you feel your peers might not agree with I'm talking about your peers in AI I think some people in the industry agree with me on this but um one of the things I think is of paramount importance is developing the technology with extreme responsibility And I think a lot of the concerns around safety um you know both the traditional concerns around AI safety as well as new concerns around how do you ensure that this technology is used safely by the billions and billions of people who are going to use it every day. I think those are incredibly important and I think we're seeing this with as with any new technology as it gets deployed um you know they raise novel safety concerns and the responsibility really is on us to develop the technology um in in a responsible way. You know, the other piece that's very important for this is the vision of the future that we see where it is a personal agent, something that is sort of with you all the time that you really trust with your goals and your hopes and your fears and sort of everything in your life. To build that technology effectively requires just a huge amount of trust from our users, from the public, from governments, from um from every stakeholder that you could possibly imagine. And so um we really take the sort of the need to build safely and thoughtfully extremely highly and I think this is shared by some in the um AI community. I think some people are have you know moved away from some of these commitments but it's something that we're uh I at least take

extremely seriously. Would you have like a chief philosopher to set the tone for your AI? I think Anthropic has somebody like this now. Um, Gemini is very like, you know, rate of refusals is very high. It's very bland. Uh, would you have as meta have a chief philosopher to set the tone for how that AI behaves? Yeah, we actually we collaborate with uh a number of both philosophers and psychologists to help us develop and build the behavior of the model in a way that we think will be most conducive for um being helpful and empowering our users to accomplish their goals. And you know, it's funny. One of the things that we've spent a lot of time thinking about is how do you develop kind of like a um uh a mutual uh you know, in some ways like a um uh like a mutual relationship between the humans and the agents where the humans obviously um want the agents to be successful and the agents want the humans to be successful. um and figuring out how to engineer then design. That is something that's I think very important for all of this to work out effectively. Very cool. I have one

last question for you because I've taken a lot of your time. What's it like working with Mark? What's his working style like? Uh what are some of the things that the public says that are true in terms of working style? What are some things that you've had a completely different experience with? Well, I think first Mark is um I mean Mark is one of the most you know notable individuals in technology for you know the past few decades and I think he um I think there's a lot out there about him that is not fair from having worked with him very closely. I mean first he is just like in many ways a very regular guy. He's a total family man. Um he uh is very devoted to his children and his family and his wife and um I think uh he's his personal values I think are quite commendable. But what's more than that, I think as a leader, he is um incredibly bold and ambitious and um and I think one of the things that's really struck me in working with him is how um uh how quickly he sees the future is maybe one of the terms I would use. I think he is able to take a technological advancement or something that's happening um all the way at the technology level and then really play that forward in terms of what does that mean for our users, consumers, what does it mean for businesses, what does that mean for our entire ecosystem and then um work with everybody on the team to make that happen as quickly as possible through Meta. So um I think he's been a very uh I've feel very lucky to be able to work with him. one of the sort of like great entrepreneurs of our time. Um, and uh, yeah, I think it's a real pleasure. He enables me and I think the whole team to dream bigger than uh, than we would otherwise.

— Very cool. Thank you so much, Alex. This was very enlightening. I learned so much about, you know, Meta Super Intelligence. I can't wait for, you know, superpowers to be on my glasses. I also can't wait for the new ones, right? Um, I saw the displays at Meta Connect, but uh, you know, I don't think they're available in India yet. So, at some point I want to get my hands on one and just, you know, use all of the AI you put in there. I can't wait to see all the cool stuff you do with the neural band as well. Um, so good luck and uh yeah, I'm I'm going to continue buying and using your products. — Yeah, it's going to be the um the future will be here faster than we think. — Yeah, this year. — Yeah, — this year. Awesome. Thank you so much and make sure you subscribe. Bye.