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. Alexandr Wang. 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 acqui-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 five years in terms of AI are going to be some of the most monumental discoveries human civilization has ever made. You know, I have the Meta Gen 2 Ray-Bans, 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?
Ladies and gentlemen, I'm with somebody who I think is very special, who I think, 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 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, 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 very high-end fidgets. It's a, it's a good company. It's very cool.
We're sending MetMo some sales. 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? But today I know that you work very closely with Mark. You're building a Meta Super Intelligence. What is Meta Super Intelligence for everybody, you know, watching?
I mean, first, 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 five years in terms of AI are going to be some of the most monumental discoveries, you know, frankly, that human civilization has ever made. And so MSL, Meta Super 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, we had the opportunity to, seven months ago when I joined, really kind of design the org and design the team from a blank slate on what does 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. How do you balance commercializing some of these products along with research? Because from my understanding 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. How does it feel like going to research, and how do you balance both?
At the core, we need to be research-led because fundamentally we are in such a special time and moment when it comes to frontier AI technologies and breakthroughs that I really think that you need to be very focused on the research and the opportunity to actually push the frontier, to have very real breakthroughs in super intelligence is just magical. And so we're frontier or we're research-driven to be able to push the frontier, but we actually view it as like a flywheel internally for all of Meta. So by building frontier models and building models that are pushing the boundaries of super intelligence, that enables us to build incredible products, 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, 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 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, I think we view this as a very evolving 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, if you look at a lot of the most successful AI products and a lot of the most successful AI developments that have happened, they come from a tandem effort between research and product. So 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 ChatGPT or Claude Code or a lot of the things that we're working on, it comes from, you know, researchers who are thinking about the product and product people who are thinking about research and then working hand-in-hand 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, Meta released agents that are working 24/7 on behalf of our users and are constantly working to, you know, accomplish your goals or make your life better. And we really see that as this is the first of a whole series of 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 Meta AI. I remember using it, you know, a few months ago. I keep going back to it again and again. It's a cool product. 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 very, you know, machines of love and grace style. OpenAI has one. It's a very consumer-pop-friendly one. But like Meta's identity is still very much on-device. At least to me as a consumer, it feels like on-device. It's there, but the device is like up front and center. But is there an identity you're building for Meta's Super Intelligence play?
Yeah, 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 we have half of the world using our products every single day. I mean, that is just 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 are very hard for any other lab to actually fully accomplish in terms of what does that mean for entire communities, what does that mean for countries, what does that mean for, you know, the whole world as we all onboard onto this technology together.
The other thing that we're really excited about is the sort of continued, what does the hardware vision look like, right? And this is an area that we've been investing in for many, many years, are wearables and sort of the next form factors for consumer hardware. And we think that with personal agents, 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 in the future, and you're going to, 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 that will always be on, be, you know, see what you see, hear what you hear, and will be able to just help you in a way that's much deeper than even the devices today are able to help them.
Cool. Like an always-on friend who's with you on all your devices. That's very 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. Which actually brings me to an aside point, which is, you know, I have the Meta Gen 2 Ray-Bans, 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. You know, I think we've been, you know, when I got to Meta something like seven months ago, the entire focus was let's set up this organization in the right way for the long term so that we're not just 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 it up with the right scientific foundations. We're going to set it 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 seven 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 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. So stay tuned. I know it's been a long wait for many people, but 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, you already have access to audio, you can do wonders, right? 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.
