The Exchanges

Q which is kind of wild, but, uh, not only that, now you have, uh, a ideal, a personal AI that's gonna tell you, you know, hey, these are some ways to do it. Um, do you think that would have helped you, like, accelerate even faster? Like, you know, talk to, what do you think it's like to start a company today with, with AI in the age of AI?

A Yeah. I mean, I really think, I think we're at this, like, amazing moment in the world where the bottleneck is not the progress of the AI models. The bottleneck is diffusing that through the rest of the world and, and helping the world adapt to this amazing technology that already exists. Like, I think if the models didn't improve at all from today, there would still be, like, decades and decades of, like, total upheaval and change in the economy and how the world operates and, and everything around us. And, Um, so I think it's, as a result, it's like one of the most incredible, it's probably a, like, once in a civilization opportunity to be a dreamer, and to have a vision, and to have ambition, and to impose a view of how the future world should look by building something amazing. Um, you know, one of the things that we were, we were chatting about, um, uh, you know, backstage is, you know, when When I started scale, or, you know, 10 years ago, if you start a company, you had to be, um, you know, it was like David versus Goliath, and you had to be clever, and you had to find, like, an angle into the market, and you had to sort of, like, you know, figure out, um, a way to compete even though you had much fewer resources. And now I actually think with the power of agents, um, and AI broadly speaking, it's much closer to Goliath versus Goliath. Like, I think, but maybe the startu…

AI assessment note: “when I started scale... now I actually think with the power of agents”

Q what would you say to people in this audience right now? Like, this is sort of a real question that people are sort of facing. Like, should they become more word cell and less shape rotator? Like, what, you know, what's the move? And, you know, has that changed, um, The kind of people you're looking to hire and, you know, how you manage your teams right now at Meta.

A I think systematic and rigorous thinking are still incredibly important because, you know, the abstraction layer, I mean, I didn't used to believe that this is how this is going to play out, but it really has, like, the abstraction layer just keeps changing. So, you know, when I started a company back in my day, we wrote code. Um, and, and now, you know, I'm sure nobody here writes code anymore. That's ridiculous. But, um, but now it's about how do you orchestrate the agents together? And then it's like, How do you develop these organizations of agents? Like, how do you get, like, a million agents to work together well? And then it'll be, how do you get, like, a trillion agents to work together well? Like, I think that there's going to be this continued, um, uh, need to figure out how you structure, uh, workflows at the abstraction layer that we're going to be operating at. And that form of, like, rigorous systematic thinking, I mean, traditionally the way this would work, like, in my era of starting companies is you would start by writing code, And then you would have organizations of humans, and you'd figure out how you, how to organize those humans. Um, and that required systems thinking. And now maybe it's like much more, much closer to first you, you orchestrate the agent, then you figure out how to orchestrate like these armies of agents. But, um, but I think systems thin…

AI assessment note: “I think it's definitely a mistake to go all in on word cell.”

Q Let's see. So, one question. I mean, when you look back on the decade, um, what do you think they'll say was obvious in hindsight about AI that people are just missing in real time right now?

A You know, so much of the debate that happens these days is around, oh, how good are the models actually getting? And can the models actually bridge this issue? And, you know, when are we going to get super intelligence? Is that in like two years or five years? And, you know, are we going to hit a wall? And, you know, so much of that debate is like, I think, um, in some ways, uh, a little bit of a waste of time, because, you know, I think it's inevitable that we're gonna have very powerful models, and, um, you know, rather than, I think we'll look back and say, oh, all this arguing around, like, when exactly it was gonna happen was sort of, um, was short-sighted, because the reality is, we are just, as a entire human civilization on this incredible exponential, Like, you cannot look at the progress of AI over the past decade and not just be totally awestruck by how far it's come. Like, a decade ago, the best AI models could recognize cats in YouTube videos, and now, you know, we're talking to, um, you know, a digital god that can, you know, uh, I mean, we've all seen some of the hacks and some of the, some of the things these systems are capable of, and You just can't help but be awestruck. And, and I think this trend will just continue. Like these, these models are going to become more and more powerful. And so I think a decade looking back, it'll, it'll be obvious that intelli…

AI assessment note: “looking back, it'll, it'll be obvious that intelligence became abundant”

Q So let's talk about super intelligence, because that's clearly, that's even in the name of your lab. Um, what does super intelligence mean operationally inside Meta right now?

A Yeah, I think that, you know, we, a year ago, Mark wrote this, um, uh, memo about personal super intelligence, which I think actually is very similar to your concept of personal AGI, but, you know, we believe that everybody in the world, you know, all the billions of people in the world are going to have a super intelligence that is adapted and tailored to them, that is, enables them to accomplish their goals, knows their context, and ultimately is an expander of their own agency. Like, I think the thing that we think a lot about is, is agency expansion. How do we help people accomplish things that they couldn't have ever dreamed of before? And what would everyone in the world do if everything was just easy? Um, and we think about this in a, in an ecosystem way, um, as well. I think, uh, you know, Patrick mentioned it, but, you know, we don't believe in this totalizing, you know, totalitarian view of, you know, AIs that control the world. We believe that these are going to enhance this very broad ecosystem. So, you know, we believe in billions of people all around the world all having their own personal super intelligence, and we also believe in, you know, an explosion of entrepreneurship. There's two hundred million businesses that, uh, are on Metis platforms today. We think that number should go to billions with this explosion of, of creativity and using AI tools, and ultimat…

AI assessment note: “Mark wrote this, um, uh, memo about personal super intelligence”

Q harness is, uh, you know, underwrapped still, but, like, can you tease us with, You know, I mean, I still use Open Claw. I still use Hermes Agent. You know, it's, ah, you know, these things are, I call them Ferraris that break down on the side of the road all the time. Like, is this a Ferrari that won't break down? Like, you know, tease us a little bit.

A Yeah, hopefully, hopefully it doesn't, it doesn't break down. I mean, I think we're really focused on speed. I think speed is, um, you know, for anyone that uses these tools, speed is probably the, you know, one of the most critical things. I think also reliability, like you mentioned, we want it to be extremely reliable. Um, We want to be very extensible and to scale to as complex and interesting of a multi-agent setup that you, that you want to have. Like, I think there's so much innovation that will occur even above the harness, frankly, um, in terms of, like, how to orchestrate and set up loops and, and develop, like, you know, very complex ecosystems of these agents working together. Um, uh, we want to be really extensible and, and, um, ultimately we want to just Empower people to harness this technology, because harness, ah, no pun, actually, pun not intended, but, um, but there's, like, I truly believe these, these models are already just incredibly powerful. Like, they should, they should be so powerful to fuel, you know, um, many, many points of expansion of GDP growth, and I think it's, like, up to smart people with vision and ambition to make all that happen.

AI assessment note: “we're really focused on speed... reliability, like you mentioned, we want it to be extremely reliable.”

Q I guess selling data at the time, you know, large language models were not even, had not really come to the fore yet, Um, but self-driving cars were sort of coming up, and, and computer vision suddenly became, so that was sort of the first market, is that right?

A Yeah, so, the, the story here is that, like, I was, when I was at MIT, I did a bunch of projects to, like, train, train models of various forms, and these were, like, you know, by comparison today, they're, like, little toy models, and, um, and I remember to train a model, uh, I needed three things. I needed a, Uh, GCP account. Like, I need an account on some cloud service to get compute. I needed, um, the code to run to actually train the model, and I needed data. I needed a data set. And, uh, for two out of these three things, you could just press a button online and get them. And then for the last one, for data, there was, like, no effective way to get data for training these, training these models. Um, and so it felt, Incredibly obvious that this was going to be the future, that there was going to be a way to, um, you know, press a button, so to speak, and get data. And, uh, and it was very funny because in the years that followed, like in the first many years of scale, data was very unsexy still. Um, every time we would go out to fundraise, even though our numbers were great and we had great revenue, you know, VCs and investors would always be very skeptical. They'd be like, Oh, I don't know if this is a good business. Does it have longevity? Is this durable? Um, and, uh, it was really weird to me, but, you know, none of the investors had ever trained a model, so I guess t…

AI assessment note: “Yeah, so, the, the story here is that, like, I was, when I was at MIT”