Nvidia and Meta CEOs Talk Generative AI at Siggraph 2024 video [CNET]

At Siggraph 2024, Nvidia’s CEO Jensen Huang and Meta’s CEO Mark Zuckerberg discuss what’s next for generative AI.

Mark. Welcome to your first C graph. How do you see the uh uh the advances of generative A I AD meta today? And how do you apply it to either enhance your operations or introduce new capabilities that you’re offering with? Generative A I? Um I think we’re gonna quickly move into the zone where not only is is the majority of the content, you know that you see today on Instagram, you know, just recommended to you from kind of stuff that’s out there in the world that matches your interests to whether or not you follow the people. I think in the future, a lot of this stuff is going to be created with these tools too. Some of that is going to be creators using the tools to create new content. Some of it I think eventually is going to be content that’s either created on the fly for you um or, or, or kind of pull together and synthesize through different things that are out there. So I I kind of dream of one day like you can almost imagine all of Facebook or Instagram being, you know, like a single A I model that has unified all these different content types and systems together that actually have different objectives over different time frames, right? Because some of it is just showing you, you know what’s the interesting content that you’re gonna be that, that you want to see today. But some of it is helping you build out your network over the long term, right? People, you may know or accounts you might want to follow and these, these multimodal models tend to be, tend to be much better at recognizing patterns, weak signals and such. And so one of the things that people, people always, you know, it’s so interesting that A I has been so deep in your company, you’ve been building GP U infrastructure running these large recommender systems for a long time. Now you’re, now you’re a little slow on it actually getting to GP US almost trying to be nice. I know. Well, tell everybody about the creator A I and A I studio that’s gonna enable you to do that. Yeah. So, so we actually, I mean, this is something that we’re, we’re, you know, we’ve talked about it a bit but we’re rolling it out a lot wider today. Um You know, a lot of our vision is that I don’t think that there’s just gonna be like one A I model, right? I mean, this is something that some of the other companies in the industry, they’re like, you know, it’s like they’re building like one central agent and, and yeah, I will, we’ll have the me A I assistant that you can use. But a lot of our vision is that we want to empower all the people who use our products to basically create agents for themselves. So whether that’s, you know, all the many, many millions of creators that are on the platform or, you know, hundreds of millions of small businesses, um we eventually wanna just be able to pull in all your content and very quickly stand up a business agent and um be able to interact with your customers and, you know, do sales and customer support and all that. So the one that we’re, that we’re just starting to roll out more now is um we call it A I studio and it basically is um a set of tools that eventually is gonna make, it said every creator can build sort of an A I version of themselves um as, as sort of an an agent or an assistant that, that their community can interact with. There’s kind of a fundamental issue here where there’s, there’s just not enough hours in the day, right? It’s like if you’re, if you’re a creator, you want to engage more with your community. Um But you, you, you’re constrained on time and similarly, your community wants to engage with you. Uh But it’s tough. I mean, there’s, there’s just, there’s a limited time to do that. So the next best thing is, is allowing people to basically create these artifacts, right? It’s um it’s sort of, it’s an agent but it’s, you train it to kind of on, on your material um to represent you in the way that you want. I think it, it’s, it’s a very kind of creative endeavor, almost like a, like a piece of, of art or content that you’re putting out there. And no, it’s, it’s to be very clear that it’s not engaging with the creator themselves. But I think it’ll be another interesting way just like how creators put out content on, on these um social systems to be able to have agents that do that. One of the interesting use cases that we’re seeing is people kind of using these agents for support. Um This was one thing that, that was a little bit surprising to me is one of the top use cases for meta A I already is people basically using it to role play difficult social situations that they’re gonna be in. So whether it’s a professional situation, it’s like, all right, I wanna ask my manager, like, how do I get a promotion or raise or I’m having this fight with my friend or I’m having this difficult situation with my girlfriend. Like how, like how can this conversation go and basically having a, like a completely judgment free zone where you can basically role play that and see how, how, how the conversation will go and, and get feedback on it. Um But a lot of people, they don’t just want to interact with the same kind of, you know, agent, whether it’s met A I or Chai PT or whatever it is that everyone else is using, they want to kind of create their own thing. So the LMA is genuinely important. We built this concept to call an A I factory, uh A I foundry around it uh so that we can help everybody build, take, you know, a lot of people, they, they, they have a desire to um uh uh build A I and it’s very important for them to own the A I because once they put that into their, their flywheel, their data flywheel, that’s how their company’s institutional knowledge is encoded and embedded into an, an A I. So they can’t afford to have the A I flywheel, the data flywheel that experience flywheel somewhere else. So, and, and so open source allows them to do that, but they, they don’t really know how to turn this whole thing into an A I. And so we created this thing called an A I foundry. We provide the tooling, we provide the expertise uh llama uh technology. Uh we have the ability to help them uh turn this whole thing uh into an A I service. And, and then when, when we’re done with that, uh they take it, they own it, we the output of it’s what we call A Nim and this N I this, this Neuro Micro NVIDIA inference, microservice, uh they just download it, they take it and they run it anywhere. They like including on Prem. And we have a whole ecosystem of partners uh from O Ems that can run the Nims to uh G SI S like accenture that, that uh we trained and work with to create llama based Nims and, and uh and uh pipelines and, and now we’re, we’re off helping enterprises all over the world do this. I mean, it’s really quite an exciting thing. It’s really all triggered off of uh the llama open sourcing. The the Rayan Met Alas um your vision for, for bringing A I into the virtual world uh is really interesting. Tell us about that. Yeah. Well, OK, a lot to unpack in there. Um The segment anything model that that you’re talking about, we’re actually presenting. I think the next version of that here at, at, at Siggraph segment anything two. And it is, it now works, it’s faster, it works with. Um Oh, here we go. Um It works in video now as well. I think these are actually cattle from my ranch in Kawaii. Um By the way, these are what they’re called delicious marks. There you go. Next time we do. So, Mark, Mark came over to my house and we made Philly Cheesesteak together. Next time you’re bringing the thing you did. I was more of a sous chef, the fun effects will be able to be made with this and because it’ll be open a lot of more serious applications across the industry too. So, I mean, scientists use this stuff to, you know, study, um, like coral reefs and natural habitats and, um, and kind of evolution of landscapes and things like that. But I mean, it’s uh being able to do this in video and having it be a zero shot and be able to kind of interact with it and tell it what you wanna track is. Um uh It’s, it’s uh it’s pretty cool research. I think what you’re gonna end up with is um just a whole series of different potential glasses products at different price points with different levels of technology in them. So I kind of think um based on what we’re seeing now with the Rayban Meadows, I, I would guess that display list A I glasses at like a $300 price point are going to be a really big product that like tens of millions of people or hundreds of millions of people eventually are gonna have. Um So you’re gonna have super interactive A I that you’re talking to visual, you have visual language, understanding that you just showed you have real time translation, you could talk to me in one language. I hear it in another language. Then the display is obviously gonna be great too, but it’s gonna add a little bit of weight to the glasses and it’s gonna make them more expensive. So I think for there will be a lot of people who want the kind of full holographic display, but there are also gonna be a lot of people for whom um you know, they, they want something that eventually is gonna be like really thin glasses. And so you guys know when, when, when Zuck calls it H 100 his data center of H one hundreds. There’s like, I think you’re coming up on 600,000 and, and they’re, we’re good customers. That’s how you get the Jensen Q and A at zig graph. Yeah, it’s uh ladies and gentlemen, Mark Zuckerberg.