NVDA Strengthens AI Dominance with Hugging Face Acquisition

Welcome back to market on close. It's time to turn our attention to Nvidia after announcing it's acquiring Hugging Face yesterday. Let's welcome in our next guest to discuss that move. Yale Osowski, the deputy director of the Consumer Choice Center, joining us. Great to have you on the show. Now Nvidia is paying close to $13 billion for Hugging Face. Its its second largest acquisition ever. What does Nvidia see here that makes Hugging Face worth that kind of premium. Well essentially Hugging Face is the playground for anyone who's playing with local AI models. And local AI models are just another way that Nvidia is providing those chips, those wonderful chips that we've been talking about that are propping up the U.S. economy. The more people that are moving to local AI, that means that they're running inference on their own computers. They're doing the compute on premises, in their businesses or at home. They're going to be using Hugging Face as the actual repository where they can get all of those models, plug into them and play around with them. So Nvidia sees that the entire future of AI. Yes. Right now it's with a large frontier companies, but it will continue to evolve and much more of it is going to come local. As consumers come online, more businesses want to have a lot more sovereignty over their data. There's going to be a huge move there. And I think that's what Nvidia is thinking and overall a pretty good move. And does this deal also signal to us that open source AI is becoming just as strategically important as some of these proprietary Myles models that are coming out of the bigger labs. I do think so. And I think every company that has played around with artificial intelligence, you know, they've gotten some token spend in there. They've kind of noticed how much it actually cost. Engineers are sometimes putting together hundreds of thousands of dollars of token spend. But if you're able to use that using open weight models or open source models, you can actually get rid of those costs altogether. And I think the more exciting thing, especially for consumers and technology nerds like me, is that the models are getting better every single day. There's an entire competitive category. Hugging face is sort of the central place where all that is. It's the source of truth for open source AI. So you can find all of those models, you can plug into them and you can change them basically at will. So I think we see that there is going to be a move. We've seen Palantir and many other companies that have really tried to put their foot down and say, look, we want sovereign AI. We want the ability to control our compute, not necessarily give it up, just OpenAI and anthropic. And I think you're going to see other companies do exactly the same thing. And let's dive into some of those numbers that they're buying in this community, the developer community, they've got a repository of more than 3 million models, 500,000 data sets. When you think about what additive value that has to Nvidia's long term strategy, I mean, just looking back over the last couple of years, they've moved from GPUs into networking, into software, into full AI systems. I mean, where does this fit in their continued domination of owning the whole AI stack? Well, I think they're not owning the stack necessarily, but they are providing the power, the thing that runs it. And I think that's really what Hugging Face is about, because it's about connecting the people who are tinkering, who are playing around with these models and who are more likely to host at home or on their premises. So they're really kind of buying into that. And I think we put so much focus, particularly on the markets, on the big models and you know, what is being released now. But there's so much value up and down the stack just for consumers and small businesses. They're the harnesses. There's all the different apps that are happening. There's all these tools that are being developed that do require more power, more chips. And we see that in the general marketplace, computers are getting more expensive. A lot of desktops are getting a lot more expensive, but it's also making AI more available. So we don't have to necessarily use a subscription from one of the larger frontier labs. If we want to, we can actually do it on our own. I think that's what Nvidia is kind of putting its money towards, is the idea that people are going to want custom models. They're going to want things that they can build. They can keep their data sovereign protected. I think that's going to be a big advantage because just imagine what we'll have for schools and hospitals and small businesses. Hugging face will be sort of the central source of truth. They'll be able to get to that. And all of that will be running on Nvidia chips. And they need to do that now because all the frontier labs are cutting their own costs and they're starting to make their own chips. So this is definitely a nice route for Nvidia to take because so many of those labs are kind of changing course. And with this case you're making for local inference. I mean how significant could that shift be from sending data to the cloud towards running AI locally in terms of privacy speed, cost? Yeah, it is a big thing. We haven't really had the conversation yet about privacy. You know, there are a couple of lawsuits that relate to chat logs, people talking to ChatGPT or Claude. There have been some police cases. There's all types of different lawsuits that are being started. But that's the thing that you do not have in private AI. You can actually encrypt the inference. You can use all of the complicated algorithms we use to protect things like our iMessage or our email. You can apply that to the inputs of your AI conversations and then also what you get as well. And I think for businesses, there's a huge case for that. For individuals who care about privacy, there's a huge case for that. And I think this is something that every consumer sees some value in. You know, everything is becoming a lot more personalized. And the more that we can do that, even with our chat bots and AI, we can actually find privacy and we can find sovereignty with technology. And I think that should make every consumer pretty bullish and all the investors too, because there's, there's tons to choose from and probably a lot more to come too. So let's talk about where Nvidia will sit if this acquisition goes through. It's simultaneously a dominant supplier of compute powering the AI. Then it will now own a major platform where developers go in and they build and share these models. How do you go about preventing these two positions from creating a conflict of interest, either real or perceived? Well, you just have to look at the latest, you know, launch of the open AI model Astra. I mean, that was basically trained on Nvidia chips. And basically Nvidia's providing power to anyone who wants to use it. And we saw this initially with Bitcoin mining. You know, that was an industry dominated by a lot of Chinese players, Chinese computing firms. And now it's an American power that's kind of taken that over. And Nvidia is going to be there to sell chips to whomever really wants them. And right now, yes, hugging face and open models. But when you have a company that's delivering those GPUs that's allowing you to do that compute at home, they're also going to be used for small businesses that are going to build on top of that and have any type of competitive tools. So I don't really see that there's any competitive questions here or anything that we need to really look at, because all the different products are going to be different. There's going to be all types of different use cases. Some might be local, some might be larger data centers, and the competition is only heating up because again, the major labs, the major frontier companies are putting tons of money into developing their own chips. AMD is putting a lot of money. You see companies like Intel also providing some kind of competition. So I think Nvidia has a little bit of runway right now. But all these other companies understand this is how you make money in the AI age. And the more tools that consumers have and small businesses, that just means we're better off. And hopefully prices can stay low for the moment. And Huggingface wasn't an unknown name to us ahead of this announcement because of that recent cyber attack. So as we look at that and now Nvidia acquiring it, what does Nvidia need to do now differently from what was being done before to ensure that it is secure now that it is going to be responsible for such a massive open ecosystem? I mean, there are definitely going to be all types of protections in place and, you know, and that we can go back to the case of the OpenAI AI agent kind of rifling through hugging face. And I think the more important part of that case is actually how they defended themselves, was using an open model to try to figure out what was going on and diagnose it and repel that attack. So I think Nvidia, that is what they have been doing. They have plenty of open models that you can use for free on their website. It's kind of insane that you can just click and get all this inference right now. And I think that's what they're going to continue to provide. They have said they're going to keep the platform open. It's going to be a place where you're not going to be forced onto Nvidia chips necessarily, but they are going to provide a lot more security, a lot more investment. And I think that's going to give a lot of the users of hugging face, of which there are hundreds of millions, a lot of basically a good confidence that this is going to be a place where we can actually trust that our, our models can be we can download them. And I think Nvidia is going to do a good job doing that. And again, there's all types of competition coming down the line. So at least we start off pretty well. Yeah. Some great breakdown and insight there. Really appreciate you sharing it with us today. I hope