Bloomberg Audio Studios, podcasts, radio, news. Bloomberg Tech is live from coast to coast with Caroline Hyde in New York and Ed Ludlow in San Francisco.
This is Bloomberg Tech. Coming up, AMD signs a historic deal with OpenAI to roll out AI infrastructure, a pact the chipmaker said could generate tens of billions of dollars in new revenue.
Plus, we speak with the White House AI and crypto czar David Sacks about relations between the US and China in the context of the AI race.
And Meta's CMO joins us to discuss how AI is changing the advertising landscape, what that means for small businesses. Here and now, we turn our attention to the broader markets. Bitcoin at a record high, the NASDAQ 100 at a record high. We're up six-tenths of a percent. The mood music around AI, AI infrastructure, and the frenzy therein, Ed, it continues. I'm looking at the SOX up 3.5%. A new record high for the index that tracks the semiconductor industry. But what is leading it? Of course, you know, it's one key name. We look at AMD at one point hitting a record high. We are up the most on this stock in 9 years. 28% surge. At one point, it was 37% higher. All as we hear that tens of billions are going to be added in terms of revenue because of the OpenAI infrastructure pact. A sign of real confidence in Lisa Su's AI accelerator and buildout. Ed, we've got such an interesting conversation coming out about this new deal.
Welcome to Bloomberg Radio and TV audiences around the world. AMD has signed a definitive agreement with OpenAI to deploy 6 GW of AMD GPUs. AMD says it will equate to tens of billions of dollars in revenue. OpenAI will get up to 160 million AMD shares in tranches and set against both operational and financial milestones. The focus is inference. Let's bring in AMD CEO Lisa Su and OpenAI President Greg Brockman. Both of whom join us on set here at Bloomberg Tech in San Francisco. Good morning.
Good morning. It's great to see you.
Let's frame the opportunity, Lisa. You know, the market reaction is very clear, but for AMD and the AI industry at large, what do you think this represents?
Well, look, this is a huge milestone for AMD. You know, we are so thrilled with the partnership with the OpenAI team, and it's also, you know, a huge moment for the AI industry because, you know, when you get right down to it, you need more AI compute. I mean, that's where we are today. Compute is the foundation for all of the intelligence we can get from AI, and, you know, we are a compute provider. We have spent years on our roadmap. We've spent years working with OpenAI and the team, and, you know, together now we're embarking on, you know, a massive buildout of 6 gigawatts of AI compute, and it's a big deal for us, for our shareholders, for our teams, and for really, you know, the partnership and the overall AI ecosystem.
Greg, I said at the top the focus is inference. I think that's really important to be specific about what you will do with this capacity. So, literally explain that part, and I'm conscious that, you know, in the first instance, the first target is 1 GW and then eventually 6 GW, but what will you use it for?
Well, I think that the world continues to underestimate the amount of demand for AI compute, right? We've seen this explosion of demand with things like ChatGPT. You know, we're at 800 million weekly active users now. This product didn't even exist 3 years ago. And we're in a position where we cannot launch features, we cannot launch new products simply because of lack of computational power. And we see these models continuing to get exponentially better. And I think we're just heading to a world where so much of the economy is going to be lifted up and driven by progress in AI. And so we're very much heading to a world by default that I think looks like a compute desert, right? That there's just not enough compute to go around. And so we're trying to build as much as possible as quickly as possible. So we're starting with 1 gigawatt simply because you got to start somewhere. But honestly, we're building as fast as we possibly can and trying to bring as much computational power to bear for the economy and for the world.
Lisa, this is such a big commitment to Instinct in particular as a customer. Does it make OpenAI the largest for that particular product?
Well, this is certainly the largest deployment that we have announced by far. I mean, you know, 6 gigawatts of compute. As Greg said, we're going to start with the first gigawatt in the second half of 2026 on our new next-generation MI450 chip. I think the thing to understand is, you know, these types of partnerships actually take, you know, years to really get comfortable with the idea that we're going to, you know, go all-in together, and this is an all-in partnership in terms of building out, you know, the AI compute that OpenAI needs for everything that they're offering to the world. So yes, it's a huge deal, and it also says a lot about, you know, how much needs to come together for, you know, this entire ecosystem to operate. So, you know, we are setting up, you know, certainly there's a lot of engineering work, but our teams are working together on hardware, software, we're ensuring the supply chain, all of those elements are set up and ready to deliver on this massive commitment.
Greg, talk us through a little bit about the players that you need to also lean on. This has been years in the making, as you say, with AMD, but what other cloud providers are involved? How are you thinking about this working with an Oracle or others out there?
Yeah, we really think of this as an industry-wide effort, and in general we think that compute is something that does require the entire supply chain to really wake up and to really start building much more than people were planning on. I think this starts from energy to try to get far more power to be built. Things like nuclear, I think, are going to be very important to come online. The cloud providers are an important part of this as well. So we're going to be deploying AMD in our own data centers. We'll be deploying them together with cloud providers. You know, we have a deal with Oracle, lots of other cloud providers out there. You can really see that we're very much in the we just want compute, as much compute as possible. We think this is important for the economy. We think this is important for the nation. We think this is important for humanity. And so really, we're working with everyone in this whole industry in order to get as much compute power online as quickly as we can.
Lisa, I'm sorry, specifics. Where is this data center going to be? Is it one single site? Is it Oracle that will partner with you on this?
Well, actually what this really is is an announcement of what, you know, AMD and OpenAI are going to do together. You know, OpenAI has a lot of partners in terms of, you know, where they deploy. I imagine a lot of it will be in cloud service providers. It's really up to, you know, OpenAI and Greg and Sam and the team. But the way to think about it is, for this amount of compute, it's going to have to be in a lot of different places. I mean, it's a massive amount.
Multiple locations. I would imagine, you know, multiple providers to really get this online as fast as possible.
Greg, there is a lot of focus on where OpenAI is going to get the money from to fund all of this. Sam Altman's big picture commitment is well documented, right? And the numbers in his mind are in the trillions. But have you specifically thought about debt financing for this relationship with AMD? Have you thought about doing a specific equity raise? You are very committed across multiple projects.
Yeah, look, the way that I would look at this is that AI revenue is growing faster than I think almost any product in history. And that ultimately at the end of the day, the reason this compute power is so important, is so worthwhile for everyone to build, is because the revenue ultimately will be there. Now, as a company that is trying to move as fast as we can, we look at everything, right? We look at equity, debt, we look at trying to find creative ways of financing all of this. That's been actually a huge focus of us for the past couple years is thinking about how can we possibly build the amount of compute that is required in order to really transform this whole economy into an AI-powered economy. And so I think you'll see lots of creative ideas. But fundamentally, I think at the end of the day it is because we believe...
I'm sorry to jump in and interrupt, and Car, just forgive me on this one. The condition of AMD issuing the stock to OpenAI requires you to spend money basically because you have to deliver that gigawatt of capacity first. Lisa, I have to ask you if you have assurances that OpenAI is good for it.
Well, let me be clear. I mean, this deal is a win for AMD. It's a win for OpenAI, and it's a win for our shareholders, and that's kind of the way we put this together. I have full confidence in, you know, OpenAI, Sam, Greg, Sarah. I mean, this is a massive opportunity for us right now, right here. It's about who has the most compute and how fast can we get it online, and we're committing to doing this together. And the fact is, as OpenAI buys chips, that's great for AMD. Our revenue goes up, our earnings go up. You know, we expect that it will also be, you know, very, very accretive to our shareholders from day one. And as we do that, you know, we're very happy to have OpenAI as a deep partner, and we win together. So it's like a virtuous, positive cycle in how we build out, you know, this big vision for having all this compute out there.
Right, and yet we still question, as you were just talking about, Greg, some of the other supply chain elements. You're talking about the need for nuclear, for power. What's really interesting is, are you feeling confident enough about the rest of the compute supply chain is there? Is this going to be US manufactured from your perspective, or are you looking at also building out internationally with AMD?
Yeah, we've been looking at really all options. Our preference and really the core thing that we try to do is build as much as possible in the US, and you can see the commitments that we've made over the past year. You know, 500 billion of investment in the US, and that's not stopping. We're continuing to build. I do think that international, that it is also going to be important for the world to have compute. I think that compute is going to become this like national security strategic resource, and every country is going to need computational power. And so we are really not limiting our sights in terms of where to build, but we do think it is important that the US leads in this technology, leads in computational power, and we're expanding the supply chain. But you can see that we've really been working with partners across the globe in order to actually meet the demand that we expect to be coming in upcoming years.
Lisa, the manufacturing of these chips, will you look to Intel at all for it, do you think, in the future?
Well, as you know, the supply chain is something that we work on very meticulously. I think we have a very strong supply chain. We're certainly deeply partnered with, you know, TSMC across the supply chain. You know, just to that earlier question, we're absolutely prioritizing building in the United States because I think that's super important. This is the US AI stack. We want to have as much of it in the US as possible, and, you know, we continue to really look at, you know, how do we ensure that there will be a strong supply chain going forward.
Greg, Sam posted on X that this deal with AMD is incremental to what's already being done with NVIDIA. But as Lisa knows, spent quite a lot of time looking at the MI family and the newer generations of products to come. Is there a very clear specific benefit to using AMD technology for inference relative to the capabilities of NVIDIA, or do you just see it broadly as some sort of diversifying factor?
Well, I would look at it this way: that there's a huge fixed cost to getting AI models running on any platform, and so that when we look at what's out there, that actually getting AI training to work is a huge, huge amount of lift. That's something we've really only done the work for NVIDIA. But for inference, that's something that's much more, that there's an easier barrier to entry there. And one thing we found is that I think that the work that Lisa and team have been doing on the MI450 series, it's looking like it's going to be a really incredible chip. I think that the way that these things work is there's niches for different balances of memory and computational power. And so as we have a diversity of workloads, we're finding that having a diversity of chips also really accelerates what we're able to do.
Lisa, at the beginning of this conversation, I said there are both operational and financial milestones to be met, and Greg explained you got to start somewhere. So, in the first instance, one gigawatt, but would you just sort of draw out the pathway to that first gigawatt? It seems like you're prepared to move quickly here.
Yeah, absolutely. And maybe, Ed, if I can just build on something that Greg said. I think he's absolutely right. You know, we're a believer in there's a diversity of workloads, and there will be a diversity of workloads across, you know, customers, models, use cases, and from that standpoint, you know, we feel really good about how we're positioned. You know, we love the work here because, frankly, you know, OpenAI is the ultimate power user of our chips and tests us in very good ways. So I think that's what gives us confidence that, you know, the technology is there. And then to your point about milestones, yes, I mean this is clearly a case where we are tied to each other. The first gigawatt of deployment is super important. We're going to start that, you know, second half of next year, and we're going to build on from there. And it really is not just the technology but, you know, commercial milestones, adoption milestones, and just how we proliferate the capability going forward. But I'm looking forward to building this as fast as possible. You know, we're already working with a number of cloud service providers who are also very active on our technology, and I think this is a great catalyst to get the industry to build faster.
Tied to each other. It's such an interesting turn of phrase. And Greg, look, you are seeing more AI users and chip makers and designers becoming more financially tied to each other. Is this going to continue? Is this the step forward for how you see this financing going forward?
Well, I really see the world transitioning to this AI-powered economy. And the interesting thing is within OpenAI that we've really seen what it's like when your progress is limited and accelerated as two sides of the coin by computational power. Like teams within OpenAI, their ability to deliver really is tied to the amount of compute that they get. And I think we're heading to a world where that is how the whole economy will function. And we're starting to see it, right? That people having access to better AI tools, if you're a coder, you're able to do far more if you have access to better AI models. And we're heading to a world where if you can have 10 times as much AI power behind you, you will probably be 10 times more productive. And so I think that we're moving to a world where the whole industry is waking up to the fact that we have just not planned. We have not planned for this moment where this explosion in AI demand is happening. So it's happening all the way from the power to the silicon, and I think this whole industry has to find a way to actually rise to meet the occasion.
Lisa, you have given us a look into the future before about how you see the total addressable market, the industry. Now that the ink is dry with OpenAI and Greg, are you rethinking either your bigger picture analysis of the market for AI accelerators and GPUs, or do you see AMD now having an improved position in that market relative, of course, to your friends at NVIDIA?
Well, again, I think, and I've told you before, I believe that this is a huge market. You know, we have sized just the AI accelerator TAM being, you know, over $500 billion in TAM over the next few years. I think some might say, you know, maybe I was a little conservative in that TAM analysis. But the way to think about it is there's so much need for compute. I mean, you just heard it from Greg. So, you know, this is a huge pie, and you're going to see the need for, you know, more players coming into it. And, you know, from my standpoint, this is a big validation of our technology and our capability. You know, as much as we love the work with OpenAI, we're working with a lot of other customers as well. There's a lot of excitement in the industry around MI450, so we're ready for it.
AMD CEO Lisa Su, OpenAI President Greg Brockman, it's been a joy having you on the show. Thank you both very much.
Thank you. And coming up, more on AMD and its impact on the broader tech markets. We've got a key investor for you, Tony Wang of T. Rowe Price. This is Bloomberg Tech.
Let's stay on that AMD OpenAI story, its impact on the broader tech market. Tony Wang, T. Rowe Price, Science and Technology Fund portfolio manager. You have exposure to AMD. It's added more than $70 billion in market cap on one day alone. What does this deal signal?
Yeah, well, I think it's a really exciting deal here for AMD. I think it validates their roadmap and their silicon and software strategy. And I think it gives them a really big lead customer to really scale. And I think that this will probably attract other customers to their roadmap and continue to build out ROCm. And I've always had this thesis that the TAM is really big, and if companies can deliver on that compute, that there's a lot of companies that can win in the overall compute TAM. So overall, very exciting, and, you know, I think it's got a good setup for the next few years for the company's runway.
I mean, Lisa Su just telling us that maybe she's being conservative when she puts the AI accelerator TAM at $500 billion. Tony, I'm interested though at OpenAI telling us, Greg saying, 'Look, we're looking at all kinds of ways of financing this.' How are you feeling about this knitting together of purchases and creators, designers of chips?
Yeah. Well, I think that taking a step back over the last kind of 10 years, everybody's kind of underestimated this TAM. And I think what's exciting about AI is that there are a lot of productivity use cases here. And we're starting to see AI agents really form, and then I think physical AI. So I think as long as the end use cases are delivering a lot of value and there's promise there, I think that's what matters in terms of the ROI. And I think a lot of these kind of contracts, I mean, they are backstopped by really blue-chip companies like Microsoft or Oracle. So in terms of, you know, how I'm feeling about the financing, I think it continues to be probably a good, attractive way to do as long as the use cases are intact.
Tony, the mechanics of the deal are that OpenAI has the right to buy up to 160 million shares of AMD at a penny apiece, but that right contingent on the operational and financial milestones that we discussed. It is not circular financing. It's something different. But how comfortable are you with that mechanism?
Well, I think it could make a lot of sense, right? I mean, it puts the two companies kind of in co-development and partnership. And I think there's shared economics and it's a win-win for both companies. I think some of the warrants are struck at a pretty high price on the AMD stock price. So I think it's good for both sides. And if they win, they win together. So to me, I think it can make sense.
Does this alter AMD's position in the AI accelerator market? In other words, they're closing the gap a little with NVIDIA.
Yeah. Well, I think that both companies are doing really well and they're doing things a little bit differently. But I think that you're alluding to kind of the market narrative of AMD was kind of in between NVIDIA on the GPU side and then Broadcom on the custom side. And I think this can help lift the narrative to go from like a second-place GPU player to a co-development partner of OpenAI on the AI compute side. So I think it positions them well, gives them credibility, scale, and additional co-development R&D to improve their roadmap. So to me, it definitely is a big positive, and I don't think it's a zero-sum game. I mean, I think it just further signifies the demand for AI computing. It's good for the country to build this much capacity because I do think the end payoffs are immense.
I mean, Tony, we're at a new record high for the NASDAQ 100. At one point AMD was at a record high. The valuations get ever higher. When I'm looking at your holdings, top holding Apple, Alphabet, NVIDIA, Meta. Do you feel confident that these are going to continue to gain in value with this AI story?
