AMD Revenue Jumps 38%, Anthropic’s $200B Google Deal, & OpenAI President Greg Brockman on Elon Musk

0:13Welcome everyone to the information's TITB. My name is Akash Pasricha. It is Wednesday, May 6th. First up today, AMD shares are rising after their quarterly results yesterday. The company reported a 38 % jump in revenue bolstered by its data center segment. We'll get into the results in just a moment. Plus, the information published exclusive reporting with new numbers that highlight the growing link between Anthropic and Google's businesses. We'll bring on the reporters who broke that story. We'll also get our daily check-in from Rocket Drew, who was covering the Elon Musk OpenAI trial. I'll then talk with the CEO of Tessera Labs, which just announced a new multi-million dollar funding round.

0:56And we'll close out the show with some insights from the Information Subscriber Survey, highlighting who is winning in the three-way race between Chachupiti, Claude, and Gemini. It's going to be a fun show, so let's get right on into it. AMD posted another big quarter. Revenue jumped 38 % to$10.3 billion in Q1, driven by its data center segment. I want to bring on the CEO of Creative Strategies, Ben Beharin, to help us break it all down. Ben, welcome back to the show. It's great to have you here. Yeah, good to be back. Thanks for having me. Okay, so AMD is up. What stood out to you from the results?

1:32Yeah, I mean, we weren't terribly shocked. I think there'd been enough signal around what we'll just say, like data center CPU as a demand trend. that I think everybody sort of assumed they would be in a similar spot, as we saw from Intel in terms of just outpacing supply with demand. And part of that's really just being driven, obviously, by changes in infrastructure, agentic inference that's happening, which was not a dynamic we had a year ago. And so there's a number of new things coming to the industry where obviously AMD is a huge beneficiary of that. And so really, the spotlight was on CPU growth.

2:10They updated their TAM, which sort of aligns with some of our forecasts around the CPU TAM because of Agentic. And really, I think overall, this is the bulk of the story right now. Not that GPUs aren't sexy. They and accelerators are still relevant. But big spotlight on CPUs. And that story alone seems to be enough to be driving this part of the market. it. So when you talk about the total addressable market expanding here, the idea here is what that agentic inference, I mean, that requires more CPUs in this environment, right? Yeah. And I think the best way to look at it, right, prior to agentics, if we were just talking about, you know, the framing that we use, which is cloud native CPUs.

2:54So prior to this moment, AMD, even ARM, right, Intel would talk about, you know, we're mostly just selling these to hyperscalers, they're running enterprise software, right? They're running their e-commerce, they're running their email, like they're hosting cloud workflows. And that market wasn't growing. It was roughly a$25 billion market a year and staying relatively flat and CPUs were not super interesting, right? Now people are coming out and saying that number is drastically changing as of even, you know, Lisa Su said last year, they changed their CPU TAM to going up to 60 billion. So from 25 to 60, which alone at the time was like, that's a pretty big jump, right?

3:32And so now saying, well, a Jettik drives another 40 plus billion, or in their case, more than that, because they're saying 125 billion. And we were around 110 at our first shot with this, is again, a drastic increase from what it was typically a$25 billion market and not growing. And so that's why I think in the market context, people are seeing that and realizing that the TAM's expanding. It used to be a share-taking environment. When we talked about AMD encroaching on Intel in data centers or even ARM, it's not share-taking anymore. It's share-grabbing in what is essentially, as Lisa said, a 35 % year-over-year growth.

4:10And just for Agentic, we have that growing 65 % year-over-year for just Agentic. Why is it share-grabbing now instead of share-taking? And what is the difference there in your mind? Yeah, I mean, again, when it was a$25 billion market, right, and growing we know how many units that moved every year it was their ability to grow for amd or intel or even when you thought about like arms potential right prior to this was purely on take share because it wasn't growing now that the market is mo is moving meaningfully to a drastically larger size both in unit volume asp you know as a dollar amount it's really just green field growth for for cpus in agentic for new data centers so in a lot of ways like we thought about right that the GPU expansion story, so NVIDIA while being dominant, right, moving to a trillion-dollar market for just AI accelerators, I'm not even including CPUs in this point, was a everybody benefits, right?

5:05It's not just dollars there for NVIDIA. There's dollars for AMD. There's dollars for other competitors. There's dollars for, you know, the guys, everybody making their own custom silicon. So in TAM expansion, like we're talking about, it's brand new dollars to go after. It's not I have to take money from my competitor. Right. I guess my question is, so in that story, though, I mean, how confident are you in AMD's prospect to then grow its market? The market's expanding, I'm with you, but in terms of growing the market share, you know, how sustainable is the current strategy in terms of trying to grab a higher percent of the market?

5:44Very. I mean, I think, you know, again, and I'll make this point for everyone in CPUs, right, that's making a claim that they're doing CPUs in the data center. This is a massive expansion that they're going after. From A &B's standpoint, what's interesting is they have typically done a lot of customization and collaboration with their hyperscale customers. So the Googles, the Amazons, the Microsofts of the world. And this will have to extend to NeoClouds, to be honest with you. This is something I've been arguing with the NeoClan cultists. I know they hate it when I say that, but like the folks in those communities is that most of their infrastructure has been in the training era, right?

6:23If you're just installing NVIDIA solutions, right? Blackwells and whatnot, those were training and some inference. Everybody's agreeing that inference infrastructure looks drastically different than training. And that's where CPU racks come in. So there's a ton of data center CPUs that have to get played out. And AMD has always had a strategy of saying, we can change our SKUs. We have a one architecture that scales and we can do agentic tweaks to our CPU or we can keep them for cloud native workloads within their pipeline. So and again, they are deep customers with the hyperscalers. And right now there's so much CPU demand, like really more than we ever thought a year ago was going to come up.

7:03And that alone, it just means if you're relevant in data center CPU, like you're going to see market expansion. Right. What did we get from the results around AMD's full rack system and how that competes with NVIDIA? Where is that at and how confident are you that that will actually pose a challenge? Yeah, I mean, not a lot yet, right? They have an event coming up in July called Advancing EI where, you know, we're going to learn a whole lot about Helios as well as the successor to Helios, which they call MI555. You know, people tried to prowl this on the call, right? Everybody wants to know what their prior.

7:37So MI, you know, 355 has looked like, again, it hasn't been gigantic, right? The role of the market has moved, again, largely to NVIDIA's accelerators as well as custom ASICs, which continue to dominate this conversation. But I think the second half of the year is where this ramp is. And I'll just sort of lump this as a broad statement, but I think this is relevant for AMD too. we're at such a compute deficit for AI that the reality is almost any viable compute will get adopted. And that's why you saw them do deals with, you know, OpenAI, right, and others. And I expect you'll see them do a whole lot more because you just can't get enough compute for one vendor.

8:17You need two, you need three, you may even need four vendors to have enough to meet this demand, right, that everybody's seeing. And so there's a lot of opportunity and growth side. And I think the second half of the year is what, you know, Lisa and management has said this starts to ramp. And I think once we see what MI455 looks like, so Helios at the Advancing AI Day and beyond, people will have a little bit more confidence about where that goes and how much they can grow that business, you know, into 27 and 28. Right. Last question for you. So what do you think it would take for investors to fall out of love with AMD?

8:54This is obviously, this is boom times for the company, but now we've seen a couple chip companies go through their boom period and then keep booming. But, you know, when does the multiple start to contract, in your opinion? Yeah, I think the debate really is how much capacity, right, can you grow and scale? And if you're just constantly in a supply-constrained environment, then most people will model in what they believe, right, your forward projections can be in terms of growth. And so if that's your constraint, then the only upside is can you get more capacity? Like where are you going to get more wafers?

9:27Where are you going to get more manufacturing capacity? And that's, to be honest with you, a dynamic that I think is hitting NVIDIA is that most people just have said, we know how much you can grow or we think we know how much you can grow based on your supply chain. And that's what we're pricing in. And that's really, I think, the dynamic that everybody's working on in their models. So the downside is that they've capped. They're capped and everybody knows it and they've modeled that. and can they defeat that narrative? But that would be the stale point if there's anything. The momentum in CPUs remains an upward trajectory.

9:59Their business will grow, but how much can they grow really becomes then where the model gets focused on. Right. Great. Well, Ben, I want to thank you for coming on. That is Ben Beharan from Creative Strategies here on TITV. It is no secret that Anthropic and Google's businesses have grown in tandem over the years, but new exclusive reporting from my colleague, Shreemupiti, Aaron Wu, and Amir Afradi reveals the great extent to which that is now the case. I want to bring on Shree and Aaron to talk more about what they found. Shree, I want to start with you. What did we find out about Anthropic's reliance on Google?

10:35We found out that Anthropic committed roughly$200 billion in over five years to Google for computing power and chips. And so that's particularly important just because Anthropic has been scaling its revenue really quickly. So for example, the company crossed more than$30 billion in annualized revenue last month, up from$9 billion at the end of the year. And so as the company continues to scale and add on more customers, it needs computing power desperately. And so Google is an excellent cloud provider that can serve that need for Anthropic. So that's Anthropic's reliance on Google. The other part of your story that was really interesting is you actually looked at the reliance that both OpenAI and Anthropic have on all the hyperscalers.

11:18Tell us a little bit about what you learned there. Totally. So along with Anthropic signing that deal with Google, we also had written about how Google had signed a$100 billion computing deal with Amazon. Amazon also has a deal with OpenAI, where OpenAI committed about$100 billion. And so that results in about a 364 revenue backlog for Amazon. And similarly with the Google backlog, which basically means the revenue contracted for future customer revenue. Google has about a$460 billion revenue backlog. And so Anthropic for them represents about 40 % of that backlog. And so you just essentially see how intertwined a lot of these cloud providers and AI labs are because as Google, Amazon, Microsoft invest money into these labs, the labs then turn back and actually spend money on them as well.

12:09And so the other one to mention, of course, is Microsoft, which has a long time relationship with OpenAI and now also has one with Anthropic as well. Right. And there's a great chart in the story that I would encourage people to go look at. but it basically shows, if I'm recalling correctly, you know, of the revenue backlogs that all of these companies have told us that they have, the cloud companies, roughly half of it, you know, give or take, for I think most of these hyperscalers is coming from open AI and Anthropic, right? Do I have that right, Shree? Totally. So much of that revenue that these cloud providers are projecting will actually come from these AI labs.

12:50And so I think that's quite important for investors to know as the AI boom continues on. Okay, so Erin, let's look at it from the other side now. So how much is Google spending on Anthropic?

13:03Erin Woo:Yeah, so Google has most recently said that it's investing$10 billion into Anthropic, and there are plans to invest another$30 billion if certain milestones are met. And that's just the most recent amount of investment. Okay. And so, Aaron, I mean, taking a step back here, what do you make of the interconnectedness here that Sri pointed out? We've talked about this circular financing in all sorts of different circles. circles, this is one of said circles, and I'm sort of imagining drawing all these overlapping circles on a piece of paper. But when you talk to people, was this inevitable? Is it something to be concerned about?

13:45What's your reaction to it?

13:47Erin Woo:Yeah, I mean, I don't necessarily think it's inevitable. I think this gets back to the big question that everyone's asking, which is, is AI a bubble? Is the bubble going to And so I think you have a week of pretty good earnings for all of these four major hyper sales like Google, for example, did very well. And then you dig into the numbers a little bit and you see that a lot of this growth is coming from Anthropic. A lot of this growth is coming from OpenAI for some of the other providers and even beyond the specific numbers that we have in this that represent the cloud deals that companies have signed with these providers.

14:22Erin Woo:like there's also additional revenue because some of the growth in google clouds revenue that's not about compute like comes from the resale of anthropic models so a lot of this is like bound up in these same two companies and so that's what's stoking fears of a bubble and the question is obviously like is anyone actually using this ai hmm shri oracle was in a uh oracle certainly in this equation, but they have sort of a slightly different case here. What is different about Oracle's relationship with these companies? So Oracle is actually working with OpenAI to build out these data centers on behalf of OpenAI.

14:59And so OpenAI has committed about$300 billion towards that relationship. And so I think a lot of investors are also sort of seeing how the data center build out on Oracle will actually play out because it definitely impacts OpenAI in in terms of having that compute available. And so I think that Oracle is perhaps in a different position from Microsoft, Google, and Amazon because it's reinventing itself as a major cloud provider to actually take on some of these huge contracts. And so I think that it's quite interesting in that more interconnected relationship that Oracle has with OpenAI because Oracle definitely realized in OpenAI to be able to get on that business.

15:38Right. But Erin, correct me if I'm wrong, I mean, Oracle is slightly different in that they're not reselling the models the way that Google and Microsoft are, right?

15:48Erin Woo:Yeah, so Google and Microsoft and Amazon, they all make additional revenue reselling the models to customers. So like Google, for example, has this thing called the Model Garden. So they offer Google's proprietary models, but they also offer Anthropics models and a lot of different open source models. So there's that additional revenue stream. And Aaron, as you look at the reporting questions that you have for this story going forward, what comes to mind? Like I said, I think one of the big questions is how companies are actually using AI. And I mean, certainly to some extent, companies are, like we've seen, the huge revenue growth that Anthropik has that comes from enterprise AI.

16:26Erin Woo:Another story that I reported yesterday was that Google and private equity firms are in talks to form a new partnership. And so this is Blackstone, KKR, EQT, and this would help distribute AI to the portfolio companies. I mean, one of the trends that I've written about recently is the difficulties that some companies are having adopting AI. And so this would be beneficial for Google, for example, because all of these portfolio companies would start using it. And as long as you believe that using AI is also beneficial for the portfolio companies, like it's also good for them and private equity firms in that way.

17:03Right. Yeah. It certainly seems like a steady drumbeat of news or announcements or stories from you and Sri, mind you, talking about how the private equity firms are really leaning into this to get their portfolios in check. It's one to watch. I want to thank you both for coming on. That is Sri Mupiti and Aaron Wu from our newsroom here at The Information. The Information's Rocket Drew is covering the Elon Musk OpenAI trial from the courtroom all week long. Here is his latest update for us on OpenAI President Greg Brockman's second day of testimony in the court on Tuesday. Greg Brockman had a slightly better day in court.

17:47After previously facing some really rough questioning from a lawyer for Elon Musk who asked about Brockman's personal finances and his stake in OpenAI, Brockman had the chance to answer some friendly questioning from a lawyer for OpenAI. That gave Brockman the opportunity to explain some of the context around his personal journal. This is the digital diary that Elon Musk's side has presented as though it contains a smoking gun, an admission of guilt from Brockman that he was intending to lie to Elon Musk or deceive him about his plans for OpenAI's future and for its corporate structure. In particular, there was one passage where Brockman contemplated a path forward that he said would be morally bankrupt for him to pursue.

18:29Under questioning from OpenAI's lawyer, he explained that that was a path they never ended up taking. That was a path that would have involved firing Elon Musk from OpenAI's board and then creating a for-profit subsidiary without him. In fact, they didn't fire Elon, and when they did create a for-profit subsidiary, the questioning revealed that Brockman and others were looking for ways to include Elon in that plan, were looking for ways to offer Elon equity. Under Brockman's testimony, it was only once Elon was unable to have control over that for-profit entity that Elon gave up on the project and left OpenAI.

19:07Elon's side says that he would have had control initially, but that control would have been intended to dissolve or reduce over time as further board members were added and new investors were brought on board. One of the most interesting exchanges during Brockman's testimony today was that Brockman said he doesn't think Elon is very good at AI. He said he knows cars, he knows rockets, sure, but he doesn't know too much about AI. And to illustrate that, he gave an example of when Elon was given a demo of an early iteration of the technology that would later power ChatGPT, and Brockman says while the rest of the team understood the promise of the technology, Elon thought it seemed kind of stupid.

19:47He thought kids talking to you on the internet could do a better job. He was not impressed, and the researchers who worked on that technology ended up feeling disheartened. So Brockman said for him, this was an early illustration that he didn't really trust Elon's judgment on matters of AI as far as the technology goes. That was kind of contrasted with an anecdote that Brockman gave earlier in his testimony of a time when Elon asked a bunch of open AI researchers to come visit Tesla and improve some of the technology and the processes at Tesla. In Brockman's telling, Ilya Sutskaber, who is also a co-founder of OpenAI and is regarded as a brilliant AI scientist, went to Tesla and gave them some encouraging words of wisdom, saying that if you can collect, say, 10 ,000 images of roads with poor conditions where Tesla cars currently struggle with self-driving, then I guarantee you that AI will be able to handle the problem.

20:42So that was kind of an illustration of what maybe it does look like to have a natural intuition or a familiarity with AI and a sense of the promises that it has. So that was what we heard from Brockman. Up next in Musk v. Altman, we're expected to hear from Siobhan Zilis, who is a mother of four of Elon Musk's children, but was also on the OpenAI board. The question for her is whether she was sort of observing and honoring her commitments on the board or whether she was also funneling information back to Musk in a personal capacity during that time. So that's what's up next in the Musk-Fialtman trial.

21:21AI platform Tessera Labs announced$60 million in a new funding round led by Andreessen Horowitz. I'm joined now by the company's CEO, Kabir Negrecha. Kabir, welcome to the show. It's great to have you here. Great to be here. Thanks so much, Akash. Okay, so I am excited to talk about the company, but I have to ask you the question. You started college at age 13. How does one even do that? It's a long story, long journey. I mean, it wasn't that long. You did the same four years, just you were 13 to 17 years old. That's right. Four years of college, three years of PhD, ended up wrapping it all up around 20.

21:58Okay. And what, you just applied at age 12? Ended up skipping high school with some programs for it out in California. So went down that route. Okay, well, that's a route I would like to hear more about later on. Let's talk about your news this week. So Tessera Labs is raising$60 million. What does the company do and what do you plan to do with the money? Yeah, so what we do is really AI around IT transformation work. All of the heavy legacy work around ERP migrations activities, mergers and acquisitions, consolidations, revamps of portfolio companies for private equity firms. IT transformation work all around the world, currently done primarily by services activity.

22:40We instead try to drive via AI. The money, it's really going to help drive our expansion. We've been on a good rip so far, getting our first few blue chip Fortune 500s, and now pushing out to that broader market. We really appreciate the support and confidence from Andreessen to help lead our round and drive this activity. So on a good rip so far, how much revenue are you guys generating? I don't know if I can mention specific numbers, but what I can say is that the programs we're going after are multi-billion dollar programs. I think the lowest one I've ever seen was$200 million. These are the heavyweight services engagements of the world, and we're doing what we can to cut down those costs by orders of magnitude.

23:24And what was the valuation that you guys raised at? So the valuation we raised at, I'm not sure if I'm able to disclose, but it reflects the substantial value we've been able to bring to those enterprises so far. Great. So I just want to understand this a little bit. So, you know, when you talk about these enterprise, these software transformations going on in enterprises, I mean, are we talking like, you know, the old school digital transformations, like, you know, companies trying to get their IT systems from on-prem to the cloud? Like, you know, because there was certainly that transition. Now there's the whole transition of, you know, using AI, which is a whole separate story.

24:03But am I correct in understanding that you are actually focused on sort of the more traditional digital transformations that we have been doing for the last 20 years? Very much so. You know, I think we tend to believe that a lot of these digital transformations have already come to fruition, have already ended. What I can say is even the on-prem to cloud transition is very much still alive. We still see it in many, many customers out there that they're running on-prem data centers. Their entire businesses are still being run through mainframes, through systems from the 80s, the 90s. And the reality is we talk about this AI transition and moving to AI usage.

24:39Oftentimes this is gatekept and bottlenecked behind making that first digital transformation. So our view is not just focusing on the AI at the end of the journey, but actually bringing AI into that digital transformation journey to solve the prerequisites for AI. And so how are you using AI then tactically to help with that on-prem to cloud transformation? We're essentially helping to solve out all of those traditionally long-pole items, the ones that would have taken six, eight months, multiple years to drive, code transformation, data cleanup activities, configuration of new systems, identification of business process gaps.