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Grok 3, AI Memory & Voice, China, DOGE, Public Market Pull Back | BG2 W/ Bill Gurley & Brad Gerstner

BG2Pod with Brad Gerstner and Bill Gurley

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  • Grok’s Performance Ceiling
    • Grok’s rapid progress shows pre-training models’ potential, but also reveals a performance ceiling.
    • Continued growth may depend on novel training techniques or leveraging unique data assets. Transcript: Brad Gerstner And so maybe you can just help us zero base what you thought when the model came out, where it stands in the rankings, then we can have a conversation about the impact and what it means. Bill Gurley So we’ve talked about this in the past, but everyone in the ecosystem was super impressed with how quickly they built the Memphis facility and how big it was. And it was the largest contiguous cluster in the world. And there was a lot of chatter about that ahead of time. Yes. And I can remember some of the investors there saying, this will prove that pre-training still has headroom because this will be the biggest cluster ever trained on. Correct. And you can decide what your expectation was that kind of line in the sand. The things that happened, I mean, I think the generic way of saying it is like it went right up near the top of all the benchmarks. Right. Ahead on some, not on others. Some people argued about whether they- The reasoning component, the beta reason. Or did they cheat or tune to a benchmark? But I don’t think it matters. Like, like, I think the biggest positive takeaway is there’s a new player in the model market. And we had often a lot of people said, as a sport of Kings, there’s only going to be so many players. Correct. There’s a new one in the market invested what they needed to do that has access to capital, has a data asset that they argue is important and special, and was able to get at the front of the Race. Let’s just call it that. Right. (Time 0:01:53)
  • Consumer Adoption as Success Metric
    • Benchmark performance is important, but consumer adoption is the ultimate metric of success in AI.
    • Grok’s integration with X’s platform is impressive and differentiating from competitors. Transcript: Brad Gerstner And you’re looking at, you know, we’re looking at this artificial analysis that just shows, I mean, there’s this clustering here in the upper right. You know, Deep Seat kind of got up there a couple of weeks before you had Grock. You know, what’s interesting is they all seem to be coalescing in an impressive way around the top of these benchmarks. When we say they all, I mean, we’re really only talking about five or six players who have a chance to be in this game at this point. Bill Gurley Correct. Correct. And I saw people who interpreted Grok’s fast rise as proof that pre-trainings still got legs. And to me, I kind of had the opposite reaction, which is I felt like they just slammed up against the ceiling that’s holding everyone in. Brad Gerstner Right. Although, again, an incredibly capable level. Oh, no doubt. Bill Gurley I’ve said this for a while. I’ve been, I’ve been concerned that the way an LLM works and the way it’s optimized that building bigger clusters and more parameters won’t buy you much. And whether I’ve said it or not, Ilya said it, Andreessen said it, other people have said the same thing. And so to me, this reinforced that, that point I was expecting. If, if there were-training headroom, I was expecting this to go through. Now, I will qualify this was their first run. Maybe there were some tricks they didn’t know. They can very well back up and do another run on that same large cluster and maybe shoot past these people. Or maybe these benchmarks aren’t the exact right thing to be looking at. Brad Gerstner I would say a couple other things. Number one, it’s not just a pre-trained model. They also have an inference time reasoning component to the model that’s incredibly capable. We have this benchmark chart that I tweeted the other day, and I compared it to the search index benchmarks that we all use to track. The, you know, the benchmarks are one thing, but the reality is, is how do we feel when we’re using the product? And what I will say is Grok3 rocketed to the top of all app downloads, you know, on the iPhone charts. The, you know, at least my Twitter thread was full of people having great experiences, showing those great experiences on Grok 3. So it had a personality and an interaction with people that I think people were enjoying. So number one, it just has to be capable enough, right? And it clearly crossed the threshold of being capable enough. Now the real question shifts to, can they leverage the X platform, right? Which reaches a massive and important audience to really drive that. And what I would say, the early indications to me, when you compare it, for example, to how Meta has used Meta AI, like, as incredible as I think Zuckerberg and Meta are, and the advancements They’ve made, I have not particularly been impressed by the productization of meta AI, right? It’s basically just a search box stuck at the top of Instagram or stuck in my WhatsApp thread. And when I’m on it, I never intend to be there. Bill Gurley It’s not the right context. Brad Gerstner Right, whereas on X, they figured out, you know, the first thing they did is they put that button at the bottom of the app that clearly distinguishes it as its own standalone application. They launched a standalone application. They’re using X to drive those app downloads. And now I just opened up my, you know, my X app today and it said, hey, go out and try the new voice for Grok 3. So to me, the execution on the product side to drive consumer use has been pretty damn impressive and took them to the top of the charts. Bill Gurley Yeah, and only DeepSeek and Grok of all the others have shown the ability to break into the top 10 on the app store download. (Time 0:03:30)
  • OpenAI’s Consumer Velocity
    • OpenAI’s large user base provides an advantage in model improvement through diverse feedback.
    • Competing with this consumer velocity is crucial, but OpenAI’s lead is significant. Transcript: Bill Gurley It. So I think one thing to be good for the audience, I know you’ve said it in the past, but you’re an investor in OpenAI. I think you have a theory about their prowess in the consumer market and their lead in the consumer market. So why don’t you reiterate that? Brad Gerstner Yeah. Well, I mean, you know, I’ve showed this chart before, right? That in the search wars, we had Google and Yahoo and AltaVista and Lycos and Ashgeef and Excite and Infoseek. And by the way, they all did pretty damn good on the benchmarks, right? But the reality is that didn’t get them to any value creation because ultimately all the consumers aggregated around Google. So the real question is, does that same pattern play out of winner take most in consumer around AI, right? It did in search and it did in social, but it’s not necessarily, you know, follow on that it will in AI because, you know, I’ll stipulate X has an incredible installed base that they can Market into. Meta has an incredible installed base. Google has it. And it’s existential for those companies in order to, you know, market to those consumers. So I don’t think it’s going to be win or take as much. I don’t think we’re going to see a 99% monopoly here. But I do expect that we’re going to see 70% or 80% share go to the winner. Now, if we look at the numbers. Yeah, the numbers. Yeah, if we look at the numbers today, I think last week, Sarah reported that OpenAI has crossed 400 million weekly average users. And that’s a user number, not a paid user. That’s a user number, right? The number of paid users is a fraction of that. I think they also reported last week something like $11 or $12 billion in expected revenue this year. So you can reverse engineer your way into kind of what percentage are paying for that. But more importantly, I think the number of monthly average users must be somewhere on the order of magnitude of seven to 800 million monthly average users. And you and I followed consumer for a long time. There’s this magic number around a billion. I mean, I already think they’re nearer at escape velocity. But at a billion monthlies, you can funnel all of those folks into weeklies. And then you funnel the weeklies into paying subscribers or people who are consuming advertising. So what I have seen is everybody else catch up on the benchmarks. What I have not seen is people catch up on the consumer velocity. (Time 0:08:10)
  • Google’s AI and SEO
    • Google’s integration of AI answers directly into search results is killing SEO.
    • This presents both a challenge and an opportunity for other search-oriented AI products. Transcript: Bill Gurley Let’s handicap some of the other players a bit. Yeah, I’m good. Who do you think is closest from a user standpoint? Is it probably, you’d have to count the Gemini searches in the Google search, right? Yeah. To get to a number that’s close to opening. Brad Gerstner Yeah, I mean, listen, I think, you know, let’s just start with Google, okay? So there’s been a lot of reports out over the course of the last couple weeks. We have public companies now reporting that are reporting their Google organic clicks are down 20 to 40% year to date. So the question is why? Like why is Google’s clicks down so much? Because if I do a Google search today on my phone, half of the page is taken up with an AI answer to whatever my Google query is and the rest are all paid links, right? I think Google, I think that’s the right decision for them to make. If you want to compete, you ultimately have to be willing to take the innovator’s dilemma head on and really just cannibalize your product with AI. Bill Gurley Now, if they do that- And if you’re one of these humans that thinks SEO wasn’t dead already, which I would have declared it dead a while ago. Yes. It’s really f***ing dead. Brad Gerstner SEO is dead. And just, you know, those are the free links. I understand. That was the core product that used to attract everybody to Google. And the idea that SEO is basically now gone is pretty short. Bill Gurley You know, I think, and this is just an aside, but I’ve been remarkably frustrated with Google’s organic links for the past five years because you go in and search for your favorite team Schedule. Right. And all the ticket guys are up front. Now, like the link you’re looking for, you have to hunt for. Okay, so let’s talk about that for a second. Brad Gerstner I mean, now the obscure link or the obscure information that you and I may be looking for may be on page three, four or five. You and I are never going to get to page three, four or five. What’s so interesting, for example, about OpenAI’s deep research. Now, if I launch a query using deep research, it will go to page four or five or 10 or 100 and find those obscure pieces of information. So I think the evolution of Google actually provides acceleration to the deep research projects because I don’t want to go do that deep research. So Google, I think you just can’t discount their installed base, the number of people going there who will, inertia will continue to carry them there. But I would say this, and you can go search for this on Twitter or anywhere else. And I know certainly with my own behavior, the amount of activity that I used to do on Google has been 80% cannibalized by ChatGPT because there’s search embedded within ChatGPT. And so, you know, I’m getting all of that information, all of those answers. So I think that they’re going to, you know, be formidable. I think they’re being bolder than they’ve been. But I think they’ll have to continue to do that. Bill Gurley I think that we’ve talked about this, but I think some of their assets are remarkable. I mean, you got the YouTube data set and all the search queries over all the years, their understanding of structure, of structured data around a lot of the consumer verticals. I mean, they built that out in airlines and things. They should be able to do those agent type queries better, faster, should. Brad Gerstner Their velocity on product has not been impressive. Their velocity on consumer has not been impressive. So they have them. They’ve had them for a long time, Bill. They had ChatGPT before ChatGPT. Bill Gurley They also have Android, which is a massive asset. And they also have browser. They’re their own browser, which both Perplexity and OpenAI have started toying with the idea of either having a browser or in the operator case of using a browser in the cloud to go do This work. Anyway, they have so much. I still think they have a bit of the innovator’s dilemma in that they can’t, they still have to try and maintain those paid links on that page. Brad Gerstner And this chart here, the black line, is Google’s paid click growth plotted against the weekly average user growth at OpenAI. It’s not going in the right direction. Bill Gurley Well, and I think it benefits from the fact that informational searches are what chat GPT cannibalized first, not the commerce searches, which is where most of the money is on the paid. (Time 0:10:35)
  • AI Agents and the Internet
    • AI agents will expand the internet’s domain and potentially disrupt existing business models.
    • Companies like Meta are well-positioned, but product execution and speed are key. Transcript: Brad Gerstner Although, you know, again, and we’re going to see this out of X, we’re going to see it out of everybody. Right. Everything, the entire domain of the Internet is the domain of agents. So if you think about operator as one of the first agents rolled out by OpenAI. What does operator do? It goes and it mimics me as a human going out and researching a hotel and booking a hotel or whatever on the internet. And we’re in a very embryonic state. I agree with you. We’re not there yet, but it’s very clear what the roadmap is going to be. Bill Gurley It’s going to want your credentials and whether you give it your credentials or not is going to matter because it’s searching against an so let’s talk about meta you know i know that actually One last thing on google like there was a point where meta went public at 40 we had backed up the truck we had some so i was like paying attention and zuck as he has many times got woken up on Brad Gerstner 100 and everyone thought he was dead because he had also built an html5 he didn’t believe in native app there’s a whole thing that they weren’t going to be able to monetize mobile he was On it was on the cover of baron’s magazine yeah the weekend magazine right it was like meta’s dead or facebook’s dead right Right. Bill Gurley But he woke up and fixed it. Can Google do that here? Is that possible? Can they have a similar like, and what would it look like? And what would it take? Brad Gerstner Well, I mean, listen, I’ve said publicly that Google’s moat was not a technological moat with search. Their moat was a distribution moat. Their moat was a mindshare moat. We Googled everything when we wanted to know anything. And the only thing that could attack Google was never anything head on. It had to be an orthogonal attack from something that was 10x better, 100x better, because it gave us answers instead of blue links, right? That’s why it was such a mortal sin for them to ever, ever allow else to go first. Because the only thing that could give you a trillion dollars worth of free mindshare is going first with something that was 100x better. And that’s exactly what ChatGPT did at the end of 2022. Bill Gurley All right, go to Meta. Brad Gerstner So, I mean, you know, again, Meta, if you had to handicap the big guys, 3 billion users of their product, I think they have products that are tailor-made for chat-oriented AI, whether It’s Instagram and having shopping agents and co-shopping agents, or whether it’s WhatsApp and just having a bunch of agents live within my WhatsApp channel. It feels natively much better positioned for AI. And we know that Zuckerberg is in complete beast mode. But I am surprised, I have to say, that we’re now kind of 18 months into kind of the llama thing. And it feels like the manifestation of it into the product was slower than I expected in 2024. Bill Gurley Back to your product point. Right. Exactly. Right. Like Meta hasn’t. Brad Gerstner And I will say I will say even, you know, we know he was rip about Deep Seek, right? Kind of blindsiding Llama in the release of R1. And so I would say it’s not just product for them. I think they have, you know, I heard from several inference players that you and I are friends with that all of a sudden DeepSeek rather than Llama is the enterprise open source model Of choice that everybody’s experimenting with and playing with. Problem for them as well. So I think 2025 is a critical year. I think they will come through. And remember, when it comes to almost all product stuff, stories, copy, you know, catching up with Snapchat or whether it’s reels catching up with TikTok, they’ve always showed up To the party late, but they are grinders and they always deliver the product. (Time 0:15:05)
  • Differentiating Features in AI
    • Memory, voice integration, and unique features could differentiate AI products.
    • Developing a network effect based on user contributions is a key challenge. Transcript: Bill Gurley So here we go. Here we go. I have four things I’m watching out for that could potentially lead to either further lock in by OpenAI or a window for someone to do something else. And some of them I mentioned before. But I think, you know, memory is still this thing that could just tie you to something. And OpenAI has probably done more with memory than anyone else, but no one’s really got to the place where I’m telling it to remember things, to store things, to create lists, like where It starts to become like an executive assistant for you yeah and we’re i haven’t seen that yeah i still think that’s a a dimension that could really be important voice we’ve talked about Like and they’re all playing with it um i think voice and also uh ties in with device type and And this is where Alexa may have some assets, but if the voice were spectacular, they might Not have to carry the phone around as much. Brad Gerstner And by the way, by the way, I need it. Yeah, you need an earbud. I will say advanced voice mode on ChatGPT is excellent. Grok 3’s new voice, excellent. And they’re getting better at an accelerating rate. You know, we’re an investor in this company, LiveKit, that’s powering a lot of this voice. And I will tell you what I see in the product pipeline is super impressive as to what’s coming with voice. Bill Gurley The third one’s nebulous, but just someone could focus on a feature that no one has to date. And right now, the game looks so much like with the benchmarks and voice, everyone’s running at the same place. So I don’t know. That’s an easy thing to say, but it’d have to be really out of the box. And then fourth, I just have been thinking about this. No one’s really thought about a network effect. And I wonder how you could make the quality of the AI experience a function of your user base. (Time 0:23:06)
  • AI-Powered Life Story
    • Brad used advanced voice mode to interview his mother, highlighting memory’s potential for personalized storytelling.
    • The challenge lies in helping users discover these powerful, yet often hidden, features. Transcript: Brad Gerstner Let me give you an example of a network effect I think that is happening. I think around model improvement. If you have seven or 800 million monthly average users, your diversity of information and questions and answers and follow-ons, et cetera, is much, much higher. Those questions and data, that’s now being fed back into the models to improve the models. Bill Gurley And some users may have seen, I know I have, you get two answers and the OpenAI ask you to. Right. Brad Gerstner So I think that’s an example of open AI very actively attempting to build network effects in terms of the quality of the model, the quality of the answers. Bill Gurley But there could be a more intense form of network effect if you found a way to leverage the user base as part of the value property. Brad Gerstner Let me go back to your first one, memory, because you and I have talked about this a lot, right? If you get memory, the switching costs explode, right? And I would argue not only does switching costs explode, the conversion rate from free to paid probably also goes up, right? Just because the value delivered. And so I was with my 89 year old mother last Sunday. And my mom has wanted to write a story of her life for a long time. And the reality is she’s never going to sit down and write the story of her life. And yet when I’m with her, podcast style, I’ll ask her questions. And I’ll just record it on my phone, right? So that I have it and I could perhaps go back later. And then I started thinking about it. And I said, I don’t need to be the interviewer, right? Advanced voice mode could be the interviewer. And so I was sitting there with her last weekend. Here’s the prompt, you know, that I gave to advanced voice mode. I said, you know, I’m sitting with my 89 year old mother tonight who wants to write her life story. I want you to interview her about her life, to ask questions about her childhood stories, having kids, working, growing up in the depression, her love of computers and travel, to remember Everything you talk about and then compose a story of her life that her grandchildren would like to read, okay? And then advanced voice mode just started asking her questions. Bill Gurley How long did it go on? Brad Gerstner I mean, my mom was really nervous at the start, but then like a little tear wells in my mom’s eye, you know, because she, she realizes all of a sudden that, oh my God, this could be a massive Unlock. So here’s the thing, Bill, advanced voice mode and chat GPT already has memory. You can already do these things. The problem is the nature of the product, you don’t know that it can do those things. So part of the challenge about designing a product where prompt is your way in is you’ve got to help people imagine. Like you and I could have imagined in the age of internet, somebody building an internet website that just did that thing. Okay. I think that’s one of the challenges all these companies faces. And the innovation around that top end of the funnel in the prompt that can help people better get into it. I’ll give you another example. Deep reasoning, which is really fascinating. They basically took the O3 series of models and fine-tuned it end-to based upon all these browser interactions, right? And, but you need to, the more specific the prompt, the better the deep research report is going to be. So a lot of people are using O1 to help them build sophisticated prompts that they then feed in to deep reasoning. And so I think that there’s something in there where we’re effectively using AI to get us to the point where we’re better prompting. And one of the ways will be very simple, right? Once I have this assistant and I’m having an interaction, I just say to my assistant, hey, my mom wants to tell her life story. I’m not sure how to go about doing that. Do you have any ideas? And she would say, hey, yeah, just use this prompt. (Time 0:25:10)
  • AI and Data Integration
    • Integrating data like contacts, emails, and content repositories can enhance AI product value.
    • Seamless data flow and storage within the ecosystem are crucial for user adoption. Transcript: Bill Gurley No doubt. And I also think that there are other assets that could play a role, like a contact database, an email. Yes. I mean, I can even imagine moving my email to one that’s integrated inside just because. Contacts is a great one. If they just cleaned up your contacts well knowing my contact right and know your contacts yeah but send an email send a text i mean there’s a there’s a lot big and then for anyone that works With content there’s some app you know i i all my writing and everything i’ve done for the past 10 years has been in quip but some people use notion yes and like like type of repository and How these things can interact, there’s just a lot of surface area to figure out. Well, and this- Like where does that story land? Where is it stored once you did it? Exactly. Or do you have to take it out of OpenAI? Like, you know, you’d rather just have a place. Brad Gerstner Correct. And now you have projects in open AI and other things. So this is, it brings me to a point. When you think about these research labs and you look at the number of people who work there, right? Just the fact we even call them research labs, you and I haven’t, you know, nobody called Google a research lab, right? It was a company. It had product teams, it had marketing teams, it had finance teams, et cetera. But I think because a lot of these people came out of research, that you look at them and they’re still very small teams, very heavily tilted toward building toward the benchmark. OpenAI now has thousands of people. I know Kevin Weil, who runs the product team over there. So all these companies, if you’re going to win this race, you got to do all the things, great things that great product teams do. And it’s building all the shit that you’re talking about. And that’s hard. And you got to be thoughtful and you got to growth hack and you got to get those customers to use the product more and more. (Time 0:29:05)
  • Focus on US AI Development
    • Focus on accelerating US AI development rather than hindering China’s progress.
    • Restrictive regulations on US companies might backfire and hurt competitiveness. Transcript: Brad Gerstner We’ve talked a lot over the last few weeks about DeepSea clearly coming out of left field, very efficiently building a frontier quality open source model. But most people have kind of quietly ignored probably the company that’s the leader in AI in China, and that’s ByteDance. Their AI, you know, their chat GPT equivalent is number one in China, right? And they’ve been using AI to drive TikTok globally for a very long period of time. So I know you have strong opinions on this. It seems to me the U.S. Has underestimated China at AI. And now we’re at this inflection point where I think there are a lot of people who say, well, they must be smuggling GPUs into China or this or that. But the reality is China is going to have frontier AI. And almost all of the things we do to try to slow them down and stop them are backfiring on the United States. Bill Gurley I couldn’t agree more. I witnessed almost daily people that are either in government or even friends of ours who say we have to win the AI war with China. And I don’t know what that means. I can’t imagine an end state where we control all the AI and they don’t have any. It’s already too late. And they’re smart, as possibly can be. And they’re innovating. And you look at all the other products that they’re crushing it in. Yeah, I just don’t understand. Brad Gerstner And the reality is that we just need to focus on running our fastest race. We need the Teslas. We need the open AIs. We need rockets that land themselves. We need all of this. But to think that they’re not going to have BYD building great cars, or they’re not going to have DeepSeek building great models, or they’re not going to have rocket companies that copy Bill Gurley Us and can land themselves. That would be naive. It’s remarkably naive. And it’s going to lead to people making decisions, like you said, that either slow us down ourselves. A lot of the AI regulation would definitely do that. Or just provoke them in ways that isn’t helpful. And it’s not going to slow them down. (Time 0:33:47)
  • Diffusion Rule Backfire
    • Biden administration’s diffusion rule on chip exports may backfire by strengthening competitors like Huawei.
    • This highlights unintended consequences of regulations on technological competition. Transcript: Brad Gerstner Well, let me give you one example of this. And then I want to move on talking about the arms race, if you will. But during the Biden administration, they passed something called a diffusion rule out of the Commerce Department, which we’ve mentioned on this pod before, which created this convoluted Set of rules by which U.S. Semiconductor companies could export outside the United States. Now, this wasn’t exporting to China. We already have export restrictions with respect to China, but it basically made all these tiers and classifications on how much you could distribute. Did you have to distribute it through a hyperscaler or not? And the whole idea was to somehow prevent these chips from getting to China. But what it really does is it causes us to have to compete globally with Huawei with one hand tied behind our back. And it almost guarantees a Huawei level belt and road initiative around the world. And the world’s going to run on Huawei AI chips, which gives them then the demand that they need to build a frontier AI chip. And so, again, well-intentioned perhaps by the Biden administration, but totally backfires. And hopefully Howard Lutnick and this administration will, I don’t know, throw that out and start a new. Bill Gurley I think there are a remarkable amount of people in Washington on both sides of the aisle that have a perspective about China. They use words, enemy, threat, have to win the AI war. And those terms are so loaded. But I think they think they can achieve something. And if I owned NVIDIA, my number one concern would be excessive regulation coming out of Washington. My number one concern. Let’s shift gears here for a second. Brad Gerstner You talked about OpenAI losing this report that they were losing $20 billion a year. One thing I would just say, I’m not going to share anything, you know, that I shouldn’t share. However, I think one always has to keep in mind what is operating expense and what is capital expense, right? And, you know, there’s a variable cost of serving a chat GPT query, right? And, you know, I would posit that those variable expenses are not very high, like at maturity. Bill Gurley Although a deep, like a O1 Pro search or deep research could cost 20, 40, 50x the other. Correct, correct. Brad Gerstner But I would just posit for you that you’ll be able to come up with a variable expense structure using the right mix of models that will be a great margin. May not be as high as retrieval was for Google, but still a great margin. I think what people are conflating, Bill, is when you decide to spend $20 billion a year to build out Stargate, to build out clusters, to do all these things. Now, as you know, a component of that is the CapEx needed to serve the inference. And a component of that is CapEx to build future products, right? And so, for example, if we’re looking at Facebook or we’re looking at Google or we’re looking at Microsoft, Microsoft, I think, is spending 80% of their free cash flow, right, on CapEx. Now, we don’t quote that as their profitability. They have their net income and then they have their net income less CapEx. I would keep that in mind. But what I would say is these folks are very committed to continue to invest aggressively in a future that they see as big. But we heard from Satya on the Dworkish podcast, right, what many are characterizing as a pushback against these high levels of spending. I think of my fleet even as a ratio of the AI accelerator storage to compute. And at scale, you’ve got to grow it. And so that infrastructure need for the world is just going to be exponentially growing. So in fact, it’s mana from heaven to have these AI workloads because guess what? They’re more hungry for more compute, not just for training, but we now know for test time. (Time 0:36:04)
  • AI’s Capital-Intensive Race
    • Massive capital investment in AI infrastructure is needed to compete, raising barriers to entry. OpenAI and X have secured large funding in this capital-intensive race.
    • Resiliency and unit economics are key to surviving potential market downturns. Transcript: Brad Gerstner And as I said, test time, like here’s an interesting thing. When you think of an AI agent, it turns out the AI agents is going to exponentially increase compute usage because you now are not even bound by just one human invoking a program. It’s one human invoking programs that invoke lots more programs. So that’s going to create massive, massive demand and scale for compute infrastructure. So our hyperscale business, Azure business, I think that’s like another hyperscalers. I think that’s a big thing. And I think on the pod, he reiterated, we’re going to spend $80 billion this year. We’ll spend more next year, but there’s not a world in which we’re just going to have unlimited, unconstrained spending. Now this week, we also saw rumored that Meta is out shopping for a campus, a data center campus. The rumored amount is $200 billion, capable of building six to eight gigawatts. Now, that sounds a lot like Stargate, which is kind of in that six to eight gigawatts. Microsoft, I think, has five gigs installed, probably is going to build a few. Worldwide. What? Five gig worldwide, is that what you mean? Correct. And going to build more. So again, it seems to me that if you want to be in the group of five or six, that’s kind of the calling card you have to have. You have to either have a business or the ability to raise capital such that you can deploy a sufficient amount to build out that level of compute. Now, in the case of OpenAI, enter Masa back to Lyft Uber. And Masa is rumored to be leading a very big round, $40 billion round with a lot, which we saw they announced it at the White House. Bill Gurley It is important. Many people interpreted Satya’s comments as a tapping of the brakes. Yes. Brad Gerstner So tell me how you interpreted it. Bill Gurley Because he said, I’m happy that some of these are leases. Yes. Which I don’t know any other way to interpret that. Well, there’s two ways you can interpret it. One is he’s telling you, like, I’m hedged against this being overbuilt. Yes. Or I’m better off canceling a lease than sitting on infrastructure. Brad Gerstner I would say it even a little bit more. Like, let’s be honest. Satya said last June, we talked about on this pod, that it was very likely that at some point there would be a supply and a demand mismatch. And you had to build a resilient company that can go through a zone of disillusionment. Right? So he basically said, the reckoning is coming at some point in time. And so now he goes on dorkish, he kind of sounds like he’s tapping the brakes a little bit, you know, and so I think that the interpretations of that should not be that he doesn’t believe In AI. I think he very much believes in AI, but he’s running a public company. And I think that he’s made commitments to his shareholders. And he’s saying, listen, I need to see a certain amount of inference revenue in real time to justify that level of CapEx. Yep. Bill Gurley Look, I mean, I think everyone believes in AI. This amount of spend is something we’ve never seen before. That’s why I’ve said that it’s better than watching Secession. It’s a massive sport of kings. And I think some of the things, whether it’s the 20 billion losses or Satya saying he’s glad he’s got leases, some of these might be part of an information war with other players trying To talk capital in or out. And it’s a high stakes game. It’s fun to watch. Brad Gerstner Well, I think resiliency, business model resiliency is going to be critical here. And what do I mean by that? It means liquidity. Because we know in the internet, there was a zone of disillusionment. We know in social, there was a zone of disillusionment. We know in cloud, there was a zone of disillusionment, right? A period, what do I mean by that? A period where the prices and the spend got ahead of the revenue, right? And, you know, given the level of competition, some people describe as a prisoner’s dilemma, right? In the case of Google and Meta, they literally have a printing press in the back room spitting out billion dollar bills, right? So they are resilient. Microsoft, resilient, right? In the case of OpenAI, they have to raise money, right? So you need to have a big stack behind you. In the case of X, right, they need to be able to raise capital. I think there were some numbers out there last week. Obviously, Elon is the wealthiest person on the planet. He can sell shares in some things. But I think the most powerful thing Elon has is a global belief in him as an entrepreneur, which gives him an opportunity to raise capital (Time 0:40:13)
  • Unit Economics and Capital
    • Excess capital can lead to neglecting unit economics, a critical factor for long-term success.
    • Elon Musk’s capital constraints at Tesla forced him to prioritize efficiency and cost reduction. Transcript: Brad Gerstner From sovereigns around the world. And so if you said, is this still an open sport? I’d say no way. Right. I don’t know anybody else other than the Elon and Sam at this point. Although DeepSeek surprised everybody. Well, I’m saying if you’re going to play that game. Right. And remind you, DeepSeek spent more than, you know, the amount reported in their last training run. But even more importantly, to serve an explosive amount of inference, they would have to spend a lot of money to build that computer. Bill Gurley I want to make a point that we’ll probably come back to much later. But when you have a scenario that has this much ambition and this much competition and this much capex as part of the game yeah it’s easy to lose sight of the microeconomics it’s easy to Lose sight of the unit economics so if you’re a you know an anthropic and you’ve you’ve got training credits over here and you’ve got CapEx and you do you or not? Am I thinking about depreciation or that when I say, oh, this is profitable or when I price my API product? And you’ve got this razor edge pricing thing that I’ve never seen before. (Time 0:45:00)
  • Austerity and Market Impact
    • Government spending cuts (Doge) combined with increased tariffs signal a shift towards austerity.
    • This could lead to short-term market drawdowns but is necessary for long-term fiscal health. Transcript: Bill Gurley Work. No doubt. I know you’ve been thinking a lot. Let’s switch gears. You’ve been thinking a lot about Doge and if it happens, what it means for the capital markets. And it’s interesting to even say if it happens, because as I watch the press every day, there’s an equal number of people that say, oh, this is going to take out all these costs. And there’s other people that say, oh, they’re just saying things, but they’re not actually going to happen. Brad Gerstner So I- You and I said some, you know, so I think on our pod on like February 6th or something, you know, when you asked me about the markets, I said, hey, we have peak political uncertainty, Right? Because we have a lot of things changing. We have peak economic uncertainty. And that’s not just dose because that brings tariffs. Right, because we have tariffs and other things. And I said that we have peak technology uncertainty, i.e. It’s hard to predict the future, you know, what software company is going to be worth what in five years. And that causes discount rates to go up. It causes multiples to come down. And I said I was surprised how resilient the market was in the face of all this uncertainty. Well, now I would argue we’re starting to see a few cracks in that. And so if you look at this chart, Bill, it’s really the NASDAQ since the election. And we ran way up. The NASDAQ was up as high as 10% post-election. And now we’ve come off four or five points from that high. But we’re still four or five points higher than we were on the night of the election. And so one thing I just have been thinking a lot about and I’ve been talking a lot about is this difference between stimulus and austerity. Over the last three or four years, we had massive stimulus into the economy. Now, you and I both supported it in March and April of 2020, right when we were in the depths of COVID. You had to prevent the economy from coming to a screeching halt. And so the Fed went all in and Congress went all in, you know, in order to save the economy. But then we also were very critical that the Fed moved way too slow. The second stimulus package was way too large, and it led to this runaway inflation. We saw inflation hit 9%. But the one thing that all of that monetary liquidity did to the system is it caused risk assets to go up in value, right? And now we’re in this period where we’re talking about not adding a trillion and a half of liquidity to the system. We’re talking about pulling a trillion and a half out. Now, what do I mean by that? Okay. So last year we had $56 billion of tariffs imposed on other countries. That’s the amount of revenue we collected from tariffs. We’re talking about that going to 500 billion. So 10x in the amount of tariffs. Well, we know that some of those will be eaten by producers, right? The company that’s producing something in China will just take a lower margin. But we know a lot of those will be felt by US consumers who just end up paying higher prices for their Dell computer because Dell passes along the price increase of the computer made in Mexico, as an example. So that’s $500 billion. On the other hand, I think Doge, there’s no doubt in my mind at this point in time, and we’ll show this chart of the likely spending cuts, they’re not only making big cuts, and the president Has now, just last week, said he wants Elon to be more aggressive. They sent this email out to every employee that said, respond back to us, or you’ll be deemed to have resigned. Now they’re giving them more shots on goal. But the message is very clear that I think there’s going to be a downsizing of the federal government to the tune of, let’s call it, 40 or 50 percent. Now, a lot of people have been giving a lot of grief to doge, but I remind you, and I tweeted this the other day, that Bill Clinton, right, did doge in the late 90s. I don’t know the exact percentage of federal employees they let go. It was like between 10 and 20 percent, but we had a balanced budget. In three fiscal years, we had a $230 billion surplus. Now, it was helped by the internet, but now we’re going to be helped by AI. So I think that you can see some replay of that. But it does mean that we’re probably going to take $500 billion to a trillion dollars out of federal spending over the course of the next couple of years. And all I’m suggesting is that austerity has the reversed impact of liquidity from government into the system. So if you think about, go back to our GDP calculation, right, in macroeconomics, C plus I plus G, where G is the amount of money the government’s spending. Well, the amount of money the government’s spending is going down. So tariffs is a headwind to the economy and this austerity out of the government. Now, I am 100% in agreement. This is the short-term shock therapy we need in order to get our fiscal house in order, right? But you got to think about this as, you know, somebody says, hey, you’re out of shape. You’re going to have a heart attack. You got to take this medicine, this short-term pain. You got to work out every day. You got to get fit in order to avoid the heart attack. You would do it every day of the week. We need to get fit in order to avoid bankruptcy. And all I’m suggesting is- It might affect markets. That it might affect markets. So markets may in fact, my risk profile is lower than our standard risk profile. What do I mean by that? Very simply, you know, I own half as much as I would normally own at a point in time. Now, do I think that’s because the future, you know, is bleak? No, I believe aggressively in the future. But I think we’re going to have to take a little bit of short-term pain, which means we could see just a random run of the mill, 10% to 15% drawdown in the markets, while the market gets its Head around the fact that the economy is going to grow a little slower. (Time 0:48:40)
  • Warriors and Iguodala
    • Bill attended a Golden State Warriors game and noted their improved performance after a trade.
    • He also recounted a story from Steph Curry about Andre Iguodala, emphasizing his team-first attitude. Transcript: Bill Gurley Okay. That’s a tough note to end on. So I’ll switch to something more positive. I got invited to the Golden State Warrior game on Tuesday night. Brad Gerstner The Butler trade looks like it’s working. It’s incredible. Bill Gurley Six and one, I think, since the trade. Brad Gerstner It’s incredible. Related, I happened to go get an invite to the banner ceremony and dinner afterward for good friend Andre Iguodala. And Steph gave an incredible speech. And I had Andre speak at our investor day, maybe two years ago. And, um, two things Steph said, you know, that really stood out to me, you know, about Andre. Number one, he said, there is no this without Andre. Right. And, this, and he explained it to me, he said, he came at a moment in time, even his decision to come to the warriors made us believe in ourselves. And then he came here and he did whatever it took. And the second thing he said is Andre Iguodala always put excellence over ego. The guy would be the first to, you know, never pouted on the bench. When he came off the floor, he was the first to get guys fired up. And Steph talked about game six in Boston. I remember that game. I was at that game. And I remember Andre. He must have played five minutes in that game. And he was so fired up and really willed all the players to up their game. And so I was so happy for him. But yes, and you know, me and our good friend, Jason Chang, I never bet on sports. I never bet on sports. And he talks me in. We’re at a Warriors game during the losing streak, and the odds are so great that they’re not going to win at all. He talks me into, you know, placing a bet on them winning it all. And at the time, it was like 40 to 1, right, against them. And all of a sudden, they’re on this six-game winning streak. They trade for, you know, for Jimmy Butler, and like they may win this whole thing. So, you know, fingers crossed. It now has me with a focused mind. (Time 1:00:49)