Market Predictions, Rates & Inflation, DOGE, CES, AI Compute | BG2 w/ Bill Gurley & Brad Gerstner

29:33What I would tell you, when, you know, and without, you know, say anything other than what's been said publicly about open AI's revenues, right? You know, they ended the year. I think it was rumored four to five billion run rate growing very robustly. You know, you would expect a company at this stage to be growing at least triple digits. And so you start thinking about 10 billion plus in revenue for this company. Now compare that to some of the other companies, Bill, right? Mistral, a lot of the other model companies have fully pivoted. Like they've already raised their hand, white flag. We don't have the revenues that can support the spend to keep up, right?

30:10It's going to be interesting to see what Anthropic does, right? Their revenues are reported to be less than a billion dollars. So can they? Mostly on the enterprise API side, not in this consumer structure. So can they afford to keep up? And I would tell you that as large as Google is and as large as X is, I don't think that you can go out and spend and not have a business model to support the spend. So that would, what your hearing would make sense to me. One other thing I just want to say about this bill, one of the things we've spent a lot of time on internally is trying to really model out what we think of that compute demand relative to the compute supply.

30:47Like, are we really constrained? And I want to keep coming back to this point that Jensen made and maybe we'll insert the clip here on the pod where he talks about his inference revenue is already 50 % of his revenues. So already upwards of 50 % of his revenue. And I ask him, is the mix going to go up? And he said, well, Brad, of course, because I think inference is going to go up by a million X or a billion X. Now what drives that bill? I think you've heard a lot of people say that 2025 is going to be the year of agents. Right? And so you have these O series models and now you have deep reasoning out of Google that launch this whole different vector of scaling intelligence and reasoning.

31:33But the thing about those bills, as you well know is they are compute hogs, right? The number of tokens that you have to produce, that you have to repopulate back into the prompt, the number of branches of inference that you go down, it's dwarfs single shot kind of chat GPT. And now you add in personalization, long -term memory about each individual users, and actions, book my hotel, book my, you know, do things for me. Again, those things are all compute -consumptive. So that's why I think the frontier labs, like Chatchee BT, are modeling out that expected compute demand and then looking at what they have and saying, we're not even close, right?

32:16We're not even close. I do want to come back to that, but I want to finish the CapEx thing real quick. Obviously, one way to look at the, we're looking at a slide Google Meta Amazon Microsoft Apple and they're all spending this money And you know, you can say what does it mean for those stocks, but I'm sure as an investor, the easier thing to consider is these people are telling us, you know, forecasting that they're going to spend this amount of money. And the processes for spending that amount of money are sticky and slow. They're not fast. Like you can't back out. Like you pre -commit and you go build.

32:55Who are the recipients of this stuff? Like that's not. That's an easy win. Well, it's a great question. So we started the conversation like, how do we think about the framework for the year? What I didn't say at the start is, we started 2023 with 95 % net long. So think of that bill as all your chips on the table. So that's our longs minus our shorts. We started last year, I think around 80 % net long. Now that can go up and go down, but it's less chips on the table. and you might say, well, Brad, if you think it's a gold age and if you think all this money's being spent, then why the hell do you have fewer chips on the table?

33:34And I just told you, valuations are a lot higher, right? So let's start there. Warren Buffett has told us the most important thing, Charlie Manga, the most important thing in investing is the price of entry. So the price of entry to play is higher. The variant perception is lower. When I look at Q1, when it comes to the Mag 5 or Mag 6, what I say is there's gonna be a lot of FX headwind, okay? So the strength of the dollars going up a lot, a lot of these companies have revenues denominated in non -US dollars. So their revenues will have headwinds from that FX exchange. I'm not sure that's totally appreciated.

34:08Then secondly, their capex is going up a lot. I think Dylan set on our podcast and I agree with him that the capex is higher than people think. Okay. So both of those things aren't particularly good for the biggest companies trading high valuations. Now, I don't think it's going to cause some cataclysmic event, but it's a headwind, okay? But who are the recipients? Who are the winners? I understand you're seeing Vity as the biggest one, but who else is a recipient here? Yeah, well, first I want to show a slide on a video because I hear a lot and I get a lot. We owned it since it was $120 a share.

34:43Today, split it just as $1 ,500 a share. So this, you know, 1450, it's gone up a lot. But people say, oh my God, I remember when it went up to X and Jim Kramer was telling everybody, sell it, it's up to X. and then three excel it. It's up every time you have to recalibrate based upon the facts on the field. It went up a lot because it's earnings went up a lot. It went up a lot because it's revenues went up a lot. So here's a slide bill that just shows the consensus data center revenues for Nvidia. And the key here is to remember that Nvidia prior data center revenues are mostly these chips that are driving training and inference.

35:24And this is a business that's got very high margins on it. And in 2023, it was $61 billion. In 2025, it's estimated to be close to $200 billion. And so if you notice the jump between $24 and $25, again, this is consensus. That is about a $60 billion increase 24 to 25. Well, sh**, if you just add up the hyperscalers that we just went through, that's $60 billion. And where also, are they spending the money? Yes, they're spending some on custom A6, but it's tiny on a relative basis. Most of this stuff is in video wall to wall in 2025. You know, Jensen told you at CES, he's got 40 AI factories. So we didn't have six people in the world building this stuff.

36:07He's got lots of people building this stuff. So I actually think if you look at the consensus numbers, they probably would imply that in VIDEOS market share is going down 24 to 25 and I don't think that to be true. But so in video - X -pen. Correct. And your expectation, you know, we're percentage of that. Correct. And remember, if any of stock is not gone up from June of last year, until now, it's basically, you know, because this debate's been going on, you know, we had a lot of debates about have we hit a wall on pre -scaling? Can the models continue to scale? We had the deep -seek model come out.

36:42It was a smaller model, very capable. So people say, maybe you don't need all these chips. So like, there is real tension in the world about the about this name. Now, Well, I think there's also, I mean, another one that comes up is if we're moving from more spin on inference than pre -training, do you need this big large holistic cluster? Can you use a more distributed approach? What would you use products that aren't GPUs? You know, TPUs from Google's some of the some of the startups as well. Of course, they can't ramp anywhere near this scale anytime soon. Right. And Google, I think it's a, you know, pre -shooters have publicly that, you know, they're spending a lot on GPUs, not just TPUs.

37:28So, you know, but you asked a question, who are the recipients? Well, NVIDIA is clearly, you know, high on that list. Now remember, NVIDIA was up, I don't know, 140, 150 percent last year, but Intel was down over 20 percent AMD, I think was down on the year. And so it was not winner, you know, this was not a situation where everybody in the semiconductor complex won But another group, you know, I know I share this feeling as well with with my friend Gavin Baker You know, we're also investors in the memory space. So SK high -nix Which is providing high band with memory. This becomes very important particularly in a world of inference time compute And we think that we have a memory shortage, which is a key part of the the Nvidia Supercomputer ecosystem for as far as we can see.

38:16So Micron and SK high -nix would be in that memory space. So what the paws on SK, for example. So when you look at companies like Nvidia, or others that are doing well in this environment, they have multiples that would suggest everyone understands that buys into it. If I'm reading the numbers correctly, SK trades at like six times forward earnings, which is insanely low for most companies. What's going on here? Do people not believe the number or is this the commodity argument that happens with hard drives where you buy it with the highest multiple and sell it with the lowest amount? Yeah, no, I think the reason it has that multiple is because people do think it's hard drives, it's commodity memory, that it's a boom and a bust, and that they don't add a lot of kind of sticky value that you can just easily put on a lot more supply, that supply will ultimately drive down the cost and the margins, and that demand is cyclical.

39:26We believe those things are not true. We think this has become a way, way more sophisticated product, lots of software baked into it, that this is secular, not cyclical. And so there are two ways to win there. Number one is just you get the earnings growth of the business, but the second one is you could have a re -rating hire in terms of the multiple people are willing to have. If people come to believe that, if that SK gets treated more as a non -commodity company overcome. And then of course, you and I talked a lot around the Diablo episode last year, just we We have power issues in this country, right?

39:59And so how are we going to power up, you know, this five, 10, 15 gigs of data center that we need to bring online? Because remember, if they're spending this money bill, then they're telling you that they are like, you have to have power, you have to have a shell, and you have to fill it with chips. And so, you know, one of the things that I have. And I can tell you to have people tell me like, I know they'll say like, I know this It's hard to believe, but we are power limited. Like we are power limit. We have capex that we would put online that we're not putting online, because we can't power.

40:35I will tell you this. I had a call this week with a COO of PG &E and with the head of Diablo Canyon. And we, I'm very focused in talking to our friend, David Sachs and others in this administration. We have to give regulatory relief. Otherwise, we're going to have huge hurdles placed in the front of our AI industry. We know China is building 100X as much as we are in terms of power. And power is the single most important primitive to AI. So I'll just give you one example. Gavin Newsom still has not signed the extension for Diablo Canyon beyond 2029. It's insane. We have to make that happen. This year, it's 10 % of California's green, clean power.

41:21we have to extend that so that they can begin doing the appropriate planning. Hell, you and I think they should probably be expanding it, but at a minimum, the idea that you would take 10 % out of the grid at a time that we are already capacity constrained is totally insane. Let me ask you this. So, so all tumors, you know, historically been tech -focused. Do you, when your information leads this direction, do you start moving in and out of energy companies? Well, I'll tell you, a lot of my tech peers have. And if you look at some of the highest returning companies in what I would call the semi -conductor related complex last year, they were in fact companies in the energy space.

42:04And we looked at all of those. Ultimately, I think one of the over -arching altimeter north stars is essentialism. Like just don't make anything any more complex than it has to be. And so I would always ask my analysts when they would bring me a power company. I would say, why is that better than Nvidia? Right? It's a derivative Nvidia. It's the exact same bet. So why not just buy more Nvidia? So we tend to just take bigger bets on our best ideas rather than diversifying out into these other things that we know less about because the truth of the matter is I do know that we need a lot more power bill.

42:42But I don't necessarily know exactly how the regulatory is going to play out exactly how whether these small nuclear reactors all this other stuff. This falls into the Buffett comment. There's a fool in every market and if you don't know who it is, it might be you. You know, one of the things we ought to come back to though, Bill, is because you said, what could the boogeyman be? And I said interest rates. So maybe just spend a few minutes double clicking on rates. What's going on? Why are rates going up? And, you know, how do I think that, you know, how do I think that may or may not change? But if you look at this chart, the black line on here shows the 10 year just over the course of last couple of months has been, has been trending up and is now around 4 .7%.

43:29This despite the fact that inflation has largely, you know, like, remember, just a, just a couple of years ago, we had a nine handle on, on headline inflation. And I remember when I said a couple years from now, we'll be back to a two handle, people laughed. They said, no way. And in fact, that's where we were. And if you look at the Morgan Stanley consensus forecast for this year, they expect it to finish the year at 2 .2. Okay? But you have to ask the question, why then are people concerned? Right? What's going on? Why are rates going up? And I think there are a few things at play here. Number one, the Trump election got people really excited about more growth in the economy.

44:11And you're going to have 400 billion of stimulus by way of on an annual basis if the Trump tax cuts are passed. That's a lot of stimulus into the economy. Regulatory relief will stimulate the economy. And so what's that stimulus going to do? A lot of people are concerned it could reignite inflation. And they're just saying there's a chance that inflation goes higher because we have all this stimulus. And if it does, rates are not going to be able to go lower. So if you look at the next slide, Bill, we show the expectation in the world now has gone from a lot of rate cuts to only one rate cut in the first half of next year.

44:49Right. So basically the market's saying that there's too much that there's a lot of stimulus. We're not going to get rate cuts. So I think in the first part of this year, there's going to be a lot of tension back to that core PCE is inflation continuing to roll over. We think that a lot of the components like rent equivalent and shelter, etc. We'll cause it to continue to go down. But the other thing going on here, and this is something I know you and I are close to and care a lot about with Doge, the market is saying we expect this stimulus to come in, but I think it's also saying we do not expect Congress to have the courage to cut an equivalent amount out of the deficit.

45:31right? So if you think about this, if we have 400 million of tailwind from this tax stimulus, then I think what the market would like to see is three or four hundred billion dollars of cutting come out of the budget, right? And when you look at what Congress has done over the last, I don't know, five, ten years, there's no evidence. We've never done it. So, you know, the market's just saying, I believe it when I see it. Trump has talked about interest rates being too He talked about it at the press conference the other day. He wants them to go lower. If he talks to his chief economist in the White House, I think they'll say these are the issues that are at place.

46:07We really have to make these cuts. Well we have a reconciliation package. All of this is going to get determined. They've told us in a single reconciliation package by April or May of this year. This is what I'm telling you. This is the backdrop that is going to impact valuations that we have to grapple with. We have to try to understand. So here's my forecast. My forecast is that doge is actually and this administration are actually going to cut a lot out of the budget. And, you know, I think that you have the leadership in the house and the Senate. And so if they cut hundreds of billions of dollars out of this budget, then I think the market will say great fiscal discipline.

46:52We don't have as much stimulus and I think you'll see the 10 -year come in. And if the 10 year comes in, then I think it could be off to the races. But if it doesn't, if we do the opposite, if we don't make the cuts, if the 10 year goes to 525 or 555, Bill, it's going to be an anchor on the stock market. It's going to be an anchor on the economy. So I actually did a little analysis. I shared with you on this that I want to review with folks on the pod because given how important I just said that I think this is, I think it's important to try to do that. to try to get our arms around and understand, is it possible?

47:29Is it even possible to cut three or $400 billion annually out of spending? And so here's this federal spending chart. And what we did here, Bill, we went back to 2019, and you can see the total spending by the federal government in 2019 was $4 .4 trillion. And you can see the subcomponents. So security, we spent $1 trillion, $640 billion, Medicare $644 billion, Medicaid $409 billion, you can see the different categories under that, defense $676, et cetera. And you can see what our net interest expense was at the time because interest rates were relatively low, right? And our debt was a lot lower.

48:09The next column is what we actually spent in 2024. So this is our best estimate. The CBO is given us an estimate. You can see in the footnotes here. So total spending was 6 .7 trillion. Okay, well the question is is that what we would have expected? Now what we had expected? The next column, what we did, Bill, is what we call a fiscal year 24 baseline. How do we determine that baseline? We went back to 2019 and we grew every category roughly at 2 .5%. We said the GDP is growing at 2 .5 % and inflation is growing. Roughly that rate, the population is growing at that rate. So that's what government spending should roughly grow at.

48:49And if you see there, the baseline 2019 budget adjusted 2 .5 % Kager, we should have spent 5 trillion, but instead we spent 6 .7 trillion. That's a 1 .7 trillion dollar differential. So when you hear Doge talk about the ability to find 2 trillion dollars in savings, like this is I think really what has people optimistic that there's an opportunity to make cuts. So you go through there and I think there are some interesting ways in which we can go after those savings. You know, there are some proposals and I'll post this proposal, which goes through and says here are $700 billion of easy deficit reduction that both Democrats and Republicans agree on over 10 years.

49:37So that doesn't get us there, but it is certainly a start. But I think this is going to be critically important that we get our arms around federal spending this year, because that to me is the biggest potential boogie man out there. And there are ways that Trump can potentially do some of this unilaterally through recision, challenging the Empowerment Control Act, and just refusing to spend what Congress allocates. But given that the Republicans control both houses of Congress, I think that, you know, I'm expecting, and I hope, that we see cuts that at least offset the tax cuts. Yeah. I mean, one of the challenges, obviously, is some of these spin, you know, take healthcare, for example, those categories on a per population basis have been growing way above your two and a half percent baseline assumption and expanding as a percentage of the overall spin for the government.

50:35And so it may require you to attack that specific problem within that industry, not just, you know, say we're gonna spend less. Listen, no doubt about it. There is a global demographic problem that you and I, you can look at any population chart of any country on the planet. The number of people over the age of 60 is increasing at a very fast rate. The number of new people coming into the workforce is slowing down as a total percentage. That means that you're working population that is paying taxes to pay for all of these things is a much smaller percentage. So, demographically, that is going to be challenged, but, you know, so, how do you deal with it, right?

51:21Well, you can either just give less things to the people than what you've promised in the past, or you can come up with more efficient delivery mechanisms. Obviously, we know all of the easy and crazy shit the government spends money on that doge has been talking about that we can cut. My assumption is we're also going to have to harness technology, harness AI, defense spending, it's got to get a lot smarter. You really have to go through every category. And if you zero base this, I tend to be where I think there are huge opportunities here. But listen, the track record of Congress, both Republicans and Democrats have not been good cutting these costs and what I would say is if we don't do it, then there's a real risk that the bond vigilantes come into the bond market.

52:10You end up with higher rates because they don't believe that we're on a stable fiscal path. Look, I mean, I think it's an assumption in American life that the government's inefficient. Like I don't think there's anyone that anywhere that's would stand up and say, we think our government is graded execution and spending dollars. There's no one that defends it. They might argue that it has to exist regardless, but they don't argue that it's efficient. So there's plenty of opportunity. Elon said it's like, you know, shooting fish in a barrel if I'm being asked to look at inefficiency in the government.

52:47And so there will be opportunity. I think there's an even bigger opportunity, which you also hinted at, which is if you if you find policy that's restrictive and unnecessary you could unlock GDP growth, which helps in this equation as well. And I totally agree with you that the inhibitor here won't be the identification or knowing what to do to be whether the system can actually reform itself and we'll have to find out. I mean, we'll put in here the charts that we showed last year on how you get to a balanced budget in 2029, but it is just not that hard to get to a balanced budget at $6 trillion.

53:31That's one trillion above what we should be spending on the baseline today. But it just gets you back to that 2019 baseline. It assumes that we have some acceleration, but not a lot, in terms of growth. We are going to get acceleration. Cutting taxes, three to four hundred billion dollars a year is going to accelerate it. We are going to get efficiency and productivity gains from AI. Like these things are happening. So we've got a lot of goodness. And by the way, relative to Europe, which is a basket case and a disaster, like the US is in such an incredible position. We just have to have the courage of our conviction and get rid of some of this wastefulness.

54:11That's the only boogie man I see out there. But Bill, there's one other thing. You know, like, we've talked a lot about spending. Let's talk for a second about regulation because I know So there's an AI bill brewing down in Texas, akin to California's 1047 that we got killed. So maybe just, you know, as again, we got a lot of changing politics. I suspect that Trump is going to rescind all or at least part, the major part of the Biden EO executive order on AI. But what's going on in Texas and around AI? Well, you and I have talked about this in the past and there had been a huge movement underway and I would call it an unusual movement when there's a new market evolving where people are literally begging for regulation and that got a bunch of different parties up on both sides.

55:04That part of those people believe part of those efforts led to the buy -neil and they And I also led to this big push in California, which we talked about. What was it 1092 that everyone got on one side or the other, everyone in our community had a point of view. You had Scott Weiner as the person inside the administration in California pushing for that. And it ended up with this huge argument and then Gavin Newsome vetoing it. And I suspect that most people see administration change or a friend, David Sacks coming in as the AIs are. And they would expect that this is kind of at least for now put to bed.

55:51What's happening and people are probably not aware of is that the people pushing for this regulation have moved underground to a certain extent. and they're pushing it in a bunch of different states. I've heard there's as many as 25 now, state by state initiatives. And I guess this is how policy works in this country. But there's a bunch of reasons to be really worried about this. I can't stand that the one that's got kind of the most heat right now is in Texas. I think Governor Abbott and obviously Elon and all his companies have had this massive impact on the Texas economy by making it the state that has the least red tape that's kind of the most pro innovation and pro business.

56:39And for this thing to pop up there is just so ironic in my mind and would be literally brain dead. When 1092 was being proposed 1047 sorry people even including myself say why don't you just write a sign that says move your AI company to Texas. Well now those words sound stupid because Texas is, and the first thing that people should realize is, there's no reason to do this on a state -by -state basis at the end of Obama's term. He had this initiative that he didn't get around to. I wish he had, where he had identified like a hundred different industries where they're state -by -state regulation, including like hair care and stuff.

57:22And it's just wasteful red tape. And for us, you know, when so many people in Washington are worried about our competitive position versus China, to build a gauntlet that our companies would have to move through to adhere to state -by -state interpretations and rules is just mind -numbingly. You know, I want to say the word stupid, you know, out loud. The only reason I fear saying it is that someone trying to write that legislation would use it against me, but like I can't imagine Like we should we have a changing administration. We have people looking at this if we feel we just have to do something God please, you know, I prefer it at a national level Yeah, no federal preemption.

58:12I mean like listen This is the interstate commerce clause like there's nothing Our great advantage over the Europe is you know They got this crazy patchwork of regulation across all these different countries. And here, if you're operating in an internet company, you have one rule of the road, right? And we need to have one rule of the road around AI. And I think that it should be promulgated and it will be promulgated in the federal level. And just some people, you know, I've heard this boogie man out there that people are like, oh, everybody in Silicon Valley, they don't want any regulation. They're just a bunch of crazy libertarians.

58:42is that no, what I think you hear is pushback to uninformed regulation that would slow us down and cause us to lose an important race to China. If we care about the race with China, then the first thing we need to do is to reduce the impediments to us running the fastest race we can run, right? While still carrying about AI safety while still carrying about national security, while I'll still carry in about all of these things, but if you have this patchwork, where these states are honorously regulating all of these companies out of the gates, all you're doing is holding, handing the gold medal to China.

59:25And so I think the unintended consequences are really bad. I'm quite confident. Let me tell you about some of the details. And I'll include a link in here. Dean Ball wrote a really solid analysis of everything that's wrong with the Texas proposal. But one of the things that's in there is that you have to do a risk assessment. So this is similar to creating an audit. And for those of you who have run companies who've gone through audits, you know how difficult it is. But not only would you now have to, you have to publish your risk assessment. So whatever product I'm working on, I've now stepped through these hurdles and wrote these reports.

1:00:06And then there's liability associated with it looking backwards. And so if I do something bad, I'm liable for it, but I also then get a second look back and did I run the analysis where I should have known about the risks that's there. And it applies very broadly. I give the people that are looking for regulatory capture credit. And I think they saw that they were losing at the national level and realize that they could create messy anxiety at a state level which made actually promote trying to get to a national output. But, man, this would be horrific. I think they're going to get a lot of pushback.

1:00:53I'll be very, I would be shocked if this happened in Texas. I don't think they're, you know, I think you have a lot of coordination going on in Washington. I think it's quite smart. I think it's on both sides of the aisle. You had a great report published by Congressman J. Obernolte in the House, who was a co -chair of the AI Committee in the House. The Senate's done some work. And so hopefully, SACs will get there and provide a really clear coordinating function, and that we'll have federal preemption, and that we'll get great direction out of Congress. What I think, Bill, is I'm just thinking about 2025 predictions.

1:01:32Because there was a lot of, when we're talking about regulatory capture, I think there was a lot of fearfulness. A lot of it directed at OpenAI that these companies with a closed model were trying to, who had the lead, lock everything down before people could catch up with them, trying to squash what was happening in open source. I think you're going to see in 2025 a lot more companies open source more of their models Microsoft put out some open source models last week, which is like really surprising and so I think that my own sense on this is that there's a lot more in Cominality between all of the major players around AI than there is division and And, you know, we'll see, but that's a, when I'm hearing out of a bunch of them, is that we're gonna see a bunch more open source.

1:02:28Yeah, but there's two dimensions to this. So you could be right that the bigger companies could all agree on a regulatory framework. There's also the issue of small versus large. And, you know, there's a lot to pay attention to there. Before we wrap up, I had like four or five things things that I'd like to bounce off of you and get your opinion on as I look forward into the year. The one that I've been thinking about a lot is Google. We talked a lot about how search is at risk. And clearly for those of us that are doing so many searches first on a chance, CBT or other product like that, there is a real argument as what's the point of Google and the long run and does that still hold.

1:03:22On the other side, when we've looked at them in the past, we said, man, they have an incredible number of assets. When you look at whether it's their Gmail product and then their docs product and then their Slack -like competitor products and they're zoomed like competitor products. And then the fact that they own Android and this this mobile operating system, I was you know surprised to hear Jason on all -end get super excited about Google in this way and then announced that he had switched to a Pixel phone. And I'm thinking to myself, you know, this could be kind of the perfect AI basket of assets.

1:04:10And you know, you look at a company like Glean that I know your your ending is doing well. You know, you can create Glean for the rest of us if if a company commits to being on the Google stack and has all these things and and it becomes a combination that no one else has. Apple doesn't have it, Microsoft doesn't have it. It requires insanely great execution to get it all right, but I find myself want, You know, that if a whole bunch of people said, man, I want this so bad that I'm going to switch from my iPhone and get on to Android, that would be a real tell. That'd be something special. Yeah.

1:04:49Well, you know, I'll tell you, I don't know what it was late November, maybe early December. Before the recent run up, you know, I started seeing a bunch of breadcrumbs around Gemini, around Deep Reesoning, around notebook, LM. just a cycle time improving there. I talked to a lot of companies. A lot of companies were still seeing growth in their search volumes. They're lead generation, so online travel companies, et cetera, from Google. And I started to see a lot more evidence of them just getting fit and getting more efficient. And frankly, I think a lot of credit goes to Sundar. I think he's starting to get feisty and see the things that need to get done here.

1:05:29I would say, let's keep a few big pieces in perspective. They are facing the largest innovators dilemma in the history. I know. From my perspective, the historic Valley. And I think it's almost impossible to replace a 99 % incremental margin business, right? A monopoly search business with whatever comes next because whatever comes next, they may be important in it, but they're not going to be 99 % monopsy. Right? Like open AI is going to be there. Meta is going to be there, et cetera. So, and I don't think their margins are going to be the same. So that's the first thing. And number two is, like, how could I be wrong?

1:06:03Well, you could envision a world where the pie grows so damn much, Bill, that, you know, Gemini and if they were able to displace Apple on the phone, then all these things could really replace that. I think you have plenty of time to wait and see, you know, to pick up the breadcrumbs on whether those things are occurring. But I will tell you this, I suspect at Apple for the first time, They look at Google's assets and they say, okay, this is orthogonal. Like, they were never worried about picks over the course of the last eight years, but I imagine to your point, this is the first time in a long time that they've worried that Google could appropriately embed Gemini and Deep Reasoning and assertion, you know, an assistant on the phone that can book my hotel and just make it a 10X better product.

1:06:51I'll tell you another area where they have an advantage, which is hopefully useful to everyone out there. Geminize really good at local, because they have all the local reviews. So I find myself now if I'm going to a restaurant, you can say, what are the three dishes people of love the most, what are the two that you stay away from and get down at a level of detail that's interesting you wouldn't have used before and very valuable. So that's another aspect. What are they like at Tony Blas? Well, you have to go to the certain. The second one that I think is super interesting to me that we're going to see play out first half of this year.

1:07:32X .AI, Elon's commitment to the largest cluster. So the concerns about running out of data, the concerns about maybe there's a parameter limit, at least against the text data set, draws into question, do you need the largest? single cluster, GROC3 has been promised, I guess, in the first half of the year. It would be super interesting to see if something comes out of that product that is competitive with the cutting -adjet -open AI or maybe above it. I don't know, but I'm very curious about how that flows out. I mean, I think there's been a lot of attention focused on that. I'm not sure that I would measure, you know, X .AI success, solely on the dimension of, is the Grok3 model better than whatever OpenAI's latest is or Gemini?

1:08:28Because remember, what they're doing really bill is building larger cluster on pre -training. So they can do more on pre -training. But remember, these other models are infused with post -training, and test time compute, et cetera. So I suspected that what I think is a test of that pre -training argument. Like let's say they do achieve something and come out with something that's brighter than everybody else. That would be a new data point relative to where everybody's thinking. I think, here's the way I think about ex and Elon. He's got three vectors on which he is leveraging AI. Number one is robotics and he recently said, and I've heard Google and others say this, that he expects there to be millions of humanoids live and in the wild by 2028.

1:09:18Think about that. That's three years away. It's really, it's incredible. And you just will post this video of this Chinese humanoid that, you know, somebody said past the visual touring test because humans were confused whether or not it was real. It was so damn good. And so he's got that vector. The second vector he has is autonomy, right? And I picked up a new test last at the end of last year with hardware for just so I could be on the latest of FSD and drove me home from San Francisco last night. So those are two real world, like not language models. Now we're talking in the world of bits and, you know, and and Adams.

1:09:53And then the third one is really around. But by that you're implying just because those are in separate companies that that X dot A, I could become the hyperscaler for 100%. I think there's no doubt about it. It already is. And it will continue to be like he has a kuretsu as they say in Japan of companies that can leverage each other's insights. And I fully expect that they will an x .ai. So his need to build these large clusters and place these bets is because he's got to support huge potential businesses, not just building GROC to compete with JGBT, although I think they'll try to do that too as part of X, etc.

1:10:35But he has lots of ways that he can leverage it. And remember, if you build a large coherent cluster for pre -training and you decide, okay, we're hitting up against some scaling limits of pre -training, you can use it for training, reasoning models. You can use it for post -training. You can use it for inference. You can, you know, so it's not like you're wasting this just by building these larger clusters. I think what I'm most convicted in is that these guys are going to spend a lot of money on GPUs because, as Jensen says, more of the world is moving to workloads that demand machine learning and accelerated compute.

1:11:11Okay, that was number two, Bill. What's number three? Well, I don't ask question on number two. It seems to me that there's the extra I want to make the argument that having their own hardware is a competitive advantage versus opening up. Do you buy into that argument? How do you think that plays out? Well, I think it's not necessarily owning it or having it, but it's being more competent. I do think that the ability to rapidly stand up compute that works, that works really well, that doesn't have as many hiccups and productions, etc. Like that's a superpower. I mean, Jensen's gone into, you know, talk about this crazy timeline that the Elon hit.

1:11:56I think he's unique in that regard. I think he has a balance sheet and an ability to raise global capital bill that his cost to capital is really low for doing this.

1:12:12So, full speed ahead in AI and keeping anthropic and Google and open AI and everybody else honest. It's part of the reason I'm so bullish on team America when it comes to AI because we've got the smartest people in the world investing more money than we've ever seen investing anything other than perhaps the Apollo project on an inflation -justed basis to make sure that we're in the lead. At the end of the day, it's a combination of things. You've got to have the best research in the like you can have the best computers and chips and biggest cluster in the world. But if you don't get the architecture right around your reasoning model and the other guy does, they're probably going to win.

1:12:50All right. Number three, we'll do four and then we'll wrap it up. Number three, I don't recall in any of the previous waves, you know, PC wave, flying server wave, mobile wave, the amount of chatter about co -opitation that I'm seeing here. And people took out of our video with Sacha where he said, oh, I already have my own models. You know, and then they released a few, you know, implying that they're in some kind of co -option with OpenAI. You've heard all of these hyperscaders talk about doing their own processors of some sort, you know, both Trainiam and Amazon and then the TPU at Google, compete with Nvidia, but they're buying Nvidia Sprout.

1:13:36and Vitya put out models this week which competes with some of those customers. And then they announced this AI -driven PC unit, which would, you know, presumably compete with Dell, even though Dell's on stage helping them with the Elon build. But I don't recall, you know, at least I think about the windtell, you know, world, which I was on Wall Street covering. I just felt more like people stayed in their lane and were thankful to be a part of this broad ecosystem that was growing and I just see so much tension like it's super interesting to me as a Just someone that's watching it, but I'm curious what your thoughts are.

1:14:22Yeah, I don't know that I have any any strong You know perspectives there There may be a couple of things. Number one, the amount of capital that it takes to do these things is not the domain of venture capitalists. So if you're a new enterant, if you're anthropic or you're open AI, frankly, they were forced into this because there was no other choice. When they realized the amount of capital was going to be a nuclear level of capital, you just had to turn to these big companies. So these big companies ended up owning pieces of them, but they couldn't be totally dependent it upon them. So you had Google who hedged their bets a little bit with Anthropic and you had Amazon that made a bet on Anthropic and Microsoft on OpenAI.

1:15:05And now as these companies become big and successful, like listen, if they don't become big and successful, inflection just gets subsumed by Microsoft. Character gets subsumed by Google. But if they get some scale on their own like OpenAI, and now it probably couldn't be subsumed from an antitrust perspective by Microsoft and it has standing on its own. And so I think you have that dimension. I think the competition is as aggressive as it's ever been. I think sometimes we make more out of this competition than there is. Like I don't think Microsoft, you know, Nvidia launching a few models. I don't think they intend to be in the, you know, frontier model game where they're competing heads up with these other folks at the same time.

1:15:48There's a long tail of their customers who are more than satisfied to use a tightly coupled model rather than maybe trying to clooge it together themselves by going to Lama or using a lot of these other plumbing services. And so, you know, we'll have to wait and see. Here's one thing that I would just point out in that regard. We just looked at that CAPX chart. Almost $300 billion of non -governmental R &D being spent by the biggest companies in the world to advance causes that are aligned with America. Right? Like we harken back to the age of Bell Labs in Silicon Valley, you know, and where you had nationally government spending.

1:16:31And I just think this is so damn bullish for us that we have printing presses. We have companies generating enough cash flow to invest this much money to put us at the bleeding edge and it creates incredible national strategic. Well, they were getting pushback for doing stock repurchases. Now that people said they don't have any use for this cash flow, and now they do. So I guess that's a positive. All right. The last thing that's on my mind and that I'm really looking forward to better understanding in 2025, it does appear like for the time being the majority of the enthusiasm on the the advancement in AI is around this chain of thought thing.

1:17:17And as you've talked about, you know, I think it's somewhat ironic that it's less efficient, but now that's a good thing. I think if someone had built a model that was just hyper or shit -fishing that where the margins expanded, that would be better. But okay, so now the argument is it's less efficient, but it's gonna consume more compute, so that's a good thing. So, seeing how well this applies eyes to different uses of AI. I don't be super interesting. So, you know, what are the coding companies seeing, you know, when they use Chain of God precisely against that? Because when this model was first released, even open AI said it's not forever use case.

1:17:59Or they hadn't seen it be successful when they were use case. Now maybe they will in the future, you know, and I've signed up and paid for all these pro versions now in the past few weeks been throwing problems at, you know, especially the one that's interesting is it goes away, you know, both the Google and the OpenAI products, it'll go away for 10 minutes. So, and it is, you know, how much better is that output? And so, it's super interesting. I think that's going to be something that's really important to watch. Obviously, if the compute price keeps falling, you, I think you fall into this, why not argument?

1:18:33Like, why not run 20 passes on something if the marginal cost gets somewhat irrelevant. And with the fast followers, you know, and the way you're using synthetic data, creative and smaller models, maybe you can get the smaller model to run, you know, the second, you know, double checking your work, if you would. But anyway, this, I think this will be the fun part to watch on the edge. I can tell you a couple of things on that. Number one, I can tell you that the researchers inside these labs, they feel like they're looking into AGI and they're surprised how skeptical the world is. Yeah, like there's a lot of dissonance that I think they have because I think they're like, oh my god, we're getting close.

1:19:24The second thing I would tell you is... seeing things ahead of time. Correct. And they're unable to release them because they're not fully baked. 100 % and they don't have the compute. Yeah. They don't have the compute bill. But I'll tell you that I tell you this, they also part of the reason they're so bullish on these reasoning models is that from a scaling perspective, right? So remember, reasoning models can get better just because you throw more compute at them as well. So where are we on that scaling curve for reasoning? Most of them tell me that we're around a chat GPT 2 .0 level from that log rhythmic scaling.

1:20:10So they expect a lot of scaling advantages in 2025 and 2026 on the reasoning models. And then finally, when it comes to utility, so where are these things going to be put into practice? I think you're going to see some pretty dramatic breakthroughs this year on coding, right? So think about all the startups that we've seen in the coding space. A lot of them have used prompt injection and other techniques in order to, you know, kind of get these agents to do things that they want. I think you're going to see real coding agents baked by Google and by OpenAI driven by their most sophisticated inference time reasoning models that are going to be meaningfully better than what's in the market today.

1:20:54That's one. And I would say secondly, so if at the enterprise level you think of coding as kind of the tip of the spear as to what these agents can do. Remember, like you and I started last year talking a lot about the consumer, right? Memory and actions. And I think that you're going to see chat GPT imbued with these capabilities. And I imagine the same happens with Gemini, et cetera. And we've seen it, like we, we effected a, one of my partners did a demo using booking .com in the anthropic computer use where, you know, booking a hotel and doing other things. It's still fairly embryonic, but I think that, again, that's not built on the back of O3.

1:21:36Now build that on the back of O3, it becomes very, very capable. So if you said to me like, how wide is the use case going to be, I think now the use case is very narrow. It's researchers, okay? But I think you're going to see the aperture on the reasoning models expand pretty dramatically. And I think you're gonna see increasingly a blending of the pre -trained and the O -series model because ultimately it's one model that's going to help you do all the things that you wanna have done. Well, here's, I didn't discuss this with you head of time. So we can edit it out if we don't use it. But I would invite, if there are people that are doing particularly interesting things or leveraging this in a particularly interesting way, I would invite them to reach out to us.

1:22:26And I'd love to not only learn about it, but be obviously willing to share with the audience what these things are as they uncover them. I'll close with this and you didn't ask for my input on it. But you know, I'm not a fan of macro analysis and that I think it falls in the too hard bucket because of all the different variables it play. Great seeing you and I look forward to a fun year of doing these with some incredible guests and you know I learned a lot kicking around with you it's a lot of fun. All right take care. Take care.

1:23:07As a reminder to everybody, just our opinions, not investment advice.