← BG2Pod with Brad Gerstner and Bill Gurley 
BG2Pod with Brad Gerstner and Bill Gurley
Grok 3, AI Memory & Voice, China, DOGE, Public Market Pull Back | BG2 w/ Bill Gurley & Brad Gerstner
01:03:19
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- [00:00]
A
I witness 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. Like, I can't imagine an end state where we control all the AI and they don't have any. It's already too late.
- [00:19]
B
It's too late.
- [00:20]
A
And they're smart.
- [00:22]
B
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 deep seat building great models, or they're not going to have rocket companies that copy us and can land themselves like that, that would be naive.
- [00:43]
A
It's remarkably naive.
- [00:57]
B
Bill, it's good to be with you.
- [00:58]
A
Good to see you.
- [00:59]
B
I mean, we're in this. Should we tell him that Steve Ballmer gave us this man cave?
- [01:03]
A
It's a private cave in the. In the interior.
- [01:06]
B
I mean, the truth of the matter is the hardest thing about this pod, I love this pod, but you and I getting our schedules to match and actually getting together. And so I've gotten a ton of feedback. I've seen on Twitter, people like, when are you guys going to record the pod first? Thank you for the audience encouraging us to do this, because I love doing it, know that we would love to do it more. It's just a little challenging to get together and to do it. We have an ongoing dialogue, I think pretty much 24 by 7. Correct. About the stuff going on in the world. And then occasionally we get to get together and share it with you all. So I don't know, I thought maybe today, Bill, we'd kick it off with Grok3. So we're now like 10 days out since Elon and his team unveiled, in pretty record time, an unbelievable model. And so maybe you can just help us zero base where you thought, what you thought when the model came out, where it stands, you know, kind of in the rankings, then we can have a conversation about kind of the impact and what it means.
- [02:08]
A
So, you know, we talked about this in the past, but. But everyone in the ecosystem was super impressed with how quickly they built the Memphis facility.
- [02:16]
B
Exactly.
- [02:17]
A
And how big it was. And it's the largest, you know, contiguous cluster in the world. And there was a lot of chatter about that ahead of time.
- [02:26]
B
Yes.
- [02:26]
A
And I can remember some of the investors there saying, you know, 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 after that inter, that, 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 ahead on some, not on others. Some people argued about whether the reasoning.
- [02:59]
B
Component, the beta beta, or did they.
- [03:01]
A
Cheat or overtune to a benchmark. But I don't think it matters. 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 that 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.
- [03:30]
B
Right, Right. 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, Deepsea kind of got up there a couple weeks before you had Grok. 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.
- [03:55]
A
Correct. Correct. And I saw people who interpreted Grok's fast rise as proof that pre training's 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.
- [04:13]
B
Right. Although again, an incredibly capable Right level. So, so, oh, no doubt.
- [04:20]
A
I'm not, I, I, I just, you know, 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.
- [04:31]
B
Right.
- [04:31]
A
And whether I said it or not, Ilya said it Right. 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 pre training headroom, I was expecting this to go through now I will qualify. This was their first run.
- [04:50]
B
Right.
- [04:51]
A
Maybe there were some tricks they didn't know.
- [04:53]
B
Right.
- [04:53]
A
They could 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. Right.
- [05:02]
B
Well, 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, right. That I tweeted the other day and I compared it to kind of the search index benchmarks that we all used to track. And you know, the benchmarks are one thing, but the reality is, how do we feel when we're using the product? And what I will say is Grok 3 rocketed to the top of all app downloads, you know, on the iPhone charts 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, 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.
- [06:31]
A
It's not the right context.
- [06:32]
B
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, and it said, hey, go out and try the new voice for Grok3. 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.
- [07:05]
A
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.
- [07:16]
B
Exactly. And so I think that while we all have a fascination where, where did they get to on the benchmarks? My own sense at this point in time is, you know, this is going to be one of these battles, kind of like search was at this point in time where, you know, the five or six players. And it's going to be, you know, just out today, literally as we're about ready to go on. You know, OpenAI has released Chat Chat CBT 4.5 and they've kind of hinted in, I guess this presentation as to chat GPT5 or 6, I guess that was shown on a screen. And if you look at 4.5, one of the important distinguishing elements that they're pitching is it's more human, like, it gives better answers, more concise answers, et cetera. Not a big breakthrough on the evals, although there are some improvements in the early looks against the evals. But I think ultimately we're going to measure the success of these things by how many people are using them.
- [08:12]
A
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 and 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?
- [08:25]
B
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 Ash, Jeeves and Excite and Infoseek and by the way, they all did pretty damn good on the benchmarks. Yeah, 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 winner take as much. I don't think we're going to see a 99% monopoly here, but I do expect that, you know, we're going to see 70 or 80% share go to the winner. Now, if we look at the numbers.
- [09:30]
A
Yeah, the numbers.
- [09:30]
B
Yeah, if we look at the numbers today, I think last week Sarah reported that OpenAI has crossed 400 million weekly average users.
- [09:38]
A
And that's a user number, not a paid user.
- [09:41]
B
That's. 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 dollars in expected revenue this year. So you can back, you know, 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 7 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, like, I already think they're near 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.
- [10:36]
A
Let's handicap some of the other players a bit.
- [10:39]
B
Yeah.
- [10:40]
A
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. To get to a number that's close to opening.
- [10:51]
B
Yeah, I mean, listen, I think let's just start with Google. Okay, so there's been a lot of reports out over the course of the last couple of 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 done so much? Because if I do a Google search today on my phone, half of the page is taken up with an AI answer, no doubt to whatever my Google query is. And the rest are all paid links.
- [11:21]
A
Yeah.
- [11:21]
B
Right. So I think Google, I think that's the right decision for them to make. Right. 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. Now, if they do that, and if.
- [11:36]
A
You'Re one of these humans that thinks SEO wasn't dead already, which I would have declared it dead a while ago, it's really dead.
- [11:44]
B
SEO. SEO is dead. And just those are the free links that was the core product that used to attract everybody to Google.
- [11:53]
A
Yeah.
- [11:54]
B
And the idea that SEO is basically now gone is pretty. Pretty.
- [11:57]
A
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.
- [12:09]
B
Right.
- [12:09]
A
And all the ticket guys are up front now. Like the link you're looking for, you have to hunt for.
- [12:14]
B
Well, okay, so let's talk about that for a second. 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 3, 4 or 5. 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 4 or 5 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 those, 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.
- [13:36]
A
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, and all the search queries over all the years, their understanding of structure of structured data around 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.
- [14:00]
B
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.
- [14:11]
A
They also, they also have Android which is a massive asset. And they also have browser, you know, 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 Iterator's dilemma in that they can't, they still have to try and maintain those paid links on that page.
- [14:42]
B
And this chart here, the black line is Google's paid click growth plotted against the user, the weekly average user growth at OpenAI. It's not going in the right direction.
- [14:53]
A
Well and I think it benefits from the fact that informational Searches are what chat GPT cannibalize first, not the commerce searches, which is where most of the money is on the paid.
- [15:05]
B
Right. Although 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.
- [15:35]
A
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.
- [15:41]
B
So let's talk about Meta. You know, I know that actually one.
- [15:44]
A
Last thing on Google, like there was a point where Meta went public at 40. We had some, backed up the truck, we had some. So I was like paying attention and Zuck, as he has many times, got woken up on mobile 100% and everyone thought he was dead because he had.
- [16:02]
B
Built an HTML and 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 COVID of Barron's magazine. Yeah, the weekend magazine. Right. It was like Meta's debt or Facebook's dead.
- [16:19]
A
Right, but. But he woke up.
- [16:21]
B
Yes.
- [16:21]
A
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?
- [16:29]
B
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, a hundredx 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 anybody 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 in 20. At the end of 2020.
- [17:14]
A
All right, go to, go to, go to Meta.
- [17:16]
B
So I Mean, you know, again, Meta, if you, 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 you know, 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, you know, in complete beast mode.
- [17:47]
A
Yep.
- [17:48]
B
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.
- [18:01]
A
Back to your product point. Right, exactly right. Like the Meta hasn't.
- [18:06]
B
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 Deep Seek rather than Llama is the enterprise open source model of choice that everybody's experimenting with and playing with. And so that becomes a real 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, with Snapchat or, 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.
- [19:00]
A
Interesting to see what they do. Who else would be in the list? I mean Anthropic is really not been.
- [19:06]
B
No, they've. They pretty much seeded the game on consumer. You know there was a product announcement yesterday about they're going to be powering Alexa but you know, now we're stretching. Right. The idea.
- [19:16]
A
And Amazon did do a big. Alexa launched yesterday.
- [19:20]
B
Correct.
- [19:20]
A
Pretty late in this game.
- [19:22]
B
Yeah. And by the way, Alexa is not really in again, it's. It occupies a different space in most consumers minds. It is not what ChatGPT does. And so I think to dislodge something that has the momentum ChatGPT does, you have to go at them and do better than what they do at the thing that they do. And this is why I think X, you know, if I go through the whole list here, X to me is so interesting because they have a platform that is the number one news platform in every country. On the planet, the people who are most actively engaged are using this platform. And they go there for information, right? They go there for answers, they go there to engage. So I think it's an audience that's very well suited for AI. I think the integration they've done is as good. By the way, they've done this in a very short period of time. And I mean, I'm talking everything from the logo.
- [20:19]
A
Some of the tweets will have the logo pop up and then it'll summarize or do more research.
- [20:24]
B
So I'm really, really impressed at the velocity of not only catching up on the benchmark, but catching up on the consumer product side. And so listen, they're number one on the App Store, and that stands for something coming out of nowhere. And people said that Elon couldn't do this. I never doubted that they would catch up on the benchmarks if they got a big enough cluster, because Elon set a mission that people become messianic about, you know, and his engineering capability to build out the cluster and do all those things. So that was never the question for me. The real question was can anybody. Can he close the gap on the consumer race?
- [21:03]
A
Yeah.
- [21:03]
B
Okay. And there I think, you know, the I he. The odds on favorite there has to be OpenAI. I think they continue to widen their gap, by the way, Bill. I think they're accelerating at scale, but that's where the race is. And it may very well be that coming in second place with 20% share is a pretty good place to be.
- [21:25]
A
I want to mention one more company and then I'm going to make a guess at four ways someone could try and win this game. But the one I want to mention before I do that is just perplexity. Real briefly, I will give them credit for being product centric, to your point, and innovative in ways that the others haven't and kind of on their own terms, they don't have near the usage of OpenAI. So there's a question that kind of looks like an acquisition candidate to me. I don't know if anyone can agree on price, but for one of these other players that hasn't been as successful from a product standpoint.
- [22:04]
B
I mean, you and I just had this conversation. I mean, you could imagine, for example, a world in which Microsoft were to buy perplexity and now they have a consumer brand to go battle it out. We know how much Satya wants to win in consumer. Now he owns a bunch of OpenAI and so he's got some potential channel conflict there. But I think the bigger issue at this point now we know with linacon out you're probably more likely to be able to do a deal like that. But when founders are raising $8, $9.
- [22:33]
A
Billion, you take it off the table.
- [22:36]
B
It becomes a much, much more diffic for a company like Microsoft. Not saying that it couldn't happen. And I will say this, that when it comes to, you know, punching up, being innovative, being scrappy product velocity, I've the founder there, Arvind is psych and the team spent super impressive to watch. I think they've made other people better. But the numbers I think as we look at them today, you know, they're really powerful but but much, much smaller player.
- [23:06]
A
So here we go, here we go. I have four things I'm watching out for that could pot potentially lead to either further lock in by OpenAI or a window for someone to do something else as some of them I mentioned before. But I think 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. And I haven't seen that yet. I still think that's a dimension that could really be important. Voice we've talked about and they're all playing with it I think voice and also ties in with device type and this is where Alexa may have some assets but you know, if the voice were spectacular, I might not have to carry the phone around as much. And by the way, by the way, I need it.
- [24:13]
B
Yeah, you need an earbud. You need an earbud. I will say advanced voice mode on ChatGPT is excellent. Grok3's new voice excellent and they're getting better and accelerating rate. You know we're an investor in this company live kit 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.
- [24:35]
A
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. 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.
- [25:12]
B
Let me give you an example of a network effect I think that is happening, I think around model improvement. If you have 7 or 800 million monthly average users, your diversity of information and questions and answers and follow ons, et cetera, is much, much higher that those questions and data that's now being fed back into the models to improve the model.
- [25:31]
A
Some users may have seen. I know I have. You get two answers and the OpenAI asks you to.
- [25:38]
B
Right? So I think that's an example of OpenAI very actively building, attempting to build network effects in terms of the quality of the model, the quality of the answers going.
- [25:50]
A
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 proposition.
- [25:59]
B
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.
- [26:06]
A
Exactly right.
- [26:07]
B
And I would argue not only do switching costs explode, the conversion rate from free to paid probably also goes up. Right. Just because the value delivered.
- [26:16]
A
I think you're right.
- [26:16]
B
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. Advanced Voice mode could be the interviewer. And so I was sitting there with her last weekend, here's the prompt that I gave to Advanced Voice mode. I said, 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.
- [27:23]
A
How long did it go?
- [27:24]
B
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 ChatGPT 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 gotta help people. Imagine like you and I could have imagined in age of Internet, somebody building an Internet website that just did that thing. Okay. So 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. Right. Which is really fascinating. They basically took the O3 series of models and fine tuned it end to end 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 you know, 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.
- [29:06]
A
No doubt. And I also think that there are other assets that could play a role like a contact database, an email.
- [29:15]
B
Yes.
- [29:15]
A
I mean I can even imagine moving my email to one that's integrated inside.
- [29:20]
B
Just because contacts is a great one. If they just cleaned up your contacts. When knowing my contacts and knowing your contacts.
- [29:27]
A
But send an email, send a text, I mean there's a lot. 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.
- [29:41]
B
Yes.
- [29:42]
A
And like, like that 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?
- [29:54]
B
Right.
- [29:54]
A
Once you did it like. Or do you have to take it out of OpenAI? Like, you know, you'd rather it just have a place.
- [30:01]
B
Correct. And now you have projects in OpenAI 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, had finance teams, et cetera. But I think the, 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, you know Kevin Wile, who runs the product team over there, you look. 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 a growth hack and you got to, you know, get those customers to use the product more and more.
- [30:54]
A
One thing came out this week which, which I don't know if it was intentional or not. You may know more than me. There was someone published the internal forecast of OpenAI which included, I think in 25 and 26 losing 20 billion each year. And someone said to me, why would they publish that? Why would, you know, lose that? And to me, I think there's a information war out there trying to scare capital in or out and to, to be rational, to lay a statement that if you want to be in this game, and keep in mind there's a variable cost every time you serve a deep research. And so if, if, if this is a, one of these situations where people think it's winner take all, just like we had with Uber Lyft and they're going to go hard at trying to win. You probably need to be willing to lose 20 billion a year to step into this game. And X looks like they have the potential to raise that kind of money. I don't know if a Microsoft or an Amazon are prepared to lose incrementally that amount of money.
- [32:04]
B
Well, this is, I mean, this is just such a fascinating segue into.
- [32:08]
A
By the way, there's one company we didn't even mention. Yeah, like when we went through all this, we didn't mention Apple. Right. Like at all.
- [32:14]
B
Pretty shocking, right? Pretty shock.
- [32:16]
A
Why didn't we mention.
- [32:17]
B
Well, I mean, so Apple has self selected out of the race. Right. They're not building a big model. They've been very public about. They think that they can be kind of late mover here. They did this Apple intelligence integration with ChatGPT and now they're low, they're Gonna do a Gemini. And the reality is, you know, as I shared with an Apple executive the other day, I said, here's the only integration that matters. My ChatGPT app on the front page of my Apple phone.
- [32:45]
A
Right, that's me.
- [32:47]
B
Well, I mean it's the truth. Like I just don't use any of the integrated features on the phone, which I think creates vulnerabilities for Apple. But I think, you know, listen, this is the first time that they've been faced, I think with this level of product risk. But the reality is they have such lock in on this device for somebody else to build a device, maybe Huawei around the world they're going to be able to ship, you know, perhaps better AI phones around the world, they're not going to be able to ship them into the United States. We'll see what, what this Google ruling is at the end of the year. If Google's no longer allowed to be the default search app because of this consent decree, you know, do they really turn Android into the thing that it potentially could be? So I think there's a bunch of potential risks. So we didn't talk about Apple. I'd say the other company we didn't really talk about because we're so focused on the United States is when you look outside the United States, you really have to look to China because I would say the acceleration and velocity of AI in China is off the charts. We've talked a lot over the last few weeks about deep sea 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 ChatGPT 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 US 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 the things we do to try to slow them down and stop them are backfiring on the United States.
- [34:44]
A
I couldn't agree more. I witness almost daily people that are either in government or even friends of ours who say we have to win the AI war with China.
- [34:59]
B
Right.
- [34:59]
A
And I don't know what that means. Like, I can't imagine an end state where we control all the AI and they don't have any. It's already too late.
- [35:09]
B
It's too late.
- [35:09]
A
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. I think.
- [35:21]
B
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 deep seat building great models, or they're not going to have rocket companies that copy us and can land themselves, that would be naive.
- [35:43]
A
It's remarkably naive. 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.
- [36:05]
B
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 US Semiconductor company 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.
- [37:15]
A
Yeah, I don't know.
- [37:16]
B
We'll throw that out and start.
- [37:18]
A
I think there are remarkable amount of people in Washington on both sides of the aisle that have a perspective about China that 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.
- [37:49]
B
Let's shift gears here for a second. 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 that I shouldn't share. However, I think one always has to keep in mind what is operating expense and what is capital expense. There's a variable cost of serving a ChatGPT query. You know, I would posit that those variable expenses are not very high, like at maturity.
- [38:22]
A
Although a deep, like a 01 Pro search or deep research could cost 20, 40, 50x.
- [38:29]
B
Correct? Correct. But I would, 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 capital 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 that doesn't, we don't quote that as their profitability. They have their, you know, their, 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.
- [39:44]
C
Think of my fleet even as a ratio of the AI accelerator to storage, to compute. And at scale, you got to grow it. And so that infrastructure need for the world is just going to be exponentially growing, right? So in fact, it's mana from heaven to have these AI workloads because guess what? They're more hungry for more compute. Right? Not just for training, but we now know, for test time. And as I said, test time. 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 but one human invoking programs that invoke lots more programs. And 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.
- [40:42]
B
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 6 to 8 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 worldwide.
- [41:14]
A
What, five gig worldwide, Is that what you mean?
- [41:17]
B
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 you know, Masa is rumored to be leading, you know, a very big round, $40 billion round, you know, with a lot which we saw they announced it at the White House.
- [41:51]
A
It is important many people interpreted such as comments as a. As a tapping of the brick.
- [41:57]
B
Yes. So tell me how you interpret it.
- [41:59]
A
He said, because he said, I'm happy that some of these are leases.
- [42:02]
B
Yes.
- [42:03]
A
Which. Which I don't know any other way to interpret that. Well, there's two ways you could interpret. 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.
- [42:21]
B
I would say. 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 could go through a zone of disillusionment.
- [42:36]
A
Yeah.
- [42:36]
B
Right. So he basically said the reckoning is coming at some point in time. And so now he goes on Dwarkish. 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.
- [43:09]
A
Yep. Look, I mean I think everyone believes in AI, this amount of spend and is, is something we've never seen before. That's why I've said, you know, that it's like better than watching secession. This is just like it's a, it's a massive sport of kings and there's, you know, and I think some of the things, whether it's the 20 billion losses or Sacha saying he's glad he's got leases, some of these might be part of an information, you know, war with other players trying to talk capital in or out, you know, for sure. And it's, it's a high stakes game, it's fun to watch.
- [43:47]
B
Well, I think resiliency, business model resiliency is going to be critical here. Yeah, right. And what do I mean by that? It means liquidity because like 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 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.
- [44:35]
A
Yeah.
- [44:36]
B
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 are some, some numbers out there. Last week, obviously Elon is, 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 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.
- [45:09]
A
Although deep seek surprise everybody.
- [45:12]
B
Well, I'm saying if you're going to play that game.
- [45:14]
A
Yeah.
- [45:14]
B
Right. And remind you, Deep Seek spent more than 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.
- [45:28]
A
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, it's easy to lose sight of the microeconomics. It's easy to lose sight of the unit economics.
- [45:56]
B
Totally agree.
- [45:56]
A
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? Like, 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.
- [46:17]
B
Yes.
- [46:17]
A
That is, I've never seen before.
- [46:19]
B
Explain what you mean by that.
- [46:20]
A
I mean the price difference between today's model and Yesterday's model is 20x.
- [46:28]
B
Yes. So it's a fast depreciating asset the second you're off the frontier.
- [46:34]
A
Yes, yes, yes. And so it's just, it's a dangerous. Yeah, like these are all traps, you know, and it makes it, you know, once again, fascinating. I'm. Maybe we can transition to the public markets a bit, but there's a lot of talk that we're going to see a core weave filing and I'm just excited to see the numbers and to piece together more of the information.
- [46:55]
B
Yeah, there's a rumor out there that the core weave is going to file an ipo and so you can see the numbers. Well, I just want to underscore this point that you just made though, because I mean, and there's, there is some, there is some rhyming to Masa coming back into the scene here. Right. You know, Masa is one of the greats of this industry of the last 25 years. But I think people would also describe him as somebody who's a bit of a gambler and places gigantic bets. Right. And some people would say that he's a total visionary and other people would say he's just not price discriminating. Right. But clearly he's shoving all in with OpenAI.
- [47:38]
A
I don't think he knows any. I don't think he has any other way of operating.
- [47:42]
B
Right. And so I think the point being that we're at this moment in time where the danger for the company, I just Want to underscore what you said. The danger for the company of getting this volume of capital is that it's hard to focus on really building the muscle and the grit and the ingenuity on how to drive unit economics. Think about what Elon had to do at Tesla, right, Because capital was hard to come by, so he had to figure out how to make money on every damn car. How do I take costs out of the manufacturing at every single stage of production? And when you have excess capital, right, you lose that discipline. You don't build that muscle. And so I think it's an important admonition for the board and leadership at OpenAI and all these companies to hear that, sure, it's one thing to invest aggressively in the future, but you better make sure that along the way your unit economics work.
- [48:41]
A
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 market. 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. So you.
- [49:06]
B
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.
- [49:19]
A
And that's not just dosh, because that.
- [49:21]
B
Right, because we have tariffs and other things. And I said, and we have peak technology uncertainty. That is, it's hard to predict the future. You know, what software company is gonna 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, okay, 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 in order to save the economy. But then we also were very critical of 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 the, you know, 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. Right. They sent this email out to every employee that said, you know, right. Respond back to us or you'll be deemed, you know, to have resigned. Now, they're giving them more, you know, 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%. 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.
- [52:34]
A
Yeah.
- [52:35]
B
I don't know the exact percentage of federal employees they let go. It was like between 10 and 20%. 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 on, of liquidity from government into the system. So if you think about, go back to our GDP calculation, right, in macroeconomics, C +I +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, you know, you got to take this medicine, this short term pain. You got to work out every day, you got to get fit, right? 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. Right. 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 right, in the markets while the market gets its head around the fact that the economy is going to grow a little slower. When the economy grows a little slower, that means companies grow a little bit slower. When they grow slower, you know, the earnings goes down and the multiple goes down.
- [54:39]
A
Let me ask you this question. When, when Elon went into Twitter, one of the stories that came out was that they found there were software licenses for a whole bunch of people that weren't using. And yes, that they cut that dramatic. Do you anticipate that one of the outcomes of DOGE will be obviously a headwind for a bunch of Companies that have sold software and or services into Doge 100%.
- [55:09]
B
I mean, there's just no way around it. If you go from 3 million federal employees to a million and a half federal employees, and you don't need as many licenses, you don't have as much cloud consumption. And so if you think about the multiplier, right, you take the federal government or federal person salary, employee salary, now you have all the health care and benefits and pension and all the other stuff, and then you have all the ancillary spend. So I won't say the exact company, but I talked to an airline the other day.
- [55:36]
A
Yeah.
- [55:36]
B
And at this airline, their number of government tickets sold year to date is down 50% already impact 5, 0%. Yeah. Because they said, we don't want, you know, you traveling, we want you in the office every day and all this other stuff. And so this airline has already been impacted. So I think everybody in the ecosystem, if you have revenue line items, if you're a business, if you're a public company, you have revenue line items from the federal government, it's not just that the rate of growth is going to slow, it's that they're actually going to be negative on a year, on year basis. Now, again, I happen to think this is a, generally a good sacrifice for us to make. Those are our tax dollars. There is no government money. This is our money that's being, you know, being consumed. But I don't think the public markets or investors generally, and certainly not Silicon Valley, has kind of gotten their head around what this means. Now, what's the. What's.
- [56:31]
A
Well, in fact, I would say, like, ironically, this happens quite a bit in our world, but the Silicon Valley and the venture capitalists have just gotten comfortable with backing companies that sell to government.
- [56:44]
B
Exactly. We see a lot of that interesting timing. People get excited about. Well, you saw what happened to Palantir stock the other day when the President directed his cabinet members, Secretary of defense, to find 8% cuts in the Department of Defense every year. Right. And so this austerity, again, is real. Now, that probably means we're going to have a rotation of money out of like, the less technologically innovative folks into the more technologically innovative folks. But, you know, he went further.
- [57:16]
A
He suggest. Trump went further. He suggested in one thing, which I was really blown away by this. I actually thought it was kind of the most interesting thing he's done. He suggested to Xi that China and America should both cut their military budgets in half.
- [57:32]
B
Yes.
- [57:32]
A
Now, maybe that's provocative. Maybe it's a card. That'd be an amazing idea.
- [57:36]
B
That was extraordinary. Back to the, you know, this idea, you know, we've been, we both blow.
- [57:41]
A
Up the world many times over. So, right.
- [57:43]
B
There's a certain camp of folks, right? And I think Mearsheimer is in this camp, right, which is great power politics. And like, you just got to build, build and build. And, you know, eventually you're going to have a war or something like this or, or maybe the fact that you have these stockpiles deters, you know, the ultimate war. One thing that is just fascinating. I've never heard an American president in my lifetime suggest that he wanted to sit down at a table with China and Russia and talk about they could cut their, they could collectively cut their military spending in half. And just from an entrepreneur perspective, like, as it caused me to stop in my tracks and be like, that's an interesting idea.
- [58:25]
A
I thought it was the coolest thing he's thought of.
- [58:28]
B
That's an interesting idea. Well, I will tell you, back on the public market, the other interesting thing here, Warren Buffett just put out his annual letter. He's going to have his annual meeting coming up here, has a $400 billion cash stockpile, has been liquidating stocks, his biggest stockpile in ages. Stan Druckenmiller, Howard Marks, Stevie Cohen came out over the weekend and said, I'm nervous about the markets for the same reason that we were talking about a month ago. So I think there is a growing chorus of players now. What's the flip side to this? Well, since Trump's been elected, the cost of a mortgage or credit card, et cetera, is starting to come down. Why is that? Right? There are two reasons. The first reason, I think, is because we're saying, okay, the economy's going to slow a little bit. And if the economy slows, equities as an investment are a little less positive relative to a bond. So you rotate that into cash. And when the cash is sitting on the sideline, it's invested in a US treasury, just to put it in perspective. And the only anecdote I really ever hear about this is while China doesn't want to own our Treasuries anymore, China buys 3% of our treasuries annually. It's tiny. They used to buy, you know, 10 years ago, they bought 12% of our treasuries, and everybody panicked that they were too big a buyer. So, you know what I see is just the opposite. Every sovereign around the world and every domestic investor who's, who's Starting to put more money into cash. Who's hedging a little bit. All of that's going into US Treasuries. So I just think that one should brace over the next three months. I think these tariffs are very real, they're structural, and the President is committed to them. I think, number two, the reconciliation package is now rolling, and I think they are very committed to balancing the budget within this president's term. And the only way you balance the budget is a trillion dollars has to come out of spending. Remember 2019, baseline, we were spending about 5 trillion. The COVID high, 7 trillion. We got to get that back down to at least 6 trillion, probably to 5.75. If you're going to balance the budget, that means a trillion out in a year. That's austerity, and that's going to be a headwind to the economy, but it's the right thing to do.
- [60:49]
A
Okay, that's a tough note to end on. So I'll switch. I'll switch to something more positive. I. I got invited to the Golden State Warrior game on Tuesday night. The Butler trade looks like it's working.
- [61:03]
B
It's. It's incredible.
- [61:04]
A
6 and 1. I think since the trade, it's.
- [61:06]
B
It's incredible. I was. I 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. Yeah, I remember. And 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 by 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 was. He was. I don't. 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, you know, our. Me and our good friend Jason Chang, I've never. 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, so great that they're not going to win, 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 the six game winning street. They trade for, you know, for Jimmy Butler and, like, they may win this whole thing. So, you know, fingers crossed I'm not. It now has me. Now has me with a focused mind. With a focused mind. It's great to see you. Great to be with you.
- [63:06]
A
Take.
- [63:16]
B
As a reminder to everybody, just our opinions, not investment advice.