Invest Like the Best with Patrick O'Shaughnessy
00:00:00 · Patrick O'Shaughnessy
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00:01:50 · S1, Patrick O'Shaughnessy, Gavin Baker
[00:01:50] S1: O'Shaughnessy is the CEO Of PositiveSum. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of PositiveSum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of PositiveSum may maintain positions in the securities discussed in this podcast. To learn more, visit p s u m dot v c. [00:02:19] S0: Gavin, it's only been two months. Like the model release cycles, the gap between our podcast episodes are shortening. We're, we're basically-- You and I are basically on a model release cadence at this point. [00:02:30] S2: Well, I was, I was sensitive to criticism that I think somebody pointed out that our podcasts were coincident with like local market peaks. And nobody can say that after this. Yes. What's on your mind? It's been a crazy- Yeah, I would describe July as two thousand and twenty-two in a month. Yeah. There are some fundamental negatives which, which we should talk, but on the whole, the balance of fundamentals, I think, is improving significantly Loads of AI names are down 50, 60% from their highs. Well, call it 40 to 60% in a month in a straight line. And I asked you before we started, you've been out here for the summer, have you heard a single negative? Quantitative metric about AI, a single instance of deceleration. [00:03:23] S1: Nothing. [00:03:24] S2: Nothing.
00:03:24 · Gavin Baker, Patrick O'Shaughnessy
[00:03:24] S2: Nothing. [00:03:25] S0: In fact, every metric is accelerating. And to your point, not just blind optimism from people excited about AI, but like, here's some data that they can show you and from their different vantage points.
00:03:35 · Gavin Baker
[00:03:35] S2: Absolutely. I mean, however you cut it, whether you cut- GPU availability, whether you cut GPU rental pricing, I mean, whether you cut like the spot price of DRAM this month, token growth Everything is actually accelerated, and I do think a big part of the problem is one, the market doesn't have visibility into Anthropic, OpenAI, and then I would say these open-source inference clouds that monetize Inference here in America, FireWorks, based on Mosaic together. And the picture looks very different when you see that, because open source has accelerated massively because of Golang 5.2, Kibana 3, and then Neutron continues to kind of chug along. We had a great Very small American open source model release. OpenAI has accelerated, and Anthropic continues to grow really strongly, and is almost certainly pumping out significant amounts of free cash flow. And I just think if you know, there's this chart that everybody looks at of semiconductor cash flow going like this, and hyperscale free cash flow going like that, and you're missing these private companies. But I also think that, that chart misses something very important, which is just that you have everyone in twenty-four and twenty-five, even if you're really bullish. You thought that GPU prices, if you were really bullish, you thought they would decline slowly. If you were bearish, you thought it would decline precipitously. I don't think anyone in '24 or '25 Thought that the prices of old GPUs would be going vertical. Everybody thought, "Hey, we're gonna be smart, we're gonna sign these long-term contracts." And to some degree, like a lot of the neo clouds had to do that because they needed an off-take agreement to finance the GPUs. And so essentially, you have the contracted base of installed compute Trading at a massive discount to the current spot market, and as those contracts roll off and compute gets repriced higher If SPAC can decline and compute will still get repriced higher, I think you're gonna see a lot of acceleration that's gonna answer these ROIC questions. You've started to see that this quarter, if we look at operating cash flow, not free cash flow, operating cash flow from Microsoft, Meta, and Amazon has reported accelerated from twenty-eight to thirty-two.
00:06:02 · Gavin Baker
There are some actually pretty big unusual items now, like these hyperscalers that always seem to have billions of dollars of legal expenses that are unusual, mostly fines. To the EU, but there was an unusual amount of one-timers this quarter, and if you adjust for that, we went from twenty-eight to thirty-five, and that's, that's a material acceleration at this scale, and that's really before they start to light up the rubids Which will come at a meaningful premium before these contracts reprice. It's been a challenging month. Is it helpful to kind of like walk through the month, how we got here? Yeah. So first, Meta is gonna rent out compute, and this is seen as like very bearish. They have excess capacity, they're gonna cut CapEx, this is a disaster. This isn't at all what it was. They just reported they didn't cut CapEx. What it was is they saw SpaceX have a big installed base of compute and sell some big trading optimized clusters into the market at a truly massive premium to these contracted rates, and at least the analysts liked that, they saw an opportunity. There's a lot of speculation they're gonna raise capital, so maybe what they're thinking is like, "Hey, we will show on a small chunk of- Of capacity that we can generate really strong IRRs, then we'll go raise equity capital and we'll be off to the races and probably raise CapEx. That doesn't look like that's what they're doing, but nonetheless, the market sold off because it interpreted this very negatively. And I was really sure it wasn't negative. A lot of telemetry and TIBETAS CapEx plans, none of that telemetry had shifted at all. If anything, they're continued to get more aggressive. And then shortly after that, they released their best model in a long time, Muse one point one, which was actually a very good model. I mean, it was overshadowed by Croc four point five, but it was a good model, way better than anything in two years. So just no chance they're taking their foot off the gas. Then Kimmy comes out, and then there's this Huge freak out about open source, and at the same time this Silicon Data token index kind of dips and flattens, and the two are connected.
00:08:23 · Gavin Baker, Patrick O'Shaughnessy
What the Silicon Data token index captures is mix, and they don't see all the tokens, but because of GLM five point two and then Kimmy, all that took a while to layer in, there's kind of a mix shift in this data from more expensive frontier tokens, which probably have an inference margin We can debate whether it's eighty, ninety, or ninety-five, but super high towards open-source tokens. And for whatever reason, the market thought this was negative, but the reality is, a token is a token, and you need the exact same amount of compute to make a token all else equal. It takes the same amount of flops, the same amount of memory, the same amount of watts. Tokens aren't equal, but broadly speaking, all open source take-- share does is take margin dollars out of the frontier model layer. There is elasticity, thereby driving token demand. You need more demand for compute, and the margins, you know, Anthropic and open source, they all run on the same underlying cloud providers who charge the same amount of compute. So you're literally just taking margin from frontier models and essentially driving more margin dollars into the AI infrastructure layer [00:09:39] S0: that was the catalyst with this combination of things.