BUY MEMORY

“Huawei is arguably the only company in the world that has all the legs. Huawei has cracked software engineers. Huawei has cracked networking technologies. That's, in fact, their biggest business historically. And they have cracked AI talent. But furthermore, beyond NVIDIA, they actually have better AI researchers. And furthermore, beyond NVIDIA, they have their own fabs. It's very arguable that Huawei, if they had TSMC, would be better than Nvidia.”

“We are constantly trying to take these long term projects, which when you first announce them, slightly marginally looks ridiculous. Okay. You know, like, we're in the earliest stages of thinking about data centers in space. But to your earlier discussion around constraint inspires creativity. But if you take a twenty year outlook, right, where are you going to put most of these data centers? Really hard problems to solve.”

“I'm coming here as we just shipped Gemma four. And, it's a really good open source model. The frontier to Gemma four is both huge and not so huge in terms of time. Like, of, Gemma four is based on Gemini three architecture. You know, it's a very weird thing. Right? You're talking about a set of ways which can fit on a USB stick.”

“I think your question earlier on, like, you know, I think you were asking in the context of way more robotics, like, companies. I do think companies which are that's one advantage startups are gonna have. More AI native teams. And and, you know, you can probably get at it through your interview processes, etcetera. Whereas for us, we would have, like, retraining, transformation etcetera. And I think that that's maybe an advantage, like, the younger companies are gonna have.”

“If you ship out all the process engineers and assuming it's, like, hot enough that you destroy the fabs, no one has all the fabs in Taiwan now, which is a big risk. These tools actually use a lot of semiconductors, which are manufactured in Taiwan. So it's like a snake eating its own tail sort of like meme because you can't make the tools without the chips from Taiwan, which you can't use without the tools in Taiwan. Just shipping out all the engineers and blowing up the fabs means China has a stronger semiconductor supply chain than the rest of the world.”

“Memory is definitely one of the most critical components now. There is no way that the leading memory companies are going to dramatically improve their capacity. So you have those constraints in the short term, but they they get more relaxed as you go out. By the way, I think it'll push a lot of innovations on. We will make these things 30 x more efficient.”

“Typically, people want to invest in preferred stocks because they have a bit of an income focus. They typically pay higher fixed dividends than common stocks and often have some pretty attractive yields, anywhere from 5% to 8%, and so that makes them pretty attractive for these steady cash flow seekers. But that also changes where they are as well with respect to their position in the capital stack. They sit above common equity, meaning if a company goes bankrupt, you would get some claim on assets before common stock shareholders do, but they are below bonds as well.”

“Micron Technology has had quite, quite a positive performance recently. It is a leading semiconductor memory and storage company, so they make DRAM, NAND, Flash, and high bandwidth memory. It's one of the few major global suppliers in an industry that has a lot of high barriers to entry, not just because of input costs, but also because of the required technological understanding and ability to develop these very complex and small products. This HBM, it's high bandwidth memory, right? This is really what's been driving it here.”

“ASML makes the world's most complicated machine, I e, an EUV tool, and the selling price for those is $304,100,000,000 dollars. And currently, they can make about 70. Next year, they'll get to 80. Even under very aggressive supply chain expansion, they only get to a little bit over a 100 by the end of the decade. ASML's commented their supply chain has over 10,000 people in it.”

“We've all seen how tech earnings calls have really highlighted a new risk. There isn't enough electricity to power the new data centers. We'll talk about the utility super cycle as power companies raise rates to build this new capacity. We'll also touch on a story I saw today about KPMG pressing its auditors to cut costs, or rather to cut the price they charge KPMG due to AI cost savings. What does that mean for the audit industry and really industry as a whole?”

“What really drove the market today? Well, it was the feeling that there was a bit of a bottoming in software. It was a focus as groups attempted to break seven straight declines. Bit of a pick up in commentary. We saw a lot of discussion about very oversold conditions and some pushback against some of the more dire predictions revolving around that AI competition that was part and parcel for why the market was doing what it was doing. In addition, you had elevated hyperscaler capex, still a positive for the broader AI trade.”

“Hey. The overton window shifted. We have like, I felt like the company was built for that moment. The vertical thing, it's it's it's not an accident or something. It was a very intentful we were on the seventh version of TPUs. So to me, we were behind in terms of frontier LLM models, but we had all the capabilities internally, and we had to execute to meet the moment.”

“I believe an iPhone has 12 gigabytes of memory. Each gig cost used to cost roughly 3 or $4. That's $50. But now the price of memory is, like, tripled. Let's call if it's now, it's $12 per gig for DDR. So now you're talking about a $150 versus $50. A $100 increase in cost on Apple. Apple has some margin. They're not just gonna eat the margin. So now that's a $100 cost increase. The NAND also has the same sort of, like, market. So in fact, you know, it's probably a $150 increase on the on the iPhone. That means the end consumer is paying $250 more for an iPhone.”

“In isolation, you almost always wanna go with a smaller model that gets RL'd faster and gets deployed into research and development. So you can build the next thing and get more compute efficiency wins. And then this compounding effect of, oh, I made a smaller model that I r l'd more that I then deployed into research and development earlier, and I spent less compute on the training itself because I was able to allocate more compute to the research. This compounding effect of being able to do the research faster and faster is potentially a faster takeoff.”

“Space data centers effectively are not limited by, you know, hey. We have this energy advantage. It's actually just limited by the same contended resource. We can only make 200 gigawatts of chips a year by the end of the decade. So what are we gonna do to get that capacity? It doesn't matter if it's on land or in space. Elon doesn't win by doing, you know, 20% gains. Elon never wins that way. Elon wins when he swings for the fences and does 10 x gains.”

“And so you sort of have this, like, dynamic that is quite interesting in that. An h one hundred is worth more today than it was three years ago.”

“Used to be 1,400,000 smartphones were sold a year. Now we're at, like, 1.1. But our projections are we maybe get down to, like, 800,000,000 this year. And next year, like, 600 or 500,000,000. They see Xiaomi and Oppo are cutting low end and mid range smartphone volumes by half. Today, you already see all the memes, like, on PC subreddits and PC gaming PC Twitter is, like, cat dancing videos. And it's like, this is why memory prices has doubled, and you can't get a new gaming GPU.”

“Google sold, I think, a million was it the v sevens, the Ironwoods, to Anthropic? DeepMind people are like, this is insane. Why did we do this? But then Google Cloud people and Google executives saw a different, like, thought process. They saw this dislocation. They negotiated a deal, and they were able to get access to these to this compute before Google realized. We saw capacity on anthropic or sorry, on TPUs go up by a significant amount over the course of those six weeks. Google even had to go to TSMC and explain to them why they needed this increase in capacity because it was so sudden. But that a lot of that capacity increase was for selling to Anthropic. Because Anthropic saw it before Google.”

“But now it is really acutely constrained. Right? So you spend a lot more time. I at least spend a dedicated hour a week thinking about that question at a pretty granular level. So I will know by projects and by teams the compute units they are using. Right? And, you know, or or at least I have that information, and I'm looking at it and assessing it.”

“Transformers was done in the context of a lot of, like, like, TPUs, transformers were all done to solve a specific product need to some extent. Right? Like, the team's thinking about how to make translation better. In the case of TPUs, how do you, pay speech rec works? We suddenly have to serve it to 2,000,000,000 people. We don't have enough chips for it.”

“Dario, when he was on your podcast, was very, very, like, conservative. He's like, you know, I'm not gonna go crazy on compute because if my revenue inflects at a different rate, at a different point, I don't wanna go bankrupt. But in reality, you know, he's definitely missed the pooch in terms of, like, going, like, OpenAI, which was, let's just sign these crazy fucking deals. And OpenAI has kind of got way more access to compute than Anthropic by the end of the year. And so what does Anthropic have to do to get the compute? Well, they have to go to lower quality providers that they would not have gone to before.”

“But to give an example, like, search, you know, I was speaking with the teams. Right? Like, they now have for sub teams, like, latency budgets, like, in the milliseconds. You'll get 50% credit if so if you ship something which, you know, shaves off three milliseconds, you earn one point five milliseconds for your latency budget, and one point five milliseconds gets passed on to the user.”

“Waymo was a great example where I think we increased our investment two to three years ago when the rest of the world got pessimistic on it. When others, some of the people are backing off. For example, if Waymo had reached this point earlier, I think I would have invested the capital earlier. But I would have been glad to invest more capital in Waymo earlier, but we weren't at the level of maturity needed to do that.”

“Ticker XLI is the State Street Industrial Select Sector SPDR ETF... Even if the economy is starting to turn, you're not really seeing signs of a breakdown in industrials and certainly not seeing a sign of a breakdown in this ETF. A lot of what has happened in the market this week has been centered around the narrative of AI, AI spending, and really the lack of monetization across the board and hasn't really spilled over into other sectors. Unless you're overweight a ridiculous amount relative to what the market weight is of industrials, I don't see any reason why you would want to fully exit this industrials ETF.”