Speaker 1: I know your funds are a big holder of NVIDIA, one of your top holdings, at least in a couple of those funds. When you look at a sell-off like this, one that seems to have come out of nowhere, basically we get this, I guess, analyst report, if you will, about DeepSeek, but you go back on the Bloomberg Terminal. We've been writing about this for a while.

Speaker 2: Does this worry you? Well, I think there's so many headlines out there, there's so much news flow. So let's take a quick step back and think about what's happened over the last month. Because this news that's really getting all the headlines today and got all the headlines over the weekend with DeepSeek, really started, well, I guess a year ago when they released their model called V2, which introduced a lot of these potential breakthroughs. Those breakthroughs came to fruition in a model they released a month ago. So a lot of this has been out there. Last week, they released their latest reasoning model that coincided with the inauguration. There's been a lot of headlines since then. So what my take on DeepSeek is, in particular, is I think a lot of the advancements that they've made are very real, and it's something to pay very close attention to if you're an NVIDIA shareholder.

Speaker 1: I want to read to you a statement that NVIDIA emailed to our reporters, Ian King here at Bloomberg, basically saying that it is an excellent AI advancement. But they say the work illustrates how new models can be created, but they kind of dismissed some of these concerns as somehow this is a negative for NVIDIA itself.

Speaker 2: Well, I mean, I think there's probably there's clear negatives for NVIDIA. There's also potential longer term positives, I'd say, too. So on the negative side, what's clear is DeepSeek has created a way to, I'd say, do more with less. What they've done, the way I think about it in simple terms, is take a professional certification exam like I took the CFA exam. There's a lot of ways to study for that exam. One way is you read all 5,000 pages of the textbook. On the other extreme, you just do practice questions. What DeepSeek did is when they trained this reasoning model, they kind of took the practice question approach. They took some shortcuts, but created something that's definitely good enough and capable enough that was done very cheaply. I love that analogy.

Speaker 1: By the way, I did the practice route, too, and I failed level two twice. But eventually, I just read the book and I passed.

Speaker 3: I was like, but then you passed.

Speaker 1: So it's OK.

Speaker 3: And it was interesting to see also NVIDIA talk about how DeepSeek was export control compliant. It was like, please don't restrict us anymore when it comes to exports.

Speaker 2: Do you buy the dip? So again, I think with NVIDIA, you don't trade the stock. You own it for the long term. And I think two points I'd make on sort of the positive side for NVIDIA, what could this do for the industry more broadly? If the cost of AI inferencing, the cost of AI training comes down, it could make the applications more broad-based. It could unlock new pools of demand, new potential customers. So this could be good for innovation in the AI space broadly, which would be good for NVIDIA in the long term. The other point I'd make is, you know, I think this is good for big tech as well, separate from NVIDIA. I think lower cost of inferencing, very good for a company like Meta, very good for a company like Google, very good for a company like Amazon, companies that have AI embedded in their P&Ls. And then back to NVIDIA, the other point I want to make is this happens from time to time in tech investing. Big tech stocks get left for dead and they come back. This happened with Microsoft many years ago. This happened with Apple after Steve Jobs passed away. This has happened many times with Meta, many times with Google. Amazon was never going to turn a profit. Netflix was never going to turn a profit. These existential questions tend to come up from time to time. That's what's happening today with NVIDIA. I think, you know, there are plenty of near-term questions that these companies are going to have to address during earnings this week, but I still am a holder of NVIDIA long-term. Buy the dip is not really how I generally trade NVIDIA, but I'm still owning NVIDIA for the long-term.

Speaker 3: At the end of the day, though, if we get into a world where we can reduce the cost and you don't actually, you can't charge us a lot for AI services, like the everyday consumer, who is that bad for?

Speaker 2: Well, I think, so I'd say, first of all, it's probably bad near-term on the training side. I do think it's not, it's seeming to be not as important to invest massive amounts of dollars in training to get the best output. I think DeepSeek is showing us that it's, there's ways to optimize your AI spending in a way that hasn't been done yet. So I think that's probably, it's probably bad for them. For someone like OpenAI and some of the model companies, so Google Gemini would be another one there. I think this is showing that there is, those models commoditize pretty quickly. I think it could be bad for these model companies. We'll see. Again, it's very early. This is evolving very quickly. That's where I'd start as kind of the losers. Then the derivatives for some of that stuff. So some of the industrials, some of the power companies, we'll see how this unfolds. I think near-term, probably fewer massive training data centers constructed, but long-term, could there be more inferencing data centers constructed? Could there be more AI run at the edge? Could there be more AI infrastructure built in that way?

Speaker 1: We'll see. I'm curious as to, I mean, you mentioned some of the earnings we're going to get. We're going to start to hear from some of the hyperscalers and some of the, basically the buyers, the ones that have been investing a lot of money in this. Do you think we're going to hear any sort of material change in the amount of money that they've committed to these projects?

Speaker 2: Well, Romain, I mean, that's one of the really interesting things about the last week. So this R1 model from Deekseek was launched on Monday. And then the next day you had this Stargate announcement with Oracle and OpenAI. We can debate how real that is, but a $500 billion AI investment program. And then on Friday, Meta pre-announced, unexpectedly, their 2025 CapEx plans, $60 to $65 billion, about $10 to $15 billion above the street. So clearly, Meta is going all in on this. And I think their Lama models are the closest Deekseek comp, by the way, instead of open-source models like Deekseek. So to answer your question, will these companies backtrack on the CapEx plans? I don't think so near term. I think the question is more next year, 2027, is the investment cycle finally starting to crest?

Speaker 1: We'll see there. We only have time for one quick question, but I do want to ask you about the market reaction to Meta. Because when you see all of these other stocks getting decimated, Meta spent most of the session in the green. I think it's now just dipping into the red, but you're not seeing these double-digit percentage losses there. Why do you think investors were maybe a little bit warm on Meta as opposed to some of the other software companies out there?

Speaker 2: I think near term, people trading Meta stock, the big unknown ahead of earnings this week, there's two unknowns. What are the CapEx plans? What are the OpEx plans? CapEx plans, those were announced. So that was kind of a potential negative event that they got out of the way on Friday. So that's why that stock reacted okay on Friday. And then today, I think Meta is just a really interestingly positioned company. You've got, first of all, as I mentioned, cost of inferencing going down. That's a direct positive in their P&L, for sure. And then secondly, DeepSeek open source model company. That's what Meta, Meta's made a big bet on open source models. That's what they have with Lama. So I think there's excitement about that asset moving forward as well. And you are a holder of Meta. We are a big holder of Meta. Yeah.