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- [00:00]
A
We have Tae Kim in the waiting room. Let's bring him in to the TVPN ultradome. Tae, how you doing?
- [00:06]
B
Hey guys, doing great.
- [00:08]
C
What's going on?
- [00:09]
A
So. So tell me, last time you were on the show, you bottom ticked it. What's going on?
- [00:14]
B
I think I made the bullish call on CPUs memory and Nvidia. Nvidia is up like 5, 10%, but nice. The CPU names have still doubled even after this big drawdown and the HBM names are up 100%. So I'm hoping that it's the same thing again. I come on here. Stocks go up again.
- [00:35]
C
Yeah. Ideally we could have an emergency reserve of take him. So if the market is ever down, strategic reserve, we call you up, you jump on.
- [00:44]
B
And then it was funny because it was literally the exact bottom and it went exponential after that take him effect.
- [00:52]
A
So where are we right now with the level of fudge, the level of downward pressure on the AI trade broadly, the chips, the semi trade, like reset for us on like where sentiment is and then we can work through the different pieces of counterexamples.
- [01:08]
B
So I think sentiment's very negative. We kind of had this huge up parabolic up move the last few months and likely a lot of retail and hedge funds piled in and we were seeing this unwind. Now I think the first, a big part of it was Iran war getting worse. Every time we had the first ceasefire negotiations, stocks started taking off right after that. And then when we had the actual ceasefire, we had a follow through. And then as soon as Trump started bombing Iran again, chip stocks have kind of plummeted in the last two, three weeks. And then now we're seeing just back to the old pattern of media and the viral hot takes spreading a lot of fud. I think we saw earlier this month, I think Reuters quoted like Zuckerberg about agentic AI. They took it out of context. And then every media person was with a hot take that this Meta was seeing bad returns and they're going to cut CapEx. And then we had leaks right after that saying that it looks like Meta is going to raise CapEx. So we're seeing a lot of this hot take FUD. Yesterday, I think we had a flurry of stock stuff that scared people. The Wall Street Journal vendor financing article that we'll see what happens with that. We had CMXT IPO in China and everyone freaked out over that. We had the information article on asml. We could go through each one. And then the Kimi thing, it's obviously a Big thing.
- [02:40]
A
Yeah, we'll definitely get there. And I want to talk about open source and Nvidia's strategy there, obviously starting with the Mark Zuckerberg news in Reuters. This was July 2nd. Meta's Zuckerberg says AI agent tech progressing slower than expected. Zuckerberg added that the company's reorganization that included major job cuts was not as clean as it could have been. Zuckerberg and other media executives have been seeking to moderate some of the of the organizational changes introduced this year. And they said that the trajectory of agentic development over the last four months hasn't really accelerated in the way we expected. The company's bets on new structure haven't come to fruition yet and so people were sort of reading this as maybe Meta's going to pull back. But then it felt like the response was extremely quick with Boz going on a podcast and Alex Wang sharing a whole bunch of progress across a few different models and data points. And then Semianalysis wrote a whole bull case for MSL talking about how they have COMPUTE and also they have more of like the INF internal structural alignment to sort of properly YOLO in the AI era. If I'm boiling it down as brutally as possible just because with Google there's always this debate between oh, do you sell the TPUs or do you sell the cloud comp? Do you have vended in the product? Whereas Mark Zuckerberg is able to sort of like go all in on this new idea and so maybe there's more glimmers of hope there. But what else have you been tracking downstream of Meadows ambitions?
- [04:19]
B
Well, I mean they've been very upfront that they're investing heavily in. Alexander Wang is tweeting multiple times every few weeks that they're going full force, they're going to redo open source AI models. I think he said that the YC event over the weekend, it's. I mean if you actually look at. And then Reuters came out, I think with an article saying that they're actually going to raise capex dramatically this year and next year. So all that kind of fear that that quote about it's fintech AI from the town hall that kind of like spooked the market for a few days. It kind of, it was completely false, the stuff like this.
- [04:56]
A
Yeah, it feels like it's a comms error because the, the language that's been coming out of Meta has been a little bit like AI is going to replace our employees and it feels like it'd be much better for them to, to come to the market with a message of we're going on the offensive. Like we're a hyperscaler.
- [05:15]
B
To be fair. That was the internal town hall. They didn't mean to leak it. And Reuters leaked that one quote and put out, put out the headline before the article.
- [05:23]
C
Yeah, it's interesting like Meta. Did Meta basically go through like an eight year period where like internal town halls didn't instantly leak?
- [05:30]
A
I think everything leaked always. I think everything's been.
- [05:33]
C
I know, but there was, there was a period where like the sort of attention of the media way, way, way less on like what Meta was doing internally relative to the 2010s and all that attention just went to the labs. Right?
- [05:48]
A
Yeah, yeah, yeah. No, that makes sense.
- [05:51]
C
Yeah. I guess the question is like the question that I keep coming back to is like where is their revenue ramp? Where is their AI revenue going to ramp and when.
- [06:03]
B
Right.
- [06:04]
A
Because as super say ads like the ads like the AI has.
- [06:08]
C
Yeah.
- [06:09]
A
They're accelerating.
- [06:11]
C
That's always been my view too. But when you're, when you're continuing to ramp Capex.
- [06:16]
A
Yeah.
- [06:17]
C
With and saying like we're going all in on Agentic and we're building a harness and we're also going to do open source and it's like well what is the strategy?
- [06:25]
A
Sure.
- [06:26]
C
Like yeah, yeah. What is going to take you to a billion dollars of like pure AI product revenue or, or, or just API revenue? What's going to. And then to 5 and 10 and what's going to allow you to like justify the spend other than I think the market would love if they just said yeah, we actually need all these GPUs because we can actually be 10 times. We're already good at ads. We could be 10 times better. And that's where we're going to get the ROI on all of this Capex.
- [06:55]
B
Well they're definitely getting ROI on that. The market is worried about know all this extra capex on the. They're going for the frontier AI model race again and they had to reset like they had a lot of people left and now Wang hired a ton of people and yeah, we'll see what happens over the next. It's going to take time. It's going to take six to 12 months before we see any more progress. But just model that came out a few weeks ago was a lot better than people expected. It wasn't, you know, the frontier, but it was much better than what people expected.
- [07:25]
A
Yeah, yeah. So how have you been processing the Nvidia letter around open source and all the back and forth, all the people jumping on the companies that have been staying back. How do you work through that?
- [07:42]
B
It's been very impressive what they've been. They basically united the entire tech industry against Anthropic. In the last like 3, 4 days,
- [07:50]
A
18 trillion in market cap has signed on. Last time I checked across Google took a little time.
- [07:57]
B
Amazon signed on eventually. Yeah.
- [07:59]
A
Okay.
- [08:00]
B
They signed on yesterday. They tweeted out I think Apple is
- [08:03]
A
still the holdout, which is kind of
- [08:06]
B
strange because they're the one that would most benefit from open source open weight models being, you know, more available I would think but I don't know what Apple but I mean they pretty much got the whole tech industry to kind of corner Anthropic in their position. Yeah. OpenAI signed on.
- [08:26]
A
Yeah. What did you think?
- [08:27]
B
Obviously Nvidia it's afraid.
- [08:29]
A
Yeah.
- [08:29]
B
I don't know.
- [08:29]
C
I don't know how, how if. I don't know if they're really. I don't, I don't read it as being like cornered by any means. Right.
- [08:41]
B
Well, Jensen is on the record that he said I think to Bloomberg that there was rising sentiment that something was going to happen on the, on the regulation front. Oh, White House or whatever. So this.
- [08:53]
C
Yeah, we saw that this was. Yeah, this was last week. You had at least four people in the admin say we're not against open weights, we're against distillation. And at least I was reading into that of some type of regulatory action around open weights and then positioning it as we're targeting.
- [09:11]
B
This is, this is like yesterday. Yeah, yeah. About you know, pushback and restrictions and he's doing it under the safety umbrella but definitely Microsoft, Nvidia are worried that the White House or Congress is going to do something on this front and yeah, that's why they took.
- [09:32]
A
It seems very reasonable that he would have no problem with like Gemma or Llama or any of the open source from like American hyperscalers where if you find out that they're distilling you just walk across, cross the street and sue them. And also these big companies have huge, huge. I mean they have safety teams but also just like huge incentives to not have a safety incident happen on their watch because you're trying to like catch up to the frontier and then all of a sudden you have a safety incident that's going to be really bad for your overall brand and you have a different business to protect whether it's social networking or Google search. If all of a sudden they. The GEMMA model winds up being A thorn in someone's side for a cybersecurity reason or a bio reason, that would be really, really bad. But a foreign company that is just like hurling it over here can kind of just be like you guys deal with the consequences potentially. So I think that's what Dario's worried about. What about the overall idea of like where it feels like we're sort of replaying the Deep SEQ moment? Open source is going to reduce cost and so that's a reason to pull back on the AI trade overall. How have you processed that?
- [10:41]
B
It's almost a perfect catalog. People are worried about kimi. But when you actually read the technical paper and their blog posts, this is not a tiny efficient model. This is 2.8 trillion parameters. It's going to require a ton of compute to serve. I mean we saw it the first day they put it out that their servers got slammed. Even in the blog post they say it's best run on kind of a, a server with 64 GPUs, so big super clusters that are networked well. And that's perfectly. Runs great on Nvidia. And if you remember during the whole deep sea thing about a year or so ago, the market freaked out that Deep SEQ was so efficient that it will lead to a compute glut. But DeepSeq was an example of the reasoning model that actually it was the opposite. It created a ton of demand. And I think the same thing is going to happen with Kimi where when you have more capable models that come out, people find uses for them. And right now, just like last year when reasoning miles took off, agentic AI and agents are taking off right now. And the market is kind of like not realizing that because right now, just like last year when reasoning models were taking off, right now agentic AI is taking off and the next six, nine months are going to be bigger than anyone believes. And Sam is on the record, Stan is on the record over the weekend saying at the YC thing again, like people don't, I don't know why people don't listen to you. It's on YouTube that the next six months it's going to be much more dramatically better for AI than the last two years in terms of advanced capabilities. And I heard you say RSI before. I think it's going to be RSI people inside OpenAI and definitely anthropic. Anthropic put a blog posts on this. RSI I think is a lot closer than people think. And if RSI actually happens in the next three, six Nine months. That's going to soak up insane amount of commute. I mean we have this exponential ramp for reasoning, exponential ramp for agentic. And then if RSI actually happens, and I think it sounds like both Frontier Labs think it's going to happen very soon, that's going to soak up an unbelievable amount of compute as the AI models, you know, use more compute to self develop and improve. And I think that's one thing that you're missing, that both Anthropic and OpenAI are kind of winking that, oh, it's happening anytime I tweet something on rsi. All these Frontier AI researchers like my tweet. So I think that's good.
- [13:09]
C
What is your sort of framework around compute hoarding? Because certainly, certainly it is, it has been happening. When you look at, when you look at, you know, like going back to the Metta example, right, they're not selling compute yet. They're maybe curious about it or exploring some deals, but they have all this compute and they're betting on their own ability to create the capability that will have enough demand to justify, justify that. Do you just think it there, there's so much demand overall that it just, you know, even if there's hoarding, it just will leak out and there's so much demand overall.
- [13:51]
B
I mean, the SK Hynix executives said during their IPO run that their customers are asking five to six times more than they're able to serve and they're going to double capacity over the next five years, they said. And their customers, and I'm going to assume it sounded like Jensen, are asking for five to six times more than they're able to build. So there's overwhelming demand. You guys were at the advanced AI and the event. Lisa Su raised her CPU Agentix CPU forecast just three months ago. It was 120 billion for 2030. Three months later they raised it to 220 billion. Yeah, like she doesn't do that. She doesn't do that.
- [14:33]
A
You have that just on the.
- [14:35]
C
I've got that ready.
- [14:35]
A
I can do whatever.
- [14:36]
B
I mean like.
- [14:38]
C
Well, I just love this chart because he called it perfectly.
- [14:42]
A
He actually did. It's crazy.
- [14:44]
B
CEOs don't raise their TAMs by these multiples in a few months if they're not seeing insane demand coming in.
- [14:53]
A
Especially not public CEOs who are serious business leaders who've been running non meme stocks for decades.
- [15:00]
B
In early series, everyone's freaking out that this is the dot com bubble all over again. But what if these hyperscaler GPU cloud businesses are amazing businesses. Like Morgan Stanley says, if you do inference, it's 60 to 80% profit margins. These are amazingly profitable businesses. As long as we keep growing the next few years again, just like last year, we're on this exponential run right now over the next two quarters and the market isn't seeing that. Everyone's freaking out that, oh no, we're spending too much. And even Sam Altman podcast came out today and another podcast, Sam is out there. He said that he regretted pulling back on the compute purchases. They made a mistake by not putting the pedal to the metal because now things are taking off again. Amazon, the CEO in April, if everyone read his annual letter, Andy Gyasi wrote, he talks about how free cash flow works. We're not betting $200 billion on a hunch. We see the demand. We know it's going to be insanely profitable and free cash flow positive in the medium to long term. So that's why you're investing $200 billion now. And in a year or two we're going to see insane amounts of free cash flow. The thing that people are worried about right now, it takes time to build out these data centers and fabs and you bet now bring that in a couple years.
- [16:27]
A
Hold on. If you see free cash flow, that assumes that like the revenues have to catch up and then the capex can't grow more exponentially. And so that means you have to see some sort of plateauing. Maybe it's at the end of the chart, maybe it's this 2030 range. But there is a different world of just like continued growth forever and then we sort of run out of money.
- [16:51]
B
The pushback I have there is, that's a static view, right? If they don't grow revenue for the next three years, yes, you can't do that. But they're growing. Azure is growing 40%, Google Cloud is going 80%, Amazon's growing double digits. So if revenue is growing 40 to 80% this year, next year and the year after, that's more revenue you have, that's more operating cash flow you have to invest, right?
- [17:21]
A
Yeah.
- [17:23]
B
So that's what people are missing. And if this stuff, if the data center you're building now, you're spending all this now, generates unbelievable free cash flow in 12 to 18 months because this agentic AI is actually aging and re architecting all the workflows inside companies. And you need to do the agentic AI coding agents to make your product better. Because if you don't, if you don't iterate 100 different iterations of your product in R and D if you don't do AI, just like AT&T is doing at the Gentex, advancing AI at AMD he's talking about, they're putting 100 gen AI models into production, they're burning a trillion tokens a month and then that's growing double digits. The reason why they're doing that is because by using agentic AI, you're providing a better customer service, you have a better product R and D and you're helping your companies make better products and services. And if you don't incorporate AI into your company, Verizon, your other company, is going to incorporate AI and then disrupt you and then you lose all your revenue. So everyone's worried about roi. ROI is important, but you also need return on revenue because if you don't use AI, your rival is going to use AI to beat you in the market.
- [18:40]
A
Yeah, I think the diffusion story is still. Even though we got sort of jitters by the token maxing thing, just the actual usage of AI across companies is still pretty limited in terms of the amount of people that are using it, the time that those people are using it. Like there definitely is a San Francisco bubble of startups where everyone is using AI a lot, but if you just walk into a normal business, a lot of people are like, yeah, I got to check that out. Which is.
- [19:08]
B
Let me give you some, some context here.
- [19:10]
C
Ara Karazian, Jared Sleeper over on enterprise adoption disparity remains enormous. And he cited Ara saying usage would 100x if every company adopted AI to the degree of the most advanced companies like this. There's small group of companies that are.
- [19:29]
A
People forget in the ramp. In the ramp data, like adopting AI can mean like having a ChatGPT Pro account for someone, which is like not exactly the same as like using Codex and like coding agents and stuff. Like it's important, I think that, you know, if I have someone on my team, I want them to be able to go and do a deep research report. But that's like table stakes. The question is like, are you actually speeding up anything that's repetitive in your job? And that diffusion is just starting to take hold.
- [19:57]
B
So the total market size in terms of IT and knowledge management in corporations, it's about $6 trillion right. A year. The two main frontier AI model companies, OpenAI and Anthropic, I'm going to say I think this is roughly accurate. Are doing $120 billion combined in ARR. Yeah, you know why can't that go to 200, 300, 400 billion in the next year or two? I mean, they're growing at exponential rates when we're taking off. And if the market is $6 trillion, right, why can't they grow to 200, 300, 400 billion in the next couple of years? I mean it's like just do a little logic and rational deduction. This is definitely possible and it's happening right now and it's accelerating and people aren't, you know, they just taking, you know, these big headlines where we had this, you know, $50 billion for financial times and we find out over 30 years. It's like on the homepage.
- [20:55]
A
Yeah. Okay. I wanted to ask you about this. Nvidia revealed as tenant for $50 billion data center that will use its chips. Explain what is actually going on here.
- [21:04]
B
So the Financial Times, you know, put on their homepage today that Nvidia is going to backstop a lease for a data center in Texas, $50 billion. And I saw that, I was like, oh my gosh. Oh, that doesn't sound good.
- [21:18]
A
It literally sounds like they're buying their own chips. Like it sounds like the most bad thing you could do.
- [21:23]
B
Yes. Then they actually read the article like halfway down the article. It's like a 15 year lease and it's only $50 billion if they renew the lease after 15 years. So it's like over 30 years that they renew it. Then if you think about that, you're like, wait a minute, 50 billion divided by 30 if they renew it.
- [21:43]
A
That's okay. Yeah. Nvidia's 15 year lease commitment for the Texas site is worth basically 20 billion. And renewal options would take the total value to 50 billion over 30 years according to Hut 8.
- [21:56]
C
Okay, what do you think their, what are their plans for the site? Is this, they are going to have some like, what do you expect them.
- [22:06]
B
So my point is this is a billion, you know, whatever, a billion or $2 billion a year. Right. It's a non story, but it's a, it's a big headline, sensational headline on the homepage.
- [22:16]
A
Yeah. And also it's not like you're taking a $2 billion loss every year. It's you are the tenant and then you are also renting that out. So hopefully you're making profit.
- [22:28]
B
It's a rounding error. It's like, you know, they're doing 320 billion run rate a year now. That's going to go to 400, 500 billion next year. And we're talking about Something that might be a billion. This is not a story, but this is how people run with the sensationalized headlines and people panic and freak out.
- [22:49]
C
I think they just wanted to say the biggest number.
- [22:52]
B
That's exactly the point. And we're going to see what happens with this Wall street journal article. Both OpenAI and Nvidia are not commenting so far. We'll see.
- [23:01]
A
But take us through the rumor.
- [23:02]
B
Wait, rumor? Well, it's not rumor. It's the Wall Street Journal and other people reporting that. Yeah, Nvidia is in talks with OpenAI to backstop SoftBank up to 250 billion. We don't know the details, and I don't want to speculate and comment, but let's actually see the details before we. I think the market had a really big negative reaction yesterday to this story because everyone, I mean, Jim Cramer was telling his audience, like, sell everything at the open today because AI and data centers dot com. You know, it was insane. It's just, let's see the actual deal and the metrics and the numbers before we panic and freak out.
- [23:44]
A
Yeah, yeah, yeah, yeah. That makes sense.
- [23:47]
C
So honestly, when you say freak out and sell everything, sell your dollars, sell your house, Sell your house, sell your stocks, then I'll freak out. But until then, I feel. I feel okay.
- [24:00]
B
I mean, I just see the fundamentals. I see the CEO of AMD expanding her tam, you know, dramatically over the last three months. I see RSI under horizon. Like every AI researcher is like, oh, my God, this is going to happen. We have to get there sooner. And then I see, you know, the obvious use case of agentic AI where you have to re architect your workflows internally. Every company has to do this. So everything is taking off. You see. Like, you see when the president of Korea came to San Francisco area last week, you know, they had like a day in the Valley. Instantly. Nvidia CEO Jensen Huang, Broadcom CEO Hock Tan Dario, you know, Sam Altman are there, right? Do a little logic, deduction. Why are they there like crazy? Because they need HBM memory and they're dying to have it. So if you think about that, that means there's insane demand and HBM memory is in shortage. There's tremendous demand for it. Right?
- [25:07]
A
Talk about the Nvidia Cuda mode. It feels like a big piece of AMD's advanced AI event was. Maybe the cuda mode isn't as much of an issue anymore. In the age of agentic AI, you can have an AI agent write you the software that you need to use any chip and that creates less pricing power for Nvidia. But there's another world where you're not really like, Nvidia doesn't necessarily need a moat because everything's just growing so fast that they're still growing. But how have you interpreted the product processing of like the potential death of the CUDA moat?
- [25:45]
B
So AMD is on it. Kimmy wrote like a couple paragraphs in their blog post about how they created a GPU kernel, all that. So everyone, you know, sure gets scared or whatever. It's like, we'll see what it's like in real life. You know, this is just, you know, AMD is incentivized to say, oh, CUDA is not a problem anymore. Cuda's been a tremendous moat and I think it continues to be a moat. And the reason why is it's super reliable. All the bugs have been optimized and fixed and that comes from hitting the software millions of times and billions of times. You don't know if you use clock code or Kimi that what they figure out using their training data is going to work in the real world. They could talk about one little piece that does well, let's see how it actually works. But Nvidia's big moat is its scale, its co design of actually working through the networking, the cpu, the GPU and how everything works together. And the other big thing is their balance sheet and their ability to get supply commitments from. I think I said this before. Optical startups are upset because Nvidia secured all the supply for all the optical components. Same thing with TSMC wafer, same thing with HBM memory. So Nvidia is using their size and gorilla and be able to prepay and get components that are in shortage so they become the dominant, you know, over the next year or two you're going to see Nvidia able to add tons of revenue because they were able to lock up all the supply components. That's another thing that people don't really talk about is their supply chain and their ability to work with partners and secure, secure component inventory.
- [27:31]
A
Is there still energy FUD that we would run into an energy bottleneck before we run into a chip bottleneck.
- [27:37]
B
So Jensen said this last week on the Bloomberg interview that there are a lot of bottlenecks including data center, shell power and all those things. Components, energy, whatever. So all those things. It sounds really bad, right? And then right after that he said, I think we have, the chip industry has enough supply to double their revenue every year. Basically implying Nvidia has enough supply for energy and all that stuff. No one is pricing that in. So everyone talks about bottlenecks. Nvidia CEO just basically told you on Friday that they have enough supply chain and all the bottleneck stuff to double revenue every year. No one, you know, Nvidia's revenue estimates for next year are a lot lower than double, I'll tell you that.
- [28:25]
C
Do you think the market prices in just how much of almost every important AI company in every category Nvidia actually owns. Like it feels like every single, like we're constantly focused on who's going to raise Capex next and where is this quarter coming in. And it feels like in two or three years people will look at Nvidia's balance sheet and be like, wait, they have what, what I imagine then will be, you know, could, could end up being a trillion dollar plus of just like ownership and all these great companies. Which again just goes back to the advantages of that early scale while they're, you know, while, while all these companies are trying to compete away Nvidia's margins and all these different things, they've been able to accumulate again positions in, in all of these incredible companies. I mean we saw the SSI news yesterday, is a great example of that. But how do you look, how do you see it?
- [29:26]
B
So I think look at Jensen's history in investing in these companies and Core Weave and see how much money they made. They just bought stake in the optical companies, Lumentum and Coherent. Jensen is enabling the future because he sees this overwhelming title of demand and he needs these companies to be able to build up their supply chain and to give supplies and chips to Nvidia so they actually ramp very hard. Everyone's freaking out that this is vendor financing. What if hyperscale GPU cloud is so profitable and these companies need capital to build up that supply so they can serve the GPU cloud services over the next year or two. Maybe Jensen sees that coming like he did with all these other companies like core weavers and that's why he's investing in these companies, to be able to expand their ability to make the components the industry needs. So I think you're exactly right. In a year, two, three years, Nvidia is going to have all these stakes in these companies and it's going to look like he was a good investor because he has been in the past.
- [30:39]
A
Buy a leather jacket for like five grand and sell it for a million dollars. I don't know what else you need to see.
- [30:44]
B
I mean think, think about the secret bidder.
- [30:47]
A
Did you win that?
- [30:48]
B
No.
- [30:48]
A
I gotta get you a jacket. The real question is.
- [30:52]
B
I do. I do.
- [30:52]
A
How long until someone distills a jacket and open sources it? You can get a dupe of a Jensen jacket for two bucks. That's what I want anyway. Thank you so much for coming on the show. Jordy, you got anything else?
- [31:05]
C
This was great.
- [31:06]
A
Yeah, this was great.
- [31:06]
C
Always. Thanks for. Thanks for putting up with all of our jokes.
- [31:10]
A
Yeah.
- [31:11]
B
Hopefully this becomes the lucky charm for the markets.
- [31:14]
A
Yes, I agree.
- [31:16]
C
I. I agree. I agree.
- [31:18]
A
We'll talk.
- [31:18]
C
Bottom is in. Great to see you, Tay.
- [31:20]
A
Have a good rest.