TBPN - FULL INTERVIEW: Why I Think Nvidia Is Perfectly Positioned In The AI Race

Episode Date: March 30, 2026

This is our full interview with Tae Kim, recorded live on TBPN.We discuss why he believes fears around Nvidia and AI infrastructure are overblown despite recent market pullbacks, unpack how exploding inference demand from coding agents and enterprise adoption is driving a sustained compute shortage that Nvidia is uniquely positioned to capture after locking up key supply, and debate what this next wave of AI means for everything from GPU scarcity and chip strategy to token demand, vertical agents, and whether the current boom is the early innings of a multi-year expansion or the setup for a future compute glut.Sign up for TBPN’s daily newsletter at TBPN.comTBPN.com is made possible by:Ramp - https://Ramp.comAppLovin - https://axon.aiCognition - https://cognition.aiConsole - https://console.comCrowdStrike - https://crowdstrike.comElevenLabs - https://elevenlabs.ioFigma - https://figma.comFin - https://fin.aiGemini - https://gemini.google.comGraphite - https://graphite.comGusto - https://gusto.com/tbpnLabelbox - https://labelbox.comLambda - https://lambda.aiLinear - https://linear.appMongoDB - https://mongodb.comNYSE - https://nyse.comOkta - https://www.okta.comPhantom - https://phantom.com/cashPlaid - https://plaid.comPublic - https://public.comRailway - https://railway.comRamp - https://ramp.comRestream - https://restream.ioSentry - https://sentry.ioShopify - https://shopify.comTurbopuffer - https://turbopuffer.comVanta - https://vanta.comVibe - https://vibe.coSentry - https://sentry.ioCisco - https://www.ciscoaisummit.com/ai-virtual-summit.htmlFollow TBPN:https://TBPN.comhttps://x.com/tbpnhttps://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231https://podcasts.apple.com/us/podcast/technology-brothers/id1772360235https://www.youtube.com/@TBPNLive

Hey, Kim, how are you doing? Thank you so much for taking the time to come to chat with us. And congratulations on the incredible launch of your business. Yes. Thank you. I mean, it's been really gratifying. That first day, you never know who's going to show up. Totally. I was like maybe 15 subscribers or 20 subscribers, but like hundreds of people showed up.

It's tons of billionaires and tech founders. It's insanely gratifying. Yeah, it's great. Incredible. So is it over for NVIDIA? They're down 21% we just read since the 52-week high. Is it doom and gloom? Is it over?

No. I think I was on last December, and the stock is semis and chips that's gone up, and now they're back down to where they were in December. The chip sector is flat on the year, and Vidia's down 10%. And it reminds me a lot about a year ago. So do you guys remember, everyone's freaking out about Deep Seek, the super efficient models,

we're going to destroy AI compute. There will be a huge compute glut. And then everyone freaked out about Trump's Tower for War is the Liberation Day. And this year seems very similar to that. Almost it's like Groundhog Day. We have fears over AI CAPX. People think that it might be the peak. And then we have the Iraq War.

And one of these things is oil up here. Iran. Easy to get them mixed up. It feels like the same thing over. Yeah. But, but, someone said,

we wanted to distract. We wanted to, we wanted to show respect. Yeah, that's true. To a real podcaster. I mean, it's very similar to Iraq,

but in a hundred dollar oil, this stuff is unsustainable and oh, probably subside. Okay, so, so, because when I, when,

I like the deep seek analogy, and I feel like the market half digested the agentic coding narrative and the Satrini article, whether you thought it went too far or was too hypothetical, like clearly the markets did react and a lot of names sold off, but in a world where you believe that narrative, you would think that Invidia would be going up, but you're saying that there are other factors at play that are sort of tamping down the excitement in the market broadly? I mean, there's no that. Just like tariffs a year ago, Indivia had 30% drawdown when they're

business was actually flying the actual flight of the business. I think the same thing's happening here with the Iran war. Things will eventually subside. Oil can't be $100 forever, and Trump will probably backpedal in next few weeks ahead of the Trump. So let's recap a few of the key stories around Nvidia. We just came off of GTC and there's a lot going on at the company. I mean, it's a huge company. maybe it'd be good to start with just next generation chips, changes to strategy, what people are actually buying. Maybe that means grace CPU standalone sales or the development with the GROC partnership. What's sticking out just on the actual AI product side to you that you're most excited about? Well, inference demand is exploding, driven by the AI agents.

Sure. The genetic coding assistance. I met with Ian Buck, I met with dozens of engineers at Meadow, Google, and VDIA, and all of them are seeing crazy inference demand and AI compute shortages. So across the board, people are in crazy clamoring need for AI. And we're, I mean, yeah, you're seeing that from talking to engineering leaders at big tech companies, but we're also seeing it from vibe coders who are just on X and Twitter and talking about how they're hitting rate limits and they're subsidized.

and they have multiple plans and they actually shift around from one model provider to another just to make sure that they're getting the tokens that they need to build whatever they're building. And you see the tweets. Like people are like building bots to pick up any kind of B200 GPU that can. Oh, yeah. They're waiting like weeks and months or whatever. Basically like sneaker bots, but for NeoClauds. That's great.

Exactly. I can't believe that. And the great thing is Jensen, you know, he's very prescient. he probably saw this demand months away. He locked up all the supply agreements for memory, co-os connectors ahead of time. He saw this inference demand. And to take advantage of this coding system boom, it's almost like a gold rush. You see open AI pivoting toward it.

Anthropic obviously is thriving on it. Billions of ARR every few weeks. Jensen acquired Rock, acquired the assets of Brock and the people of Brock. And the combination of integrating GROC's technology, together with Vera Rubin, lets NVIDIA serve this tremendous wave of compute demand economically. And Ian Buck talked about it, Jensen talked about it. So, NVIDIA's positioned perfectly to thrive on this coding agent wave that we're seeing right now. On the GROC deal, Jensen did a fantastic interview with Ben Thompson

and was sort of asked the same question two years in a row about A6, the threat of A6, the idea that the GPU, the general, like general architectures can truly satisfy 100% of demand. It feels like there's a shift in Nvidia's strategy there. Do you see that? It feels like the right move, but do you see it as a shift in the philosophy of the company or the strategy? or is this just something that the gears have been turning for a long time, and this is maybe just an unveiling of a strategy that makes a lot of sense and has made a lot of sense for a while?

I think what Jensen does, he sees where the market is shifting and where the economic value is. With Melanox, he did this in 2019. Yeah, that was an Aesk. Bye. It's a networking chip, but he saw the world shifting to like these 10,000, 100,000 GPU clusters and Melanox on the need for that. In the same manner, he saw,

AI agents and the inference behind that taking off. And he said, oh, this GROC thing will work perfectly with Verra Rubin. It doesn't replace everything. It just has talked about 25% of the inference demand would be, GROC would work on that. But them working together where 75% of the inference is Verar Rubin, 25% is a GROC low latency stuff. It's like the perfect combination to take advantage of this.

And the other thing is, like, we're just in this, great liftoff of AI innovation. We've talked about anthropic mythos, the blog book that leaked out. So we're going to have this step-up function. They told Fortune there's going to be a huge step-up change. Open AI is coming out with their model soon. And then when I went to GTC, the biggest takeaway I had was this session between Jeff Dean and Bill Dalley, both chief scientists of Google and NVIDIA.

And it's online. I highly recommend people watch it. And he talked about, Jeff Dean talked about the context, have context window innovations where they could focus on the 10,000 documents that work well with your requesting query. So we're going to have this context window innovation. Both two scientists talked about stacking memory right on top of the GPU or TPU, and that's going to be a huge innovation in the coming months or years. And so you have, and then Jeff Dean talked about synthetic data for audio. and video, there's this huge runway that data is not over, and then they're going to be able to take advantage of all this data that people don't realize yet. So you have all these vectors

where AI models, you can just keep getting better and better. Yeah. How are you processing the idea that Nvidia will be investing in an open source frontier lab capability? That feels like potentially competitive with some customers. Nvidia's like never really been in that market before. But at the same time, I've been the biggest, like, supporter of open source American AI models. I loved when Meadow was doing it. I want more of it. I loved when OpenAI, open source GPTOSS. It feels really, really important, really great, but it does feel like a strategic shift. How did you process that announcement? It's not acute. I think it's like $25 billion over the next few years, which doesn't really compete with what open AI

anthropically. But these smaller models are going to be helpful for people running these smaller use cases. So GPUs, as long as they're utilized even locally or in the cloud, the video benefits. And saw the top people at Quinn left, and we don't know where they left to. Quinn is an amazing model.

It's kind of like what deep is what people thought deep it should be when it works well locally. If Quinn kind of subsides because all the people left. Wait, what's your theory on where they all went? Another Chinese lab? I asked all the engineers when I loved at GTC. No one really knew. But people are trying to say Nvidia should actually hire them.

Because the more capable open source model, Nvidia doesn't care if you're using GPD to run open source or not. They just want more AI adoption across the board. Yeah, and Nvidia has probably more levers to pull. If it turns into a negotiation with China, like we're tracking like the Manus story with Meta. And there isn't that much that Meta can give to China in exchange. If there's like, hey, like look the other way on this particular deal, like let this one flow through. We'll trade this. Meta not really doing any business there, but Nvidia, of course, is going to be selling Blackwells at some point in the near future.

And there's probably some level of pricing. you know it can be part of a larger discussion which makes a lot of sense and one thing that kind of went on under the radar jensen literally said at gtc they got license approvals on both the u.s and china side so we're going to see billions of dollars of h 200 orders okay so yeah i mean it seems like it seems like there's a path on the demand side that's very very clear you've mapped it out a few times it's a huge number um it's already massive revenues just an incredible growth but uh what is what is the what is the support supply side looking like because it feels like TSMC is not ramping CAPEX nearly fast enough over the next few years. And if we see another 10x increase in compute demand, we could be really constrained on the leading edge FAB side. So how do you think NVIDIA is going to process that? Well, NVIDIA is in the driver's seat because Jensen goes there five, six times a year and his best friends, the TSM, and speaks at their employee day. So they're going to get higher. They are getting a high allocation to waferers and co-wasson all of them.

So, InVVVILA will benefit. But I agree with you that industry-wide, like Google is dying to get more TPU wafer capacity. Sure. All the hyperscalers that have ASICs are trying to get more wafer capacity. So there is going to be an AI compute shortage in the years to come, just like you said. And Vividia just benefits because, you know, they're the biggest dog in the house, and they can prepay tens of billions of dollars

to get the allocations they need. Yeah. I mean, maybe there's some offtake in ASICs that can potentially be fabbed somewhere else at some point. I know that a lot of the ASIC companies wind up fabbing at TSMC, but it feels like if you're already doing some sort of re-architecture, maybe there's a way that you can squeeze something a little bit out of, you know, an Intel deal or something else.

I'm not exactly sure. It's Samsung and Intel. Samsung and Intel, yeah. Fab's that could possibly do it. Yeah. That's the bookcase on Intel. Yes, yeah, is that at some point the labs and Google, like, we're across TPU, extra GPU capacity, Nvidia, the new R, like, there's just so many buyers of lab capacity

of fab capacity now that you could imagine everyone coming to the table, potentially in Washington, D.C. or Mar-a-Lago, since the U.S. government owns a slice now and everyone's saying, okay, let's hold hands and jump across this and say that if the supply comes online, we will buy it at this price because we have really, really solid use cases that will justify the investment for us and for Intel. So that would be a really, really good case. But again, even if the money is there, how long does it take to get to good production numbers? I mean, I suspect like Apple and Vida are considering either Intel Samsung for their lower end stuff.

Whether it be like a mid-range iPhone or Nvidia side, definitely their consumer gaming GPUs. They may go back to Samsung and maybe even Intel. Yeah, I have one more, but go for it. I wanted to know how you're processing the ARM CPU announcement. It's an interesting dynamic because they're sort of frenemies with Nvidia now. they're competing in many ways to break the X-86 monopoly because they both are selling ARM CPUs, but then they're also competing. And so I'm wondering how you think that plays out what that means for Nvidia and just the rest of the semiconductor supply chain.

I think ARM is their CPU opportunities, a longer term, even they said 2030, 2031. It's a longer-term opportunity. I don't really expect the major hyperscalers like Amazon. to switch to ARMS product offering, they have their own. And same with the same with NVIDIA. They have their own ARM CPU that they're going to incorporate and sell. So it's not that big of a, I don't think Amazon or NVIDIA really worry that arm is going to take any big share. It's probably going to be on the margin for companies that can't develop their own

ARM CPU, the more of the mid-tier, hyper-scalers or enterprises that use these things. But I think the arm thing is very important because it kind of confirms what the biggest underlying thing that that's not really consensus yet is this massive CPU shortage that we're seeing. Just over the last few months, we have Dell, AMD, Intel, CFO talked about, they're talking about three to five-year locked in supply contracts and hyperscalers. So this is a major trend that's going to go over the next few years. And the reason why is AI agents need more CPUs. The RMCEO talked about four times more CPU cores versus last year's kind of AI infrastructure model. So we're going to see this massive demand for CPUs that people aren't really understanding it. Because AI agents, the whole thing, requires orchestration, tool calls, database queries, web searches,

and that's all handled by the CPU. Give me your bull and bear case for tariffab. Terrafab, I'm not that optimistic. I mean, it's so hard to build that. Do your absolute best to give me the bowl case. Because TSM is so short that, you know, Elon needs to find. But even then, like, how are they going to buy, like, semi-cap equipment from ESML and AMAT? Like, there's just no capacity there, so I'm not optimistic on that.

And this is stuff that takes decades. Chip fabs is almost like cooking, and it's not like something you could just follow a manual. It's like it's almost like cooking where it takes a lot of trial and error accumulate over decades, TSMC and even Intel. So it's not something you could just jump right in and do. Yeah, unless they partner with the long. Yeah, it's someone goes back to the XAI debate about, like, do they need AI researchers or should everyone be an AI engineer? Like, are we in a research period or a, you know, the Ilius Sutskever age of research versus the Elon Musk age of engineering? Where are we in semiconductor production?

It feels very engineering, like an engineering process. But what we've seen from ASML is that it and TSM is that it does feel like there's a little bit of research and artistry to it and the cooking analogy holds. Yeah, I've been doing a lot of research into space and it's a lot of trial and error and almost like cooking a recipe. And it also feels like in, at least with XAI, if all the researchers are in San Francisco, you can sort of just like walk across to the coffee shop, poach someone. But if the best semiconductor engineers or technicians are in Taiwan and they see it as a national urgency to bring stability to the country both economically and geopolitically, then you have a very different calculation. It's like, oh, yeah, I could make five times as much if I left my home country to be abandoned. That's a very different calculation. and everything that I've heard about the culture at TSM is that the folks who work there are extremely dedicated beyond the economics.

They are true missionaries, not necessarily mercenaries. And so it does feel like it's even harder to do like a talent raid in the leading edge Fab world than even the AI world, which is extremely competitive. And there are still tons of missionaries. But FAB is, I guess another question I have is would you expect, would you expect, would you expect, XAI slash SpaceX at any point to get to basically just open up a shop as like a neocloud. Because the thing that was like probably the one of the least compelling aspects of the TerraFab pitch was him just saying we need all of this compute. We need to do this because we we're going to be so chip constrained, we're going to be so supply constrained, but there was no

explanation of where the demand was going to come from. Is it going to come from? Training Tesla models, Optimus, or Croc or Twitter. Yeah, it was just very unclear. There's a lot. But there's even the question right now is, should XAI be kind of renting GPUs? I don't know. Renting out GPUs. Because the biggest win has been Colossus too.

Yeah, Colossus too, which was built very fast. I think Elon's pitch with the SpaceX IPO and we'll see it in the coming months is the AI compute. It's going to be so, there's going to be so much demand over the next five, ten years that you're going to have to use these SpaceX satellites that have GPUs in them to serve that. And maybe, I mean, even though Tesla's been vertically integrated to the point of being a consumer product, SpaceX has not. It's been a railroad. And there is a world where you fab the chips, you put them on satellites, on Starlink's in space, and then you let other companies do whatever they want with those GPS.

I think what Elon did with Starlink. That's a telecom infrastructure play, and this will be an AI computer. Yeah, yeah, yeah. That fits that model. There's a world there. I'm not going to bet against Elon. It might just take long. Yeah, yeah.

What about what's going on with helium? What are you tracking there? There's chatter about helium shortages, potentially. Jensen has talked about this. This is the risk, but there is probably like six months, six to nine months of inventory in the channel. Bernstein has talked about it's not a risk in short term so so if this thing if this iran stuff lasts yeah you know two three four five months then becomes a problem okay but if it you know gets solved or straight or moves opens up with the toll or whatever uh final negotiation

they come up with over the next few weeks i don't think it's got a problem yeah i do think that like like most of these uh materials there are uh extra deposits they're just not economical to mine i don't think that all the helium exists in the Middle East. It's similar to the rare thing, just like you said. Yeah, where, you know, supply-constrained scenario, it becomes more economical to mine American helium. Let me put this way. If helium becomes the issue, we're going to have bigger problems in our hands.

Okay. I mean, there's going to be world starvation. Let's hope not. Let's hope not. That'll be the least of our problems if healing becomes the problem. Take me through depreciation gate. How did you process that and where do we stand now with the fear that GPU, the, you? will depreciate precipitously, and H-100s will be worthless in six to 12 months.

It's totally not a problem right now. Like, Corrieve has talked about these things are lasting five to six years, and they're getting like almost 90, 95% of the pricing. So it could potentially be a problem if the whole, if this is a bubble, I don't think it's a bubble. But if this is a bubble two, three years from now and there's a compute glut, then the stocks don't go down because there's a compute glut. But as of now, it's the opposite.

All the GPU rental prices, even for stuff that's six years old, is still being sold out. And the AI compute demand outpacing supply is so large that this is not an issue right now. Do you have any theories on where the next step change in token demand could come from? Because right now we're seeing it in code gen, and there's a lot of optimism around these types of workflows being applied to other forms of work. we were talking about this on Friday, like even if AI can just one-shot beautiful financial models, it won't necessarily even make a real dent in token demand, at least compared to code gen, because no company needs to just constantly be generating models at the rate that, let's say, Gary Tan generates code. And so I'm like kind of been trying to wrap my head around where could these

incremental use cases. I actually think code gen is still just early innings. Yeah, and I don't disagree with that. 10, 20 agents and they're kind of overseeing them. But then we have this other stuff where these models, the mythos and open AI, they're just going to get better where you could automate all these work process flows. Companies are going to use them for every single vertical customer service research, simulating chip design where they can verify drug discovery where they verify drug molecules can do.

So we're just getting started at this stuff. So you're going to see vertical AI agents on every single category. And I think Logan's coming on. He wrote this great post on X that he says the AI agent wave is going to kind of attack this $6 trillion knowledge economy, right? It's not just about programming anymore. They're coming for us. Yes. I don't think, say, I'm actually. They're attacking the key context economy and the TBPN economy. No, I think it's like a calculator, a spreadsheet.

You know, 30, 40, 50 years ago, we had like, you know, 50 accountants doing the spreadsheet manually, right? And now after a spreadsheet came, it didn't get rid of all of knowledge work. It just enabled people to think at a higher level and get more done. And I'm very optimistic about that. I mean, one way that you 10x token demand around a financial model without 10xing the number of financial models that you're building is having the agent go and collect 10 times as much data. And so there's a lot of situations where, I mean, you look at hedge funds that want to understand the price of Walmart stock. there are hedge funds that will task satellites to take pictures of Walmart parking lots, estimate the number of people on a day-by-day basis that are going into the Walmart to shop,

and then using that as a proxy to project revenue and then flow that through to cash flow, and then flow that through to the DCF and the actual evaluation of the company. And if you think about all the different financial models and all the different businesses where you could go and say, well, for this company, I need to go to every single, local, like, I want to know the price of Squarespace. Let me go to every single website that's powered by Squarespace and estimate the revenue that they're bringing in and their willingness to pay for their hosting service, something like that. And all of a sudden, like, it's just one spreadsheet, it's just one number at the end of the day, but it's like a thousand times more work went into it. Let me give you this great example. Every year I do this, the same store sales for these fast casual companies.

So like Chipotle, Kaaba, and I put out this tweet, it goes viral. A year ago, when I do it, I would have to manually go to every IR website for these six fast casual restaurants. It would take me like an hour or two. I would try to use a chatbot. They would get it wrong. I did it like a few weeks ago, and all the chatbots got perfect. So it just saved me two, three hours of tedious manual labor. So that's only going to get better and better.

Yeah, it's only going to take you one. Like, like, this year is the year that you, you do it with multiple chatbots and you fact-check it yourself. And then forever, it's going to be just one prompt. And it got it right. And it got it right. And it got it right. But now, in one, two minutes, I put, give me the same sort of sales for these six restaurants.

Yeah. I put in Gemini, put in chat GPT, and just to make sure they're right and they're right. So that, all the tedious labor, all the manual labor, all the data entry that, you know, all of us are used to, that stuff is going away. And we could think higher level. So I could look at the same store sales and say, oh, the economy is at risk and whatever. But all the grunt work, all the tedious work is going to be taken care of by these AI agents. I agree completely.

I agree completely. We got a lot more sound effects since the last time you joined. Last question for me, what's your outlook on meta? it feels like the broader market right now has zero faith in meta to actually put all their AI investments to use. I have this history with meta is that every time it starts falling apart, I say it looks cheap and then it goes down another 30%. But nothing has changed. No one's going to replace meta digital ad position. I mean, I would even say in the AI world, they're even better position because Google might lose

digital ads share to chop hots, their search positions are in the future. So, like, no one's going to replace Instagram, no one's going to place Facebook. Billions of people are still going to use those social media apps. And, you know, it's every six months

to 12 months, everyone goes to this bare meta cycle, but their pure competitive position really hasn't changed. And you saw what happened to SOAR, right? Like, you know, everyone's all excited about SORA, and that got totally. Yeah. Yeah. And There's just this world where even if the AI spending is like a side quest, it's like really

they just pulled forward like three or four years of CAPEX and they will use that for their other products. It's probably even less like wasteful than reality lab spend, which might take even longer to realize that the cash flows from. Like they can recoup, okay, we built this massive data center, we did this training run, we didn't get to the frontier, we're not getting a lot of like gen AI usage. But we can apply it to our ads platform and tools and Reels recommendations and a million other things just in years 2028, 2029. And yeah, we're a little bit ahead of schedule.

Our core ad engine monetization. 100%. Yeah, the gem model. Reality Labs, he made a waste of $70 to $80 billion. He might waste $100 billion of dollars on these frontier AI models. But they're core ad engine, core business, that money-making engine has been. it's not going to be affected by this yeah well thank you so much for taking the time to come hang out always a great time tay uh go subscribe to key context on substack follow take him on social media

first adopter join the many beaners that we're the first adopters yes yes you'll be in good company and thank you so much we'll talk to you soon have a great week great to see you bye