Gerstner notes Nvidia revised Q2 datacenter guidance from $7 billion to $11 billion, defying negative expectations.
“People thought data center revenues this year were gonna be negative, and they just revised their guide from 7,000,000,000 in q two to to 11,000,000,000 in q two.”
Gerstner suggests selling long-dated Nvidia calls for downside protection after stock's parabolic rise to $400.
“take something like Nvidia, if I'm playing at home or I'm a, you know, a professional investor, I may say, oh, I'm gonna go sell some long dated calls to buy a little protection to the downside.”
Gerstner says AI stocks including Nvidia are now at or within 10% of his year-end price targets.
“a lot of the AI related stocks are now at or within 10% of our end of year price target. And when you when you see that, take something like Nvidia,”
Gerstner argues NVIDIA at $400 from $100 looks expensive but trades only 20x next year's earnings.
“But the fact of the matter is on consensus forecast for next year, it's trading just over $20 or 20 times earnings.”
Gerstner notes consensus forecast predicted negative 6% NVIDIA data center growth and hard landing in early 2024.
“if we look at the start of the year, the consensus forecast for NVIDIA was that data center growth would be negative 6% this year.”
Gerstner argues NVIDIA at $400 trades at 20x earnings, lower multiple than many cyclical stocks.
“But the fact of the matter is on consensus forecast for next year, it's trading just over $20 or 20 times earnings. It's trading at a lower multiple than many cyclicals in the public market.”
Gerstner says professional analysts predicted NVIDIA data center revenue would decline 6 percent, highlighting how wrong forecasts were.
“The consensus estimate for NVIDIA this year was that data center growth revenue growth was gonna be negative 6%. Right? That's the pros. They got it that wrong.”
Gerstner says MANG (Microsoft, Amazon, Nvidia, Google) went from near-zero VC investing to $25 billion last year.
“we have this explosion in venture capital investing coming out of four companies, right? He called them MANG. Microsoft, Amazon, know, Nvidia and Google.”
Gerstner argues MANG participation is distorting market prices compared to arm's length transactions with financial investors.
“I do think that it is a really important thing that you're pointing out, which is at a very minimum, I think we can say that the participation of MANG, Microsoft, Amazon, Nvidia, and Google, is distorting the price in the market in a way that wouldn't occur if it was all arm's length transaction with financial investors.”
Gerstner says MANG (Microsoft, Amazon, Nvidia, Google) went from zero to $25 billion in VC investing in six years.
“He called them MANG. Microsoft, Amazon, know, Nvidia and Google. And so as you can see on this chart, we go from almost no venture capital investing, you know, out of these folks six or seven years ago to all of a sudden this $25,000,000,000, last year in VC investing.”
Gerstner cites Zuckerberg announcing Meta will have 600,000 H100 GPUs by year end.
“You saw that, tweet or thread out of Zuckerberg this week, where he said by the end of the year, they're gonna have the equivalent or this year, 600,000 h 100 GPUs,”
Gerstner argues MANG participation is distorting AI startup valuations beyond what arm's length financial investors would pay.
“I think we can say that the participation of MANG, Microsoft, Amazon, Nvidia, and Google, is distorting the price in the market in a way that wouldn't occur if it was all arm's length transaction with financial investors.”
Gerstner says NVIDIA holds 90% plus market share and trades at historical average multiples.
“So if you wanna express that bet, right, which is AI leadership at 25 to 30 times earnings, which is consistent with historical averages for NVIDIA.”
Gerstner recalls NVIDIA data center revenue forecasts shifted from -6% to +25% last year.
“Think about NVIDIA at the start of last year. Data center revenues were expected to shrink by 6%. Right?”
Gerstner notes NVIDIA traded at 20x earnings last year, its lowest multiple ever.
“So NVIDIA ended last year at 20 times earnings. Its lowest multiple of earnings it's ever traded at, despite the fact that it's the the the purest play AI name in in the space.”
Gerstner says Altimeter's NVIDIA numbers remain well above Street consensus for this year.
“Our numbers are still well above the street for this year. I think there's a lot of doubt. You know, the the common, discussion at the end of last year”
Gerstner highlights NVIDIA data center grew over 25% versus consensus forecast of minus 6%.
“Data center revenues were expected to shrink by 6%. Right? We thought we we had huge variant perception by being up 16%, and it ended up over 25%.”
Gerstner says Altimeter's best AI bets over the past two years were NVIDIA, Microsoft, and Snowflake.
“the best bets on AI over the course of the last eighteen months or two years, we were fortunate to be in, were NVIDIA and Microsoft, Snowflake.”
Gerstner says NVIDIA traded at 20x earnings, its lowest multiple ever, and is now up 25-30 percent.
“It was overvalued despite the fact it was trading at 20 times earnings, its lowest multiple in history. Now it's up 25 or 30% after opening, the year down.”
Gerstner notes critics compared AI training spending to 2001 dark fiber, claiming pullforward had occurred.
“Everybody said at the last end of last year, we had pulled forward all of the training. You know, this was dark fiber from Internet in 2001.”
Gerstner says Microsoft, Amazon, and Meta all signaled massive inference and infrastructure investments driving NVIDIA higher.
“It's up because Amazon told us the same thing. It's up because Susan Lee from Meta just told us yesterday that they're going to make huge future investments in infrastructure, read NVIDIA,”
Gerstner claims Meta is the largest AI profit beneficiary in public markets outside NVIDIA.
“They are the single largest beneficiary of AI from a profit perspective in the public markets today outside of NVIDIA.”
Gerstner cites Microsoft, Amazon, and Meta all confirming massive AI inference and future infrastructure investments in NVIDIA.
“It's up because Susan Lee from Meta just told us yesterday that they're going to make huge future investments in infrastructure, read NVIDIA, in order to support all of these initiatives.”
Gerstner declares Meta the single largest AI profit beneficiary in public markets outside NVIDIA.
“They are the single largest beneficiary of AI from a profit perspective in the public markets today outside of NVIDIA. And so I really think it's about that.”
Gerstner notes consensus forecasts assume Nvidia's share of global compute buildout drops from 55% today to 26% by 2028.
“The line running through the center that starts at 55% and goes down to 26%. That is Nvidia's share of that global compute build out based on current consensus numbers for Nvidia.”
Gerstner says dozens of sovereign nations prioritize AI buildout as top-three national priority, with GCC spending rivaling hyperscalers.
“And I think the size you're talking about for some of these GCC countries is gonna be competitive with the hyperscalers itself.”
Gerstner quotes Jensen predicting data center infrastructure will double from $1T to $2T in four to five years.
“And over the course of the next four to five years, we'll have 2,000,000,000,000 of data centers powering software around the world and it will all be accelerated compute.”
Gerstner argues consensus Nvidia forecast assumes market share drops from 55% to 26% by 2028.
“Okay, so the consensus forecast that has the stock at $700 a share assumes, if you believe this TAM to be accurate, assumes that their share will go from 55% today to 26% in 2028.”
Gerstner uses employee analogy to explain why B100 chips command premium pricing despite higher cost through 10x performance improvement.
“If you had an employee bill and you were paying them a $100,000 and I said, Hey, you ought to hire this other guy.”
Gerstner says NVIDIA EPS was forecast at $5.70 but ended up at $25, far exceeding expectations.
“The EPS at the beginning of last year, the earnings per share was expected to be $5.70, and now it looks like it's gonna be $25.”
Gerstner notes NVIDIA consensus data center revenue estimate was $22B but actual came in at $96B.
“at the start of last year, the consensus estimate of the smartest people covering NVIDIA day to day was that the data center revenue was going to be 22,000,000,000 for the year.”
Gerstner says Microsoft and NVIDIA remain relatively safe investments for AI exposure amid uncertainty.
“I think that if you're an investor, owning some of the companies that you think you're really confident are going to continue to compound and benefit from AI, the Microsofts of the world, the Nvidias of the world, seems to me like a relatively safe place.”
Gerstner says NVIDIA demand continues as customers must order chips five years ahead for infrastructure.
“Nothing is slowing down, Scott, because they have to place orders five years in advance for these products. They have to go find power.”
Gerstner's Nvidia estimate is closer to $5 per share, ahead of consensus since fall 2022.
“we're we're closer to $5 a share. We've been ahead of the consensus estimate since the fall of twenty two.”
Gerstner says AI customers must place orders five years in advance and secure power and data centers.
“they have to place orders five years in advance for these products. They have to go find power. They have to find data centers”
Gerstner notes buy-side estimates reach $5 per share for NVIDIA, implying $150 price target at 30x.
“There are numbers on the buy side that are as high as $5 a share. So if you if you go to $5 and you place a 30 times earnings multiple on that,”
Gerstner states consensus Nvidia estimate for next year is around $3.50 per share.
“the consensus estimate for next year for Nvidia, I think is around $3.50 per share.”
Gerstner proposes dedicating individual nuclear reactors at Diablo to major tech companies for their data centers.
“I could imagine if you had four more reactors sitting here, right, if you could land them at the right price, you could have one reactor for Meta, one for Amazon, one for Microsoft, one for Nvidia, you could have the data center sitting right next to them.”
Gerstner says Altimeter has returned to average exposure levels, expects NVIDIA supply chain to remain undersupplied.
“We have average levels of exposure. I think, for example, we think the entire in NVIDIA and AI infrastructure supply chain is gonna continue to be undersupplied.”
Gerstner frames NVIDIA debate as 6 million GPUs versus bearish 4.5 million estimate for next year.
“We're kind of at 6,000,000 GPUs for next year. The bearish people are at like 4,500,000. The numbers will ultimately tell.”
Gerstner says Jensen confirmed GPU clusters are already at 200-300k scale and will reach 500k to 1 million
“I said, are we already at the phase of two and three hundred thousand cluster scale? And he said, yes. And then I said, and will we go to 500,000 a million?”
Gerstner says NVIDIA generates $4M revenue and $2M profit per employee, unprecedented efficiency.
“You know NVIDIA is in a league of its own really, know, at about 4,000,000 of revenue per employee, about 2,000,000 of profits or free cash flow per employee.”
Gerstner says CUDA library now has over 300 industry-specific acceleration algorithms across diverse fields
“he talked about, you know, the the the CUDA library now has over 300 industry specific acceleration algorithms. Yep. Right? Where they deeply learn the industry.”
Gerstner reports Jensen predicts inference will scale 100x to billion-x with 40% of NVIDIA revenue already from inference
“he said as a consequence of that, inference is going to a 100 x, thousand x, a million x, maybe even a billion x.”
Gerstner reports CUDA library contains over 300 industry-specific acceleration algorithms across synthetic biology, image generation, and autonomous driving.
“the CUDA library now has over 300 industry specific acceleration algorithms. Yep. Right? Where they deeply learn the industry. Right?”
Gerstner cites 3 million CUDA developers globally as evidence of NVIDIA's ecosystem lock-in.
“I just asked Chet GPT how many CUDA developers are today just to be on top of 3,000,000 CUDA developers.”
Gerstner says Jensen claims NVIDIA can scale business 2-3x while increasing headcount only 20-25% using AI agents
“This idea that Jensen can scale the business two or three times with, you know, increasing the headcount by, you know, 20 or 25%. Right?”
Jensen believes NVIDIA can triple revenue adding only 25% more humans using 100,000 autonomous agents for software and security.
“he thinks they can three X, you know, the top line of the business while only adding 25% more humans because they can have a 100,000 autonomous agents doing things like building the software, doing the security, and that he becomes really a prompt agent,”
Gerstner says NVIDIA will do 125 billion revenue this year versus prior billion dollar ceiling.
“Give or take you'll do a 125,000,000,000 in revenue this year. You know there was at one point somebody told you the company would never be worth more than a billion.”
Gerstner notes NVIDIA's 2023 revenue was $60B versus analyst forecasts of $26B in January 2023.
“The forecast for Nvidia at that dinner in January 2023 was that you would do 26,000,000,000 of revenue for the year 2023. You did 60,000,000,000, right?”
Jensen confirmed AI clusters are already at 200,000-300,000 scale and will reach 500,000 to 1 million GPUs.
“are we already at the phase of two and three hundred thousand cluster scale? And he said, yes. And then I said, and will we go to 500,000 a million?”
Gerstner notes NVIDIA's Hopper demand remains exceptional and will continue into next year, defying expectations it would end.
“We may have people thought hopper demand would be over by now, frankly, and he said it's going to continue well into next year.”
Gerstner says Jensen confirmed a trillion dollars of data center CPU replacement workloads over four years beyond AI training.
“he said, but we're also going to have a trillion dollars of CPU replacement, of data center replacement workloads over the course of the next four years.”
Gerstner argues NVIDIA at 30 PE versus Cisco's 120 PE means comparison to 2000 bubble is uninformed.
“So you would have to think that there would be 70% PE compression from here or that their revenue was going to fall by 70% or that their earnings were going to fall by 70%.”
Gerstner contrasts buying NVIDIA in fall 2022 based purely on tech fundamentals versus today's layered policy risks.
“What do I do as an investor? You know, what did I do in the fall of twenty two that led me into NVIDIA in the first place?”
Gerstner says 3.7 million kids born yearly would get private accounts, with Uber, Dell, Oracle, and Nvidia contributing.
“And we have companies like Uber and Dell and many, many others, Oracle, Nvidia, etcetera, all say they'll contribute to the accounts of the kids of their employees.”
Gerstner estimates NVIDIA lost track to $50 billion China business from chip export ban.
“I think if you forecast out two or three years, they were on track to be a $50,000,000,000 business, I think in China.”
Gerstner says the UAE-US AI campus announced is five gigawatts, equivalent to 2.5 million GPUs.
“So in in Abu Dhabi, they announced a five gigawatt US AI you know, it's a UAE, US AI campus. It's an incredible architectural campus.”
Gerstner says UAE announced five gigawatt AI campus with NVIDIA, OpenAI, Oracle, totaling 2.5 million GPUs.
“So in in Abu Dhabi, they announced a five gigawatt US AI you know, it's a UAE, US AI campus. It's an incredible architectural campus. It's in collaboration with NVIDIA and OpenAI and Oracle.”
Gerstner argues NVIDIA's $40 billion China business keeps them on CUDA and export bans risk forcing Taiwan conflict.
“It's $40,000,000,000 business NVIDIA in China to keep them on the CUDA ecosystem rather than allowing them to have a monopoly on the Huawei ecosystem.”
Gerstner proposes trading rare earth access for permission to export deprecated NVIDIA B30 chips to China.
“I would trade rare earths for AI chips, deprecated b thirties, which NVIDIA is now producing. Why would I do that? Because The U. S.”
Gerstner explains B30 chip removed high-bandwidth memory to prevent training use, unlike H20.
“Number one, this, you know, this b 30 is this deprecated chip. So one of the concerns we had about the h 20 was that there was too too much high bandwidth memory on it.”
Gerstner says NVIDIA had 80% China market share with developers in CUDA ecosystem, generating billions in US taxes.
“NVIDIA has you know, it went from 80% market share in China where all the developers, second largest developer market in the world, were were developing in CUDA.”
Gerstner says NVIDIA raised total compute buildout estimate to $3-4 trillion from $2 trillion.
“Last night on the call, they said 3 to 4,000,000,000,000 of total compute. He told us that inference was gonna billion x. Right?”
Gerstner calculates 50% growth would bring NVIDIA to $300 billion datacenter revenue, about $8 per share.
“So the consensus for next year is 250,000,000,000 of data center revenue. If they grow up 50%, that's gonna be closer to 300,000,000,000 or closer to $8 a share.”
Gerstner notes Jensen raised compute buildout forecast from $2 trillion to $3-4 trillion through decade end.
“Jensen said, you know, when he was on our pod last year, he said, we think the build out between now and the end of the decade's $2,000,000,000,000 of total compute.”
Gerstner believes there's over 50% probability NVIDIA can sell Blackwell chips in China, a $50 billion market.
“China is a $50,000,000,000 market for NVIDIA unto itself. So I believe that the probability they're gonna be able to sell chips China is north of 50%.”
Gerstner cites NVIDIA forecast of $200B revenue this year growing to $350B in five years, equating to specific gigawatts.
“This is the NVIDIA sell side forecast. Okay? Forecast this year is for about 200,000,000,000 in revenues, growing to about 350,000,000,000 in revenues over the next five years.”
Gerstner warns red flags arise when chip makers fund single customers who then buy their chips with that capital.
“So there's no other potential customers, and the buyer would not have had the ability to buy it but for that capital. That to me raises big red flags.”
Gerstner says CoreWeave and NVIDIA transactions are disclosed in public companies, allowing scrutiny of demand.
“These are public companies, both CoreWeave and NVIDIA. It is a disclosed transaction. It's not like this stuff's occurring in the dark at night.”
Gerstner notes NVIDIA dropped to $92 on tariffs but has recovered to $180.
“Remember the deep sea moment? Stock stock was down 25%. And then on the tariff moment, the stock got down to $92 a share. It's at a 180 today.”
Gerstner says NVIDIA is cheaper now than at $200 despite being up 35% this year.
“does it make sense that NVIDIA is up 35% given that their top line has grown way faster than 50? The answer is yes. It's cheaper today than when the stock was $200 a share.”
Gerstner says Lisa Su is betting 10% of AMD to OpenAI on the MI450 chip competing with NVIDIA.
“I'm gonna give 10% of my company to OpenAI, and I'm gonna bet that the m I four fifty is going to work, and it's gonna be competitive with NVIDIA.”
Gerstner breaks down OpenAI's compute commitments: $500 million to Nvidia, $300 million to AMD and Oracle, $250 billion to Azure.
“with, you know, big commitments, 500,000,000 to Nvidia, 300,000,000 to AMD and Oracle, $250,000,000,000 to Azure.”
Gerstner views recent selloff as healthy, notes NVIDIA now trades below 20x his 2027 estimates.
“I think it's healthy. We're taking some of the air out of the bubble. There's a wall of worry that stands in front of us. NVIDIA now is trading below 20 times our 27 numbers.”
Gerstner warns that if AI revenues don't materialize, the public market AI trade will have a problem beyond NVIDIA.
“The market the public market does not have a way to play pure AI outside of NVIDIA. It is going to be watching.”
Gerstner says AI added 100 basis points to GDP this year despite NVIDIA's 225% drawdowns.
“It added a 100 basis points to GDP this year. But remember, this year, we had 225% drawdowns in Nvidia.”
Gerstner argues NVIDIA at 23-24x next year's earnings and 18x 2027 earnings isn't bubble territory.
“I think it's trading at 23, 24 times fully taxed earnings on next year's numbers, 18 times on 27 numbers. That is not the stuff that bubbles are made of.”
Gerstner notes NVIDIA added almost $200 billion of revenue in the last three years.
“You know, you've seen NVIDIA add almost $200,000,000,000 of revenue in the last three years. Yeah. Truly extraordinary.”
Gerstner argues NVIDIA at 23-24x forward earnings and Mag Seven at 25-30x are not bubble valuations.
“That is not the stuff that bubbles are made of. Right? I think the rest of the mag seven all trades somewhere between twenty five and thirty times, maybe met is at 21 times earnings.”
Gerstner reveals Altimeter invested in NVIDIA in December 2022, up 10x as revenue grew from $30B to over $200B.
“The stock's up over ten ten times. 10 x over that period of time as the revenue went from roughly $30,000,000,000 a year to over $200,000,000,000 a year.”
Gerstner says NVIDIA indicated a $100 billion run rate expected by end of next year.
“And they just told us that we should expect a run rate by the end of next year of a $100,000,000,000.”
Gerstner says $250B NVIDIA spend implies $500B total capex requiring $1 trillion in AI revenue to justify.
“Assuming that is just 50% of the CapEx, you're spending about 500,000,000,000 on CapEx, and then you've gotta earn about a trillion dollars of AI revenue for all of this CapEx to be worth it.”
Gerstner says $250 billion on NVIDIA implies $500 billion total AI CapEx spending.
“one of the things that keeps investors like me up in the nights is a 250,000,000,000 being spent on NVIDIA on on the semi side of things.”
Gerstner says CoreWeave stands alone among Neo Clouds due to its performance and strategic importance to NVIDIA's Rubin deployment.
“We think CoreWeave stands alone, in terms of its performance, the software that is built on top of the cloud, its execution capability, its strategic importance to NVIDIA in terms of deploying Rubin, etcetera.”
Gerstner notes NVIDIA consensus is 65% earnings growth in 2025 and 30% in 2027 at 25x multiple.
“The consensus estimate this year, I think, is that they're gonna grow earnings about 65%, maybe 30% in 2027. You said it's an earnings driven market, so they don't need to expand multiple.”
Gerstner predicts Google's TPU will not match NVIDIA Rubin's token efficiency despite advantages.
“First, Google is a massive consumer of NVIDIA GPUs, Right? Not only for its own workloads, but also the workloads, you know, in Google Cloud.”
Gerstner says AI capex jumped from $150B in 2023 to over $500B this year in committed purchase orders.
“In 2023, these companies spent $150,000,000,000 on capex building out data centers. This year, over 500,000,000,000. That's not speculative. That is purchase orders. Those are buildings.”
Gerstner cites 5x inference and 3.5x training performance improvements on NVIDIA Rubin chips.
“He just improved his inference performance by five x, not even including Grok, which I think will give him, you know, another huge boost.”
Gerstner says the world will be supply constrained on inference compute indefinitely, citing NVIDIA's Grok acquisition.
“The world is going to be supply constrained on inference compute as far as the eye can see. It was part of the inspiration. We were also investors in Grok.”
Gerstner says NVIDIA delivers Blackwell performance at one-fifth the cost with annual improvements exceeding Moore's law.
“It means you can get the exact same performance you get out of Blackwell for one fifth the cost. Right? That's better than Moore's law. He's doing that every twelve months.”
Gerstner says the big five will spend $650-700 billion on AI and are still token constrained with unfulfilled demand.
“650,000,000,000 to 700,000,000,000 of spend out of the big five companies in The US, and they say they're still token constrained.”
Gerstner says every child will have an app showing ownership of shares in NVIDIA, Walmart, and Microsoft.
“Every child is gonna have on their phone an app. They're gonna see. They own a little bit of NVIDIA, a little bit of Walmart, a little bit of Microsoft.”
Gerstner says he wants his personal and fund net worth levered to AI, with NVIDIA as largest public position.
“I want my personal net worth. I want my funds net worth levered against AI because all human progress is gonna be derived from machines helping humans think and augment human thinking.”
Gerstner says NVIDIA is one of the most efficient on token per watt per dollar basis.
“Token per watt per dollar. NVIDIA is one of the most efficient in the world.”
Gerstner says 80% of Altimeter's capital is in memory, logic, and compute companies like Nvidia, SK Hynix, and CoreWeave.
“80% of our capital has been in memory and logic and compute, you know, companies like Nvidia, companies like SK Hynix, companies like CoreWeave, etcetera. And so that's consumed a lot of capital.”
Gerstner asserts Nvidia is terribly under-owned and undervalued, and Altimeter is happy to hold it.
“I think NVIDIA is terribly, under owned. I think it's terribly, undervalued today, and so we're happy to sit in that and to own it.”
Gerstner notes Nvidia at $195 trades lower than six months ago at 13-14 times fully taxed earnings.
“At a $195, Nvidia is trading lower than it was six months ago. So it's hard to say at 13 or 14 times fully taxed earnings”
Gerstner mentions ChatGPT 5.5 trained on Blackwell chips and Vera Rubin rolling out later this year.
“On new Blackwell chips. We got Vera Rubin rolling out later this year. Notwithstanding all of the noise in the market,”
Gerstner cites a trillion dollars in Nvidia orders over the next six to eight quarters.
“But I think if you just look at the numbers, a trillion dollars over the course of the next, you know, six to eight quarters, I think speaks for itself.”
Gerstner notes Nvidia at $195 trades lower than six months ago at 13-14x earnings.
“At a $195, Nvidia is trading lower than it was six months ago. So it's hard to say at 13 or 14 times”
Gerstner predicts NVIDIA will be the first $10 trillion company and still believes this in May 2026.
“I've said before, I think NVIDIA will be the first $10,000,000,000,000 company. I you know, as I sit here, you know, in in May '26, I believe that to be true.”
Gerstner says memory trades at 5x earnings and NVIDIA at 13-14x fully taxed GAAP earnings.
“Think about memory as an industry is only trading at five times earning. In the case of NVIDIA, trading at 13 or 14, fully taxed gap earnings.”
“They've announced a trillion dollars over the course of the next six to eight quarters of demand on on, you know, Blackwell's and now Vera Rubins.”
Gerstner explains Invest America funds will be invested in the top 500 US companies, making children direct shareholders.
“All of the money that goes into these accounts will be invested in the best 500 companies in America. They will be direct shareholders, a little bit of Nvidia,”
Gerstner says rumors suggest Elon Musk is ordering 20% of all Vera Rubin volume from Nvidia.
“There are rumors out there that he's already putting in for 20% of all the Vera Rubin volume, right, from Jensen Huang.”
Gerstner relays Jensen Huang's view that nobody can stand up data centers as fast as Elon Musk.
“ The July pullback — Coreweave and semiconductor names down roughly 40% — was triggered by the open-source scare (Kimi and friends undercutting frontier revenues), because the entire edifice depends on frontier labs having the revenue to offtake the compute. If demand slips, the leverage cuts both ways and violently. Credit spreads on these deals remain wide — fear is already priced into the debt market. The counterweights: Gerstner relays Jensen Huang's assessment that nobody — not Microsoft, not Google — can stand up data centers at Elon's speed, and Jason's conviction that ”