Who is on this subjectordered by the date of their first quote here
2 of 4 lanes rest on fewer than 5 quotes and are marked thin. Offsets are days from the middle first-quote date, 26 Oct 2023 — a date, and nothing else. It is not a claim about who reached a view first.
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Gavin Baker
45
26 Nov 2019 – 4 Aug 2026
-1430 d
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Brad Gerstner
35
26 Oct 2023 – 15 May 2026
+0 d
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Bill Gurley
1
thin
11 Jul 2024 – 11 Jul 2024
+259 d
- David Sacks 1 thin 1 Aug 2026 – 1 Aug 2026 +1010 d
The chronologysourced and dated, oldest first
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Gavin Baker
Baker argues AI revolution stems from cloud computing power and mobile-generated data, not algorithmic advances.
“The only thing that has enabled the AI revolution that we're living through, which I think we're at the bottom of the first inning in, is one, we had the ability to do cloud computing, so just apply significantly more computational power to old algorithms, and then b, we had dramatically more data.”
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Gavin Baker
Baker states data quantity is the single most predictive element of AI quality, not algorithms or infrastructure.
“The single most predictive element of knowledge about AI quality is the quantity of data used to train the algorithm.”
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Gavin Baker
Baker cites research showing every 10x increase in training data doubles AI quality.
“and it's been very well established in multiple papers from both Google and Microsoft research that for every order of magnitude increase in the data you use to train an algorithm, the quality of the AI doubles.”
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Brad Gerstner
Gerstner predicts next year will see more compute deployed globally than in all of human history combined.
“We're going to deploy more compute on a global basis next year than all the compute ever deployed by humanity combined. That's how much compute is going to drive these training models.”
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Brad Gerstner
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.”
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Brad Gerstner
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.”
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Brad Gerstner
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.”
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Brad Gerstner
Gerstner identifies four ingredients to compete in AI: capital at $40B/year, data scaling, compute infrastructure, and distribution.
“I think there are four important ingredients to compete in this market. Number one, you have to have capital, and the leaders are spending $40,000,000,000 a year.”
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“In two years, that company has gone from $22,000,000,000 in net income to $55,000,000,000 in net income. They've reduced their headcount from 85,000 people to 69,000 people.”
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Brad Gerstner
Gerstner says hyperscalers' total capex is now at $200 billion, raising questions about return on investment.
“In fact, I think if people are gonna be critical of anything, a lot of people are looking at the total CapEx of the hyperscalers now at $200,000,000,000 and saying, when are you gonna get a return on the dollars that you're spending?”
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Brad Gerstner
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”
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Brad Gerstner
Gerstner argues AI wave differs from internet era because hyperscalers are deploying massive capex directly, not customers.
“because all AI tools are being delivered as a service in the cloud, there's just a massive amount of CapEx happening.”
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Brad Gerstner
Gerstner notes Satya called AI a supply-driven wave with much experimental work, creating reset risk.
“Satya very quickly said this is a supply driven wave. And I think up to date, that is true. We're we're building ahead of demand.”
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Bill Gurley
Gurley questions whether AI CapEx spending is ahead of itself, citing Goldman and Sequoia research.
“One, could the CapEx spend be ahead of itself? Which is what Sequoia mentioned and what the second piece of the Goldman piece is.”
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Brad Gerstner
Gerstner says big four tech companies will spend $220 billion on capex this year.
“if you look at the big four, they're gonna spend $220,000,000,000 this year on CapEx.”
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Brad Gerstner
Gerstner argues this would be the first major technology phase shift with capex and revenues perfectly aligned.
“the idea that we're going to go through this phase shift with CapEx and revenues perfectly aligned and perfectly matched, right?”
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Gavin Baker
Baker says tech CEOs aren't thinking about ROI because they believe they're racing to create a digital god.
“Mark Zuckerberg, Satya, and Sundar just told you in different ways, we are not even thinking about ROI.”
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Gavin Baker
Baker predicts GPT-7 or GPT-8 will cost $500 billion to train, ending commodity status of models.
“By the way, these models are commodities today, but I am suspicious once we get to scaling laws continue, GPT seven or eight literally cost $500,000,000,000 to trade.”
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Gavin Baker
Baker says only three US locations can provide gigawatt power to data centers at 10x normal cost.
“There's only basically three places in The United States today where you can get a gigawatt of power to a single data center that's reliable enough, I.”
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Gavin Baker
Baker argues return on invested capital has risen for AI spenders, dismissing ROI skepticism.
“These companies are all public, and there is something called return on invested capital. And ROIC has gone up for all of these companies since they ramped CapEx.”
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Brad Gerstner
Gerstner notes Google Cloud grew 35% year-over-year, adding $2.5 billion ARR in one quarter, equivalent to Databricks.
“So just to put that in perspective, they added about 2,500,000,000 of new ARR in the quarter. That's like adding a Databricks in the quarter.”
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Brad Gerstner
Gerstner reports Masa Son said $9 trillion cumulative capex on 200 million GPUs is reasonable, possibly too small.
“Masa at FII today said 9,000,000,000,000 of cumulative capex on 200,000,000 GPUs is very reasonable. He said, in fact, I think it may be too small.”
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Brad Gerstner
Gerstner cites CoreWeave's $12 billion OpenAI Stargate deal announced yesterday as evidence AI buildout continues.
“CoreWeave announced yesterday a $12,000,000,000 deal with OpenAI on Stargate. Those things are getting constructive. We're investors there. I I can tell you those things are getting built.”
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Brad Gerstner
Gerstner reports X.AI targets 50 million H100 equivalent units, requiring 4 million GPUs and 11 gigawatts.
“If you look at this one out of Elon talking about the X dot AI goal is 50,000,000 in units of H100 equivalent.”
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Brad Gerstner
Gerstner says Anthropic raising $5B at $170B valuation on $5B revenue, unprecedented venture scale.
“I think that Iconic is going to lead a $5,000,000,000 round into Anthropic at $170,000,000,000 In the case of Anthropic, it's, you know, 170,000,000,000 on rumored $5,000,000,000 in revenue.”
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Brad Gerstner
Gerstner suggests Apple should acquire AI capabilities given their $2 trillion market cap and cash position.
“What's your opinion on the build it versus buy it debate around Apple? I feel like for $2,025,000,000,000, they should just buy it, just given how much cash they have”
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Brad Gerstner
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.”
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Brad Gerstner
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.”
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Brad Gerstner
Gerstner quotes AMD's Lisa Su calling this year two of a ten-year compute buildout supercycle.
“Lisa said we're in year two of a ten year super cycle to build out the compute in America. If you're not on the AI wave, then you're not gonna participate in all that upside.”
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Brad Gerstner
Gerstner compares AI buildout to Manhattan Project, calling it both national and economic security imperative against China.
“We are in a global AI race with China. This is like the Manhattan Project. We have to build out compute. It it's a it's not only a national security imperative.”
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Brad Gerstner
Gerstner argues that $100-200 billion in revenue by 2028-29 makes the capex spend responsible.
“Now if they're doing a 100 to 200,000,000,000 in revenue in 2829, then now we're in the zone of responsible.”
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Brad Gerstner
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.”
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Gavin Baker
Baker argues Google has a temporary pre-training advantage as the lowest cost producer of tokens using advanced TPUs.
“So I think Google for sure has this temporary advantage right now from a pre training perspective. I think it's also important that they've been the lowest cost producer of tokens.”
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Gavin Baker
Baker explains Google pays Broadcom a 50 to 55 percent gross margin for back-end chip design and Taiwan Semi management.
“And the managing Taiwan Semi is like stamping out that house like Lennar or, you know, D. R. Horton. And for doing those two latter parts, Broadcom earns a 50 to 55% gross margin.”
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Brad Gerstner
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.”
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Brad Gerstner
Gerstner argues AI must generate $1 trillion revenue to justify current CapEx versus $400 billion for all software.
“then you've gotta earn about a trillion dollars of AI revenue for all of this CapEx to be worth it.”
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“In 2023, these companies spent $150,000,000,000 on capex building out data centers. This year, over 500,000,000,000. Though, that's not speculative. That is purchase orders. Those are buildings. That's power.”
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Brad Gerstner
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.”
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Brad Gerstner
Gerstner says the major tech companies will spend over $500 billion on AI capex this year.
“The spending, the CapEx from that group alone is gonna be over $500,000,000,000 this year.”
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Brad Gerstner
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.”
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Brad Gerstner
Gerstner compares the next three years of AI investment to building the interstate highway system, all privately funded.
“I think for the next three years, this is like building the interstate highway system. Right? This is significant. It's important to The United States Of America, by the way.”
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Brad Gerstner
Gerstner says the Mag Five will spend $800 billion in total capex this year.
“This year, we're gonna have 800,000,000,000 in total CapEx by the Mag five. And the question was, would there be revenues to justify that?”
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Gavin Baker
Baker says he would take the over on every AI capex and demand number given by other speakers.
“And I would just say, I take the over on every number that they gave. Every single number. As what I think, you know, they're conservative guys.”
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Gavin Baker
Baker takes the over on every AI capex and memory forecast number given by other speakers at the conference.
“And I would just say, I take the over on every number that they gave. Every single number.”
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Gavin Baker
Baker argues this may be the first true capacity cycle and that fundamental shortages help avoid a destructive bubble.
“This may be the first true capacity cycle. And I and and I and I do think that these fundamental shortages are good for us as investors.”
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Gavin Baker
Baker believes NVIDIA could sell $11.5 trillion worth of chips next year if TSMC expanded capacity sufficiently.
“And if they doubled or tripled capacity, like, NVIDIA could probably sell $11,520,000,000,000 worth of chips next year. I really believe that.”
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Gavin Baker
Baker believes NVIDIA could sell $11.52 trillion in chips next year if TSMC tripled capacity but bubble risks prevent it.
“And if they doubled or tripled capacity, like, NVIDIA could probably sell $11,520,000,000,000 worth of chips next year. I really believe that. But the other side of that might be very painful for everyone.”
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Gavin Baker
Baker says AI models shifting to usage-based pricing with overage reveals no ceiling on spending yet.
“We're just moving from these all you can eat plans to usage based plans with overage, where those usage tokens cost a lot more, and we're finding out that there's we're nowhere near the amount of, you know, people ceiling price for how much they'll spend.”
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Gavin Baker
Baker emphasizes only 0.1% of the world uses AI models properly yet there's massive shortage despite trillions spent.
“And we're in an insane shortage despite spending cumulatively trillions of dollars. What happens when 5% of the world's population is using these models the way the cutting edge 10 basis points are?”
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“What happens when 5% of the world's population is using these models the way the cutting edge 10 basis points are? Like, it's just it's unimaginable. This is why orbital compute is a necessity.”
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Gavin Baker
Baker predicts Trainium will dominate 2026 like TPUs did in 2025, with Trainium 3 ramping in second half.
“Tranium is going to be to 2026, especially in the second half of this year when Tranium three really ramps, as TPUs were to twenty twenty five.”
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Gavin Baker
Baker reveals Atreides could have invested over $50 million in CoreWeave at $1.1 billion valuation but was conflicted out.
“I could've Atreides could've invested over $50,000,000 in the round at 1,100,000,000, And I was conflicted out by Crusoe,”
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Gavin Baker
Baker predicts terrestrial data center buildout will stop within seven years, causing pain for power and cooling companies.
“And the years leading up to that are gonna be very painful for a lot of the companies and the power cooling spaces, you know, these industrial names,”
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“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.”
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Brad Gerstner
Gerstner warns that 30-40% of compute is delayed this year, which could slow the entire AI trade if delays persist.
“And you heard the rumors and seen the headlines that 30 or 40% of compute now is delayed this year. So keep your eye on power and compute.”
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Brad Gerstner
Gerstner says the US is financing nearly a trillion dollars in annual AI capex privately, unlike China's government subsidies.
“I think it's extraordinary that we're financing almost a trillion dollars of capex a year to build out the the entire AI infrastructure without any money from the US government.”
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Gavin Baker
Baker says Anthropic added $11B ARR, comparing it to the entire SaaS revolution's $5-10T value creation.
“Anthropic, they added $11,000,000,000 of AR. And what is astonishing to me about this is that the SaaS and cloud revolution it created, we'll call it between 5 and $10,000,000,000,000 of value.”
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Gavin Baker
Baker says Anthropic added $11B ARR in one month, matching what Palantir, Snowflake, and Databricks built in ten years combined.
“And these three companies employ thousands of people, tens of thousands collectively. They've all spent ten years building their businesses and Anthropic added their combined businesses in one month.”
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Gavin Baker
Baker says Anthropic adding $11B ARR in one month is unprecedented in capitalism's history.
“Anthropic added their combined businesses in one month. Nothing like that has ever happened in the history of capitalism.”
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Gavin Baker
Baker estimates Anthropic would be doing $100-150B ARR if not compute-constrained, versus current $50B.
“And I think maybe a true statement is that Infantropic could just wave a magic wand and get all the compute they wanted. They'd probably be doing well north of $100,000,000,000 today, maybe 150.”
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Gavin Baker
Baker argues America will consume all available compute, reducing edge AI bear case concerns.
“And I just think the same is true of compute. It's why I'm probably less worried about like an edge AI bear case than I was.”
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Gavin Baker
Baker argues America will consume all available compute, making him less worried about edge AI bear cases.
“It's why I'm probably less worried about like an edge AI bear case than I was. We're going to consume as much compute as we can.”
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Gavin Baker
Baker argues NVIDIA could sell $2-3 trillion in GPUs if TSMC expanded capacity, but TSMC's restraint prevents a bubble.
“If Taiwan Semi did what Jensen wanted, I think Nvidia could sell $2,000,000,000,000 of GPUs in '26 or '27, maybe 2,500,000,000,000, maybe 3,000,000,000,000. But there is a limit where consumers would consume so much.”
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Gavin Baker
Baker argues Taiwan Semi's capacity constraint prevents AI bubble; NVIDIA could sell $2-3T GPUs otherwise.
“If Taiwan Semi did what Jensen wanted, I think Nvidia could sell $2,000,000,000,000 of GPUs in '26 or '27, maybe 2,500,000,000,000, maybe 3,000,000,000,000.”
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Gavin Baker
Baker argues Taiwan Semi's capacity discipline is single-handedly preventing an AI bubble.
“So Taiwan Semi, if we don't get a bubble, we need to throw a party for them because they will have single handedly prevented a bubble.”
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Gavin Baker
Baker identifies Taiwan Semi's capacity decisions as the single most important indicator of AI bubble risk.
“The pace at which they expand capacity. If I were to watch one thing to understand where there's a bubble, it's Taiwan Semi's capacity decisions.”
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Gavin Baker
Baker says understanding frontier AI now requires enterprise usage-based plans, not $250 monthly subscriptions which are rate-limited.
“To understand what Frontier AI is capable of today, even for a non coding use case, need to have Cloud Code or Codex five point Codex.”
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Gavin Baker
Baker says AI shifting from flat pricing to usage-based is extremely bullish as people consume more AI.
“AI is just shifting from all you can eat to pay by the drink. Then it turns out people really like to talk to their friends long distance.”
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Gavin Baker
Baker argues GPU useful lives will extend to 10-15 years due to inference disaggregation, contradicting AI skeptics.
“The disaggregation of inference means that I think these GPUs are going to have ten or fifteen year lives. The AI skeptics are like, oh, these companies are all cooking their books.”
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David Sacks
Sacks predicts AI capex will deliver returns and calls current volatility temporary and leverage-amplified.
“I think there will be a return on all of this capex and this is temporary market volatility amplified by leverage.”
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Gavin Baker
Baker reports AI stocks down 40-60% in a month despite no negative quantitative metrics or deceleration.
“Loads of AI names are down 60% from their highs. We'll call it 40% to 60% in a month in a straight line.”
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Gavin Baker
Baker says no one predicted old GPU prices would go vertical, everyone expected gradual declines.
“I don't think anyone in '24 or '25 thought that the prices of old GPUs would be going vertical. Everybody thought, hey. We're gonna be smart. We're gonna sign these long term contracts.”
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Gavin Baker
Baker argues contracted compute trades at massive discount to spot, repricing will accelerate cash flows and answer ROI questions.
“And so, essentially, you have the contracted base of installed compute trading at a massive discount to the current spot market.”
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Gavin Baker
Baker reports hyperscaler operating cash flow accelerated from $28B to $32B despite unusual legal expenses.
“Operating cash flow from Microsoft, Meta, and Amazon has reported accelerated from '28 to '32. There are some actually pretty big unusual items now like these hyperscalers.”
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Gavin Baker
Baker says adjusting for one-time items shows hyperscaler operating cash flow accelerated from $28B to $35B.
“But there is an unusual amount of onetimers this quarter. And if you adjust for that, we went from 28 to 35. That's that's a material acceleration at this scale.”
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Gavin Baker
Baker says incredible Anthropic results made him comfortable with Blackwell air pocket risk.
“I think one reason to the podcast two months ago, I got comfortable with that risk was just that you were seeing such incredible things out of anthropic.”
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Gavin Baker
Baker explains breaking memory LTAs could destroy companies by losing allocations when market tightens again.
“Well, if they're breaking their LTAs, it probably means, you know, your oversupply, prices are coming down, and then, you know, capacity naturally contracts. Well, what do you think is gonna happen to Google's allocations?”
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Gavin Baker
Baker suggests memory companies should copy NVIDIA's credit wrapper model while they have cash and credit markets are tight.
“I'm just making this up. But, like, do something. Like, you can because you have money now and credit markets are revolting.”
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Gavin Baker
Baker cites analysis showing compute margins, quantity, and inference margins all rising simultaneously, driving lab acceleration.
“The amount of compute is going up and inference margins going up. And if you multiply those three, that's how you're getting this crazy acceleration into some of the labs plus open source,”
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Gavin Baker
Baker cites report that SpaceX plans to bring on eight gigawatts of compute in eighteen months, calling it incredible.
“A Substack writer will fund the AI. They think that SpaceX is gonna try and bring on eight gigawatts of compute over the next eighteen months.”
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Gavin Baker
Baker calculates eight gigawatts at $50B per gigawatt implies $400B revenue versus $73B consensus for SpaceX.
“If they bring on anywhere near that, the consensus estimate is 73,000,000,000. That's eight gigs at 50,000,000,000 a gig. And, obviously, that would not all be lit up at the beginning of twenty seven.”
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Gavin Baker
Baker calculates 20% token spend on knowledge work implies $5 trillion addressable market.
“There's 25,000,000,000,000 in knowledge work. And so let's, you know, let's say that that's, you know, let's take your 20% number. That's 5,000,000,000,000.”
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Where they overlapsame programme, same subject
- BG2 Pod also carries Bill Gurley and Brad Gerstner on this subject, at different times.