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.”
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.”
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.”
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.”
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.”
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.”
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.”
Baker predicts big businesses will pay a million dollars for AI to think for six weeks on key questions.
“I think you're if you're a big business and you can pay a million dollars to let an AI think for six weeks about the most important question for your business, that's gonna be a profound advantage relative to small businesses that can't afford that.”
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.”
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.”
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.”
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?”
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,”
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.”
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,”
Baker notes only 10 basis points of the population uses AI models properly despite trillions spent.
“10 basis points of the world's population is using these models the way they should probably be used. And we're in an insane shortage despite spending cumulatively trillions of dollars.”
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.”
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.”
“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.”
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.”
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.”
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.”
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.”
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.”
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.”
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.”
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.”
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.”
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.”
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.”
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.”
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.”
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.”
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.”
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.”
“Market is overreacting to hyperscale credit spreads widening from my perspective. TL;DR Spot pricing for renting GPU compute materially above contracted rates implies hyperscalers are underearning while operating cash flow acceleration is an underestimated source of funds for AI https://t.co/D9FSHXQ8F8”
Baker acknowledges real yields rising and spreads widening but argues less credit needed given operating cash flow acceleration
“@dampedspring Of course. Real yields going up and spreads widening is undeniable. I am saying we may need less credit than expected given a likely continued acceleration in operating cash flow.”
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.”
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?”
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,”
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.”
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.”
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.”
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.”
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.”
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.”
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.”
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.”
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.”
Baker says Terafab will create over 3000 high quality jobs in heart of Texas, AI good for America
“AI is good for America, episode 1001. Terafab will create over 3000 high quality jobs right in the heart of Texas. https://t.co/FA2KHqMd11”
Baker announces Chase Lochmiller of Crusoe as second Tomorrow X Summit speaker, jokes about first time seeing him in suit
“Happy to announce @ChaseLochmiller CEO and Founder of @crusoeai as the second confirmed speaker at the @TomorrowXSummit This photo is my first time ever seeing Chase in a suit! https://t.co/mL4kKOTfwf”
Baker says Crusoe CEO will have interesting perspective being vertically integrated from dirt through electrons through tokens
“@benitoz @ChaseLochmiller @CrusoeAI @TomorrowXSummit He will have an interesting perspective on the buildout. Vertically integrated from dirt through electrons through tokens.”
Baker announces Antonio Gracias interviewing Jon Gray of Blackstone at Tomorrow X Summit November 17-18, notes Blackstone leaning into AI
“Looking forward to listening to @AntonioGracias interview Jon Gray, President and COO of @blackstone at the @tomorrowxsummit November 17-18 in Austin, TX. Blackstone is leaning into AI more than most of its peers and they are integral part of financing it. So many topics: their https://t.co/6xK1XtNKl1”
Baker says future is multiple models working together, lower model margins mean more AI infrastructure demand
“Important. The future is almost certain to be multiple models working together. Lower margins at the model layer whether from open-source or vertically integrated players = more AI infrastructure demand. https://t.co/YBWlCNnrDD”
Baker would not take under on 250 billion for Anthropic unless they stumble or fail to secure compute
“@altcap Love the expectations management! Let me say this: I would not take the “under” on $250 billion *unless* they stumble or fail to secure enough compute. Maybe you can discuss with @DarioAmodei at @TomorrowXSummit before I interview you about public policy!”
“@Shaughnessy119 @TMTBreakout 2 of the 3 parts of your equation are correct (first and last, not the middle). An open-source token costs just as much compute and energy to produce as a frontier token for a model of comparable size. And they are often less token efficient.”
Baker explains Anthropic and OpenAI have more leverage over infrastructure providers than open-source does over cloud providers
“@Shaughnessy119 Y is higher than X - Anthropic and Open AI have more leverage over the infrastructure/cloud providers. For a given token over time all else equal, the cloud and infrastructure players charge more for open source tokens vs. what Anthropic and OpenAI pay per token b/c open source”
Baker says Citadel probably added AI exposure elsewhere after reducing position
“@hitraderjoe @CNBC Yes. And probs means they added AI exposure elsewhere. He is super strategic.”
Baker says Atreides internal AI spend will be 100x higher in August 2026 versus March 2026 and still doubling monthly
“Suspect we will start to hear about a “Pareto optimal” balance of computationally efficient humans, cheaper open-source tokens and frontier tokens. Our internal AI spend @Atreidesmgmt will be roughly 100x higher in August 2026 vs. March 2026. Still roughly doubling every month.”
Baker explains open-source lowers compute spend by ratio of frontier to open-source margins because frontier marks up compute more
“@itsvlady Well it lowers compute spend by the ratio of the margins of the frontier tokens to the margins of the open-source tokens - frontier tokens mark up underlying compute dramatically more than open-source.”
Baker argues cheaper open-source tokens are net positive for AI infrastructure because they cost same compute as frontier tokens
“@arakharazian Respectfully this is not correct from my perspective. Cheaper open-source tokens are net positive for the AI infrastructure names, although maybe not for the model companies. An open-source token broadly costs the same amount of compute (watts and wafers) as a frontier token to”
Baker says frontier labs claim their tokens use less compute than open-source tokens and have more intelligence density
“@JoshPurtell @arakharazian Frontier labs would say their tokens use less compute than comparable open-source tokens but that would break people’s brains. And for sure they have more intelligence density per token which compounds their efficiency advantage.”
Baker calculates Ultrafast timeline from December deal through wafer and server production to August debut
“@DratchCap @anni_sen @stefanveliki137 @thsottiaux I am also curious about this. Along with why Ultrafast mode is capacity constrained. Deal struck in late December, 4.5 months to make a wafer, 6 weeks to make a server, a month to energize a server. So logical that Ultrafast debuted in August and would think it would be less”
Baker asks whether OpenAI or production constraints are limiting Ultrafast capacity
“@anni_sen @stefanveliki137 @thsottiaux You think OpenAI is constraining the capacity or production volume constraints elsewhere are constraining the capacity? Genuinely curious.”
Baker says GPU price increase means anyone spending on Blackwell and Rubin before January 2027 gains competitive advantage
“The most obvious implication of GPU price increase is that anyone who is spending a lot on Blackwell and Rubin before January 31, 2027 is in a good relative position vs. competitors. Super curious to know if GPU prices are going up more than rack prices.”
Baker argues open-source gaining share is net positive for everyone except model companies
“@arakharazian Markets do irrational stuff all the time! But open-source gaining share is net positive for everyone except for the model companies.”