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, 2 Oct 2024 — a date, and nothing else. It is not a claim about who reached a view first.
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Brad Gerstner
4
thin
25 Oct 2023 – 31 Jul 2025
-343 d
- Dylan Patel 5 2 Oct 2024 – 25 Aug 2026 +0 d
- David Sacks 2 thin 31 Jan 2025 – 31 Jan 2025 +121 d
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Gavin Baker
6
20 May 2026 – 4 Aug 2026
+595 d
The chronologysourced and dated, oldest first
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Brad Gerstner
Gerstner predicts 2024 will see more compute deployed than all previous years combined for AI.
“We're gonna launch more. We're gonna deploy more compute in 2024 than in all previous years combined.”
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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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Dylan Patel
Patel claims China could match individual US labs in compute by 2025-26 through centralization alone using foreign chips.
“China can be centralized enough to compete with each individual US lab. They could have just as many flops in '25 and '26 if they decided they were scale built. Right? Just from foreign chips”
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David Sacks
Sacks cites Dylan Patel's estimate that DeepSeek has 50,000 Hopper chips across different models.
“Dylan Patel, who's leading semiconductor analyst, has estimated that DeepSeac has about 50,000 hoppers. And specifically, he said they have about 10,000 h one hundreds, They have 10,000 h eight hundreds and 30,000 h twenties.”
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David Sacks
Sacks says DeepSeek's compute cluster costs over $1 billion, contradicting the $6 million narrative.
“you add up the the cost of a compute cluster with 50,000 plus hoppers and it's gonna be over $1,000,000,000.”
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Brad Gerstner
Gerstner reports DeepSeek is massively compute constrained now, with GPU differential growing versus OpenAI for o3.
“On top of that, we learned, you know, they are massively compute constrained right now. So you've seen some tweets about this, people that are, you know, getting server delay and all this stuff”
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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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Dylan Patel
Patel says the Oracle-OpenAI deal involves many gigawatts of compute with unprecedented four-year revenue guidance.
“It is literally many gigawatts. And then in addition, right, not just about securing OpenAI ridiculous amounts of compute, but what what was really interesting is Oracle gave a guidance of four years.”
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Dylan Patel
Patel notes Oracle gave unprecedented four-year revenue guidance, something no company has ever done before.
“Oracle gave a guidance of four years. They told everyone what their revenue is gonna be for the next four years. No company has ever done that.”
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Gavin Baker
Baker estimates Anthropic could be doing $100-200 billion in revenue if unconstrained by compute availability.
“So I think they would be doing materially more a hundred, one hundred and fifty, maybe 200,000,000,000. So you might be buying it at more like five times unconstrained.”
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Gavin Baker
Baker estimates Anthropic would do $100-200 billion ARR unconstrained by compute, valuing it at 5x URR.
“I think they would be doing materially more a hundred, one hundred and fifty, maybe 200,000,000,000. So you might be buying it at more like five times unconstrained.”
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Gavin Baker
Baker estimates Anthropic could do $100-200B in unconstrained revenue if compute weren't limited.
“So you might be buying it at more like five times unconstrained. I'm gonna make up a new number. URR, unconstrained revenue.”
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Dylan Patel
Patel predicts OpenAI and Anthropic alone will deploy over 100 gigawatts of compute by 2030.
“by 2030, just OpenAI and Anthropic will have over 100 gigawatts combined, and then you'll add Meta and Google and so on and so forth.”
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Gavin Baker
Baker argues silicon will eat the world because AI is far more computationally intensive than deterministic software.
“And the nature of AI just as AI eats the world, silicon is going to eat the world because it's so much more computationally intensive than deterministic software written by humans.”
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Gavin Baker
Baker explains AI recomputes answers probabilistically each time, enabling superhuman capabilities but requiring extreme computational expense.
“AI, even if you put a harness on it, even if you do the chain of thought, even if you have multiple agents, it's probabilistic that it is recomputing the answer each time.”
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Gavin Baker
Baker notes SpaceX added massive compute capacity instantly without any market price impact.
“they put a vast amount of compute into the market overnight, and it wasn't even really a blip. It was like the market just utterly absorbed it.”
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Dylan Patel
Patel predicts Anthropic and OpenAI will take 40-50% of all new compute in 2026, accelerating centralization.
“You've got Anthropic OpenAI are taking as much as 40% to 50% of compute next year. And the centralization doesn't look like it's slowing down or stopping. In fact, it looks like it's only accelerating.”
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