Because as per usual it's silicon valley misunderstanding economics. AI is HPC. And how the HPC market worked before:

If you're the best performing "computing cluster" (ie. whatever you call the entity that can complete a massive calculation), you get a blank check from Congress.

Why? Because you need those calculations to "pump" nuclear weapons. They are needed to calculate both the geometry to make fusion bombs possible at all and to calculate the effect of a given geometry. They are the reason US/Russia/China have the biggest and strongest weapons known to humanity. And of course, they were replicated worldwide for this reason. I mean not that anyone will admit this but we don't have the best possible solution, and we don't know either the upper or lower limits for fusion devices (plus the lower limit would be very useful for energy generation, which for the US would effectively mean almost literally unlimited large marine ships that never need refueling. And yes, the solution to that problem is almost literally a 3d shape. Not just that, but mostly)

Now it appears it does not work the same when you democratize computation. Humans want a particular amount of computation and are willing to pay a given price for that. But the accountants still saw the blank check from before and ... do what accountants do. Economics don't change because you make things bigger and accessible, do they? Oh ... wait a second ...

As someone put it recently though, we now have data. 2.3% of humans in the US are willing to pay $20 per month for the support of a model like GPT-5.5/Claude code. If that's true (and after years of having this model, why wouldn't it be?) ... it means AI startups are doomed (because it's not even 10% of what they need it to be to make economic sense).

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mlyle 3 hours ago | parent | next [-]

> Because you need those calculations to "pump" nuclear weapons. They are needed to calculate both the geometry to make fusion bombs possible at all and to calculate the effect of a given geometry. They are the reason US/Russia/China have the biggest and strongest weapons known to humanity.

We have a couple new nuclear weapon designs, but not really going for bigger or stronger. Just packaging.

We built the big powerful ones with 1960s computing.

Now, stockpile stewardship -- being sure that stuff will keep working without ongoing testing -- is a bit expensive in compute. You need early 2010s supercomputer power.

In other words, I strongly disagree that nuclear weapons are the primary driver of high-end compute.

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spwa4 3 minutes ago | parent | next [-]

> We built the big powerful ones with 1960s computing.

And they are radially symmetric and simply totally overpower the initial fusion reaction, and that gives a secret number of solutions (>=1). But they sucks for many reasons, they're overpowered, heavy, and brittle and that is something we can "improve". And if you calculate the theoretical lower limit of device size for a given yield, you'll stop sleeping well.

And what do you need to approach that lower limit? Explosion simulations that are incredibly precise for a large number of different 3d shapes. And ironically the solution to the lower limit will also let you make the biggest yield devices.

Physically smaller bombs, with bigger yields. All you need is the correct shape (well, no, in practice there's no end to other things. Having the shape does not mean you can make it, for example, but it is the difficult part).

Hence the calculations, and hence the blank check.

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bobthebob 3 hours ago | parent | prev [-]

High end compute also existed in the 60’s.

The military has already mastered fusion (power), and likely has mastered gravity in some form in secret. They aren’t using mainstream compute for these discoveries

	▲	mlyle 2 hours ago \| parent [-]
		> High end compute also existed in the 60’s. Believe me, I know-- my dad did some work on the 360/44 and other large systems. High end late 1960s compute -- of the sort used to go to the moon or to design big nuclear weapons -- was roughly 486DX4-100 class. Not individual computers; the total computing at DOE or NASA. Of course, it would be hard to replace either with a single 486 because of availability, usage at different geographic locations, etc. You can assume a single large AMD Threadripper machine ($25k?) outclasses late-1960s DoE by roughly a factor of 50,000. And that assumes you didn't bother to put a GPU in it. > The military has already mastered fusion (power), and likely has mastered gravity in some form in secret. They aren’t using mainstream compute for these discoveries K

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gwbrooks 4 hours ago | parent | prev | next [-]

I disagree with some of the framing, but that's what good discussion is about -- figuring out where we agree and disagree.

But consumer uptake strikes me as the worst way to judge whether the big AI shops will make it. That's not where most of the leveraged user return or deployable capital is.

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2 hours ago | parent | prev | next [-]

[deleted]

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m4rtink 3 hours ago | parent | prev [-]

I'm sure Teller could make you a 10 gigaton nuke with a slide rule if you did not mind some sub scale tests.