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Anthropic raises $13B Series F

(www.anthropic.com)
585 points meetpateltech | 1 comments | | HN request time: 0.001s | source
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llamasushi ◴[] No.45105325[source]
The compute moat is getting absolutely insane. We're basically at the point where you need a small country's GDP just to stay in the game for one more generation of models.

What gets me is that this isn't even a software moat anymore - it's literally just whoever can get their hands on enough GPUs and power infrastructure. TSMC and the power companies are the real kingmakers here. You can have all the talent in the world but if you can't get 100k H100s and a dedicated power plant, you're out.

Wonder how much of this $13B is just prepaying for compute vs actual opex. If it's mostly compute, we're watching something weird happen - like the privatization of Manhattan Project-scale infrastructure. Except instead of enriching uranium we're computing gradient descents lol

The wildest part is we might look back at this as cheap. GPT-4 training was what, $100M? GPT-5/Opus-4 class probably $1B+? At this rate GPT-7 will need its own sovereign wealth fund

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powerapple ◴[] No.45107915[source]
Also not all compute was necessary for the final model, a large chunk of it is trial and error research. In theory, for $1B you spent training the latest model, a competitor will be able to do it after 6 months with $100M.
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SchemaLoad ◴[] No.45110291[source]
Not only are the actual models rapidly devaluing, the hardware is too. Spend $1B on GPUs and next year there's a much better model out that's massively devalued your existing datacenter. These companies are building mountains of quicksand that they have to constantly pour more cash on else they be reduced to having no advantage rapidly.
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1. utyop22 ◴[] No.45113911[source]
Yes indeed if we look at it from this equation:

FCFF = EBIT(1-t) - Reinvestment

If the hardware needs constant replacement, that Reinvestment number will always remain higher than what most people think.

In fact, it seems none of these investments are fixed. Therefore there are no economies of scale (as it stands right now).