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Anthropic raises $13B Series F

(www.anthropic.com)
585 points meetpateltech | 1 comments | | HN request time: 0s | 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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AlexandrB ◴[] No.45107239[source]
The whole LLM era is horrible. All the innovation is coming "top-down" from very well funded companies - many of them tech incumbents, so you know the monetization is going to be awful. Since the models are expensive to run it's all subscription priced and has to run in the cloud where the user has no control. The hype is insane, and so usage is being pushed by C-suite folks who have no idea whether it's actually benefiting someone "on the ground" and decisions around which AI to use are often being made on the basis of existing vendor relationships. Basically it's the culmination of all the worst tech trends of the last 10 years.
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dpe82 ◴[] No.45107517[source]
In a previous generation, the enabler of all our computer tech innovation was the incredible pace of compute growth due to Moore's Law, which was also "top-down" from very well-funded companies since designing and building cutting edge chips was (and still is) very, very expensive. The hype was insane, and decisions about what chip features to build were made largely on the basis of existing vendor relationships. Those companies benefited, but so did the rest of us. History rhymes.
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BrenBarn ◴[] No.45112438[source]
The difference is once you bought one of those chips you could do your own innovation on top of it (i.e., with software) without further interference from those well-funded companies. You can't do that with GPT et al. because of the subscription model.
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almogo ◴[] No.45112812{3}[source]
Yes you can? Sure you can't run GPT5 locally, but get your hands on a proper GPU and you can run some still very sophisticated local inference.
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1. BrenBarn ◴[] No.45122817{4}[source]
You can do some, but many of them have license restrictions that prevent you from using them in certain ways. I can buy an Intel chip and deliberately use it to do things that hurt Intel's business (e.g., start a competing company). The big AI companies are trying very hard to make that kind of thing impossible by imposing constraints on the allowed uses of their models.