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snek_casetoday at 4:41 PM3 repliesview on HN

They're also getting closer to IPO and have a growing user base. They can't justify losing a very large number of billions of other people's money in their IPO prospectus.

So there's a push for them to increase revenue per user, which brings us closer to the real cost of running these models.


Replies

giwooktoday at 4:52 PM

I agree, and I'm also quite skeptical that Anthropic will be able to remain true to its initial, noble mission statement of acting for the global good once they IPO.

At that point you are beholden to your shareholders and no longer can eschew profit in favor of ethics.

Unfortunately, I think this is the beginning of the end of Anthropic and Modei being a company and CEO you could actually get behind and believe that they were trying to do "the right thing".

It will become an increasingly more cutthroat competition between Anthropic and OpenAI (and perhaps Google eventually if they can close the gap between their frontier models and Claude/GPT) to win market share and revenue.

Perhaps Amodei will eventually leave Anthropic too and start yet another AI startup because of Anthropic's seemingly inevitable prioritization of profit over safety.

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ljmtoday at 6:00 PM

They're also getting into cloud compute given you can use the desktop app to work in a temporary sandbox that they provision for you.

I was about to call it reselling but so many startups with their fingers in the tech startup pie offer containerised cloud compute akin to a loss leader. Harking back to the old days of buying clock time on a mainframe except you're getting it for free for a while.

zozbot234today at 6:06 PM

The "real cost" of running near-SOTA models is not a secret: you can run local models on your own infrastructure. When you do, you quickly find out that typical agentic coding incurs outsized costs by literal orders of magnitude compared to the simple Q&A chat most people use AI for. All tokens are very much not created equal, and the typical coding token (large model, large noisy context) costs a lot even under best-case caching scenarios.