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Okay, let’s see you guys get passed the inference costs disclosure. According to WSJ it is enough to kill the frontier shop business model. It’s one of the bigg

Okay, let’s see you guys get passed the inference costs disclosure. According to WSJ it is enough to kill the frontier shop business model. It’s one of the biggest things blocking OpenAI https://www.wsj.com/tech/ai/big-techs-soaring-profits-have-an-ugly-underside-openais-losses-fe7e3184 https://www.wsj.com/tech/ai/big-techs-soaring-profits-have-a...

politelemon 10mo ago
Do you mean as part of going public they need to make public how much they spend on inference versus how much they make?
- blackjack_ 10mo ago
  Yes to IPO you have to submit an S-1 form which requires the last 3 years of your full financials and much more. You can’t just IPO without disclosing how your business works and whether it makes or loses money and how much.
ac29 10mo ago
Inference costs aren't a problem, selling inference is almost certainly profitable. The problem is that its (probably) not profitable enough to cover the training and other R&D costs.
- disgruntledphd2 10mo ago
  Don't forget all the other costs of their business, like paying sales and solutions people (expensive, not going away any time soon).
  - fragmede 10mo ago
    Wait, I thought AI was gonna put us all out of jobs tho.
    - disgruntledphd2 10mo ago
      If that does happen, salespeople will be the last to go.
vessenes 10mo ago
You did not parse that article properly. It regurgitates only what everyone else keeps saying: when you conflate R&D costs with operating costs, then you can say these companies are 'unprofitable'. I'd propose with a proper GAAP accounting they are profitable right now; by proper I mean that you amortize out the costs of R&D against the useful life of the models as best you can. I am not aware of any frontier inference disclosures that put margins at less than 60%. Inference is profitable across the industry, full stop. Historically R&D has been profitable for the frontier labs -- this is obscured because the emphasis on scaling the last five years has meant they just keep 10xing their R&D compute budget. But for each cycle of R&D, the results have returned more in inference margin than they cost in training compute. This is one major reason we keep seeing more spend on R&D - so far it has paid, in the form of helping a number of companies hit > $1bn in annual revenue faster than almost any companies in history have done so. All that said, be cautious shorting these stocks when they go public.

politelemon 10mo ago

Do you mean as part of going public they need to make public how much they spend on inference versus how much they make?

blackjack_ 10mo ago
Yes to IPO you have to submit an S-1 form which requires the last 3 years of your full financials and much more. You can’t just IPO without disclosing how your business works and whether it makes or loses money and how much.

ac29 10mo ago

Inference costs aren't a problem, selling inference is almost certainly profitable. The problem is that its (probably) not profitable enough to cover the training and other R&D costs.

disgruntledphd2 10mo ago
Don't forget all the other costs of their business, like paying sales and solutions people (expensive, not going away any time soon).
- fragmede 10mo ago
  Wait, I thought AI was gonna put us all out of jobs tho.
  - disgruntledphd2 10mo ago
    If that does happen, salespeople will be the last to go.

vessenes 10mo ago

You did not parse that article properly. It regurgitates only what everyone else keeps saying: when you conflate R&D costs with operating costs, then you can say these companies are 'unprofitable'. I'd propose with a proper GAAP accounting they are profitable right now; by proper I mean that you amortize out the costs of R&D against the useful life of the models as best you can. I am not aware of any frontier inference disclosures that put margins at less than 60%. Inference is profitable across the industry, full stop. Historically R&D has been profitable for the frontier labs -- this is obscured because the emphasis on scaling the last five years has meant they just keep 10xing their R&D compute budget. But for each cycle of R&D, the results have returned more in inference margin than they cost in training compute. This is one major reason we keep seeing more spend on R&D - so far it has paid, in the form of helping a number of companies hit > $1bn in annual revenue faster than almost any companies in history have done so. All that said, be cautious shorting these stocks when they go public.