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> does work for Google and Meta I will point out that this is contentious, both of these companies are subject to regulatory investigations around their monopo

by N70Phone 11mo ago

> does work for Google and Meta I will point out that this is contentious, both of these companies are subject to regulatory investigations around their monopolistic practices & the matter that they are pretty much the only companies for which this is profitable. > Their model, today, is far more relevant than calling back to antiquated banner advertising models from 25 years ago Hardly. It's fundamentally the same model; Content with an advertisement next to it. Whether that is a literal banner ad or a disguised search result, none of the formfactors are new. For all the advances in ad-tech, CPMs are still the same old dogshit they were shortly after the dotcom bubble, looking better only because of inflation. > you'll have to convince me that Google and Meta's model cannot work for OpenAI, which you have not adequately done. That's the "orders and orders of magnitude more expensive" part. Neither Google Search nor Facebook are that profitable per single ad, they make it up in volume. LLMs are simply more expensive to operate than a search engine or a glorified web forum. Can OpenAI cut down their opex and amortized-cap costs down to less than the half-penny they'd extract with good CPMs? Probably not. But there's a deeper layer. The "fund AI with ads" model paints a scenario in which OpenAI would have to overtake Google; They need the ad-tech monopoly to push up CPMs or you can cut that half-penny down an order of magnitude. This is unlikely. To make ChatGPT work as a search engine requires all the infrastructure of a search engine. Ipso-facto they are always more expensive than a standalone search engine. Yet at the same time, people only care about ChatGPT as search because Google Search is shit now. Were ChatGPT to ever become a serious threat to Google, Google can simply turn off the search-enshittifier for a bit and wipe out ChatGPT's marketshare, and push them into bankruptcy by drawing down CPMs below OpenAI's sustainability level.

famouswaffles 11mo ago
>That's the "orders and orders of magnitude more expensive" part. It's not orders of magnitudes more expensive and if we take the most recent report for the half year, then they need a per quarter ARPU of $8 for their free users to be profitable with billions to spare. That is low. This is not some herculean task. They don't need to 'overtake google' or whatever. They literally don't need to change anything.
- N70Phone 11mo ago
  You can't average out the userbase like that because the individual usage of the service varies wildly, and advertising revenue is directly tied to amount of usage. Especially because OpenAI highly inflates user figures. > It's not orders of magnitudes more expensive This too is skewed by averaging with users who barely use the service.
  - famouswaffles 11mo ago
    >You can't average out the userbase like that because the individual usage of the service varies wildly Yes you can. This is how Meta, Google et al report their numbers. Obviously I'm not expecting each user to bring in exactly $8. The point is that the value they need to extract from their free users to be profitable is very small and very achievable. You and many people here have completely incorrect notions on how expensive inference is. Inference is cheap, and has been for some time now. >and advertising revenue is directly tied to amount of usage. Open AI with 800M weekly active users processes 2.6B messages per day. Google with ~5 billion users processes ~14 billion searches per day. >This too is skewed by averaging with users who barely use the service. No it's not. Inference is just not that expensive. Model costs have literally crashed several orders of magnitudes in the last few years. Sure, in 2020, this would be a very serious concern. In 2025, it just isn't.
    - N70Phone 11mo ago
      My point is that for these purposes, users are not fungible. You can't just divide the cost-revenue equation by the amount of users N on both sides. > No it's not. If you add a pile of fictious users to the usercount, the apparent average cost-per-user drops as the fictious users do not use the service and do not add their own costs. This lowers the apparent amount of per-user revenue you need. However, as fictious users also do not generate revenue, this is all smoke and mirrors.
      - famouswaffles 11mo ago
        >My point is that for these purposes, users are not fungible. You can't just divide the cost-revenue equation by the amount of users N on both sides. Again, yes you can if you're simply trying to see the relative level of value you need to extract from your users. It's not a complicated idea. $8 is well below what Google, Meta report. You were wrong. They don't need to reach a high bar. End of story. >If you add a pile of fictious users to the usercount, the apparent average cost-per-user drops as the fictious users do not use the service and do not add their own costs. This lowers the apparent amount of per-user revenue you need. As always, nonsensical hypotheticals are just that. Nonsensical. Not only can the users you're talking about not exist in reality, the numbers being thrown around are literally based on their Weekly active users.

famouswaffles 11mo ago

>That's the "orders and orders of magnitude more expensive" part. It's not orders of magnitudes more expensive and if we take the most recent report for the half year, then they need a per quarter ARPU of $8 for their free users to be profitable with billions to spare. That is low. This is not some herculean task. They don't need to 'overtake google' or whatever. They literally don't need to change anything.

N70Phone 11mo ago
You can't average out the userbase like that because the individual usage of the service varies wildly, and advertising revenue is directly tied to amount of usage. Especially because OpenAI highly inflates user figures. > It's not orders of magnitudes more expensive This too is skewed by averaging with users who barely use the service.
- famouswaffles 11mo ago
  >You can't average out the userbase like that because the individual usage of the service varies wildly Yes you can. This is how Meta, Google et al report their numbers. Obviously I'm not expecting each user to bring in exactly $8. The point is that the value they need to extract from their free users to be profitable is very small and very achievable. You and many people here have completely incorrect notions on how expensive inference is. Inference is cheap, and has been for some time now. >and advertising revenue is directly tied to amount of usage. Open AI with 800M weekly active users processes 2.6B messages per day. Google with ~5 billion users processes ~14 billion searches per day. >This too is skewed by averaging with users who barely use the service. No it's not. Inference is just not that expensive. Model costs have literally crashed several orders of magnitudes in the last few years. Sure, in 2020, this would be a very serious concern. In 2025, it just isn't.
  - N70Phone 11mo ago
    My point is that for these purposes, users are not fungible. You can't just divide the cost-revenue equation by the amount of users N on both sides. > No it's not. If you add a pile of fictious users to the usercount, the apparent average cost-per-user drops as the fictious users do not use the service and do not add their own costs. This lowers the apparent amount of per-user revenue you need. However, as fictious users also do not generate revenue, this is all smoke and mirrors.
    - famouswaffles 11mo ago
      >My point is that for these purposes, users are not fungible. You can't just divide the cost-revenue equation by the amount of users N on both sides. Again, yes you can if you're simply trying to see the relative level of value you need to extract from your users. It's not a complicated idea. $8 is well below what Google, Meta report. You were wrong. They don't need to reach a high bar. End of story. >If you add a pile of fictious users to the usercount, the apparent average cost-per-user drops as the fictious users do not use the service and do not add their own costs. This lowers the apparent amount of per-user revenue you need. As always, nonsensical hypotheticals are just that. Nonsensical. Not only can the users you're talking about not exist in reality, the numbers being thrown around are literally based on their Weekly active users.