2025-12-31 21:40:24

OpenAI's leadership has been painting an optimistic picture about the company's path to profitability. As the organization scales, Sam Altman suggests that training costs for large models will become less of a financial burden relative to overall revenue—a classic economies of scale argument. The math sounds reasonable on paper. But there's a disconnect worth examining: despite these scaling projections, the company's actual losses have been climbing rather than shrinking. This gap between the theoretical model and real financials raises some tough questions about whether the current approach to AI development is truly sustainable, or if the economics need a fundamental reset.

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CryptoSourGrape

· 01-03 13:21

Another story of "believing we can make money." I wish I had believed it earlier. --- The difference between the paper bill and the actual loss is so big. Who still believes in economies of scale? Laughs. --- Sam is back to telling stories, claiming to cut costs despite increasing losses. If I hadn't missed the boat, I might have believed it. --- If I hadn't been fooled by this theory back then... Never mind, it's too late to say anything now. --- A classic AI startup routine: burning money for dreams, then "believing we will be profitable." It's really the old trick. --- The numbers look good, but the money in the account doesn't lie. The gap is ridiculously large. --- It sounds good, but the actual losses are still rising. Why am I so easily swayed by this kind of rhetoric? --- No wonder they have strong fundraising ability—while investors keep pouring in money, they are losing it rapidly themselves.

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DataBartender

· 01-02 21:25

Paper numbers always deceive, I find OpenAI's accounting suspicious --- The bigger the scale, the more severe the losses. Can this explanation really hold? --- Sam is talking about economics stories again... but the wallet will tell the truth --- Is it my misunderstanding or is there a problem with the model that scaling ultimately costs more money? --- The economies of scale on the books are completely different from actual losses --- It seems that the path of large models has gone off track, with costs not decreasing but increasing --- This kind of disconnect is the most revealing. Numbers can deceive, but real money won't

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MemeTokenGenius

· 2025-12-31 22:09

Sam is back to storytelling again. Armchair strategizing always sounds good, but the ledger won't lie.

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HashRateHermit

· 2025-12-31 22:06

Haha, it's the same old armchair strategizing, a show that gets slapped in the face by reality. Sam's story sounds good, but the losses are actually getting bigger? This logic is a bit hard to hold up.

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MetaReckt

· 2025-12-31 22:06

Sam is telling stories again. The mathematics on paper is always perfect; what about reality? Losses are still increasing...

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GasFeeBeggar

· 2025-12-31 21:59

Economic models on paper clash with real financial data. Just listen to Sam's explanations; don't take them seriously.

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NftMetaversePainter

· 2025-12-31 21:50

ah, the classic disconnect between algorithmic projections and actual hash values in the ledger... altman's talking about economies of scale like it's some immutable blockchain primitive, but the real computational aesthetics here? the losses keep climbing lmao. it's giving "generative promises, non-generative results" energy ngl

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GetRichLeek

· 2025-12-31 21:45

Buddy Sam is telling us stories again. The numbers on paper look fine, but in reality, the losses are even bigger. Isn't this just like when I was trading cryptocurrencies? 😅

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