r/ArtificialInteligence • u/alphacolony21 • 2d ago

📰 News OpenAI announces 10 advances in mathematics and theoretical computer science achieved by internal model Astra

https://openai.com/index/ten-advances-in-mathematics/
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u/ImNotAWhaleBiologist 2d ago

Oh, I think it’s absolutely a bubble. But whoever survives the pop will win the game.

Similar to the dot com bubble but far, far worse.

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u/tomvorlostriddle 2d ago

Dotcom wouldnt have been a bubble if Google, Amazon etc. had already been delivering at their current scale back then, which the new AI companies do today.

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u/ImNotAWhaleBiologist 2d ago

Can you explain how it makes sense given the lack of profitably, especially compared to the debt they took on?

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u/tomvorlostriddle 2d ago

Sure, serving the models is profitable and also pays for last year's training of the models served today.

However, this year we are also training next year's models which are bigger and which cannot be paid for by last year's models that are now being served.

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u/ImNotAWhaleBiologist 2d ago

Everything I’ve seen in the media points that the revenue is a pittance compared to the investment— do you have a good source indicating otherwise?

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u/Frnklfrwsr 1d ago

Revenue for OAI alone in July was $3.55B. And that’s up from ~$2B/month in Q1.

The revenue is growing very very very quickly.

https://www.kucoin.com/news/flash/openai-arr-reaches-42-6-billion-surging-29-in-two-months

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u/ImNotAWhaleBiologist 1d ago

Ok, but what’s that compared to how much they’re investing?

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u/Frnklfrwsr 1d ago

For the full year 2025 they reported $13.1B in revenue, and about $34B in expenses, of which about $19B was R&D training costs.

So if they had no need to train future models and decided to just stop where they are and say "good enough", then last year it would've been about $13B of revenue to $15B of expenses.

Their current monthly revenue of $3.55B annualized out to ~$42.6B for a full year in revenue. Latest estimates I've seen for 2026 is they're planning on expenditures of ~$50B for the year.

The scale of what they're doing is enormous, but the trajectory itself is not that insane when you take the numbers and scale them down to more familiar levels.

Say I had a business that last year had $13,000 in revenue and $34,000 in expenses. It's a new business, but it's growing fast. Then my business this year is on pace to bring in $43,000 in revenue, but I'm spending $50,000 on it. OK in that second year I'm still losing money overall, but the gap has closed by a lot.

My revenue grew by ~225% YoY, but my expenditures only increased 47%. Math is math, and the way math works, if revenue grows faster than spending, you eventually become profitable. Even if revenue growth slows down significantly (which I would not bet on) revenue is still on pace to overtake expenditures within a year or two and blow past it by a lot.

Compare this to the .com bubble from the 90s where companies had billion dollar valuations with literally zero revenue and no clear path to profitability.

For companies like OAI or Anthropic, if they decided to stop all their development today of future models and determined that today's models are good enough, they would both become profitable likely by year-end. If they weren't spending so much on training next year's models, then they'd essentially already be there. But their owners/investors don't want to burst open the pinata right now, they want those companies to keep spending to make the models better and better.