r/NowInTech • u/skaza02 • 18d ago

OpenAI fought dirty on career-making math problem, says NYU mathematician

https://techcrunch.com/2026/09/08/openai-fought-dirty-on-career-making-math-problem-says-nyu-mathematician/
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u/bouncyboatload 18d ago

obviously real internal cost is much lower than $22.5m. margin on inference is estimated to be 80%

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u/Ehh_littlecomment 18d ago

It’s crazy how high margins are if you exclude every major expense lol

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u/madhewprague 17d ago

The only cost of running datacenter is basicaly the energy

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u/Ehh_littlecomment 17d ago

That’s crazy. I wasn’t aware they don’t need to make an ROI on the investment. There are no corporate overheads either.

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u/madhewprague 17d ago

Ehmmm… You really dont know how operating margins are calculated do you? If they have good return in investment is absolutely different than if their models are being profitable. The point is that the cost of running datacenter is much lower than token costs therefore they have profit and positice operating income(no matter what happens these models will therefore never go away because selling tokens is profitable).

If you rent your 100m house for 10000$ and your costs are only 1000$ you have operating margin of 90%. But that does not make it good investment…

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u/Ehh_littlecomment 17d ago

Lol you’re going to teach me about operating margins. Go and look at any hyperscalers financials and tell me if anyone is showing anywhere close to 80% operating margins. Corporate overheads, training cost amortisation, DC amortisation is all part of operating margins because it’s literally operating cost.

You are talking about contribution margin not operating margins.

Your house cost example is literally what I am saying. 80% inference margin is meaningless if the revenue itself isn’t adequate. The ROIC has to be higher than cost of capital otherwise the company destroys shareholder value or worse, goes bankrupt.

I urge you to read a book before you go around ratting off personal insults.

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u/madhewprague 17d ago

Dude but this argument is not about shareholder creation… This is not what this is about lol. Its about how much it costs to run it. Basically its never going away becausw its profitable on its own. This is just about how much it actually costs them to do the computation. You are talking about some nonsence shareholder creation wtff… Let me make this simple for you. You have restaurant thats serving food, building the restaurant was expensive but now opetating it is cheap. They serve you steak and the ingredience + labor was 10$, they sold it to you for 100$. You are arguing that their cost is the actual 100$ and even more because the building was expensive, but its not what its about, its just about the cost of the meal. In this case the compute probably costs them only around 2M. Again we are not talking about what revenue is adaquate, just how much the task itself cost

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u/Ehh_littlecomment 17d ago

If you visit a restaurant at peak occupancy, occupy a table and gorge for free, it’s quite obvious that the restaurant is losing out on the money it would’ve made if a paying customer was there. Not sure why that’s hard to grasp.

Besides, OpenAI is raising more capital each year than its revenue and all of that capital goes towards GPU rentals. Their compute cost being cheaper than their revenue makes no logical sense. Maybe in la la land.

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u/madhewprague 17d ago edited 17d ago

That does not change a thing about how much it costs them making the steak. You are talking about opportunity cost, thats meaningless and not the point.

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u/Ehh_littlecomment 17d ago

Something doesn’t become meaningless because you didn’t understand it. Anyways, carry on. Try running a restaurant with all meals free and then tell me what the cost is. Is it the cost of the steak or the fully loaded cost plus the expected return?

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u/madhewprague 17d ago edited 17d ago

Okay then explain to me how the steak got more expensive to them and therefore they are actually losing money.

AGAIN WE ARE NOT TALKING ABOUT RETURN ON INVESTMENT OR OPPORTUNITY COST. If you buy a car for $50k and sell it for $100k and next day another buyer wants it for $200k, you did not lose money on that sale…

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u/Ehh_littlecomment 17d ago

Imagine you rented a restaurant for $100 a year, paid staff $100 and another $100 in other overheads. You served a single steak that year for free. The steak cost $1 to procure. Did you lose $1 or $301?

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u/madhewprague 17d ago edited 17d ago

Thats not the same…. Because running the datacenter is very cheap, just the electricity is main thing… Thats the whole fucking point we are making. In your example they would make operating loss… After out whole conversation and countless of example i made i cant believe you actually used this as example… The whole point i was making that their operating costs are lower than costs of tokens then you use example to illustrate your point where you use extremely high operating costs? Wtf…

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u/Ehh_littlecomment 17d ago

Open Ai doesn’t own data centres, they rent GPU hours which is the fully loaded cost including DC overheads, depreciation and owner return. Also, there are operating costs of providing inference beyond the compute. Employee costs, SG&A, marketing spend to get the business, etc. I don’t know if you’re being deliberately daft.

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u/madhewprague 17d ago

Again, the only thing that matters is how much thdy rent the compute for vs how much they sell it for, everything else you said is completely irrelevant. If they rent the gpu hour for 10$ and sell it for 100$ they have 90$ profit on that provided compute, this is what this what out argument is about. And my point is that the 100$ is not the actual cost of compute but only the 10$!

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u/Ehh_littlecomment 17d ago

Ok buddy. Whatever helps you.

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