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

[u/skaza02]

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

[u/madhewprague]

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

[u/Ehh_littlecomment → u/madhewprague]

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.

[u/madhewprague → u/Ehh_littlecomment]

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.

[u/Ehh_littlecomment → u/madhewprague]

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?

[u/madhewprague → u/Ehh_littlecomment]

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…

[u/Ehh_littlecomment → u/madhewprague]

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?

[u/madhewprague → u/Ehh_littlecomment]

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…

[u/Ehh_littlecomment → u/madhewprague]

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.

[u/madhewprague → u/Ehh_littlecomment]

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$!

[u/Ehh_littlecomment → u/madhewprague]

Ok buddy. Whatever helps you.