3 ms·

There's a huge difference between cost of inference and profit margin of the "big" providers, and the cost of inference for cloud-hosted open-weights. It's the

• vessenes 8mo ago
  Thank you for real data. Please moderate the use of the word profitable talking to engineers! We get the same circle jerk over and over here. Profit implies a GAAP accrual of some sort. On any accrual schedule tied to reality, the companies are profitable now - that is, inference margin on each given model has more than paid for capital costs of training and deploying those models. That the companies get to show a loss is a feature of cash-basis accounting: they made $100m net on that last model? Good news, We’re spending $1b on the next! Infinite tax losses! The companies will not be cashflow positive for years. Why does this persnickety difference matter? It matters to me because I care about the engineers here - and they seem collectively likely to either short every AI company IPOing, or just quietly ignore AI impact on their livelihood, or head off into a corner and go catatonic - all based on a worldview that “this is collective insanity and everything here is going to eventually go bankrupt” — none of those are good outcomes. Shorting might be, but it should be done judiciously, and understanding the financial factors at play. So, anyway, long plea over - but, allow me to plead: cashflow positive if you want to make the point you were making.