Earlier quoted context omitted.
> None of these companies, be it Anthropic, OpenAI, xAI, Google, Meta, Microsoft, are profitable in the AI department, Citation needed. All reporting is that they are profitable on the inference side and all the VC money is going to building more data centers to run more inference. (Note that the coding subscription models are probably only break even on average - the money is in the API) > The Chinese models are kee…
What does profitable on inference mean? As far as I can tell, none of these companies have rigidly defined it, let alone it being a GAAP number. And yeah, if you subtract out all your R&D, payroll, sales, marketing, and other overhead, and get someone else to take on the debt or dig into their free cash flow to build the hugely expensive infrastructure on which you depend, it'd be pretty hard to not be "profitable".…
No. Anthropic at least expects to be profitable this year:
> Anthropic expects its gross profit margin, which measures how much revenue it makes compared to the cost of producing that revenue—largely from running servers—to swing from negative 94% last year to as much as 50% this year and 77% in 2028.
> And yeah, if you subtract out all your R&D, payroll, sales, marketing, and other overhead, and get someone else to take on the debt or dig into their free cash flow to build the hugely expensive infrastructure on which you depend, it'd be pretty hard to not be "profitable".
I think excluding capital expense on infrastructure isn't unreasonable and is done in most industries.
It's worth noting that AI infrastructure has turned out to be an unbelievably good investment. Inference on a 4 year old H100 chip costs more now than it did brand new! That makes the hyperscaler's depreciation schedules look very (and unexpectedly!) conservative (!!)