> Business minded folks are already starting to deeply question where the value is relative to the amount of money spent on training.
Not just training but inference too, right? They have to make money off each query.
Not just training but inference too, right? They have to make money off each query.
A challenge at the moment is a lot of the AI movement is led by folks that are brilliant technologists but have little to no experience running viable businesses or building a viable business plan. That was clearly part of why OpenAI has its turmoil in that some where trying to be tech purists where others knew the whole AI space will implode if it’s not a viable business. To some degree that seems to behind a lot of the recent chaos inside these larger AI companies.
This is saying nothing about "technologists" (or as they're starting to become derided as "wordcels": people that communicate well, but cannot execute anything themselves).
It would be... not trivial, but straightforward to map out the finances on everything involved, and see if there is room from any standpoint (engineering, financial, product, etc.) to get queries to breakeven, or even profitable.
But at that point, I believe the answer will be "no, it's not possible at the moment." So it becomes a game of stalling, and burning more money until R&D finds something new that may change that answer (a big if).
if the Good Lord's willing and the creek don't rise
They played their cards so damn right when deep learning was taking off.