How do you profit of a company that hemorrhages a few billion a year?
While it runs a deficit you don’t or at least only through increased valuations, which ofc assume that you’ll eventually be able to turn a profit. Will this ever happen for OpenAI, i have no idea, but that is the bet. And for the likes of Microsoft spending a few billions on bets like this isn’t that big of a deal, just look at how much Meta burns in their VR department.
Even Amazon had AWS, which was the absurdly profitable core business at the center of a cost bleeding distribution center.
Uber was running a deficit for a long time until it turned profitable. It’s pretty normal for many new companies to burn money first before they turn a profit. The biggest cost seems to be training new models constantly, and i assume one hope is that eventually this slows down. Then they need to get operating costs down that where i think they currently roughly break even (?) or maybe run a minor loss, but that seems doable, considering the pace at which hardware is still improving.
OpenAI is doing nothing to generate economic value.
I wouldn’t say that it is nothing, but at this very moment it probably doesn’t equal the immense amount of resources poured into it. That said, if things improve both in terms of the quality of responses you can get from models as well as reduced costs to run them, then there is definitely huge economic potential.
That said, if things improve both in terms of the quality of responses you can get from models as well as reduced costs to run them, then there is definitely huge economic potential.
lmao, yeah if it worked it’d be impressive, but it hasn’t, it doesn’t, and it won’t ever because it fundamentally can’t.
Will this ever happen for OpenAI, i have no idea, but that is the bet.
More than a bet. It’s an engineered outcome, as Microsoft tries to force people into their AI walled garden.
Only question is how many people go along for the ride.
Uber was running a deficit for a long time until it turned profitable.
Uber is a great example of negative externalities, as the average Uber driver doesn’t earn money once you depreciate the value of the car being used.
That said, if things improve both in terms of the quality of responses you can get from models as well as reduced costs to run them, then there is definitely huge economic potential.
The line I’ve seen on AI boils down to this. AI won’t meet human economic potential. But it will run cheaper, which means paper growth, which means the investment is “worth it” at an industry level.
But at a macro level? Economy wide? Big Number may go up, but real productivity is going to slide the more AI attempts to replace human labor.
Uber ran at a loss to undercut the competition (traditional taxis) and passed the costs of that onto the drivers. Then once people were onboard they increased prices while hanging the drivers out to dry, to the point where ultimately the consumer pays as much as they did for a normal taxi but there’s some ease-of-use improvements from the app, a hell of a lot of money ending up in silicon valley instead of local taxi companies, and an ever-growing mass of human suffering as the gig economy erodes the ability of the working class to find economic security.
While it runs a deficit you don’t or at least only through increased valuations, which ofc assume that you’ll eventually be able to turn a profit. Will this ever happen for OpenAI, i have no idea, but that is the bet. And for the likes of Microsoft spending a few billions on bets like this isn’t that big of a deal, just look at how much Meta burns in their VR department.
Uber was running a deficit for a long time until it turned profitable. It’s pretty normal for many new companies to burn money first before they turn a profit. The biggest cost seems to be training new models constantly, and i assume one hope is that eventually this slows down. Then they need to get operating costs down that where i think they currently roughly break even (?) or maybe run a minor loss, but that seems doable, considering the pace at which hardware is still improving.
I wouldn’t say that it is nothing, but at this very moment it probably doesn’t equal the immense amount of resources poured into it. That said, if things improve both in terms of the quality of responses you can get from models as well as reduced costs to run them, then there is definitely huge economic potential.
lmao, yeah if it worked it’d be impressive, but it hasn’t, it doesn’t, and it won’t ever because it fundamentally can’t.
Just one more teraflop, bro.
More than a bet. It’s an engineered outcome, as Microsoft tries to force people into their AI walled garden.
Only question is how many people go along for the ride.
Uber is a great example of negative externalities, as the average Uber driver doesn’t earn money once you depreciate the value of the car being used.
The line I’ve seen on AI boils down to this. AI won’t meet human economic potential. But it will run cheaper, which means paper growth, which means the investment is “worth it” at an industry level.
But at a macro level? Economy wide? Big Number may go up, but real productivity is going to slide the more AI attempts to replace human labor.
citation needed
waves hand vaguely at a stack of FT articles
Uber ran at a loss to undercut the competition (traditional taxis) and passed the costs of that onto the drivers. Then once people were onboard they increased prices while hanging the drivers out to dry, to the point where ultimately the consumer pays as much as they did for a normal taxi but there’s some ease-of-use improvements from the app, a hell of a lot of money ending up in silicon valley instead of local taxi companies, and an ever-growing mass of human suffering as the gig economy erodes the ability of the working class to find economic security.