The cost per 1M tokens has dropped, significantly, since 2023 or so.
The problem is that it’s just not commercially viable, because you can’t just say “We make money on inference”, because that’s a stupid thing to say. That’s like saying the cash register at the supermarket is really profitable, because you sell a product for a higher price than it costs you to buy it. It may be true, but that’s not how any of this works.
You can’t just stop developing new products, because if you do, your existing product becomes worthless. If Ford just started selling their current models, they would make a lot of profit right now… and then none in a few years as their competitors sell newer, fancier cars. If OpenAI stops training new models, they will make a lot of money right now, and then nothing in 3 to 6 months from now.
Token pricing could double, and be free for OpenAI, and it still wouldn’t save them, because you can’t judge a business on how much money they earn at the cash register.
I just don’t get the business model at all, but maybe I’m just too stupid to understand
There is no businessmodel. The trick to keep burning cash, keep the stock high, keep the compensation for the people at the top flowing. The company can burn all the capital it wants, because the people at the top will keep getting paid.
One layer below that, there’s a whole bunch of business idiots who think LLMs will let them save on paying their employees, so they’re very invested in it.
One layer below that are a bunch of senior managemers who are just as stupid, but whose performance goals were just tied LLM use, so they’ve got a great reason to push it on everyone.
If OpenAI stops training new models, they will make a lot of money right now, and then nothing in 3 to 6 months from now.
A problem the 2 big labs have, with OpenAI the bigger problem, is forced compute leases. The training is basically free because they have way too much GPUs already rented.
The problem is that it’s just not commercially viable, because you can’t just say “We make money on inference”, because that’s a stupid thing to say. That’s like saying the cash register at the supermarket is really profitable, because you sell a product for a higher price than it costs you to buy it. It may be true, but that’s not how any of this works.
You can’t just stop developing new products, because if you do, your existing product becomes worthless. If Ford just started selling their current models, they would make a lot of profit right now… and then none in a few years as their competitors sell newer, fancier cars. If OpenAI stops training new models, they will make a lot of money right now, and then nothing in 3 to 6 months from now.
Token pricing could double, and be free for OpenAI, and it still wouldn’t save them, because you can’t judge a business on how much money they earn at the cash register.
There is no businessmodel. The trick to keep burning cash, keep the stock high, keep the compensation for the people at the top flowing. The company can burn all the capital it wants, because the people at the top will keep getting paid.
One layer below that, there’s a whole bunch of business idiots who think LLMs will let them save on paying their employees, so they’re very invested in it.
One layer below that are a bunch of senior managemers who are just as stupid, but whose performance goals were just tied LLM use, so they’ve got a great reason to push it on everyone.
A problem the 2 big labs have, with OpenAI the bigger problem, is forced compute leases. The training is basically free because they have way too much GPUs already rented.