3 ms·
The cash burn is not the problem. You can’t build a big business without it. The difference is network effects. With ride sharing apps, you need a lot of dri
by arctic-true 2mo ago
The cash burn is not the problem. You can’t build a big business without it. The difference is network effects. With ride sharing apps, you need a lot of drivers and riders collected on one platform. It is nearly always better, for both drivers and riders, to switch to a larger platform. Thus, it was worthwhile to spend the money to become the biggest fish. Once this was accomplished, Uber could raise prices because switching to a smaller rival would mean less availability, and thus less utility (for riders) or less earnings (for drivers).
With AI, by contrast - at least in its current state - there is no benefit to be gained from using the same model provider as somebody else. Switching is trivial for most use cases. Since they can’t capture consumers using network effects, the labs only have the levers of price and quality to pull to acquire and retain customers. To pull the price lever, they have to reduce their revenues; to pull the quality lever, they have to increase their expenditures. Indeed, they are sowing the seeds of their own demise by making inference cheaper and more efficient: since they can’t exercise pricing pressure, efficiency gains will be passed on to the consumer, which is unsustainable if your GPU debt is priced based on yesterday’s efficiency expectations.
- rich_sasha 2mo agoThis only works up to a point. Plenty of different makers of phones for example all making fungible phones at ever lower prices, yet managing to eke out a profit. I can see a world where OpenAI, Anthropic, Chinese companies corner the market, make themselves indispensable and start charging market rates, while also getting better and more cost efficient.
- arctic-true 2mo agoHere again you have network effects, though. I personally have an iPhone because it’s what all my friends and family use and there are communication functions that are much easier to engage with if you all have the same sort of device. It’s also not trivial to switch, you need to, at minimum, go to the store or wait for something to get delivered - to say nothing of the wasted money from buying multiple phones. If I have unused OpenAI tokens I can burn them on side quests or something. If you have an unused iPhone you need to find a way to sell/return it or eat the cost. There’s also potential violations of your contract with your mobile carrier, etc. If I’m using ChatGPT and I decide I want to use DeepSeek instead, I am only a couple of keystrokes away from doing it, and that’s if I have never used DeepSeek before. As for your “corner the market” scenario, it’s possible, but unlikely. It is too easy to enter; even if you somehow got all of the major players to commit to growing their margins - and somehow manage not to violate the antitrust laws in the process - a newcomer could spoil the party far easier than it could in an industry like mobile phones (where you need tons of components, manufacturing capacity, network relationships, etc.) or ride sharing (where you need a large user base to justify your existence).
- rich_sasha 2mo agoMmaybe- not sure. For technical applications like coding, perhaps. Though even there you have plenty of opinions about different models’ differences on subtle features, this model writes bad tests, that one is bad at JavaScript etc. But the real sales pitch is that AI overtakes everything. That the YC cohort of 2032 will be just CEO, sales guy and a massive AI bill. It’s not entirely impossible IMO, either. Then you totally get network effects. All your company documents, discussions, context etc are in there, your agents/employees whom you finally taught to do the job right. And I’m guessing the REST API for extracting your data is absent.