Uber’s situation was different, though. The reason Uber were bleeding money is because they purposefully made all their rides cheap to undercut the taxi businesses. People used Uber because it was cheaper than renting a taxi.

Now you can’t really find taxis anywhere, even at airports it’s a lot more difficult than it used to be.

Once the taxi business was disrupted enough, Uber’s pricing skyrocketed and customers had basically no other options for competition on pricing.

OpenAI basically created a new market. There is no AI chatbot incumbent to disrupt and swallow.

Before Uber did it, Amazon had been doing it for almost two decades. It's nothing new. There is a difference between 1 billion and 20 billion in losses, though. Amazon in, I forget, 2014? Ran a profitable quarter with I think $1 in profits, simply to prove they were in control of their finances, and "we can stop any time we want". Sam gets a lot of shade, but he's been around the YC block once or twice, I suspect whatever risk they're taking on is at least somewhat measured.

The problem here is that open weight models are already good enough for a majority of process automation and intelligence tasks and that is where a good chunk of efficiency corporate dollars are. So there's an ever shrinking slice of inference that will hit the frontier models and inference is where the insane margins are. Now to be fair, Claude co-work and Claude code/Codex do seem magical today and these potentially will continue to be high margin/leverage plays. Frontier models are also likely to push towards decision making - so we'll have to see how it shakes out but the bottom end is already commoditized and it is getting bigger and bigger.

Uber did not need this much money to cross the finish line, and faced less competition.