While there is no reasonable explanation for why Uber can't just turn a profit (and it looks like they have for the last few years), deep-learning models have very hard physical constraints on how much they cost.
I would argue that physical cars driven by people have much harder constraints on cost than LLMs which can see huge cost savings (for the same performance model) as hardware improves. I agree that they aren't perfect parallels but in principle there's nothing stopping AI companies from massively cutting R&D and raising prices until marginal revenue is positive, it just would mean accepting not getting "take over the world" level profitability or getting run out of town by someone willing to keep burning money.