Both Uber and Spotify (and AWS too) had economics of scale going for them - the more users they have, the more the infrastructure could be leveraged. This does NOT work for LLMs. More users means using more compute, more advanced tasks (like coding) uses exponential amounts of compute. A single user running a complex task can make 8 Blackwell GPUs run full tilt, and you don't even have any guarantee that the output will be useable.

There are a few narrow areas where LLMs might be successful, like scanning for security vulnerabilities or searching large amounts of documents. The massive amount of money invested will never be recouped with these usage scenarios.

Although, most people aren't talking about Alphafold when they're talking about AI. They're usually specifically referring to the generative transformer models that are currently all the rage.

I doubt anyone would care too much about a linear regression model, or multi-layer peceptron , for example.

solving something like the Erdős unit distance conjecture

Tell me you listen to media news cycle without understanding what that actually mean without telling me that.

That's not exactly what happened, isn't it.

Not to bring up what’s also been accomplished in cyber security

Multiple new vectors of attacks, automation of attack pipelines...