[hibikir]

Competition is great, but it's so much better when it is all about shaving costs. I am afraid that what we are seeing here is an arms race with no moat: Something that will behave a lot like a Vickrey auction. The competitors all lose money in the investment, and since a winner takes all, and it never makes sense to stop the marginal investment when you think you have a chance to win, ultimately more resources are spent than the value ever created.

This might not be what we are facing here, but seeing how little moat anyone on AI has, I just can't discount the risk. And then instead of the consumers of today getting a great deal, we zoom out and see that 5x was spent developing the tech than it needed to, and that's not all that great economically as a whole. It's not as if, say, the weights from a 3 year old model are just useful capital to be reused later, like, say, when in the dot com boom we ended up with way too much fiber that was needed, but that could be bought and turned on profitably later.

[skybrian]

Three-year-old models aren't useful because there are (1) cheaper models that are roughly equivalent, and (2) better models.

If Sonnet 4.6 is actually "good enough" in some respects, maybe the models will just get cheaper along one branch, while they get better on a different branch.

[tomjakubowski]

It's funny, it sure seems like software projects in general follow the Lindy effect: considering their age and mindshare, I can safely predict gcc, emacs, SQLite, and Python will still be running somewhere ten, 20, 30 years from now. Indeed, people will choose to use certain software specifically because it's been around forever; it's tried and true.

But LLMs, and AI-related tooling, seem to really buck that trend: they're obsoleted almost as soon as they're released.

[teaearlgraycold]

People are rapidly learning how to improve model capabilities and lower resource requirements. The models we throw away as we go are the steps we climbed along the way.