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Correct answer, never think about the future in terms of linear extrapolations. It's a non-linear differential equation with lots of variables and expect complex feedback loops. Systems react to change.

Jevons paradox: https://en.wikipedia.org/wiki/Jevons_paradox

you are assuming that cost is stopping from ppl using these technologies.

These things are not actually useful. They hyper optimzed it for coding usecase but it still sucks balls at it.

When the cost of training a model goes down, it doesn't simply become cheaper to the end user. In addition to that, the provider will train even larger and more capable models.

> the provider will train even larger and more capable models.

cost isn't the limiting factor in this though. 'even larger' models arn't 'more capable' . where did you get that from?