Hardware is bound by even harder limits (transistor's gate thickness, speed of light, Amdahl's law, Landauer's limit and so on).

But that doesn't disprove the hypothesis that in principle you can have an effective self-improvement loop (my guess is that it would quickly turn into extremely limited gains that do not justify the expenditure).

Any such "self-improvement loop" would have a natural ceiling, though. From both algorithmic complexity and hardware limits of underlying compute substrate.

P.S. I am not arguing against, but rather agreeing with you.

The natural ceiling is the amount of compute per unit of energy. At the point you can no longer improve energy efficiency, you can still add more energy to operate more compute capacity.

Which hints that truly superintelligent AIs will consume vast amount of energy to operate and matter to build.

At some point they’ll hit the speed of light as a limit to how quickly it can propagate its internal state to itself - as the brain grows larger, the mind slows down or breaks apart into smaller units that can work faster before rejoining the bigger entity and propagating its new state.

Must feel really strange.

Realistically, the physical limits to computation are the speed of light and energy dissipation.