If brains were just very fast and powerful computers, then neuroscientist should be able to work with computers and engineers on brains.

Does not follow. Different architectures require different specialisations. One is research into something nature presents us, the other (at least the engineering part) is creating something. Completely different fields. And btw the analytical tools neuroscientists have are not exactly stellar, that's why they can't understand microprocessors (the paper is tongue in cheek but also serious).

But they are not equivalent.

They are. If you doubt that, you do not understand computation. You can read up on Turing equivalence yourself.

Consciousness, intelligence, memory, world modeling, motor control and input consolidation are way more complex than just faster computing.

The fuck has "fast" to do with "complex". Also the mechanisms probably aren't terribly complex, how the different parts mesh together to give rise to a synergistic whole creates the complexity. Also I already addressed the distinction between "make things run" and "make them run fast". A dog-slow AGI is still an AGI.

The brain is not a Turing machine. It does not process tokens one at a time.

And neither are microprocessors Turing machines. A thing does not need to be a Turing machine to be Turing complete.

Turing completeness is a technology term

Mathematical would be accurate.

it shares with Turing machines the name alone,

Nope the Turing machine is one example of a Turing complete system. That's more than "shares a name".

Turing’s philosophical argument was not meant to be a test or guarantee of anything. Complete misuse of the concept.

You're probably thinking of the Turing test. That doesn't have to do anything with Turing machines, Turing equivalence, or Turing completeness, yes. Indeed, getting the Turing test involved and confused with the other three things is probably the reason why you wrote a whole paragraph of pure nonsense.

From all I know none of the systems that people have built come even close to testing the speedup: Is error correction going to get harder and harder the larger the system is, the more you ask it to compute? It might not be the case but quantum uncertainty is a thing so it's not baseless naysaying, either.

Let me put on my tinfoil hat: Quantum physicists aren't excited to talk about the possibility that the whole thing could be a dead end because that's not how you get to do cool quantum experiments on VC money and it's not like they aren't doing valuable research, it's just that it might be a giant money sink for the VCs which of course is also a net positive. Trying to break the limit might be the only way to test it, and that in turn might actually narrow things down in physics which is itching for experiments which can break the models because we know that they're subtly wrong, just not how, data is needed to narrow things down.