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 do microprocessors. 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.