Thanks for the attempt at a position summary!

General purpose systems have their attractions. The human brain has done well out of the generality that it has.

However, I do see many virtues in narrower systems. Indeed, if you want to perform some specific task, a narrow expert system focussed on the problem domain will probably do a somewhat better job than a general purpose system. So, I would not say:

It is not interesting to build specialized compressors.

Rather, each specialized compressor encodes a little bit of a more general intelligence.

This is also a bit of a misrepresentation:

but the only empirical fact we require is that the world is computable

Occam's razor is the critical thing, really. That is an "empirical fact" - and without it we are pretty lost.

We do want general-purpose systems. If we have those, they can build whatever narrow systems we might need.

There are two visions of the path towards machine intelligence - one is of broadening narrow systems, and the other is of general forecasting systems increasing in power: the "forecasting first" scenario. Both seem likely to be important. I tend to promote the second approach partly for technical reasons, but partly because it currently gets so little air time and attention.