In my opinion, the process you describe when transforming the AI approach into an engine is simply related to our understanding of why it works and how.

And this can clearly be done to cover a wide range of useful things.

But I would make two observations, first, neural nets are much more closely related to applied statistics than biology mimicry. The historical name should not matter much but it does because humans are driven by emotions, even in research.

Second, AGI is still too badly defined to be seriously discussed.

Every time people can observe some progress in the AI field, they are tempted to make predictions that, in my opinion, are impossible to make.

We're getting closer. That's all.