[Nevermark]

We probably have similar views, with some differences.

We definitely have and will pick up inspiration from the brain as you point out.

That is especially true in terms of the basic topologies of our brains neural networks. I.e. the painfully simplified artificial neuron model, two layer networks (which may roughly corrrespind to some single biological neurons that can have hierarchies of dendrites as I understand), then deep networks, convolution, recurrence, competitive layers and other topologies.

But I think the freedom of math to produce global algorithms directly allows faster innovation in a way that incremental change via evolution never had.

I expect GAI will always have some biologically inspired roots, but my untested (obviously!) opinion is that the first GAI will significantly benefit from global gradient based algorithms, and incorporate symbolic and database sides too.

The latter two not looking anything like how our neurons operate.