If we create a neural net that has the equivalent knowledge and intelligence of a human 5 year old but that neural net learns slower and was produced on 10 trillion pieces of data then we STILL have created a sentient AI despite the fact the learning algorithm is shit.
Which doesn't stop neural networks being immensely useful (and even significantly more useful than humans in relevant domains, especially five year old humans), but might well stop them from being sentient. Neural nets are probably already better at passing Turing tests than five year olds, but the five year old's love of mummy doesn't come from statistical analysis of a corpus of texts about love and mummies.
I would soften the idea a little bit by noting that as a little human grows up and learns more things, its brain plasticity goes down over time. AFAIK there’s no evidence that learning “saturates” the ability to learn other things, and the loss of plasticity is probably mainly linked to aging and/or other factors, but functionally the effect is very much the same: humans that know a lot of things typically have less capacity for learning.
https://www.youtube.com/watch?v=ZeiMhUlipTk
These people are clearly still sentient.
There is still some form of memory there but the overall mechanism is largely gone.
I don’t think we need to emulate every connection, every neuron, or every circuit— but I do think the broader neuroanatomy (this region mainly processes inputs from that region, and has these feedback loops, and then mainly has outputs to this other region) is essential to emulating the way brains work.
I may very well be wrong, and I hope people in the field can forgive my insolent impression, but my impression as a biochemist/engineer is that people in the comp sci world and people in the neuroanatomy world don’t really speak the same language: one is usually bad at the other, so there isn’t really a tight transdisciplinary coupling of forces.