alt Hacker News> This, to me, seems to significantly underestimate the complexity of modern learning-models
One general impression I have, having read the reactions by biologists to stuff like Kurzweil and people who believe we're close to a computational understanding of biology is that all the computer science people massively, MASSIVELY underestimate the extent to which we still do not understand how even a single cell works.
Sure, we can model things stochastically, or fiddle with DNA and be able to predict the results, but there's a bunch of stuff in the middle that we only have a functional understanding of. We know with <xxx> input, you get <yyy>, etc..., but the how is still a mystery.
This is everywhere in biology.
If you think biologists are underestimating complexity, you have the sign wrong.
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I expect the conclusion is correct, but the argument isn't really valid. Our knowledge of cells tells us only and precisely about our knowledge of cells. We have some gaping holes in our fundamental knowledge of the universe (what is it, how did it happen, etc) and nobody can claim with any certainty to understand how any of the basic things happen. It is a mystery of such epic proportions it is hard to even articulate what an answer could look like, let alone how we would work it out. That hasn't stopped the development of a bunch of useful models and theories of physics that explain a lot of local observations really well.
yeah I'll believe we are close to cracking biological intelligence once openworm gets at all close
https://www.wired.com/story/openworm-worm-simulator-biology-...
I don't believe we are close to a computational understanding of biology. However, there is a difference between not having the understanding and claiming that because we don't understand it, there is definitively some Aristotelian non-computational anima in all life.
If I handed someone who had never seen an artificial neural network, and handed them a PCB with some giant LLM hard-coded into it, I suspect they would struggle to define how it reacts to its inputs, despite the fact that modern silicon designs are extremely regular compared to biological systems.