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Some users defend research on neural convergence between organic and artificial neurons as already actionable for improving ML algorithms, while others dismiss its practical implications as nonexistent or very far in the future.
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@Grady_Booch @dyamins Less sure about the neuroscience side, but studying this kind of convergence is absolutely actionable in developing better ML algs. Identifying convergent structures informs us about how to create interfaces between different nets. e.g. https://arxiv.org/abs/2602.17584 and many others
maybe it does” and “ perhaps the fact” Both quotes from your paper. Extraordinary claims require extraordinary evidence, and all you offer is an unsupported, indefensible, and vague observation of coincidence and yet you inflate this to say “ well obviously this is formed the same thing as how the brain evolved”. Furthermore, to say that AIs “evolve” ignores the reality that in the end, it’s the human driving the evolution. The evolution of the human mind had no such blind watchmaker; large language models do. You might as well say that soap, bubbles and organic cells show a convergent evolution because they’re both affected by reducing surface tension. Amusing. And unactionable.
@Grady_Booch @dyamins I just want to push back on your characterization that this work is simply amusing but not actionable. In ML it already is. In neuro one could imagine implications toward future brain-machine interfaces.
@phillip_isola @dyamins Again, a different issue. The original claim was that this was evidence of convergent evolution between organic and artificial neurons.
@phillip_isola @dyamins I can imagine many things. But that is not one of them, or at best, it is one that is very far in the future.
@phillip_isola @dyamins Again, a different issue. The original claim was that this was evidence of convergent evolution between organic and artificial neurons.