zlacker

It depends on what kind of simulation you're trying to run, though. You don't need to perfectly model the physically moving heads and magnetic oscillations of a hard drive to emulate an old PC; it may be enough to just store the bytes.

I suspect if you just want an automaton that provides the utility of a human brain, we'll be fine just using statistical approximations based on what we see biological neurons doing. The utility of LLMs so far has moved the needle in that direction for sure, although there's still enough we don't know about cognition that we could still hit a surprise brick wall when we start trying to build GPT-6 or whatever. But even so, a prediction of 2047 for that kind of AGI is plausible (ironically, any semblance of Moore's Law probably won't last until then).

On the other hand, if you want to model a particular human brain... well, then things get extremely hairy scientifically, philosophically, and ethically.

>>gary_0+(OP)
> based on what we see biological neurons doing

We have almost no idea what biological neurons are doing, or why. At least we didn't when I got my PhD in neuroscience a little over 10 years ago. Maybe it's a solved problem by now.

>>dmd+81
It made a big step forward, imagery is more powerfull now and some people are starting to grow organoids made of neurons. There is a lot to learn, but as soon as we can get good data, AI will step in and digest it I guess.

>>dmd+81
I'm referring to the various times biological neurons have been (and will likely continue to be) the inspiration for artificial neurons[0]. I acknowledge that the word "inspiration" is doing a lot of work here, but the research continues[1][2]. If you have a PhD in neuroscience, I understand your need to push back on the hand-wavy optimism of the technologists, but I think saying "almost no idea" is going a little far. Neuroscientists are not looking up from their microscopes and fMRI's, throwing up their hands, and giving up. Yes, there is a lot of work left to do, but it seems needlessly pessimistic to say we have made almost no progress either in understanding biological neurons or in moving forward with their distantly related artificial counterparts.

Just off the top of my head, in my lifetime, I have seen discoveries regarding new neuropeptides/neurotransmitters such as orexin, starting to understand glial cells, new treatments for brain diseases such as epilepsy, new insight into neural metabolism, and better mapping of human neuroanatomy. I might only be a layman observing, but I have a hard time believing anyone can think we've made almost no progress.

[0] https://en.wikipedia.org/wiki/History_of_artificial_neural_n...

[1] https://ai.stackexchange.com/a/3936

[2] https://www.nature.com/articles/s41598-021-84813-6