We don’t even know what consciousness or sentience is, or how the brain really works.
We know more than you might realize. For instance, consciousness is the ∆ of separate brain areas; when they go all in sync, consciousness is lost. We see a similar behavior with NNs.
It’s nice that you mentioned quantum effects, since the NN models all require a certain degree of randomness (“temperature”) to return the best results.
trying to accurately simulate a rat’s brain have not brought us much closer
There lies the problem. Current NNs have overcome the limitations of 1:1 accurate simulations by solving only for the relevant parts, then increasing the parameter counts to a point where they solve better than the original thing.
It’s kind of a brute force approach, but the results speak for themselves.
I’m afraid the “state of the art” in 2020, was not the same as the “state of the art” in 2024. We have a new tool: LLMs. They are the glue needed to bring all the siloed AIs together, a radical change just like that from air flight to spaceflight.
Where did I exaggerate anything?
We know more than you might realize. For instance, consciousness is the ∆ of separate brain areas; when they go all in sync, consciousness is lost. We see a similar behavior with NNs.
It’s nice that you mentioned quantum effects, since the NN models all require a certain degree of randomness (“temperature”) to return the best results.
There lies the problem. Current NNs have overcome the limitations of 1:1 accurate simulations by solving only for the relevant parts, then increasing the parameter counts to a point where they solve better than the original thing.
It’s kind of a brute force approach, but the results speak for themselves.
I’m afraid the “state of the art” in 2020, was not the same as the “state of the art” in 2024. We have a new tool: LLMs. They are the glue needed to bring all the siloed AIs together, a radical change just like that from air flight to spaceflight.