I guess the obvious question is whether something that mimics biology closer is actually useful. Computers are useful exactly because they aren't the same as us. LLMs are useful because they aren't the same as us. The goal is not to be as close to biology as possible, it's to be useful.
Neural networks have turned out to be pretty useful. The goal of distributed parallel processing wasn't to recreate the brain but to recreate it's capabilities.
Neuromorphic chips have been 5 years away for 15 years now.. Nevertheless the Schultz dopamine-TD error convergence is one of the coolest results in neuroscience
I guess the obvious question is whether something that mimics biology closer is actually useful. Computers are useful exactly because they aren't the same as us. LLMs are useful because they aren't the same as us. The goal is not to be as close to biology as possible, it's to be useful.
Neural networks have turned out to be pretty useful. The goal of distributed parallel processing wasn't to recreate the brain but to recreate it's capabilities.
From article:
> Cause and Effect: If Neuron A fires just a few milliseconds before Neuron B, the brain assumes A caused B. The synapse between them gets stronger.
A recent study from Stanford found that it's more complex than this rule, some synapses followed it, some did the opposite, etc.
Neuromorphic chips have been 5 years away for 15 years now.. Nevertheless the Schultz dopamine-TD error convergence is one of the coolest results in neuroscience