I was going for the shock value in "a poor fit approximation of a low resolution approximation"

As to what is the meaning of R^2 = 0.8, and if its good or bad, see second message:

bsky.app/profile/davi...

The real question of what is the precise threshold to qualify for a "good approximation" vs "bad approximation" unfortunately can only be truly studied at the system level

Unfortunately, these studies were never performed as of current date

Predicting the number of spikes in a 600ms time window, I'm sure you'll agree, is a very coarse temporal approximation of a neuron, and even this coarse temporal approximation is only approximated with a R^2=0.8 fit

Biological neurons are simply not approximated well with artificial neurons

There is no meaningful way in which temporal processing in the brain is actually continuous

1ms time discretization is likely sufficient for anything going on in the cortex, hippocampus, cerebellum, basal gaglia, etc.

In the periphery it might be different, but this is mostly sensing

The first line doesn't need to be true for the second line to obviously be true

A human brain can be modeled as a very large artificial neural network

The specific details about how large it needs to be can be debatable and actually matter, but the premise is not

Yeah, this is true, but maybe we're all just boomers, and the classical way should no longer be considered the best or only way?

So if you are contemplating doing a PhD sometime in your life, better enroll now

Today, code writing LLMs are the latest tools that make ideas be closer to their implementation

Not yet instant, though

Oh, i imagine the day where ideas are implemented and tested only minutes after being first thought of

That would be a great day

This is the promise of AI for me

Thanks

Thanks!