[mlyle]

> Calculate how many transistors and watts of power you'd need to replicate that functionality.

I'm curious as to your answer. Because if one's building a purpose-built analog computer for the task, my estimate is a few hundred transistors, a few thousand passives, and ... an absolutely trivial amount of power on modern process.

[Causality1]

I'm curious how we're even going to manage 420,000 pixels' worth (60,000 ommatidia, approximately 7 pixels each) of input with only a few hundred transistors, let alone do vector analysis on it.

But let's say we can. Let's say we need 320 transistors, which would be 20 transistors per pixel. That's pretending 99.7% of the seven thousand synapses each neuron has are useless for our purpose, but we'll do it. A chimp brain runs all the autonomous physical processes of a humanoid body while only having 22 billion neurons. We'll also pretend, wrongly, that chimps have no mind or emotions at all and that we only need the extra human neurons to make a sapient mind.

Humans have 86 billion neurons. Subtracting 22 gives us 64 billion, times 20 transistors per neuron gives us 1.28 trillion transistors.

1.28 trillion transistors, even with a bunch of handwaving to make it easier, and even pretending we exactly understood how sapience worked in the first place.

[mlyle]

> I'm curious how we're even going to manage 420,000 pixels' worth (60,000 ommatidia, approximately 7 pixels each) of input with only a few hundred transistors, let alone do vector analysis on it.

If you define the problem as importing 420,000 pixels, and target recognitions, and vector analysis, then you need a whole lot more computation than the organism uses. But presumably you're going to also get better results. We both know that's not exactly what's happening, I think.

That is, we know we can solve similar tracking problems with a whole lot less state.

> That's pretending 99.7% of the seven thousand synapses each neuron has are useless for our purpose

Not really... I think we can imagine a whole lot of passives / linear operations involved, along with the big nonlinear processes we need transistors for.

We're also assuming there's no net benefit to cognition that can happen using transistors, I'll note-- e.g. they have a ton of bandwidth compared to neurons, can be multiplexed more readily, etc....

> Humans have 86 billion neurons. Subtracting 22 gives us 64 billion, times 20 transistors per neuron gives us 1.28 trillion transistors.

So about half the number packed onto Cerebras WSE-2 today.

> even pretending we exactly understood how sapience worked in the first place.

This is the big problem.

[Ginden]

> 1.28 trillion transistors

So, basically, 45 x RTX 3080?