Comment by nawgz
6 months ago
> I disagree that all the computer processors in the world combined don't have enough raw processing power to simulate a single bee brain. That to me is an absurd idea.
A bee weighs 100mg. If they are 5% brain, their brain weighs 5mg. 5mg of carbon is 2.5 * 10^20 atoms.
The largest supercomputers, at hundreds of trillions of transistors, come in at 2-5 * 10^14 transistors.
I don't think that combining all the computers in the world would give us 1 transistor per atom in a bee brain, and I additionally have to imagine transistors are incapable of simulating an atom by multiple orders of magnitude (i.e. 1 atom would require > 1 * 1 ^ 4 transistors) in realtime.
So, I would argue that our level of compute is still insufficient to simulate even a simple insect brain in realtime. Perhaps you could compute 1 second of bee thinking in an hour using all our compute.
And then, of course, comes into play that we have no idea how to simulate an atom in full fidelity.
> A bee weighs 100mg. If they are 5% brain, their brain weighs 5mg. 5mg of carbon is 2.5 * 10^20 atoms.
Any rational characterization of the problem has left the building here.
Nobody wants to simulate any creature's brain or nervous system atom for atom.
Most of what atoms do in any cell, including neurological cells, is operate a vast number of complex but common survival systems. And the very small fraction supporting specifically neurological behavior, do not meaningfully contribute at the level where specifics of individual atoms matter, but at a level many orders of magnitude higher in scale.
We’re talking about whether or not humanity has enough compute to simulate a bee brain, how can us having orders of magnitude less transistors than there are atoms in the system we wish to simulate possibly be hand waved away? A single transistor doesn’t do much, regardless of how much you wish to baldly assert atoms are supposedly trivial.
Perhaps you are meaning to compare transistors with neurons? If we do that, then yes, a transistor is a lot simpler than a neuron. But transistors are also insanely fast compared to neurons, so transistors do far FAR more, per unit of time.
A bee brain might have a million neurons, operating at maximum speed of about 250 Hz.
10^6 neurons x 250 Hz
= 2.5 x 10^8 Hz for a bee brain.
We can easily model that many neurons with a trillion transistors, operating at 100 Ghz. (If that sounds fast to you, keep in mind that CPU clock speeds account for many transistors switching in series.)
10^12 transistors x 10^11 Hz
= 10^23 Hz for a CPU
That is a factor of 4 x 10^14 more powerful.
So yeah, the only problem for modeling a bee brain is identifying the organization of its neurons.
Nature does a lot with a little. Trillions of bee life years went into designing a really efficient bee brain.
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Atoms:
A bee brain might have 10^20 atoms. Atoms interact at speeds that are far beyond anything we are talking about here. But they don't "switch", they bounce around every which way and slowly end up reacting when they connect with the right conditions. This is called Brownian motion and its not computation, its natures way of using the chaos produced by heat to give compounds so many chances to find their right context that they eventually do.
While we could not easily model that many atoms, nobody wants to (with regard to bees). Atoms are neither the "transistors" or the neurons of a bee brain.
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You’re not trying to simulate a brain atom for atom. Individual atoms don’t do much on their own. Even if you did do that, you’d really need to simulate electron flow, which is whole other level.
Now, simulating what outputs the bees brain yields from a set of stimuli — that could be done. If it could be done as fast as a brain is a whole other question, and I’m not sure of that answer.