Comment by nawgz | Hacker News Reader

Comment by nawgz | Hacker News Reader

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> 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.

Oh yeah, you're right, we have 4 * 10^14 more compute than an insectoid brain in real time. Come the fuck off it.

This is the same guy who said rational characterizations had left right before waving away the complexity of a trillion atoms. Painful to imagine how smarmy you are.

Well you have left your written record of (1) persistently confusing atoms with neurons, (2) an inability to explain where your confusion comes from outside of just repeating it, along side (3) snide responses to someone who in good faith took the time to explain the difference to you.

One more time:

Not understanding something is not the same as needing high compute. And the amount of compute we have today is colossal.

Simulating a high level system (neurons or transistors) is not the same as simulating their low level implementations (all the atoms and electrons in either of them).

Some large LLMs (interactive summaries of a large percentage of the entire human race's verbalized knowledge at moderate depth), can be run on a single MacStudio M3 Ultra with 512GB of RAM.

Modeling a bee brain will require a tiny fraction of that computationally.

> 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.

I don’t see where I reference neurons, care to quote me rather than adding misleading citation looking (1) strings to your text?

Indeed, looking towards full compute simulation of a physical system, I reference one of its smallest physical components - atoms - and draw an analogy to the transistor in compute. You make no argument for why an atom needn’t be simulated in a system but nonetheless hand wave it away, lifting yourself to neurons as if their behavior is well understood, finally acting as if clock speed of a transistor is somehow related to the unsourced “clock speed” of a neuron.

So, to me it seems pretty transparently obvious you’ve failed to grasp the two topics in play here - whether there is enough brute force compute available, and what models of simulating a system like a brain exist - and in your confusion, went ahead and self aggrandized your own typing to cast out the conversation that played out before you joined.

I encourage you to not respond, and instead to use that energy to read someone else’s argument from a steel man perspective rather than this diminishing arrogance you display.

> I don’t see where I reference neurons, care to quote me rather than adding misleading citation looking (1) strings to your text?

A brain operates at the level of neurons, not individual atoms.

The vast majority of atoms in the brain are there to do non-cognitive things.

The tiny fraction actually doing neural things are insanely redundant.

You can simulate a 1 kg ball dropping from 100 meters, to time its collision with the Earth, by simulating all its atoms. But the net mass of the ball is what matters. Not the individual atom masses and movements.

Likewise, you can simulate a brain by simulating all its atoms. But the net movements of transmitters are what matter, not all those individual atomic movements.

Neurons and transistors both operate on net signals precisely so they can be insensitive to individual atomic behaviors. If they were sensitive to individual atoms, they would be noise generators instead of reliable information processors.

And because they are designed to be insensitive to individual atomic behaviors, we don't have to model them at the atomic level.

(Which is impossible anyway. The quantum field equations for even two interacting atoms are complex. There is no visible future in which the atoms of a single neuron could all be simulated accurately, much less a brain. Even then, because of quantum noise, the atomic model wouldn't be any more accurate.)

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My apologies on being so blunt at the beginning of this conversation. That was unnecessary.

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.

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