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Neurons aren't anything like transistors: they're CPU cores, and each individual neuron in a mammalian cerebral cortex is the equivalent of a deep artificial ne

Neurons aren't anything like transistors: they're CPU cores, and each individual neuron in a mammalian cerebral cortex is the equivalent of a deep artificial neural network: https://www.quantamagazine.org/how-computationally-complex-is-a-single-neuron-20210902/ https://www.quantamagazine.org/how-computationally-complex-i... In particular the human brain is an 80-billion core processor with each core running at 300Hz. Its architecture is not so good at FLOPs and other things we typically use computers for, but overall human brains dramatically outperform anything in 2024 except the world's fastest supercomputer.

spiderice 3y ago
> overall Meaning at specific tasks, right? Because obviously even the weakest modern computers out perform humans at certain kinds of tasks.
- nicklecompte 3y ago
  No, I mean in terms of raw computational power: 300Hz * 80 billion cores. Again the architecture does not work well for churning through a giant array of floating point arithmetic since 300Hz is a limiting factor for that specific type of computation. But that's not the kind of problem the human brain was designed to solve.
wruza 3y ago
I think the correct term is “outclasses”, not “outperforms”. Our performance is pretty bad, especially on average and compared to other species (when comparable).
usrbinbash 3y ago
> they're CPU cores, No, they are really not. A Neuron on its own is capable of exactly one thing, and that's signal integration from it's dendrites. That's it. Wait until the excitation potential reaches the point where the Potassium channels switch and boum: Signal cascade goes down the axon. The only moderation a single neuron is capable of, is varying signal resistance to filter out repeating noise. > https://www.quantamagazine.org/how-computationally-complex-is-a-single-neuron-20210902/ https://www.quantamagazine.org/how-computationally-complex-i... Computational complexity doesn't indicate computational capability. There are any number of systems that stubbornly refuse to be capable supercomputers, despite being incredibly hard to simulate. Accurately simulating every aspect of the liquid flow through an acorn leaf, with it's billions of micro and nanometer channels, would easily be one of the most difficult tasks in the history of computing, and yet, acorn leaves are not even capable of the simplest thought, and the entire modus operandi of water flow through an entire tree can be accurately summarized in a simple 1-page diagram. Every single muscle fiber with its trillions of moving cytoskeleton components, has a much higher complexity than a neuron, that doesn't mean muscles are supercomputers.
- Engineering-MD 3y ago
  I agree that complexity doesn’t imply capability. However, in general they are different architectures which cannot be readily compared. Saying a neurone can only do signal integration from dendrites is like saying a computer can only add 0 to 1. The reality is those dendrites are spatially arranged and may perform computations before reaching an action potential. Also, neurones are still cells and can change structure/position as well as gene expression, which may (or may not) impact on processing over a longer time interval.

spiderice 3y ago

> overall Meaning at specific tasks, right? Because obviously even the weakest modern computers out perform humans at certain kinds of tasks.

nicklecompte 3y ago
No, I mean in terms of raw computational power: 300Hz * 80 billion cores. Again the architecture does not work well for churning through a giant array of floating point arithmetic since 300Hz is a limiting factor for that specific type of computation. But that's not the kind of problem the human brain was designed to solve.

wruza 3y ago

I think the correct term is “outclasses”, not “outperforms”. Our performance is pretty bad, especially on average and compared to other species (when comparable).

usrbinbash 3y ago

> they're CPU cores, No, they are really not. A Neuron on its own is capable of exactly one thing, and that's signal integration from it's dendrites. That's it. Wait until the excitation potential reaches the point where the Potassium channels switch and boum: Signal cascade goes down the axon. The only moderation a single neuron is capable of, is varying signal resistance to filter out repeating noise. > https://www.quantamagazine.org/how-computationally-complex-is-a-single-neuron-20210902/ https://www.quantamagazine.org/how-computationally-complex-i... Computational complexity doesn't indicate computational capability. There are any number of systems that stubbornly refuse to be capable supercomputers, despite being incredibly hard to simulate. Accurately simulating every aspect of the liquid flow through an acorn leaf, with it's billions of micro and nanometer channels, would easily be one of the most difficult tasks in the history of computing, and yet, acorn leaves are not even capable of the simplest thought, and the entire modus operandi of water flow through an entire tree can be accurately summarized in a simple 1-page diagram. Every single muscle fiber with its trillions of moving cytoskeleton components, has a much higher complexity than a neuron, that doesn't mean muscles are supercomputers.

Engineering-MD 3y ago
I agree that complexity doesn’t imply capability. However, in general they are different architectures which cannot be readily compared. Saying a neurone can only do signal integration from dendrites is like saying a computer can only add 0 to 1. The reality is those dendrites are spatially arranged and may perform computations before reaching an action potential. Also, neurones are still cells and can change structure/position as well as gene expression, which may (or may not) impact on processing over a longer time interval.