Your arguments apply mostly toward arguing that brains are optimized for energy efficiency, but the important quantity in question is computational efficiency! You even admit that neurons are “optimizing hard for energy efficiency at the expense of speed”, but don’t seem to have noticed that this fact makes almost everything else you said completely irrelevant!
The point of my comment (from my perspective ) was to focus very specifically on a few claims about biology/brains that I found questionable—relevant because the OP specifically was using energy as an efficiency metric.
It’s relevant because energy efficiency is one of the standard key measures of low level hardware substrate computational efficiency.
At a higher level if you are talking about overall efficiency for some complex task, well then software/algorithm efficiency is obviously super important which is a more complex subject. And there are other low level metrics of importance as well such as feature size, speed, etc.
FWIW I agree that bit also rang hollow to me—my sense was also that neurons are basically as energy-efficient as you can get—but by “computational efficiency” one means something like “amount of energy expended to achieve a computational result.”
For example, imagine multiplying two four-digit numbers in your head vs. in a calculator. Each transistor operation in the calculator will be much more expensive than each neuron spike, however the calculator needs many fewer transistor operations than the brain needs neuron spikes, because the calculator is optimized to efficiently compute those sorts of multiplications whereas the brain needs to expensively emulate the calculator. Overall the calculator will spend fewer joules than the brain will.
You’re missing the point!
Your arguments apply mostly toward arguing that brains are optimized for energy efficiency, but the important quantity in question is computational efficiency! You even admit that neurons are “optimizing hard for energy efficiency at the expense of speed”, but don’t seem to have noticed that this fact makes almost everything else you said completely irrelevant!
The point of my comment (from my perspective ) was to focus very specifically on a few claims about biology/brains that I found questionable—relevant because the OP specifically was using energy as an efficiency metric.
It’s relevant because energy efficiency is one of the standard key measures of low level hardware substrate computational efficiency.
At a higher level if you are talking about overall efficiency for some complex task, well then software/algorithm efficiency is obviously super important which is a more complex subject. And there are other low level metrics of importance as well such as feature size, speed, etc.
So what did you mean by computational efficiency?
FWIW I agree that bit also rang hollow to me—my sense was also that neurons are basically as energy-efficient as you can get—but by “computational efficiency” one means something like “amount of energy expended to achieve a computational result.”
For example, imagine multiplying two four-digit numbers in your head vs. in a calculator. Each transistor operation in the calculator will be much more expensive than each neuron spike, however the calculator needs many fewer transistor operations than the brain needs neuron spikes, because the calculator is optimized to efficiently compute those sorts of multiplications whereas the brain needs to expensively emulate the calculator. Overall the calculator will spend fewer joules than the brain will.