"a professional tennis player can follow the trajectory of a tennis ball after it is served at a speed as high as 160 miles per hour"<p>This is false or at least highly misleading. A reader might imagine that the player's eyes track the ball in flight. This is not what happens. A pro player reads the position of the serve and begins moving before the ball is hit. The predictive power of the brain is much more important than the speed and precision the author was trying to highlight here.
I recently realized the (obvious in hindsight) fact that general intelligence better that brute force doesn't exist, as intelligence is equivalent to compression.<p>Given the recent discoveries about neurons using mRNA capsids to communicate [0] it's not that farfetched to posit that we are really dna computers [1]. The processing time (for new problems) seems human-like: "The slow processing speed of a DNA-computer (the response time is measured in minutes, hours or days, rather than milliseconds)"<p>The evolutionary argument: as DNA computing is already used by microbes [2] how could the nervous system made of (relatively) dumb neurons compete with that? Synapses still make sense - as a way to request a rna packet and/or inform that it's coming and from where.<p>One neuron with capability of ~10M pattern matches per second (encoded in dna/rna) would mean that the human brain executes ~2^60 pattern-matching operations per second, utilizing zettabytes of imperfectly copied data. Enough to brute force its way through lots of problems.<p>Memory as dna would explain high-level memory quirks: each read would be destructive, by splitting dna into rna, interacting with other rna under the presence of appropriate enzymes, then copying and disseminating the resulting rna, transforming the memory each time it's retrieved.<p>It would also explain urban legends about people's personalities changing to resemble their organ donors in some way - as a donor's memory packets that somehow ended up on the donor's organ and, with the help of immunosuppressants, managed to infect the receiver's brain.<p>[0] <a href="https://www.nature.com/articles/d41586-018-00492-w" rel="nofollow">https://www.nature.com/articles/d41586-018-00492-w</a><p>[1] <a href="https://en.wikipedia.org/wiki/DNA_computing" rel="nofollow">https://en.wikipedia.org/wiki/DNA_computing</a><p>[2] <a href="https://en.wikipedia.org/wiki/Microbial_intelligence" rel="nofollow">https://en.wikipedia.org/wiki/Microbial_intelligence</a>
The article seems to be about how it is that the brain can process so much information at so slow a cycle speed, but it doesn't really address power efficiency at all. Even assuming 100% parallel operation, our current chip designs use something like a factor of a million more energy to do the same amount of computation. I wish I knew why- it's not like we're ignoring power efficiency. Depolarization of an axon must be incredibly power efficient.
We don't know what operations the brain is actually doing, so declaring that it is performing them efficiently is pure speculation.<p>Similarly, the brain surely has limits to parallelism, for the same sorts of reasons a computer does. You only have one mouth, so if two parts of the brain tried to speak, fully parallelized, you'd get nonsense at best. They have to agree on what to say, which is effectively serialization.
The brain definitely has an edge on compute power. The computer has an edge on storage power. I would bet the brain doesn’t store more than a Terabyte of information.<p>We just need more cores without spiking energy usage.
A brain is not equal to a computer or a processor.<p>You will never get the answer if you look at it from a narrow minded perspective.<p>A brain is equal to billions of processors connected in a highly naturally efficient network functioning almost effortlessly.<p>Something along these lines seems like a plausible comparison to a brain.<p>What is a brain is not equal to a processor but a neuron is equal to a processor?
How many milliseconds does it take for one layer of neurons to adjust its output? Let's call this number X.<p>Can we conclude that if a task takes a human Y milliseconds, then a neural network with Y/X layers is sufficient for that task?
I feel like there must be some way to 'clean' our brains. As we get older it must accumulate 'gunk' that slow it down or weaken connections.<p>I guess sleep is the closest thing we have but to me that's like saying drink water to fix tooth decay.
Like a quantum computer, computing thousand calculations at once and the true answer is what remains? I guess there's a ... parallel there. And I know some people don't like this diductic reduction, analogy, metaphor, callitwhatyouwant. I'd welcome corrections.