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Very interesting, but my question is, what are the speed of these chips compared to conventional ones. The main problem with the human brain is that while it is fantastic at parallel processing, the speed at what it processes information is only a few MHz i think. The reverse is true for computers, great speed, terrible parallel. If these chips solve the problem of parallel processing but keep speeds the same it would be a great step for computers.



I always imagined the point of replicating the brain with microchips is to see if any emergent behavior (read: learning) is observed, not to improve the performance of any existing process.


> the speed at what it processes information is only a few MHz i think

More like Hz, actually. Neurons are slow - I am not sure how frequently can they fire, but I am sure it is not in the multi-thousand per second range.


Maximum firing rate differs between neuron types (i.e., cortical pyramidal neurons versus cerebellar Purkinje neurons) dependent upon cellular membrane properties (dendrite diameter and ion channel distributions, etc.), but a good rule-of-thumb to keep in mind is 1 kHz. That maximum "firing rate" is about as fast as a patch of membrane can generate an action potential (AP, or "spike"), reset, and fire another.

All that said, a relevant question to ask is, "What is the information content of a single action potential?" There is not an agreed-upon answer among neuroscientists. The metaphor linking brain and a personal computer is extremely strained: to start, it is not quite true that neurons can carry out logical functions. Neurons are firmly rooted in the analog domain and it is much more straightforward to infer polynomial-type computations from their physiology, the order and coefficients being dictated by the particulars of the scenario. Also, the current thinking is that information is encoded in bursts or repetitive APs, called "spike trains". But if we must, I'd throw out a range of 0.5 to 5 bits per spike [Rieke, et al.]. (If you want to go down a rabbit hole and explore one of the pivotal topics among people studying neural computation, look up "rate coding" versus "temporal coding". Perhaps even phrasing the question that way is misleading.)

Here's a side note that may be of interest: during an AP, the trans-membrane voltage swings from approximately -100 mV to +100 mV (very rough figures). If you consider that this potential difference is applied across the 3 nano-meter thick cell membrane, the resulting electric field is very close to the dielectric breakdown voltage for phospholipid membranes. Our neurons are constantly operating within a factor or two of literally destroying themselves! (The preceding paragraph contains very back-of-the-envelope reasoning. To be more rigorous, I'd have to dig out my notes and reference materials, but the general point nonetheless holds.)


That was an impressive explanation. Thanks.


I doubt the complexity of the brain can be reduced to cycles and the speed at which it performs each cycle. Also, I can't imagine that every operation performed by the brain would be performed at the same speed, so getting sound from the vibrations in your ear to wherever it begins to be interpreted might be much faster than the processes that would trigger memories from such sounds (or any other type of input, be it touch, smell, taste, visual…


cpu frequency scaling. CPUfreq has been in linux since kernel 2.6.




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