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Supposing that neurons function similarly to transistors: A neuron able to fire $200$ times per second and transistors can be switched on and off more than $100,000,000,000$ times per second. Let's say it fires 1 out of 2 times in average. We have $86,000,000,000$ neurons in a brain, and $4,000,000,000$ transistors in medium CPU.

A brain's total fires per second: $86,000,000,000 \cdot 200 = (1.72e+13)$.
A CPU's total fires per second: $50,000,000,000 \cdot 4,000,000,000 = 2.e+20$.
A CPU is faster than a brain by $(2.e+20) / (1.72e+13) = (8.906e+6)$, or about 9 million times faster. I gave the brain an advantage that every neuron is firing non-stop instead of just 1%, and that they fire at the rate of the fastest neurons.

Why isn't this argument valid?

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The brain is not a computer, and neurons are not similar to transistors. – Chuck Sherrington Jul 18 '14 at 14:53
@ChuckSherrington It's an analogy between them. "and neurons are not similar to transistors" They are similar that they both need specific condition to fire. (They both fire too) Anyway, you mean those scientists are wrong even when they are trying to compare those two devices? – KugBuBu Jul 18 '14 at 15:49
@KugBuBu This blog post covers it pretty well:… The (biological) neuron is a lot more complicated than you think. – Chuck Sherrington Jul 19 '14 at 22:20
Incidentally, while I seem like an old curmudgeon, what I'm really saying is learning more about the neuron itself will be a better step for your own edification than getting hung up on the analogies. Also, take a look at the enteric nervous system. It's got almost as many neurons as the brain does, but there's a key component missing and that's the number of synapses present. It's be quite a CPU as well, but it's main function is to propel food through the gut. – Chuck Sherrington Jul 20 '14 at 1:34
Sorry to be "Johnny Comment" here, but this related Bio.SE question has some good information:… – Chuck Sherrington Jul 20 '14 at 1:50
up vote 3 down vote accepted

There is a basic epistemological problem here that was only touched upon by Chuck Sherrington - everyone is making the assumption that the brain processes the same kind of information as a digital computer. There is no real evidence to suggest that it does, in fact. A digital computer is an instantiation of a Turing machine, which is equivalent to certain kinds of automata. In order for the "processing power" of the brain to be compared to that of a digital computer in the first place, one needs to show that the brain employs representations (discrete entitites/states like bits) and rules (well-defined transitions between states/bits). Nobody has even come close to doing this, even for a subsection of the brain. This would be done by showing that the brain implements some digital computation - David Chalmers' famously [1] explains how this needs to be done. According to current the state of research, the brain seems to be a complex biological system, operating at multiple levels of measurement, and does not process information in discrete terms! And yes, Chuck Sherrington says it, neurons are not simply on/off!

[1] Chalmers, David J. "A computational foundation for the study of cognition." (1993).

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Wait, I calculated how many times per second they can potentially fire, not about on and off. But still need to admit that they are different. (While it's not impossible to make transistor work like neuron) – KugBuBu Sep 29 '14 at 11:10
Okay. However, your original question made the assumption that we are talking about discrete information (see If the information is continuous, we need to analyze it differently (i.e. Besides, it doesn't just matter how fast a system is able to calculate, it matters how and what it calculates! – user6682 Sep 30 '14 at 6:17
The question is about how fast is able to calculate. Brain is recursive self-improvement device. You can't compare them without removing this feature. The thing I am comparing here is hardware, not software. (Brain's software is hardware-builtin, but still exclude that) – KugBuBu Sep 30 '14 at 10:09
The point is that the hardware of the brain may not be comparable to the hardware of a computer. – user6682 Sep 30 '14 at 10:12
"and does not process information in discrete terms!" Ultimately it must, because of quantum mechanics... – Calmarius May 5 at 15:08

Have you ever seen IBM's Watson? Watson is composed of a cluster of ninety IBM Power 750 servers, each of which uses a 3.5 GHz POWER7 eight core processor, with four threads per core. In total, the system has 2,880 POWER7 processor cores and has 16 terabytes of RAM. It must be kept in a (very) large refrigerated room.

Watson is a question answering (QA) computing system that IBM built to apply advanced natural language processing, information retrieval, knowledge representation, automated reasoning, and machine learning technologies to the field of open domain question answering. According to John Rennie, Watson can process 500 gigabytes, the equivalent of a million books, per second.

Watson's official debut was on the game show Jeopardy, where it was pitted against two of Jeopardy's best players. It won, but the humans gave it a run for its money. Most believe the win was more due to Watson's faster response time (it was electronically keyed into the buzzer; Watson could activate the buzzer within about eight milliseconds, whereas the human response time to the go ahead light signal is several tenths of a second. In addition, to access memory more quickly, content was stored in Watson's RAM for the game because data stored on hard drives are too slow to access.

Watson was devised as a medical diagnostician (as well as other applications). With many years, scores of technicians, who knows how many billions of dollars, and access to medical encyclopedias, books, medical journals and the internet, it can outperform third year medical students in only one area: oncology (and even then, only lung, prostate and breast CA).

So, one average medical resident (4 years of medical school, and, say, second year of residency) can outperform a very, very fast medical supercomputer 99% of the time. I specialize in Primary Care medicine: Family and Emergency Medicine. With a few exceptions per year, within minutes of initiating a conversation with a patient, by watching the patient, reading his vital signs, and hearing answers to perhaps a dozen questions, I already have narrowed down my diagnoses to 2 or 3 top candidates and several other lesser considerations. I am one individual with one brain which accesses only to the information to which I've been exposed, yet I will outperform a medical supercomputer >99% of the time. In under 10 minutes. (This does not mean that I only spend 10 minutes with a patient. Medicine is about more than the correct diagnosis.)

This is Watson:

enter image description here

My brain is about the size of the "W" etched on the room's window.

You tell me: Which is "faster", a supercomputer or a human brain? It really does depend on your definition of "faster", doesn't it?

Putting Watson to Work: Watson in Healthcare. IBM.
IBM's Watson is better at diagnosing cancer than human doctors
IBM Watson's impressive healthcare analytics capabilities continue to evolve

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Searching answer in "massive" data vs. keep firing until it "rings a bell". It isn't the same task at all. I meant in hardware level, rather at a level that brains can optimize their task. (Which they are good at) – KugBuBu Jul 19 '14 at 21:51
To chime in on the subject of medical informatics, I think it can be good to have a computer assist diagnosis, because doctors are subject to the same cognitive fallacies as the rest of us: Doctors & statistics – user6682 Sep 16 '14 at 7:24

I'm not sure the math checks out in the question (the CPU cycles per second seems awfully high), but I think there are some useful principles to keep in mind regardless of the details of the math.

So let's assume that we do have a computer that can perform more operations per second than the combined sum of all action potentials in the brain per second. Is the computer faster than the brain?

The answer is it depends on what the question is. There are certainly types of information processing that computers are much faster at than human brains. A cheap calculator can solve the problem 2854 x 239 much faster than the average human brain. But brains tend to be much faster than computers at pattern recognition type problems.

The main point is that looking at the speed of transistors and neurons is the wrong level -- or at least it provides an incomplete picture -- to be thinking about the speed of information processing. Not that the 'hardware' doesn't matter, but other factors matter too. For a computer, the software matters. For a brain, the network of connections between neurons matters.

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It's the cycles of a singel transistor. The score of a CPU is the potential effort of the CPU. (Same for the brain) – KugBuBu Jul 19 '14 at 21:42

I will just show the statistics of last attempt to mimic the brain process.

Last year Japan launched there fastest supercomputer:

K computer OR SPARC64 VIIIfx 2.0GHz


  • Manufacturer: Fujitsu
  • Cores: 705,024
  • Linpack Performance (Rmax) 10,510 TFlop/s
  • Theoretical Peak (Rpeak) 11,280.4 TFlop/s
  • Power: 12,659.89 kW
  • Memory: 1,410,048 GB
  • Processor: SPARC64 VIIIfx 8C 2GHz
  • Operating System: Linux

It's currently world's 4th fastest supercomputer.

Source: Top 500 Supercoputers

Image Source:


An 83,000-Processor Supercomputer Can Only Match 1% of Your Brain

...The most accurate simulation of the human brain to date has been carried out in a Japanese supercomputer, with a single second’s worth of activity from just one per cent of the complex organ taking one of the world’s most powerful supercomputers 40 minutes to calculate. Researchers used the K computer in Japan, currently the fourth most powerful in the world, to simulate human brain activity. The computer has 705,024 processor cores and 1.4 million GB of RAM, but still took 40 minutes to crunch the data for just one second of brain activity...


Human Brain:

Do we have brain to spare?

by David A. Drachman, MD

Within the liter and a half of human brain, stereologic studies estimate that there are approximately 20 billion neocortical neurons, with an average of 7,000 synaptic connections each.1 The cerebral cortex has about 0.15 quadrillion synapses—or about a trillion synapses per cubic centimeter of cortex. The white matter of the brain contains approximately 150,000 to 180,000 km of myelinated nerve fibers at age 20, connecting all these neuronal elements. Despite the monumental number of components in the brain, Szentagothai estimated that each neuron is able to contact any other neuron with no more than six interneuronal connections—“six degrees of separation.”

Image Source:!/image/far-to-go.jpg_gen/derivatives/fullsize/far-to-go.jpg

Why Brain beats Supercomputer?

Why is it so hard for computers to reproduce what your grey matter does as a matter of course? Volume. The human brain consists of about 200 billion nerve cells (neurons) that are linked together by trillions of connections called synapses. As the tiny electrical impulses shoot across each neuron, they have to travel through these synapses, each of which contains about 1000 different switches that route that electrical impulse. In total, one human brain could contain hundreds of trillions of these neural pathways. It's like a Choose Your Own Adventure book that stretches from here to Jupiter.

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what is the reason for down vote? – Devashish Das Jul 18 '14 at 18:51
I guess, the question wasn't that good in the first place, so answering it before trying to improve was considered questionable? That's my guess. It happens on these websites sometimes. Don't take it personally. – Seanny123 Jul 18 '14 at 18:52
I have undeleted this post because it had one other undelete vote, and I think it's a good answer to this question. It's a less-detailed but more-cited version of anongoodnurse's answer. Don't be too swayed by a single downvote :-) If you do really want this deleted please use the flag link on this answer and ask for us to delete it again. Also, +1 for a good answer. – Josh Gitlin Jul 20 '14 at 15:41
As Jhonny depp says in Transcendence: Human brain can't even beat the smallest of AI. But it's about the total data transfer. We can't calculate $2^{20}$in seconds, but we can sip coffee on at a beach enjoying the view. The amount of work done in the last line can't be achieved by current supercomputers combined. – Devashish Das Jul 20 '14 at 19:14
I don't think that modeling the brain processing is a fair comparison to what a computer can do. When we model the brain processes, we do some things that are inefficient form a computational perspective, but informative from a scientific perspective. A computer scientists trying to achieve the same processing task without care for the way neurons/brains do it will be able to make a much more efficient algorithm. – Keegan Keplinger Sep 11 '14 at 18:38

Anology Taking the analogy and calculations directly, you are assuming that the fundamental computing unit of the brain is the neuron; we do not know if this is true. It could be a cortical column, a group of several neurons, the neuron, a dendritic branch (a fascinating review paper!), a synapse, receptors or neurotransmitter vesicles (how about glial cells?). This paper describes the somewhat accidental fascination with the historical view of a neuron being 'the unit'.

So, to the numbers. If one treats a singular neuron's action potential as a 1/0 like a transistor, sure you're numbers kind of make sense. (Not sure where you got the 1% figure from?) However this is making the assumption I eluded to above. If you were to run the numbers with synapses, the brain might win.

You are further assuming that a 1/0, spike or no spike, representation of a neuron is all that the brain does. We do not know how the brain encodes information -- as others have said, it might not work in the same serial 1/0 fashion that we have engineered computers to operate. Information/processing in the brain could be via individual neurons firing rates, population firing rates, spike timing, etc. (sections 1.5, 1.6 and 1.7 review some). Imagine that the timing of when a transistor flipped compared to another was important! Moreover, this only considers action potentials (or EPSPs if one redoes the numbers with synapses). Neurons (and synapses) are extremely non-linear and a lot of information/processing might be undertaken before or after an action potential (EPSP). This is the age old question of analogue (brains) vs. digital (modern computers).

Serial vs. parallel I think an important point missing from previous answers is the fact that the brain is massively parallel. That is, there is not one processor serially undertaking instructions.

A typical CPU (core to be specific) in a computer may be very fast in terms of calculations per second -- arguably a great deal faster than a single neuron -- however, there are very few of these individual units when compared to the brain. This is why supercomputers take advantage of hundreds of CPUs (and cores). However, the numbers of these cores is extremely low when compared to the brain (if we are assuming that a neuron is the fundamental unit, see above), where an analogy might be that each core/neuron is a lot slower, there are however millions (trillions if 'the unit' is a synapse) of cores.

Yes, you have considered that a CPU has many many transitors on it, however the CPU itself it still only processing information in a serial fashion. It does this operation, then this operation, then this etc. As I said above, this is why supercomputers use many CPUs as this allows them to do a somewhat parallel process. However this is more complicated as in reality, a computer's parallel programme is typically just a serial one split a few times. For example, you want to calculate what A+b is where A is a huge matrix and b is a constant. One can do this in serial by iterating through all the elements in A and adding b; or, one can 'parallelise' this by using 10 CPUs and splitting the matrix in to 10 subsets and having each CPU do a serial operation on their own subset and finally concatenate the resulting subsets back in to A again. This isn't really parallel computing but rather smaller serial operations (parallel programming is hard). The brain is truly parallel. (The quote in the answer to this previous question has a great analogy in it.)

To compare the two is fundamentally flawed as the way we quantify the performance of a CPU does not apply to the brain. It might be possible to compare them if a common metric could be devised, but this would mean we would need to understand how the brain processes information in the first place, which is a long long way off.

As a final note, have a look at this article.

(Edited to include more detail as there was interest/comments.)

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I calculated the calculation that the whole neurons can do together (While actually you can fire only 1% of them at once) [not a singel one], and one 1 billion cpu. – KugBuBu Sep 29 '14 at 10:48
Citations for backup & further reading would make this a great answer @James! – Krysta Sep 29 '14 at 12:17

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