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Supposing that neurons function similarly to transistors: A neuron fires 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 on average. We have 86,000,000,000 neurons in a brain, and 1,000,000,000 transistors in a good CPU.

A brain's total fires per second: 86,000,000,000 $\cdot$ 200 = 1.72e+13.
A CPU's total fires per second: more than 50,000,000,000 $\cdot$ 1,000,000,000 = 5.e+19.
A CPU is faster than a brain by 5.e+19 / 1.72e+13 = 2.906e+6, or about 3 million times faster.

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 at 14:53
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@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 at 15:49
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I'm a lot smarter than my Macbook, for what it's worth. Stupid thing does't even speak proper English. –  jona Jul 19 at 16:43
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@KugBuBu This blog post covers it pretty well: scienceblogs.com/developingintelligence/2007/03/27/… The (biological) neuron is a lot more complicated than you think. –  Chuck Sherrington Jul 19 at 22:20
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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 at 1:34

4 Answers 4

up vote 2 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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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?

References:
Wikipedia
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 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 –  StrangeLoop yesterday

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 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

Features:

  • 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: http://wondergressive.com/wp-content/uploads/2014/01/WG-k-computer.jpg

Now,

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...

Source: http://gizmodo.com/an-83-000-processor-supercomputer-only-matched-one-perc-1045026757

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: http://www.nature.com/polopoly_fs/7.2933.1329907514!/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 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 at 18:52
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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 at 15:41
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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 at 19:14
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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 at 18:38

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