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Human brain and neural network behavior
a comparison

Ubiquity, Volume 2003 Issue November, November 1- November 30, 2003 | BY John Peter Jesan , Donald M. Lauro 

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On the matter of memory, there is no comparision. Neural networks are potentially faster and more accurate than humans.


Connection Failure

COMMENTS

"Both can learn and become expert in an area." It is just not true. At the moment ANN can't become an espert in any area. It can just adapt to specified function. It can't become an expert in architectural design, natural language translation etc. be a realist

— dzejdzej, Wed, 18 Apr 2018 14:33:10 UTC

In the opening statement, you said,"On the matter of memory, there is no comparison. Neural networks are potentially faster and more accurate than humans." This statement is confusing for humans have neural networks that help them learn. So are you trying to say computer neural networks are faster than humans? If so, you should really clarify that.(P.S, you spelt comparison wrong, you put comparision), and also you would be wrong. Although machines are faster than humans, humans have a steeper learning curve.

— Phill, Wed, 28 Feb 2018 17:13:01 UTC

Hi,your article is very helpful.I'm a student and I'm trying to translate this awesome article to Chinese(not public usage).I cannot understand well this sentence "both can learn and become expert in an area and both are mortal."What is the meaning the word "mortal" in neural network?Is it means that neural network will "die" someday as humans do?I don't really get it although I've searched in dictionary.I hope someone can explain more for me.Thanks for your wonderful work.

— Iris.D, Fri, 02 Feb 2018 18:22:51 UTC

Hi, I do agree that both "human and neural networks can learn and become expert in an area and both are mortal." While it is true that humans can forget but I do not fully agree that neural networks cannot forget. Humans forget when the cell that holds the information dies. And I believe the same is true with artificial neural networks: if the "cell" that holds or where the hard-coded information is damaged, the machine would also forget if not malfunction. But machines do have the advantage in that it is much easier to replace machine parts than that of humans. And human health issues can become very complicated. There are humans who do not forget what they know (although only very few, indeed: http://www.smithsonianmag.com/innovation/rare-people-who-remember-everything-24631448/ ). Perhaps, their brain cells are very healthy that none died so that they do not loose anything that they already know. Perhaps, if humans could activate 50% or more of their brain capabilities and their brain cells are maintained to optimum health so that they do not die, then there might not be much need for ANN? Just a thought.

— James Presbitero, Mon, 10 Apr 2017 02:42:18 UTC

First of all,the article is awesome for beginners on neural network. And I do have questions. Firstly why to use classifications or class algorithms using for the neural network? Secondly what is feedforward neural network. I really searched them but you seem like you are perfect on that. I would like to hear from you!

— Kenan Burak, Tue, 15 Nov 2016 06:22:01 UTC

I like this article, very simple and clear, as a PhD student working in ANN related topic, it is an eye opener for me.

— Jay, Wed, 29 Oct 2014 19:35:19 UTC

it's amazing bcoz it's language is so easy and face no difficulty to understand

— annu bharti, Thu, 07 Mar 2013 18:55:40 UTC

Dear sir, Is it possible to connect some device(say, neuro linker/neuro gear) that discharge calculated neuro pulse to human brain externally to create an augmented world. If it so , then I would like to know that how it can be done to send a 3D image to human visionary through brain.

— Kapilesh Singh, Fri, 08 Feb 2013 11:06:16 UTC

hi ! my name is vinod pal. I am from India. I am assistant Professor in computer science department. I really found this topic very interesting and useful who want to study about in AI. thanks for writing this. thanks.............

— vinod kumar pal, Thu, 20 Dec 2012 10:35:47 UTC

its a very good article, i learn alot from this thanku for publishing

— preetham, Thu, 20 Dec 2012 04:11:46 UTC

hi,i really enjoyed this concept.The presentation is simple and crystal clear.I have selected neural networks topic to present in my college.Thank you once again.

— omkaresh s, Thu, 11 Oct 2012 14:35:44 UTC

I am a computer science student from Nigeria. This article has also help me to fully prepare for my professional exam(CPN). I really enjoy ur write-up. Thanks alot.

— Alabere Ahmed, Sun, 29 Apr 2012 23:15:21 UTC

hi!! your article really helped me a lot about neural network really appreciated.its so clear n sensible.I did my presentation about this topic m pursuing mba.thanks:) sylvia, thur,19april 2012

— sylvia ngullie, Wed, 18 Apr 2012 21:32:47 UTC

hai! buddy your article is so awesome. I learned more things basically about neural networks. I am also a (bachlore)computer science engineering student.this will help very much for my further studies.Thank u for posting this! I want more article related to this. Please send a mail.

— vignesh, Fri, 14 Oct 2011 18:44:12 UTC

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