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No more than a neural network can be full. To anybody who has worked with neural networks, the following comes as no surprise: old information is sometimes
by hliyan 11y ago
No more than a neural network can be full. To anybody who has worked with neural networks, the following comes as no surprise:
old information is sometimes pushed out of the brain
for new memories to form
Weights in a NN like the brain would just gradually shift. Older, seldom-accessed information will slowly fade.
That said, a NN can suffer from the trying-to-be-jack-of-all-trades, ending-up-an-idiot problem.
- deleted 11y ago[deleted]
- anon4 11y agoYou could alternatively say that the brain is constantly full.
- reagency 11y agoMore so as you age. As a youth, you have very little total information.
- rndn 11y agoAnother possibility is that two activation patterns are so similar that they interfere and thus they merge, one replaces the other or they both become useless noise. See also: https://en.wikipedia.org/wiki/Forgetting#Interference_theories https://en.wikipedia.org/wiki/Forgetting#Interference_theori...
- dingbat 11y agothis sounds like whats happening during an approach that is sometimes used in therapeutic settings: where a patient or client is induced into recalling a memory with negative emotional content, and then guided into transforming that memory by introducing competing neutral or if possible positive interpretations. for this purpose the result isnt useless noise, but instead its useful because the patient or client then experiences less negative pattern matching in daily life. at least thats the idea.
- derekp7 11y agoI have that problem trying to recall some books that I've read. I used to read a lot, and so many of the books I read as a teen seem to have merged into bigger story threads.