How do we learn? And in the same way can a machine learn?

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In summary, the conversation discusses the concept of learning and its different forms, including simple conditioning and complex human learning. It also mentions the idea of machines being able to learn, but not comprehend like humans do. The conversation delves into various theories and the current limitations in simulating human intelligence with computers. The participants also suggest looking into fields such as AI, neural networks, and fuzzy logic for further understanding. The idea of programming a computer to have desire or want is also mentioned, and its potential impact on learning.
  • #1
Moni
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How do we learn? And in the same way can a machine learn?
 
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  • #2
Do you mean can a machine learn at all, or can a machine learn in the same way that we do? If it's the first, then the answer is yes, up to a point. There's a whole subsection of the field of AI dedicated to machine learning.
 
  • #3
How is sleeping related to how quickly one can attain a new skill? I remember a Time Magazine article saying that was the new theory or something. What sleep does? Ugh I'm tired.
 
  • #4
Umm...I want to know about the edge technology or development made so far!

I need that to do some paper works :)
 
  • #5
There are (at least!) two meanings to the word learning. One is the simple kind of learning that simple animals do, like conditioning. For this we have a pretty good understanding, it's based on the strengthening of a neural connection when it it is excercised repeatedly. A scientist named James Hebb had this neural idea back around 1950, and this kind of learning is called hebbian. The neural networks idea in computer software is based on it.

The other kind of learning is the complex and subtle kind we do every day. On that we have some good research but no deep understanding yet.
 
  • #6
Check this out: http://en.wikibooks.org/wiki/Intoduction_to_Psychology:chpt7"

I never finished the wikibook.
 
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  • #7
A computer can learn but not comprehend.

There's a theory that a complete and accurate simulation of an average brain would naturally produce intelligent thought, but there's no way to test this with current computers. (There's another theory saying there's bugger all intelligent thought on Earth anyway, see the PF Lounge ;) )
 
  • #8
haha...Yeah RunDMC .. but who's that Bugger? ;)

thanks Bio-Hazard :)
 
  • #9
selfAdjoint said:
There are (at least!) two meanings to the word learning. One is the simple kind of learning that simple animals do, like conditioning. For this we have a pretty good understanding, it's based on the strengthening of a neural connection when it it is excercised repeatedly. A scientist named James Hebb had this neural idea back around 1950, and this kind of learning is called hebbian. The neural networks idea in computer software is based on it.
The other kind of learning is the complex and subtle kind we do every day. On that we have some good research but no deep understanding yet.

Hmm, I'm talking about that other kind of Complex and Subtle idea :)
How's that can be studied in machine? I think I've to look on Psychology journals for that :(
 
  • #10
RunDMC said:
A computer can learn but not comprehend.

That depends on how well the programming routine is (tree'd)

The only limit is ones own programming ability.
 
  • #11
no you need to look in ALife/AI journals and Neural Net journals for what you want. It also depends on the learning..pseudo learning (ie Game AI-liek deep blue) or realistic learning liek the Blue Brain PRoject by IBM and swiss lab.
MIT has some really neat Computer vision as well as york university.
And there are industrial learning algorithms that use principals of th brain for industrial stuff like Cryptography and Satellite imaging and medical imaging.

Also look at steve grands Lucy its kinda cool or look up gary flakes book.
 
  • #12
Intuitive said:
That depends on how well the programming routine is (tree'd)
The only limit is ones own programming ability.

how about an intelligent computer system...who itself can write program for itself ;)
 
  • #13
neurocomp2003 said:
no you need to look in ALife/AI journals and Neural Net journals for what you want. It also depends on the learning..pseudo learning (ie Game AI-liek deep blue) or realistic learning liek the Blue Brain PRoject by IBM and swiss lab.
MIT has some really neat Computer vision as well as york university.
And there are industrial learning algorithms that use principals of th brain for industrial stuff like Cryptography and Satellite imaging and medical imaging.

Also look at steve grands Lucy its kinda cool or look up gary flakes book.

can you provide some link on them?

Cause, I'm about the design any new learning model...so, my approach is to first know the human/animal learning process and find something new...so that it can be any new model...what you suggest?

Do, I still have to look into NN and Fuzzy stuffs?

I've gone through few AI books...and their learning algorithms are too specific and purpose specific...why don't they talk about something general?
 
  • #14
Moni said:
can you provide some link on them?
Fuzzy stuffs?
http://en.wikipedia.org/wiki/Fuzz" 's some Fuzzy stuffs.
 
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  • #15
RunDMC said:
A computer can learn but not comprehend.
There's a theory that a complete and accurate simulation of an average brain would naturally produce intelligent thought, but there's no way to test this with current computers.
Yet comprehension could be described as an emotion triggered by new neural passage ways being opened or else altered. It is a sensation. The thing is, robots can't feel emotion which makes them different than us. They might be able to display the neurological change, but to feel it.. hmm...

Coming back to this post later I think about how computer learning is more of a conditioning more than of an actual learning process. Else and if statements I propose.

The greatest thing in the Universe is want, and if you can program a computer to want something, or create an objective, it will learn to complete that mission and then cease to exist until given a new objective. They thing one must do is have the A.I. want everything. We as humans can't simply define everything for we don't know everything. To tell a robot to learn everything would probably be process of elimation from old knowledge to new knowledge in which it goes forth trying to learn new material and constantly redefine its world.
 
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  • #16
Nicely said man :)

WANT!

That means QUESTIONING :D
 
  • #17
Moni said:
how about an intelligent computer system...who itself can write program for itself ;)

That depends on how well the programming routine is (tree'd)
The only limit is ones own programming ability.
 

FAQ: How do we learn? And in the same way can a machine learn?

1. How does our brain learn?

Our brains learn through a process called neural plasticity, where connections between neurons are strengthened or weakened based on our experiences and interactions with the world. This allows us to adapt and learn new skills and information.

2. Can we improve our learning abilities?

Yes, we can improve our learning abilities through various techniques such as practice, repetition, and active learning. By engaging in these activities, we can strengthen our neural connections and improve our ability to retain and apply new information.

3. Can machines learn in the same way as humans?

Yes, machines can learn through a process known as machine learning, which involves programming algorithms to analyze data and make predictions or decisions based on that data. While it is a different process than human learning, it can mimic similar patterns and adapt to new information.

4. What are the limitations of machine learning?

One limitation of machine learning is its reliance on data. In order for a machine to learn, it needs to be trained on a large amount of data, which can be time-consuming and costly. Additionally, machines may struggle with tasks that require human-like intuition or creativity.

5. Is it possible for machines to surpass human learning abilities?

It is possible for machines to surpass human learning abilities in certain tasks, such as processing and analyzing large amounts of data quickly and accurately. However, machines still lack the ability to understand and make decisions based on emotions and social cues, which are important aspects of human learning and intelligence.

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