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About the future of AI..

From Sky89 <Sky89@sky68.com>
Newsgroups comp.programming.threads
Subject About the future of AI..
Date 2018-08-20 12:42 -0400
Organization A noiseless patient Spider
Message-ID <pler11$lr7$10@dont-email.me> (permalink)

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Hello....

Read this:

About the future of AI..

I think also the future of AI(artificial intelligence) will also be a 
composition of both symbolism and connectionism, for example  here is 
the Deep Symbolic Networks that learns with relatively "small" data than 
connectionism alone, and read the paper to notice that it is powerful:

Read the following paper:

https://arxiv.org/abs/1707.03377


And read the rest of my thoughts about AI:

Related to my previous post about AI, read this:

"Researchers in machine learning argue that computers trained on 
mountains of data can learn just about anything — including common sense 
— with few, if any, programmed rules."


Read the rest of my thoughts:


About artificial intelligence..

I think that AI (artificial intelligence) is getting more and more 
powerful, and i think that even if AI doesn't use abstract reasoning as 
humans, it is learning from data and being able to pass IQ tests and 
this way (by learning from data) it can get much more powerful, so we 
have to be optimistic about artificial intelligence, because AI will 
learn from data and get soon (in just about 12 years) "so" powerful that 
it will permit us to solve many of our problems, and i think that by 
learning from data it can get more powerful than humans in many ways.

This is why i have posted this:

DeepMind AI Passes IQ Test, But Does It Really Think Like Us?

Look at this interesting video:

https://www.youtube.com/watch?v=zoNsbDVb4PI


And also read the following interesting thoughts to understand more 
about AI:

Artificial intelligence is becoming "powerful" because we are now 
capable of "general" artificial intelligence, read carefully what 
follows, it said that:

"Artificial intelligence up to now, including DeepMind’s AlphaGo, have 
been limited to perform well only for a specific task - hence the term 
‘narrow artificial intelligence.’ But researchers are beginning to 
embrace the arrival of artificial general intelligence, an AI that can 
perform any task that a human can. In their recent paper, Google 
DeepMind proposes a method into training AGI by using genetic algorithm."

And:

"So how well does PathNet perform in action? DeepMind’s experiments show 
that PathNet is faster than fine-tuning, and does positively transfer 
trained knowledge in supervised learning classification tasks and 
reinforcement learning tasks - successfully addressing the three 
requirements of an AGI."

Read more here to notice it:

http://www.deepbio.co.kr/2017/03/20/Weekly-paper-DeepMinds-PathNet.html


And read about the following other important step that is Generative 
Adversarial Network:

What’s a Generative Adversarial Network? Leading Researcher Explains

Read more here:

https://blogs.nvidia.com/blog/2017/05/17/generative-adversarial-network/




Thank you,
Amine Moulay Ramdane.

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About the future of AI.. Sky89 <Sky89@sky68.com> - 2018-08-20 12:42 -0400

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