Inteligencia Artificial

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Dalamar
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Re: Inteligencia Artificial

Mensajepor Dalamar » 03 Oct 2017 03:30

Esperad una carrera entre empresas y paises... esta cifra, va a aumentar mucho y muy rapido, pronto escribiremos aqui. Que los 100 se han superado!

Google's artificial intelligence technology has a considerably higher I.Q. than Apple's Siri virtual assistant, according to a new academic paper attempting to compare the smarts of various artificial intelligence systems.
The paper — written by a trio of Chinese researchers, including Yong Shi, executive deputy director of the Chinese Academy of Sciences' Research Center on Fictitious Economy and Data Science — says that in 2016 Google's AI had an IQ of 47.28. It came out ahead of Chinese search engine Baidu (32.92) and Microsoft's Bing (31.98) and had almost double the IQ of Siri (23.94).

Notably, none of these systems had a higher IQ than a 6-year-old (55.5), much less an 18-year-old (97), the researchers found.
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Dalamar
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Registrado: 09 May 2012 01:38

Re: Inteligencia Artificial

Mensajepor Dalamar » 11 Oct 2017 18:31

La conciencia por J.Bengio: https://www.quora.com/What-is-Yoshua-Be ... aper-about


What is Yoshua Bengio's new "Consciousness Prior" paper about?
https://arxiv.org/abs/1709.08568

The key abstraction point is that nobody is ever consciously aware of all possible neurons. There is only a small subset of them which corresponds to ideas and concepts a brain is thinking about at that moment. So consciousness is then a small subset, a projection, of some elements of htht.

Those are the things a conscious mind is thinking about and is aware of it. The key is that this consciousness projection is a projection, of a big vector (all the things conscious and unconscious in brain) which is probably sparse, meaning conscious mind is only focusing on a few of them.

The next part of the framework deals with what conscious mind does with this small subset. He introduces attention as additional mechanism describing what mind chooses to focus on and also predictions or actions as what such a focused mind does. Basically he is saying that such mind reasons about previous actions or formulates predictions to be observed and verified in the future.

He makes an important point that verification of such hypothesized predictions can be done by training and minimization in an artificial neural network (ANN). Predictions produce expected results which are measured against outcomes in the future. The difference is the error of prediction that could be used in training an ANN.

Amazing thing is that this is kind of how real mind works on high level abstract concepts and predictions. Upon seeing outcomes different from predictions the mind goes back to the drawing board and tries to formulate a new theory, a subset of representation RNN FF. The hope is that this new FF will reduce errors in predicted outcomes in the future.

In section 2.4 he talks about another RNN that maps a simpler structure such a sentence or an “utterance” to a (much) richer conscious state. Think of that as a hint that someone into thinking deep about something is spurred on by something seemingly simple and trivial.

Like the apple falling on Newton’s head, it was a simple event that happened many times before and did not have much information in itself, but in the context of interacting with Newton’s mind at the time it had a deeply profound effect on him.

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