--- Steve Richfield <[EMAIL PROTECTED]> wrote:
> The one mentioned in my "Comments from a lurker" thread mentions Dr. Eliza,
> that is designed to solve difficult problems in simple ways that billions of
> people have missed for a million years, and very likely ANY
> astronomically-sized AGI machine would miss for centuries. It was unclear
> how AGI was supposed to quickly do something that was only possible after
> 10E14 human years of wars and other strife, without having to go through,
> and even potentially cause the same.

As far as I can tell, it only gives medical advice based on your personal
agenda.  It knows only what you program into it.

> I published a paper at the first IJCNN in San Diego explaining how
> everything pointed to wet neurons generally computing with the logarithms of
> probabilities of assertions being true. That simple fact should have guided
> future research, but lab researchers not being mathematicians, and neither
> going to NN conferences, this guiding fact as died away like the echo of
> some long-forgotten noise. When a tree falls in the forest...

I use the same technique in my PAQ7/8 data compressors (since Dec. 2005),
although I was not aware of your research.  A set of models independently
estimate the probability p(0), p(1) that the next bit of input will be a 0 or
1 based on past history in various contexts.  The predictions are mapped to x
= log(p(1)/p(0)), combined by weighted averaging, then mapped by the inverse
squashing function 1/(1+exp(-x)), which makes it a neural network.  Then the
weights are adjusted to favor the most accurate predictions in proportion to
x*(actual - predicted), a simplification of back propagation that minimizes
coding cost rather than RMS prediction error.

I should mention the technique works quite well.
http://www.maximumcompression.com/data/summary_sf.php


-- Matt Mahoney, [EMAIL PROTECTED]

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agi
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