Message-ID: <331DEAEB.645A@pobox.oleane.com> Date: Wed, 05 Mar 1997 22:51:39 +0100 From: Francois Charton Organization: CCMSA MIME-Version: 1.0 To: Robert Humphris CC: djgpp AT delorie DOT com Subject: Re: neural network code References: Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: 7bit Well, sorry guys, pretty off-topic I'm afraid... Robert Humphris wrote: > > > Yea this is the problem, Neural nets DO NOT work! Hmm..., there are many industrial applications which use them. For example, in the US, a neural net based program (developped by AT&T) is used for reading zip codes on letters; a similar program (same developpers) has been used by some banks for reading handwritten amounts on checks. Forecasting: a French water distribution company uses such a program to forecast water consumption/needs in Paris and its suburbs. Speech processing : there has been considerable experiments on use of Neural Nets for identifying people by the sound of their voice, or "denoising" some recordings, ... > they are only designed to model the brains method of cognative function, > not to be the brain. Yes, but they also can be good tools for building learning machines. This is a common process in numerical analysis : many good algorithms were discovered by observing mother nature, think of simulated annealing, or genetic algorithms. In fact, Neural Nets have been one basis for investigating how statistical learning can be implemented. Today, the basics of why neural nets learn (in a nutshell: stochastic gradient algorithms and semi martingales) are well established, and new techniques have been discovered which yield better algorithms than neural nets. Hence, they got a bit out of fashion, but they are still powerful and easy to implement tools for machine learning. Francois