Path: utzoo!utgpu!jarvis.csri.toronto.edu!mailrus!cs.utexas.edu!uwm.edu!csd4.csd.uwm.edu!markh From: markh@csd4.csd.uwm.edu (Mark William Hopkins) Newsgroups: comp.ai Subject: Re: Can Machines Think? Keywords: Neural Networks and Computation Message-ID: <1785@uwm.edu> Date: 4 Jan 90 21:48:25 GMT References: <31821@iuvax.cs.indiana.edu> <32029@iuvax.cs.indiana.edu> <1037@ra.stsci.edu> <85217@linus.UUCP> <35@tygra.UUCP> Sender: news@uwm.edu Reply-To: markh@csd4.csd.uwm.edu (Mark William Hopkins) Organization: University of Wisconsin-Milwaukee Lines: 17 In article <35@tygra.UUCP> jpp@tygra.UUCP (John Palmer) writes: * My point: We are not going to solve the hard problems of AI by * simply developing programs for our digital computers. We have to * develope hardware that has a strong structure/function relationship. Don't let biological precedent mislead you into this conclusion. Nobody ever said that nature has the best of what is possible. If digital systems and quasi-analogical systems such as neural nets have complimentary strangths, then combining a digital computer and neural net into one integrated system (where each tackles those tasks it can best handle) will undoubtedly create a system capable of more than either is by itself ... and probably capable of much more than biological systems ever were. I can already see places where neural nets can be used in conjunction with a classical problem-solving AI program (e.g. to "learn" evaluation functions) ... and these are just simplistic applications.