From mboxrd@z Thu Jan 1 00:00:00 1970 X-Spam-Checker-Version: SpamAssassin 3.4.4 (2020-01-24) on polar.synack.me X-Spam-Level: * X-Spam-Status: No, score=1.4 required=5.0 tests=BAYES_50,INVALID_MSGID autolearn=no autolearn_force=no version=3.4.4 X-Google-Language: ENGLISH,ASCII-7-bit X-Google-Thread: 103376,48942bcd105c88c6 X-Google-Attributes: gid103376,public From: tore@lis.pitt.edu (Tore Joergensen) Subject: Re: Computer beats Kasparov Date: 1996/02/24 Message-ID: <4gmbdi$rib@toads.pgh.pa.us>#1/1 X-Deja-AN: 140876695 references: <4g29e2$ea0$1@mhadg.production.compuserve.com> organization: University of Pittsburgh newsgroups: comp.lang.ada Date: 1996-02-24T00:00:00+00:00 List-Id: Stuart Gascoyne (100525.632@CompuServe.COM) wrote: : Whats this got to do with Ada? You ask. Well it used to be : asserted that a computer could never beat a human being at chess. : Then when that was disproved it was asserted that a computer : could never beat the best human chess players. Wrong. : Recently it was asserted in this newsgroup that a computer : (compiler) could never best a human at writing assembly language. : Even those that favoured high level languages over assembler : conceded this point. : Why can't a compiler produce better assembly language than a : human? What is so intractable about the problem of writing : assembly language that prevents it ever being computable? I'm not sure if Deep Blue used a neural network or not, but let me say a few words about neural networks used for assembly programming (and let me say that my knowledge about neural networks is very limited any mostly based on talking with a friend that studies neural networks as his main topic in his master degree). For the moment, the biggest problem with using neural networks in critical applications is that the people that works with neural network can't explain in details why the network does what it does. This means that you will have to wait until they can, or find a method to validate the result. If you make machines for hospitals or air planes, it doesn't sound like a good idea to say "This code is very fast, and testing seems to indicate that it does what it is supposed to do". You may say that this is more or less the same thing that we can say about optimized code made by a compiler, but at least we can understand the optimizations and choose to use only optimizations that we are sure works properly. It is a bit harder if the compiler does something one place that makes a big difference in the code another place, just because it seems like a good thing to do (I can't give you an example, but that is part of the problem :-). I guess that what I'm saying is: Neural networks is, or will maybe soon be, good enough to make fast assembly code from higher level languages, but as long as it isn't fully understood I doubt that it will be accepted for critical tasks. Because of the danger of law suits, most commercial programming tasks is considered critical. Deep Blue on the other hand (as I said, I don't know if it used neural networks or not) is research, and even though it lost big bucks to Kasparov, that can be viewed as Kasparov's sallary for participating in the research. What the future might bring is hard to say though :-). -- +-------------------------+-------------------------------------------+ | Tore B. Joergensen | e-mail : tore@lis.pitt.edu | | Centre Court Villa | web : http://www.pitt.edu/~tojst1 | | 5535 Centre Avenue # 6 | | | Pgh, PA 15232, USA | Norwegian MSIS-student at Univ. of Pgh. | +-------------------------+-------------------------------------------+