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I'm wondering if this reply is a joke because none of those areas are still in their infancy, especially parallel processing and speech processing. If you reall
by jmzachary 20y ago
I'm wondering if this reply is a joke because none of those areas are still in their infancy, especially parallel processing and speech processing. If you really meant to say that their potential hasn't been realized, then is it possible that expectation levels were too high to begin with? Same thing with higher level programming languages. How long have people been working on ML, Haskell, LISP, etc? What you really mean is natural language programming languages, like English, Chinese, etc. as programming languages.
The flip side is that some problems that were thought to be easy to solve may, in fact, be unsolvable (practically or theoretically). Computer vision is a good example of this.
I'm not trying to start a war or play devil's advocate for the sake of playing. My comments come from a real place. I have a PhD in computer science and was a professor in the field at a top university in the US. As sobering as it is to think about, I have serious concerns about CS because the problem landscape looks a little flat. The first mountain was computation (e.g., microprocessors), then usability, then networking/communications. What's next? I believe a big breakthrough in established fields like AI, VR, etc. are low probability using existing computational models, the weak proof being that a lot of very bright people have been working on these hard problems for a very long time and advances appear to be small and incremental. I don't know if QC will hold any promises in this area, maybe so.
- awt 20y agoIf speech processing is not in it's infancy, why can't my laptop tell how I'm feeling by listening to my voice? I seriously doubt you think there's no way to accomplish that. Perhaps we are not talking about the same thing? The tone of the article was that students were being turned away from CS as a major because they felt nothing new was happening. In response to that I'm talking more about applications of these technologies. The applications of parallel processing haven't even begun to be tapped out. Same with the applications of speech processing. I once used gp to create a soccer bot for the robocup. It took hours to train it to even kick the ball on my iMac running Mandrake. With more advanced use of parallel processing I could have trained a much more sophisticated bot -- but that was not available to me at the time. As for the theory of computation, perhaps that field is completely tapped out. I have no idea -- you would probably know better than I. Perhaps you're right. Maybe all the programs have been written (theoretically). Perhaps there's nothing left to be done. Then again, computer science has only been around since the mid 20th century. Chemistry and physics have been around much much longer. It just seems that it's a bit too early to call.