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Re: No subject |
Jun 29, 2008, 16:38 |
Fang |
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The amount of processing power required for that would be huge.
Not if you design it correctly. It's possible to use linear dynamic programming to apply machine learning techniques.
One example of a leap forward in applied AI algorithms is with Bayesian spam filters. They can update their models very quickly and they work reasonably well once trained. Much better than the spam filters that came before them.
That's just an example, and there are plenty of cutting edge AI techniques that will scale very well, especially since the point of this would be to run a centralized learning system. No need to relearn for each user.
Obviously, you can't just hire more programmers to try to implement it; you'll have to hire true computer scientists to implement a next-gen AI solution.
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