Kinds of AI

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During the process of creating these ideas on AI, there's the human perception problem. As they say, if your only tool is a hammer, every problem will look like a nail. While driving screws with a hammer might kinda work, but it's not really the optimal solution. And each discipline, psychologists, philosophy, robotics, neurobiology, speech/linguistics, data processing/analysis, and mathematicians, were all blind men who had their own perceptions of an elephant, trying to recreate that elephant with different mediums. Some of the approaches to AI were things like:

  • Rule-Based Inference Engines, Knowledge base and Expert Systems --
  • "Genetic Algorithms" (aka evolutionary computation/algorithms) -- in the 1990's this became popular, and is an idea that loosely, you give the machine a way to do things (algorithm). It knows how to changing a variable (adding something in, throwing something out, or increasing/decreasing it) and seeing if it works better or not. If it does, it keeps going until it passes optimum (starts getting worse), then it stops and starts doing it with another variable/dimension. The warmer/cooler method of making things better, on each variable/attribute (mutating) until it thinks it found "the best" way to do something. The problem is that this can improve on something a little, but it can't make huge leaps (it needs to know all the variables it can tweak, and it's harder to find things that might require a complete restructuring of the problem, or tweaking many things at once), and if the originating algorithm (and assumptions are bad, too complex, or not complex enough) it will never figure out the "best" way to do something, only the best way to do it, with those flawed assumptions. (E.g. GIGO: Garbage-in = Garbage-Out).
  • "Machine Learning".



Artificial Intelligence
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AI (Artificial Intelligence) isn't what people think it is, and we're not nearly as advanced as the laypeople think, and the others prey upon that ignorance for scares, clicks and attention. This is a little primer on the terms, what it can and can't do. And where it still needs to go. more...

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