artificial intelligence

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computing / technology: artificial intelligence

Overview

The endeavor to create artificial intelligence (AI) via electronic computational methods, which is generally agreed to have begun in the 1950s, has turned out to be considerably more difficult than originally imagined.

Partly as a result of this, the field has split into areas whose goals vary in their reach:

  • narrow AI generally refers to carefully-written programs which seem to respond with a certain amount of intelligence in certain narrowly-defined areas; "programs that solve particular, highly specialized types of problems" (2007-10-18 KA).
  • general AI refers to what we more commonly think of as "intelligence", i.e. the ability to solve new types of problems; adaptability, flexibility; "programs with the autonomy and self-understandings to come to grips with novel problem domains and hence solve a wide variety of problem types" (2007-10-18 KA).

Early attempts suffered greatly from lack of computational power; Moore's Law (which more or less doubles available CPU power in several measurable ways every 1.5 years or so) has now vastly increased the available power, and the best estimates are that an average desktop PC will possess approximately the computing power of a human brain sometime before 2030. What remains is to create the software to allow it to think like one.

Efforts have been focused in a number of areas:

  • scripted conversational strategies, e.g. AIML
  • "common sense" engines, mainly Cyc
  • artificial neural networks (these seem to have fallen out of favor, but nonetheless showed great promise as a tool)

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