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This is in fact a classic criticism of modern AI. Classic approaches tried to replicate human reasoning mechanisms. The work was very cool, but far harder to un

This is in fact a classic criticism of modern AI. Classic approaches tried to replicate human reasoning mechanisms. The work was very cool, but far harder to understand and scale, compared to modern statistical algorithms. To some extent, you are faced with a choice: a small palette of mediocre techniques whose workings are beautiful theories of the human mind; or, a broadly-applicable, incredibly practical set of tools with little motivation or spirit.

PurplePanda 12y ago
I understand that other being hard to scale in a machine efficiency sense, the old techniques were also rather limited in applicable domain. They were often based on unjustified models of whatever the author decided was a good model of thought/reasoning, whether "frames", predicate calculus, constraint propagation or whatever. It seems to me that although you say statistical methods have little motivation, the motivation of the alternative - heuristics - is very questionable. Can anyone correct me on this?
- pavpanchekha 12y ago
  That's actually what I meant by scale—that they were slow isn't really a problem if you're interested in AI for the raw fun of it. While justifications for using logic or constraints or probability theory were often lacking from classical techniques, do understand that logic itself was originally developed as a crystallization of proper human thought. And many of the classic AI folks did care deeply about understanding how humans achieved certain results. For example, take a look at Marvin Minsky's work. To the contrary, modern techniques aren't interested in replicating human thought; they are simply interested in replicating human results.
tegeek 12y ago
I think one of source of intelligence in humans is "imagination". IMO "Imagination" itself isn't intelligence but an input to the last "intelligent" activity. Computers can be taught to exhibit different "intelligent" activities and that is AI & Machine learning is all about. Human imagination works without any knowledge skill or learning (it is just my understanding, and i might be wrong). Producing rough and wild-west imagination isn't problem of AI.
- pavpanchekha 12y ago
  Whatever your opinions on what "intelligence" really is and the role of "imagination" in producing it, I can assure you that many computer scientists would like to replicate human creativity, heuristics, and problem solving techniques. Many of the early AI pioneers were as interested in understanding human thought and understanding machine thought (source: conversations with some of them). Modern techniques simply have a different aim.

PurplePanda 12y ago

I understand that other being hard to scale in a machine efficiency sense, the old techniques were also rather limited in applicable domain. They were often based on unjustified models of whatever the author decided was a good model of thought/reasoning, whether "frames", predicate calculus, constraint propagation or whatever. It seems to me that although you say statistical methods have little motivation, the motivation of the alternative - heuristics - is very questionable. Can anyone correct me on this?

pavpanchekha 12y ago
That's actually what I meant by scale—that they were slow isn't really a problem if you're interested in AI for the raw fun of it. While justifications for using logic or constraints or probability theory were often lacking from classical techniques, do understand that logic itself was originally developed as a crystallization of proper human thought. And many of the classic AI folks did care deeply about understanding how humans achieved certain results. For example, take a look at Marvin Minsky's work. To the contrary, modern techniques aren't interested in replicating human thought; they are simply interested in replicating human results.

tegeek 12y ago

I think one of source of intelligence in humans is "imagination". IMO "Imagination" itself isn't intelligence but an input to the last "intelligent" activity. Computers can be taught to exhibit different "intelligent" activities and that is AI & Machine learning is all about. Human imagination works without any knowledge skill or learning (it is just my understanding, and i might be wrong). Producing rough and wild-west imagination isn't problem of AI.

pavpanchekha 12y ago
Whatever your opinions on what "intelligence" really is and the role of "imagination" in producing it, I can assure you that many computer scientists would like to replicate human creativity, heuristics, and problem solving techniques. Many of the early AI pioneers were as interested in understanding human thought and understanding machine thought (source: conversations with some of them). Modern techniques simply have a different aim.