On 11/29/06, Mark Waser <[EMAIL PROTECTED]> wrote:
> A human doesn't have enough time to look through millions of pieces of
> data, and doesn't have enough memory to retain them all in memory, and
> certainly doesn't have the time or the memory to examine all of the
> 10^(insert large number here) different relationships between these
> pieces of data.
True, however, I would argue that the same is true of an AI. If you assume
that an AI can do this, then *you* are not being pragmatic.
Understanding is compiling data into knowledge. If you're just brute
forcing millions of pieces of data, then you don't understand the problem --
though you may be able to solve it -- and validating your answers and
placing intelligent/rational boundaries/caveats on them is not possible.
Matt was not arguing over whether what an AI does should be called
"understanding" or "statistics". Matt was discussing what the right
way to design an AI is. It is the human who (at first) designs the
AI. Designs that require the designer to have super-human abilities
are poor designs. Thus, the machine-learning black-box approach is a
better design.
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