However, a machine with a lossless model will still outperform one with a
lossy model because the lossless model has more knowledge.
PKZip has a lossless model. Are you claiming that it has more knowledge?
More data/information *might* be arguable but certainly not knowledge -- and
PKZip certainly can't use any "knowledge" that you claim that it "has".
This does not change the fact that lossless compression is the right way
to evaluate a language model.
. . . . in *your* opinion. I might argue that it is the *easiest* way to
evaluate a language model but certainly NOT the best -- and I would then
argue, therefore, not the "right" way either.
A lossy model cannot be evaluated objectively
Bullsh*t. I've given you several examples of how. You've discarded them
because you felt that they were "too difficult" and/or you didn't understand
them.
- - - - -
No one here seems to be biting on your challenge. Stridently insisting
that you're correct doesn't seem to be working either. Is there knowledge
to be gained from that?
----- Original Message -----
From: "Matt Mahoney" <[EMAIL PROTECTED]>
To: <agi@v2.listbox.com>
Sent: Friday, August 25, 2006 5:46 PM
Subject: Re: [agi] Lossy *&* lossless compressio
As I stated earlier, the fact that there is normal variation in human
language models makes it easier for a machine to pass the Turing test.
However, a machine with a lossless model will still outperform one with a
lossy model because the lossless model has more knowledge.
I agree it is important to understand how the human brain filters
information (lossy compression), especially vision and hearing. This does
not change the fact that lossless compression is the right way to evaluate
a language model. A lossy model cannot be evaluated objectively. I guess
we will have to agree to disagree.
-- Matt Mahoney, [EMAIL PROTECTED]
----- Original Message ----
From: Philip Goetz <[EMAIL PROTECTED]>
To: agi@v2.listbox.com
Sent: Friday, August 25, 2006 12:31:06 PM
Subject: Re: [agi] Lossy *&* lossless compressio
On 8/20/06, Matt Mahoney <[EMAIL PROTECTED]> wrote:
The argument for lossy vs. lossless compression as a test for AI seems to
be
motivated by the fact that humans use lossy compression to store memory,
and
cannot do lossless compression at all. The reason is that lossless
compression requires the ability to do deterministic computation. Lossy
compression does not. So this distinction is not important for machines.
No; the main argument is that lossy compression allows the use of
much, much more sophisticated, and much, much more powerful
compression algorithms, achieving much higher compression ratios.
Also, lossless compression is already nearly as good as it can be.
Statistical methods will probably out-perform intelligent methods on
lossless compression, especially if the size of the compressor is
included.
The proof that an ideal language model implies passing the Turing test
requires a lossless model. A lossy model has only partial knowledge of
the
distribution of strings in natural language dialogs. Without full
knowledge, it is not possible to duplicate the same distribution of
equivalent representations of the same idea, allowing such expressions to
be
recognized as not human, even if the compression is ideal.
By this argument, no human can pass the Turing test, since none of us
have the same distributions, either. Or perhaps just one human can
pass it. Presumably Turing.
You will never, never, never, never recreate the same exact language
model in a computer as resides in any particular human. Losslessness
is relevant only when you need to recreate it exactly, and you can't,
so it's irrelevant.
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