I have already proved something stronger
What would you consider your best reference/paper outlining your arguments?
Thanks in advance.
----- Original Message -----
From: "Matt Mahoney" <[EMAIL PROTECTED]>
To: <[email protected]>
Sent: Wednesday, October 22, 2008 8:55 PM
Subject: Re: AW: AW: [agi] Language learning (was Re: Defining AGI)
--- On Wed, 10/22/08, Dr. Matthias Heger <[EMAIL PROTECTED]> wrote:
You make the implicit assumption that a natural language
understanding system will pass the turing test. Can you prove this?
If you accept that a language model is a probability distribution over
text, then I have already proved something stronger. A language model
exactly duplicates the distribution of answers that a human would give.
The output is indistinguishable by any test. In fact a judge would have
some uncertainty about other people's language models. A judge could be
expected to attribute some errors in the model to normal human variation.
Furthermore, it is just an assumption that the ability to
have and to apply
the rules are really necessary to pass the turing test.
For these two reasons, you still haven't shown 3a and
3b.
I suppose you are right. Instead of encoding mathematical rules as a
grammar, with enough training data you can just code all possible
instances that are likely to be encountered. For example, instead of a
grammar rule to encode the commutative law of addition,
5 + 3 = a + b = b + a = 3 + 5
a model with a much larger training data set could just encode instances
with no generalization:
12 + 7 = 7 + 12
92 + 0.5 = 0.5 + 92
etc.
I believe this is how Google gets away with brute force n-gram statistics
instead of more sophisticated grammars. It's language model is probably
10^5 times larger than a human model (10^14 bits vs 10^9 bits). Shannon
observed in 1949 that random strings generated by n-gram models of English
(where n is the number of either letters or words) look like natural
language up to length 2n. For a typical human sized model (1 GB text), n
is about 3 words. To model strings longer than 6 words we would need more
sophisticated grammar rules. Google can model 5-grams (see
http://googleresearch.blogspot.com/2006/08/all-our-n-gram-are-belong-to-you.html )
, so it is able to generate and recognize (thus appear to understand)
sentences up to about 10 words.
By the way:
The turing test must convince 30% of the people.
Today there is a system which can already convince 25%
http://www.sciencedaily.com/releases/2008/10/081013112148.htm
It would be interesting to see a version of the Turing test where the
human confederate, machine, and judge all have access to a computer with
an internet connection. I wonder if this intelligence augmentation would
make the test easier or harder to pass?
-Matthias
> 3) you apply rules such as 5 * 7 = 35 -> 35 / 7 = 5
but
> you have not shown that
> 3a) that a language understanding system
necessarily(!) has
> this rules
> 3b) that a language understanding system
necessarily(!) can
> apply such rules
It must have the rules and apply them to pass the Turing
test.
-- Matt Mahoney, [EMAIL PROTECTED]
-- Matt Mahoney, [EMAIL PROTECTED]
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agi
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