Forwarding in case anyone is interested.
-------- Original Message --------
Subject: [>Htech] comp.ai.nat-lang: Marcus Hutter's lossless compression of
human knowledge prize
Date: Mon, 07 Aug 2006 21:07:52 +1000
From: Alejandro Dubrovsky <[EMAIL PROTECTED]>
Reply-To: [EMAIL PROTECTED]
To: transhumantech <[EMAIL PROTECTED]>
(
http://groups.google.com/group/comp.ai.nat-lang/browse_frm/thread/9411183ccde5f7a1/22cde6b64a28741b
)
From: James A. Bowery - view profile
Date: Mon, Aug 7 2006 5:39 am
Email: "James A. Bowery" <[EMAIL PROTECTED]>
Groups: comp.ai.nat-lang
Introducing the Hutter Prize for Lossless Compression of Human
Knowledge
Artificial intelligence researchers finally have an objective and
rigorously validated measure of the intelligence of their machines.
Furthermore the higher the measured intelligence of their machines the
more money they can win via the Hutter Prize.
The purse for the Hutter Prize was initially underwritten with a 50,000
Euro commitment to the prize fund by Marcus Hutter of the Swiss Dalle
Molle Institute for Artificial Intelligence, affiliated with the
University of Lugano and The University of Applied Sciences of Southern
Switzerland.
The theoretic basis of the Hutter Prize is related to an insight by the
12th century philosopher, William of Ockham, called "Ockham's Razor",
sometimes quoted as: "It is vain to do with more what can be done with
less." But it was not till the year 2000 that this was mathematically
proven*, by Marcus Hutter, to be a founding principle of intelligence.
Indeed, Hutter's Razor** might be phrased, "It is truer to explain with
less that which can be explained with more."
There have been previous tests and related prizes for artificial
intelligence, such as the Turing Test and the Loebner Prize. However,
these tests suffered from subjective definitions of intelligence.
Hutter's recent theoretic breakthrough creates a mathematics of
artificial intelligence which accurately measures the degree of
intelligence possessed by an artificial agent. It does so by measuring
how succinctly it represents knowledge of the world. As Hutter has now
proven, the most succinct computer model of the world isn't just the
most aesthetic or memory-efficient out of all models of the known
observations -- it also most accurately predicts new observations. In
short, it is the most intelligent.
Artificial intelligence has thereby entered the realm of engineering:
Lossless compression of human knowledge.
This is momentous because by optimizing for rigorous metrics, the field
of artificial intelligence may finally clarify the murky waters of
inadequate definition, within which it has been haphazardly swimming
for the last 50 years, to become both a hard science and tractable
engineering discipline.
Named for the discoverer of the proof and the initial 50,000 Euro
donor, the Hutter Prize currently targets the compression of a 100
megabyte sample of human knowledge drawn from the broadly based
Wikipedia online encyclopedia. As Moore's Law increases the capacity
of machines, and as additional donations to the prize fund increase the
incentives of contestants, the intent is to increase the amount of
knowledge targeted for compression. It is reasonable to expect that
the 100 megabyte sample will produce, at the very least, advances in
linguistic modeling. As the targeted depth and breadth of knowledge
increases, conceptual frameworks will come into play, eventually
covering the range of disciplines from political science to physics by
applying theories that prove optimal in compressing the target.
A common objection to this approach to artificial intelligence is that
it offers little that is new -- that the computational difficulty of
searching for patterns in data remains what it has always been. This
objection misses two important points:
1) Hutter's proof provides a new mathematics of intelligence allowing
for "top down" theoretic advances which may render many problems
tractable that otherwise appear intractable.
2) There is a large overlap between succinctly codified knowledge and
an intelligent compression program. Indeed, a reasonable definition of
"knowledge" is that it optimizes the compression of new observations as
instances of old patterns. This means that even if a compressor does
nothing but apply codified human knowledge, generating no new knowledge
of its own, it can still demonstrate greater intelligence than
competing programs and thereby make measurable progress toward
artificial intelligence but also -- and this is key -- progressively
more intelligent bodies of human-generated knowledge by pitting those
bodies of knowledge against each other in what might be called an
epistemological tournament.
The formula for winnings is modeled after the M-Prize or Methuselah
Mouse Prize, which awards money to longevity researchers for progress
in keeping mice alive the longest. Here, modified for compression
ratios, is the formula:
S = size of program outputting the uncompressed knowledge
Snew = new record
Sprev = previous record
P = [Sprev - Snew] / Sprev = percent improvement
Award monies:
Fund contains: Z at noon GMT on day of new record
Winner receives: Z * P
Initially Z is 50,000 Euro with a minimum payout of 500 Euro (or
minimum improvement of 1% over the prior winner).
Donations are welcome. The history of improvement in The Calgary
Corpus Compression Challenge*** is about 3% per year. The larger the
commitment from donors to the fund, the greater the rate of progress
toward a high quality body of human knowledge and, quite possibly, the
long-held promise of artificial intelligence.
For further details of the Hutter Prize see:
http://prize.hutter1.net
For discussion of the Hutter Prize see:
http://groups.google.com/group/Hutter-Prize
-- Jim Bowery
* http://www.hutter1.net/ai/uaibook.htm
** Hutter's Razor has some caveats relating to the nature of the
universe and computability, but those conditions must be met for any
computer-based intelligence.
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--
Brian Atkins
Singularity Institute for Artificial Intelligence
http://www.singinst.org/
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