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AIList Digest Volume 5 Issue 255
AIList Digest Tuesday, 3 Nov 1987 Volume 5 : Issue 255
Today's Topics:
Queries - OPS5 Programs & Future of AI,
Comments - Future of AI & Speech Understanding,
References - PDP & AI Categories,
Comments - Success of AI
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Date: 30 Oct 87 18:11:41 GMT
From: ihnp4!alberta!ajit@ucbvax.Berkeley.EDU (Ajit Singh)
Subject: Need OPS5 Programs
I am currently working on analyzing static characteristics
as well as run-time behavior of large production system
programs for the purposes of rule-clustering and distributed
processing. I am using OPS5 as my production system model. I
need lots of large and small OPS5 programs. Does anybody know
of any publically accessible library of such programs? Any
help in this direction will be greatly appreciated.
If you have some OPS5 programs (plus data if necessary) that
you would like to send to me then you may send them directly
via e-mail at the following address:
{ubc-vision, ihnp4, mnetor}!alberta!ajit
Thanks in advance,
Ajit Singh
Department of Computing Science
University of Alberta
Edmonton, Alberta
Canada
------------------------------
Date: 30 Oct 87 20:30:06 GMT
From: kirby@ngp.utexas.edu (Bruce Kirby)
Subject: The future of AI.... (nothing about flawed minds)
I have a question for people:
What practical effects do you think AI will have in the next ten
years?
What I am interested in is discovering what people expect to actually
come out of AI research in the near future, and how that will affect
society, business and government. I am not interested in the
long-term questions of what AI will eventually accomplish.
Some supplementary questions:
- What field of AI will produce practical applications?
- What will be the effect of a new application? (e.g. how would an
effective translation mechanism affect the way people function?)
- Who is likely to produce these useful applications? How are they
to be introduced?
Any comments/responses are welcome. I am just trying to get a feel
for what other people see as the near-term effects of AI research.
Bruce Kirby
kirby@ngp.utexas.edu
...!ut-sally!ut-ngp!kirby
------------------------------
Date: 1 Nov 87 04:15:00 GMT
From: uxc.cso.uiuc.edu!osiris.cso.uiuc.edu!goldfain@a.cs.uiuc.edu
Subject: Re: The future of AI.... (nothing about
Re: Products in the next 10 years coming from AI.
One thing that is currently out there, is a growing body of expert systems.
Many new ones are being churned out as we speak, and I think they will
continue to be produced at a gently accelerating rate over the next decade.
But many expert systems are frightfully narrow. They tend to be simplistic
and only apply when problems are just right. So look for additional layers,
which begin to show some real sophistication. I expect
"multi-expert-system-management-systems" to appear and to exhibit qualities
that will begin to look like the human traits of "judgement" and "learning by
analogy", and systems that will improve with time (autonomously).
------------------------------
Date: 31 Oct 87 13:52:15 GMT
From: gatech!hubcap!ncrcae!gollum!rolandi@rutgers.edu (rolandi)
Subject: Practical effects of AI
In article <6667@ut-ngp.UUCP> you write:
>I have a question for people:
> What practical effects do you think AI will have in the next ten
>years?
>........[etc...]
I 'd say that AI will have at least two real and immediate effects.
1) given AI programming tools and techniques, many processes
previously assumed to be too complicated for automation
will be automated. the automation of these tasks will
take less time given the productivity gains that AI tools
can provide. expert systems will be common place within
the DP/MIS world.
2) AI will make computers easier to use and therefore extend
their usefulness to non-computer people.
Regarding #2 above...
It would seem to me that the single greatest practical advancement for
AI will be in speaker independent, continuous speech recognition. This
is NOT to imply total computer "comprehension" in the sense of being
able to carry on an unrestricted conversation. I am NOT referring to
abilities to process natural language. That, is a long way off, and
will most likely come about as a function of a redefinition of the NLP
problem in terms of a machine learning issue. What "simple" speaker
independent, continuous speech recognition will provide is the ultimate
alternative to keyboard entry. This would thereby provide all of
the functionality of current technology to anyone who could pronounce
the commands. This issue will have a major impact on the industry and
on society. By making "every body" a user, more machines will be sold,
and because "every body" will have different needs, tha range of
automation will be widely extended.
-w.rolandi
ncrcae!gollum!rolandi
disclaimer: i speak for no one but myself and usually no one else is
listening.
------------------------------
Date: 31 Oct 87 22:06:02 GMT
From: PT.CS.CMU.EDU!SPEECH2.CS.CMU.EDU!kfl@cs.rochester.edu (Kai-Fu
Lee)
Subject: Re: Practical effects of AI (speech)
In article <12@gollum.Columbia.NCR.COM>, rolandi@gollum.Columbia.NCR.COM
(rolandi) writes:
>
> In article <6667@ut-ngp.UUCP> you write:
> >I have a question for people:
> > What practical effects do you think AI will have in the next ten
> >years?
> >........[etc...]
> It would seem to me that the single greatest practical advancement for
> AI will be in speaker independent, continuous speech recognition. This
> is NOT to imply total computer "comprehension" in the sense of being
> able to carry on an unrestricted conversation. I am NOT referring to
> abilities to process natural language. That, is a long way off, and
> will most likely come about as a function of a redefinition of the NLP
> problem in terms of a machine learning issue. What "simple" speaker
> independent, continuous speech recognition will provide is the ultimate
> alternative to keyboard entry. This would thereby provide all of
> the functionality of current technology to anyone who could pronounce
> the commands. This issue will have a major impact on the industry and
> on society. By making "every body" a user, more machines will be sold,
> and because "every body" will have different needs, tha range of
> automation will be widely extended.
>
Those of us who work on speech will be very encourage by this enthusiasm.
However,
(1) Speaker-independent continuous speech is much farther from reality
than some companies would have you think. Currently, the best
speech recognizer is IBM's Tangora, which makes about 6% errors
on a 20,000 word vocabulary. But the Tangora is for speaker-
dependent, isolate-words, grammar-guided recognition in a benign
environment. Each of these four constraints cuts the error rate
by 3 or more times if used independently. I don't know how well
they will do if you remove all four constraints, but I would guess
about 70% error rate. So while speech recognition has made a lot
of advancements, it is still far from usable in the application you
mentioned.
(2) Spoken English is a harder problem than NLP of written English.
If you make the recognizer too constrained (small vocabulary, fixed
syntax, etc.), it will be harder to use than a keyboard. If you don't,
you have to understand spoken English, which is really hard.
(3) If this product were to materialize, it is far from clear that it
would be an advancement for AI. At present, the most promising
techniques are based on stochastic modeling, pattern recognition,
information theory, signal processing, auditory modeling, etc..
So far, very few traditional AI techniques are used in, or work well
for speech recognition.
>
> -w.rolandi
> ncrcae!gollum!rolandi
Kai-Fu Lee
Computer Science Department
Carnegie-Mellon University
------------------------------
Date: 30 Oct 87 03:16:05 GMT
From: ihnp4!homxb!homxc!del@ucbvax.Berkeley.EDU (D.LEASURE)
Subject: PDP by Rummelhart and McClelland
After posting about a good text on parallel distributed processing aka
neural nets, I've had several requests for a full reference from
people I can't reach on the net directly.
The books are:
Parallel Distributed Processing: Explorations in the Microstructure
of Cognition, Vols. 1 and 2, by David E. Rumelhart and James L.
McClelland, Bradford Books, The MIT Press, 0-262-63110-5
The two volumes in paper are about $25 together. A third volume
with software for the PC (IBM), is also out this month.
I still recommend them.
--
David E. Leasure - AT&T Bell Laboratories - (201) 615-5307
------------------------------
Date: Fri, 30 Oct 1987 17:20 EST
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: AIList V5 #253 - LISP, NIL, Msc.
In reply to noekel@uklirb.UUCP who is
>
>currently building a AI bibliography and still searching for a
>suitable classification/key word scheme.
In the IRE Transactions on Human Factors in Electronics, March 1961, I
published a big (600 item) bibliography on AI. It may have been the
first published descriptor-index bibliography or, perhaps, the first
to use the term "descriptor", which I got from Calvin Mooers. Now
NOEKE wants one that has "gained wide-spread use in the AI community"
and my 1961 set of terms must be rather dated and does not reflect
many newer ideas. However, much of it may still be useful. And I
would be curious about how useful it might remain after all those
years.
The bibliography was a by-product of work on my other 1961 article,
"steps toward artificial intelligence" which appeared in the
Proceedings of the IRE (whose name later changed to Proc. IEEE.) The
reason the bibliographic appeared in the more obscure Human Factors
journal was that "Steps" was already too long and there was no more
room. Tom Marill was editing a special issue of the HF transactions
and offered to place it there because that issue contained other
AI-related topics.
------------------------------
Date: 31 Oct 87 03:44:44 GMT
From: honavar@speedy.wisc.edu (A Buggy AI Program)
Reply-to: honavar@speedy.wisc.edu (A Buggy AI Program)
Subject: Re: Success of AI
In article <8710280748.AA21340@jade.berkeley.edu> eitan@wisdom.BITNET
(Eitan Shterenbaum) writes:
>
>Had it ever come into you mind that simulating/emulating the human brain is
>NP problem ? ( Why ? Think !!! ). Unless some smartass comes out with a proof
>for NP=P yar can forget de whole damn thing ...
>
> Eitan Shterenbaum
>(*
> As far as I know one can't solve NP problems even with a super-duper
> hardware, so building such machine is pointless (Unless we are living on
> such machine ...) !
>*)
Discovering that a problem is NP-complete is usually just the
beginning of the work on the problem. The knowledge that a problem is
NP-complete provides valuable information on the lines of attack that
have the greatest potential for success. We can concentrate on algorithms
that are not guaranteed to run in polynomial time but do so most
of the time or those that give approximate solutions in polynomial time.
After all, the human brain does come up with approximate (reasonably good)
solutions to a lot of the perceptual tasks although the solution may not
always be the best possible. Knowing that a problem is NP-complete only
tells us that the chances of finding a polynomial time solution are minimal
(unless P=NP).
-- VGH
------------------------------
Date: 30 Oct 87 18:00:42 GMT
From: mcvax!ukc!its63b!hwcs!hci!gilbert@uunet.uu.net (Gilbert
Cockton)
Subject: Re: The Success of AI
In article <4171@sdcsvax.UCSD.EDU> todd@net1.UUCP (Todd Goodman) writes:
>>"Better" concepts related to mind than those found in cog. sci.
>>already exist. There are many monumental works of scholarship which unify
>> the phenomena grouped into well-defined subfields.
>
>Please, please, please give us a bibliography of these works.
Impossible at short notice. Obvious examples are Lyons' work on
semantics (1977?, 2 vols, Cambridge University Press). My answer to
anyone in AI about relevant scholarship is go and see your local
experts for a reading list and an orientation.
By "concepts related to mind", I intend all work concerned with
language, thought and action. That is, I mean an awful lot of work. My
first degree is in Education, which coupled with my earlier work in
History (especially social and intellectual history), brought me into
contact with a wide range of disciplines, and forced me to use each to
the satisfaction of those supervising me. However, I am now probably
out of date, as I've spent the last four years working in
Human-Computer Interaction.
Any work in linguistics under the heading of 'Semantics' should be of
great interest to people working in Knowledge Representation. There is
a substantial body of philosophical work under the heading of
"Philosophy of Mind". Unlike Cognitive Psychology (especially memory
and problem solving), this work has not become fixated on information
processing models. Anthropolgists are doing very interesting work on
category systems; the work of the "New" or "Cognitive" archaeologists
at Cambridge University (nearly all published by Cambridge University
Press) is drawing on much recent continental work on social action.
Any anthropologist should be able to direct you to the older work on
such cultures as the Subanum and the Trobriand Islanders - most of this
work was done by Americans and is more accessible, as it does not
require acquaintance with recent Structuralist and post-Structuralist
concepts, which can be very dense and esoteric.
>the reasons that you find them to be better than any current models.
This work is inherently superior to most work in AI because non of the
writers are encumbered by the need to produce computational models.
They are thus free to draw on richer theoretical orientations which
draw on concepts which are clearly motivated by everyday observations
of human activity. The work therefore results in images of man which
are far more humanist than mechanical computational models. Workers in
AI may be scornful of such values, but in reality they should realise
that adherents to a mechanistic view of human behaviour are very
isolated and in the minority, both now and throughout history. The
persistence of humanism as the dominant approach to the wider studies
of man, even after years of zealous attack from self-proclaimed
'Scientists', should be taken as a warning against the acceptability of
crude models of human behaviour. Furthermore, the common test of any
concept of mind is "can you really imagine your mind working this way?"
Many of the pillars of human societies, like the freedom and dignity of
democracy and moral values, are at odds with the so called 'Scientific'
models of human behaviour; indeed the work of misanthropes like Skinner
actively promote the connection between impoversihed models of man and
immoral totalitarian socities (B.F. Skinner, Beyond Freedom and Dignity).
In short, mechanical concepts of mind and the values of a civilised
society are at odds with each other. It is for this reason that modes
of representation such as the novel, poetry, sculpture and fine art
will continue to dominate the most comprehensive accounts of the human
condition.
--
Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN
JANET: gilbert@uk.ac.hw.hci ARPA: gilbert%hci.hw.ac.uk@cs.ucl.ac.uk
UUCP: ..{backbone}!mcvax!ukc!hwcs!hci!gilbert
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End of AIList Digest
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