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AIList Digest Volume 5 Issue 251
AIList Digest Wednesday, 28 Oct 1987 Volume 5 : Issue 251
Today's Topics:
Obituary - A.N. Kolmogorov,
Review - Spang Robinson Report on Supercomputing, V1 N2,
Comments - AI Methodology
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Date: 26 Oct 1987 10:18:13-EST (Monday)
From: Leonid Levin <LND%BU-CS.BU.EDU@forsythe.stanford.edu>
Reply-to: TheoryNet List
Subject: The death of A.N. Kolmogorov.
I just learned that in Moscow died Andrei Nikolayevich Kolmogorov - a
great mathematician who also made crucial contributions to Theoretical
Computer Science, Probability and Statistics, Information Theory and
other fields. He also was one of those rare people whose personal
integrity influenced ethical and human standards to the extent possible
under the difficult conditions of a totalitarian state.
Any telegrams from organizations and persons who appreciated the
contributions of A.N. Kolmogorov will be gratefully received. They may
be directed to Moscow University, The Academy of Sciences of the
U.S.S.R. and the widow Anna Dmitriyevna Kolmogorov (117234, Moscow,
Moscow University, korpus (building) L, apartment 10, USSR).
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Date: Sun, 25 Oct 1987 12:23 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Review - Spang Robinson Report on Supercomputing, V1 N2
Summary of Spang Robinson Report on Supercomputing and Parallel Processing
Volume 1 , No. 2
The lead article is on Hypercube based systems emphasizing the offerings
from Intel, NCUBE and Floating Point Systems.
The first implementation of the Hypercube based architectures was in the Soviet
Union in the 1970's. Spang Robinson estimates revenues from 15 to 20
million dollars per year from Hypercube companies in 1987. OVUM predicts 1.15
billion dollar revenue from hypercubes in 1990.
Intel Scientific Computers has benchmarked its 80286 based vector processor with
32 nodes against a Cray X-MP on a Fluid Dynamics Code and achieved equivalent
performance. The iPSC/2 has 80386 and 80387 in each node with 512KB. They
use Unix V.3 and a Concurrent Workbench which allows multiple users to share
the node. System prices ranges from $165,000 to $1.76 million for systems
from 16 nodes to 128 nodes. The 64 node vector processor sells for $929
thousand.
Floating Point Systems reports 1.2 GigaFlps on their T200 system. They have
made a total of ten installations. The node contains a T414 Transputer as
a control node, a vector processor, 1 meg of RAM and four communication links.
Each node takes one printed circuit board and eight nodes are grouped with
an 80 meg disk storage unit. A T-20 costing $400,000 contains 16 nodes and
is rated at 192 MFLOPS. A T200 with 128 nodes costs 3 millions. They
use a DEC micro VAX II to host the system and some system programming
is done in OCCAM. One is installed at Clemson University where they are
install SPICE.
Ametek sold several S-14 systems and is working on a second-geeneration
product with announcements planned before the end of 1987. They have doubled
their building space.
NCUBE uses a proprietary chip at each node with 512 kilobytes of memory and
twenty-two DMA channels. 64 nodes are on a single printed circuit board.
The NCUBE 7 goes to 128 nodes ($350,000 with 500 MB DISK) and the NCUBE 10
goes to 1024 nodes ($1.7 million). An NCUBE 4 that fits in a PC is from $20,000
to $60,000. They use a UNIX like operating system.
A total of 70 installations have been made with half in Universities.
___________________________________________________________________
Book Review: The Supercomputer Era by Sidney Karin and Norris Parker Smith
_________________________________________________________________________
Discussions of Cray Research changes included the departure of Steve Chen.
Steve Chen has formally announced a new corporation to continue the
research.
__________________________________________________________________________
The NSA has set up its own supercomputer development project, deciding that
industry will not produce products meeting its need.
------------------------------
Date: 23 Oct 87 16:35:26 GMT
From: umix!umich!dwt@uunet.UU.NET (Dave West)
Reply-to: umix!zippy.eecs.umich.edu!dwt@uunet.UU.NET (David West)
Subject: Re: Lenat's AM program
In article <8710211650.AA18715@orstcs.CS.ORST.EDU> tgd@ORSTCS.CS.ORST.EDU
(Tom Dietterich) writes:
>The exact reasons for the success of AM (and for its eventual failure
>to continue making new discoveries) have not been established. [...]
>
>The problem with all of these explanations is that they have not been
>subjected to rigorous experimental and analytical tests, so at the
>present time, we still (more than ten years after AM) do not
>understand why AM worked!
Some possible contributing reasons for this sort of difficulty in AI:
1) The practitioners of AI routinely lack access at the nuts-and-bolts level
to the products of others' work. (At a talk he gave here three years ago,
Lenat said that he was preparing a distribution version of AM. Has
anyone heard whether it is available? I haven't.) Perhaps widespread
availability and use of Common Lisp will change this. Perhaps not.
2) The supporting institutions (and most practitioners) have little
patience for anything as unexciting and 'unproductive' as slow,
painstaking post-mortems.
3) We still have no fruitful paradigm for intelligence and discovery.
4) We are still, for the most part, too insecure to discuss difficulties
and failures in ways that enable others as well as ourselves to learn
from them. (See an article on the front page of the NYTimes book review
two or three weeks ago for a review of a book claiming that twentieth-
century science writing in general is fundamentally misleading in this
respect.)
David West dwt@zippy.eecs.umich.edu
------------------------------
Date: 26 Oct 87 19:57:47 GMT
From: ritcv!cci632!mdl@cs.rochester.edu (Michael Liss)
Subject: Re: Goal of AI: where are we going? (the right way?)
In article <285@usl> khl@usl.usl.edu.UUCP (Calvin K. H. Leung) writes:
>I agree with the idea that there must be some mechanisms that our
>minds are using. But the different reasoning methods (proba-
>bilistic reasoning, for instance) that we are studying in the
>area of AI are not the way one reasons: we never use the Bayes'
>Theorem in our thinking process. The use of those reasoning
>methods, in my point of view, will never help increase our under-
>standing of human behavior. Because our minds just don't work
>that way.
I read an interesting article recently which had the title:
"If AI = The Human Brain, Cars Should Have Legs"
The author's premise was that most of our other machines that mimic human
abilites do not do so through strict copying of our physical processes.
What we have done, in the case of the automobile, is to make use of wheels and
axles and the internal combustion engine to produce a transportation device
which owes nothing tothe study of human legs.
In the case of AI, he state that artificial intelligence should not be
assumed to be the equivalent of human intelligence and thus, the disection of
the human mind's functionality will not necessarily yield a solution to AI.
He closes with the following:
"And I suspect it [AI] will develop without reference to natural intelligence
and should so develop. And I am sure it will not replace human thinking any
more than the autombile replaces human walking."
"Why am I so soft in the middle when the rest of my life is so hard?" -- P.Simon
Mike Liss {rochester, ritcv}!cci632!mdl (716) 482-5000
------------------------------
Date: 26 Oct 87 17:03:26 GMT
From: net1!todd@sdcsvax.ucsd.edu (Todd Goodman)
Subject: Re: The Success of AI
In article <131@glenlivet.hci.hw.ac.uk> gilbert@hci.hw.ac.uk
(Gilbert Cockton) writes:
>"Better" concepts related to mind than those found in cog. sci.
>already exist. The starting point is the elaboration of the observable human
>phenomena which we are attempting to unify within a study of mind. These
>phenomena have been studied since the dawn of time. There are many
>monumental works of schlarship which unify the phenomena grouped into
>well-defined subfields. The only problem for AI workers surveying all
>these masterpieces is that none of the authors are committed to
>computational models. Indeed, they would no doubt laugh at anyone who
>suggested that their work could be reduced to a Turing Machine compatible
>notation.
Please, please, please give us a bibliography of these works. In fact a
short summary would be great, along with the reasons that you find them to be
better than any current models. Also if you could point out which are at odds
with each and which you feel are "better" than others, then I would be greatly
appreciative.
This isn't a flame about your response to the earlier posting. I just want to
take a look at the monumental works you're talking about.
Todd Goodman
todd@net1.ucsd.edu
...!{ucbvax|ihnp4}!sdcsvax!net1!todd
------------------------------
Date: 26 Oct 87 03:31:00 GMT
From: uxc.cso.uiuc.edu!osiris.cso.uiuc.edu!goldfain@a.cs.uiuc.edu
Subject: Re: The Success of AI
> tsmith@gryphon.CTS.COM writes
> Now here's the interesting point. If you were to come to me and say--
> "Smith, you have a year to develop an automaton that will play some
> kind of major sport at a championship level, competing against humans.
> Money is no object, and you can have access to all the world's
> experts in AI and robotics, but you must design a robot that plays
> championship X in a year's time. What is X?" I would say, without a
> moment's hesistation, "tennis".
>
> Why? Of all the sports, tennis is the most bounded. It is played within
> a very restricted area (unlike golf or even baseball), it is a
> one-against-one sport (unlike football or soccer), the playing surfaces
> (aside from Wimbledon) are the truest of all the major sports, and it
> is indubitably the most boring of all the sports to watch (if not to
> play). A perfect candidate for automation.
> ----------------
Hmmm, by your own criterion, I would prefer table tennis, or to make life
really easy, bowling. I had heard that a table-tennis playing robot has been
developed that is really quite good. Bowling is really way too simple.
(If what I have heard is correct, othello would also be a good choice -
computers have already been claimed by some to outperform humans here, but
it's not a major sport.)
------------------------------
Date: 27 Oct 87 02:06:56 GMT
From: topaz.rutgers.edu!josh@rutgers.edu (J Storrs Hall)
Subject: Re: The Success of AI
> tsmith@gryphon.CTS.COM writes
> Now here's the interesting point. If you were to come to me and say--
> "Smith, you have a year to develop an automaton that will play some
> kind of major sport at a championship level, competing against humans.
> Money is no object, and you can have access to all the world's
> experts in AI and robotics, but you must design a robot that plays
> championship X in a year's time. What is X?" I would say, without a
> moment's hesistation, "tennis".
Goldfain says bowling, which is a very good choice, being in a
completely artificial environment. It might have (with ping-pong)
the problem of not "really being a sport". If we define "major sport"
as something done outside in real time against competition and often
televised on major networks, I would have to go with the 50 yard dash.
If we allow any olympic event, offhand sharpshooting looks promising,
javelin throwing looks easy, shot put looks trivial.
In fact, the more I think about it, tennis is probably one of the
*hardest* sports to implement. I imagine a team of football-playing
robots: they look something like tanks...
The point in all this is obviously that in the history of replacing
human effort with mechanical effort, brute force was the first success
story.
* * * *
"The Yankees pitcher steps to the mound. It is a Cincinnati Milacron
G97A22013 just brought up from the minors. Here's the pitch! Holy
cow! A 957 mph fastball on the inside corner for strike one! ..."
--JoSH
------------------------------
Date: 26 Oct 87 03:38:41 GMT
From: imagen!atari!portal!cup.portal.com!tony_mak_makonnen@ucbvax.Berk
eley.EDU
Subject: Re: The success of AI (misunderstandings)
this is exemplary of what happens when many perspectives enter the
picture and words flow . I submit the following :
It was Von Neuman himself ( I believe) who said that anything
that can be calculated precisely i.e. mathematically can be done
better by a computer . ( I think this should pass even by the
most rabid hater of computers )
I note that man who is getting lambasted used the words computed
and computational. I should think he would agree that if one began
to talk of reflection , intuition and so on , the conversation
would be totally different . Else are we to think that with great enough
and intensive computation the machine will eventually exhibit awareness
of itself as something that is .?!
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End of AIList Digest
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