AIList-REQUEST@SRI-AI.ARPA (AIList Moderator Kenneth Laws) (10/26/85)
AIList Digest Saturday, 26 Oct 1985 Volume 3 : Issue 156
Today's Topics:
Query - PSL vs Common Lisp,
AI Tools - Micro Lisps,
Literature - AI Book by Jackson,
Correction - Concurrent Logic Programming Languages,
Opinion - AI Hype
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Date: 24 Oct 1985 14:51 EDT (Thu)
From: Kimberle Koile <KKoile@BBNG.ARPA>
Subject: PSL vs Common Lisp
I'm interested in finding out about the differences between Portable
Standard Lisp and Common Lisp. Specifically, how difficult would it be to
take something that runs on a Symbolics machine (in Common Lisp) and make it
run in PSL on a Vax/VMS or a Cray?
Many thanks,
Kimberle Koile
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Date: Wed, 23 Oct 85 23:11:04 edt
From: osiris!snk (Steve Kahane)
Subject: Micro Lisps
RE: Dr Blum's (BLUM@sumex) request for information on LISP products
that run on micros:
A paper comparing three products that run in the IBM series of
personal computers (muLISP, IQLISP, GCLISP)
will be presented at the 1985 Symposium on Computer Applications
in Medical Care (SCAMC). Information will be presented on the
following:
Memory Addressing Capabilities
Development Environment (error handling, debugging facilities,
editing, graphics, windowing)
Tutoring Tools
Benchmarks
Compilers (GCLISP (beta-test)) IQC-LISP?
SCAMC meeting will be in Baltimore (Convention Ctr) on 11/10 - 11/13.
For more info on meeting call (202) 676-4509.
Reprints of the paper mentioned above are not yet available, but
if anyone has any specific questions I would be glad to try to
answer.
Stephen N. Kahane (snk@osiris)
Operational and Clinical Systems
Halsted 124
The Johns Hopkins Medical Institution
600 North Wolfe St
Baltimore, MD 21205
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Date: Fri, 25 Oct 1985 21:59 EDT
From: MINSKY%MIT-OZ@MIT-MC.ARPA
Subject: AI Book by Jackson
The Jackson book is
INTRODUCTION TO ARTIFICIAL INTELLIGENCE
Philip C. Jackson, Jr.
Dover Publications, New York, 1985
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Date: 25 Oct 1985 11:10-EDT
From: Vijay.Saraswat@K.CS.CMU.EDU
Subject: Concurrent Logic programming languages
Lest there be any misunderstanding: the presentation on Nov. 1 at CMU
is my thesis proposal NOT thesis defence! (The "Thesis Oral" in the
Subject field was a secretarial oversight.)
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Date: Thu 24 Oct 85 11:51:35-CDT
From: David Throop <AI.THROOP@R20.UTEXAS.EDU>
Subject: Hype about Hype
A CS professor recently told me that he was worried about the AI hype.
He (who is in databases, not AI) fears that so much has been promised that
there will be an anti-AI reaction and dissapointment that will hurt all of
CS. And I've seen much posted on this list about the dangers of all this
hype.
The fears seem a bit overblown to me. I've gone through the professional
employment adds in the New York Times and Wall Street Journal over the last
weeks. I didn't notice ANYBODY advertising for hotshots in AI, Rule Based
programming, LISP etc. The Austin American Statesman had one mention, but
just the "it would also be nice if the candidate had some experience in..."
form, what they were really looking for was UNIX.
UT has been aswarm with recruiters recently. I'm not interviewing, but
I've been talking with them in the halls and restaurants. Nobody up above
seems to have told them to grab some heavy AI talent - most of them think
experts systems are inferior to decision tree systems and are not
impressed.
The average American has > 14,000 commercial messages per WEEK aimed at
them. I most people are pretty used to hype -we don't get our hopes up
very easily.
When I see the strong reactions to some of the blatant BS being said
about AI, I'm puzzled. I suspect strongly that we're the only ones giving
some of this stuff more than a second glance.
Do you believe all the claims they make about your toothpaste?
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Date: Fri, 25 Oct 85 12:22 EST
From: "Christopher A. Welty" <weltyc%rpicie.csnet@CSNET-RELAY.ARPA>
Subject: Contributions of AI
I for one am tired of seeing this guy Gary Martins polluting
the net with his childish attacks on Dr. Minsky. Did Minsky run away
with his wife or something? Whatever the cause, keep your personal
problems off the net. This should be for more productive discussions
dealing with the field. Spending almost two hours some mornings reading
my mail is not rewarding when it invloves sifting through accusations
and wild generalizations, and things like this:
>Every other area of computing can point to a steady
>succession of useful contributions, large and small. From
>"AI" the world seems to get back very little, other than
>amateurish speculations, wild prophecies, toy programs,
>unproductive "tools", and chamberpots of monotonous hype.
>What's wrong ? [Gary Martins]
Read a few books, Mr Martins. Maybe go for a trip to some research centers,
or even to some companies and hospitals. Your messages are the only things
I can see that fit into the categories of "amateurish speculations, wild
prophecies, ..., and chamberpots of monotonous hype." AI has made significant
contributions to Computer Science Research, and to the world. Underneath
the "hype" are productive systems that are used to do such "toyish"
things as diagnose illnesses, and control processes that were once controlled
by humans (some of which were hazardous to those humans). These diagnostic
and control Expert Systems come in many forms. The most sophisticated
Data Base Systems in use today come from the knowledge-base systems sectors
of AI research. Other examples are all around us, and there are too many
to discuss, this message is long enough already.
-Chris
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Date: Fri 25 Oct 85 20:20:54-EDT
From: Richard A. Cowan <COWAN@MIT-XX.ARPA>
Subject: Causes of AI hype
This is a response to Gary Martins' question about why AI is frequently hyped.
[AILIST: Volume 3, #126] I thought about this for a while, so please tell me
which points are weak, or if there are any factors I missed. Martins asks:
- why this [hype] happens ?
- is this good or bad for "AI" ?
- does this happen in all high-tech fields, or is "AI"
unique ?
- what can or should be done about it ? by whom ?
I offer a simple explanation: a lot of money is being pumped into AI to do
things the field is not ready for. There are three different ways AI seems
"not ready," depending on the intended application.
1. Some applications being funded are within the state of the art,
but too few researchers are close enough to the state of the art to
warrant the volume of money spent.
2. Other applications currently being attempted are beyond state of
the art AI, but may be possible in 5 to 100 years.
3. Still other applications are forever beyond the capabilities of
AI, because they involve responsibilities requiring human judgement.
Reason number 1 generates hype because there is a continual stream of
people from other fields into AI. They go and take crash courses in
AI at various training centers, but what can they REALLY learn in one
week? They get an excellent overview, which has to be optimistic about AI
in order to justify the $3000 expense for the course.
Perhaps the huge expenditure on AI training within industry is needed to
rapidly enlarge the "AI labor force." But such expenditure puts a
severe strain on engineering faculty supply and salaries at universities
(MIT's former provost cited this as a primary cause of large tuition
increases). This hurts university education in AI just when the need is
most critical. It just might be better to slowly wait for the
university AI community to enlarge since dramatic corporate funding
increases at this stage also run the risk of damaging academic programs
by institutionalizing the hype (i.e. MIT's 6.871 Expert Systems course).
Reason number 2 generates hype because a disproportionate effort is
devoted to goals which are not achievable. Most engineering fields
are composed primarily of people applying well-understood engineering
skills. A relatively small number of especially creative people do
exploratory work advancing the engineering field itself. But in AI,
since little is well-understood, almost everyone works on "novel
ideas." Thus the "hype ratio" is very large.
I know an AI manager at DEC who (previous to DEC) worked on government
AI research contracts but now works on expert systems for industry.
He is glad to be working on real problems; by contrast much DOD AI
work was extremely detached from reality. When private sector profits
are at stake, there must be something real underneath the hype for
funding to be continued.
For a contrast to this, I posted an inquiry about TIMM a couple of weeks
back, which received 6 negative responses, and none positive. While
problems with one product does not mean that a company is incapable of
doing good work, the company (General Research Corporation) has received
over $12 million dollars in software research contracts for the
Strategic Defense Initiative (SDI) alone. I suspect the SDI office's
budget for corporate research is so large and the talent pool so small
that they can't be selective. Sorry to pick on General Research; I
expect many other companies are the same. It's perfectly possible that
such companies would do excellent work if the government would give them
problems with a more immediate use to solve.
I believe the Japanese 5th generation project will help Japan more than
SCI helps us because it has a more commercial orientation. I also
believe that the total US effort in AI (ONR + SDI + SCI) is too large.
It's always exciting to attack unsolved problems, but AI initiatives of
the recent mission-oriented nature consume an awful lot of resources.
Why not devote some of those resources to unsolved problems such as acid
rain which have interested professors but scant funds?
-Rich
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End of AIList Digest
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