HDTenEightyP/NetNews huggingface dataset:
From: crawford@boole.mitre.org (Randy Crawford)
Subject: Re: B.S. Degree
Organization: The MITRE Corporation, McLean, VA
Date: Sun, 22 Nov 1992 03:17:34 GMT

In article <1992Nov19.232802.22588@saifr00.cfsat.honeywell.com> shanks@saifr00.cfsat.honeywell.com (Mark Shanks) writes:
>In article <BxzCKy.JtC@acsu.buffalo.edu> rapaport@acsu.buffalo.edu (William J. Rapaport) writes:
>
>>But, in any case, why do you think it matters whether your degree says
>>"BS" or "BA"?  Do you think one is "better" than the other? 
>
>Well, the corporations think it matters. Go knock on the door at
>GM, McDonnell Douglas, Boeing, or Honeywell (and these are the ones
>I know of) with a BA, and you will be given the bum's rush. It's
>a corporate "cookbook" thing. No BS - no job.

At best this assertion is incomplete.  At worst it's completely wrong.

BS degrees in music are categorically useless when applying for employment at
corporations (other than in sales).  BA degrees in physics or computer science 
are usually valued highly.

The letter after the "B" is FAR less important than the major.  Belief otherwise
is just folklore.

>
>>At MIT, I'm told, English majors get a BS in English, so I'm not
>>sure that what the degree is called really matters.
>
>Only if you're looking for a job at one of the corporations. The US
>military academies operate the same way - BS is what it says on the
>diploma. Doesn't matter what you focused on (although you don't
>get many electives there anyway.) That has been my experience over
>the last 10 years. 

In both cases (MIT or USMA English majors) the graduates must complete courses
in calculus and the sciences well in excess of that expected of BA recipients
elsewhere.  The determining factor in the type of bachelor's degree is not the
major area, but the cognates.  BS recipients are presumed to be grounded in
more general science coursework than BAs, and vice-versa for the humanities.

A case might be made for corporations preferring BS degrees in english over
BAs.  But why hire a BS in english when the alternative might be a BA in
physics or computer science?  I just can't see the BS would realistically
be preferred over the BA, unless all else were equal.

>
>I recommend a BSEE, then get your BSCS or MSCS.  Then you can work for anyone.

True, if you're fond of hardware.  But the better preparation for advanced 
work in CS is a bachelor's degree in math.  And a BS in marketing with a MS 
in CS is a very good combination (or a BS in CS followed by a MBA).  Just 
about _any_ technical or business degree followed by the MS in CS is a healthy
combination.  Just ask an ex-zoologist such as myself.

-- 

| Randy Crawford        crawford@mitre.org        The MITRE Corporation
|                                                 7525 Colshire Dr., MS Z421
| N=1 -> P=NP           703 883-7940              McLean, VA  22102
Newsgroups: comp.ai,news.groups
From: twpierce@unix.amherst.edu (Tim Pierce)
Subject: Re: RFD -- where to put "fuzzy"?
Organization: Elitist Usenet Administrators, Stuff & Nonsense Division
Date: Sun, 22 Nov 1992 05:30:47 GMT

In article <1992Nov21.052548.28052@kong.gsfc.nasa.gov> joslyn@kong.gsfc.nasa.gov (Cliff Joslyn) writes:

>So what's wrong with sci.math.fuzzy, or sci.fuzzy?

I'd recommend sci.math.fuzzy; sci.fuzzy begs cutesy newbies.  All your
points here are good arguments against sci.logic.fuzzy, however.

-- 
____ Tim Pierce                / 
\  / twpierce@unix.amherst.edu /               Rocks say goodbye.
 \/ (BITnet: TWPIERCE@AMHERST) /
From: bernard@sirius.gte.com (Bernard Silver)
Newsgroups: comp.ai
Subject: Re: Grad school comments
Date: 18 Nov 92 13:13:49 GMT
	<2B0917E4.DC7@deneva.sdd.trw.com>
	<1992Nov17.170454.9426@saifr00.cfsat.honeywell.com>
Organization: GTE Laboratories Incorporated
In-reply-to: shanks@saifr00.cfsat.honeywell.com's message of 17 Nov 92 17:04:54 GMT



In article <1992Nov17.170454.9426@saifr00.cfsat.honeywell.com> shanks@saifr00.cfsat.honeywell.com (Mark Shanks) writes:

   In article <2B0917E4.DC7@deneva.sdd.trw.com> shrdlu@willow.sdd.trw.com (Lynda L. True) writes:
   >> Much in the same way you have to have a High School Diploma or a B.S.,
   >> a graduate degree is pretty much required as proof of competency in
   >> the field of AI.
   >
   >Hah! Again I say HAH! I've been working in the field of AI for ten (count 'em,
   >ten) years, and I have a BA. Not even a BS, and not even in comp sci (although
   >I DID minor in comp sci).
   >

   Mmmmmm, I disagree with you, Lynda, at least as far as the larger corps.
   You are quite fortunate - *most* large engineering-oriented corporations
   (at least in my experience) won't even TALK to you without a BSEE/BSCS,
   and, as is largely the case with Human Factors, for AI an advanced degree
   is de rigueur. Mind, I'm not saying that's the way it OUGHT to be, but
   I think your experience is more the exception than the rule. I would
   be prepared to do a LOT of fancy tap-dancing if I wanted to get my foot
   in the door of a serious AI lab without at least an MSCS. Maybe not
   a "union card"; more like a ticket or a coupon good for 90% reduction
   in harrasment during interviews.

I agree with Mark.  Note that Lynda started in AI ten years ago.
Ten years ago, AI was very hot and there was a shortage of practitioners.
Now, there is great competition and, however good you are, you are unlikely
to make the cut in the resume review.  We get huge numbers of resumes and
need some way of paring them down.  Lack of a graduate degree is an
obvious one.


--
				Bernard Silver
				GTE Laboratories
				bsilver@gte.com
				(617) 466-2663
Newsgroups: comp.ai,news.groups
From: joslyn@kong.gsfc.nasa.gov (Cliff Joslyn)
Subject: Re: RFD -- where to put "fuzzy"?
Organization: Goddard Space Flight Center
Date: Sat, 21 Nov 92 05:25:48 GMT

tanaka@til.til.com (Yokichi Tanaka) writes:

>In article <1992Nov18.041604.8072@sol.ctr.columbia.edu>, jwiegand@moe.eng.temple.edu () writes:
>|> Sci.logic.fuzzy sounds good!

>It sounds like most people want a fuzzy newsgroup in 
>"sci.logic.fuzzy".  It sounds good to me, too.

sci.logic.fuzzy is certainly acceptible to me, but is technically not
accurate. Note that fuzzy theory began as fuzzy SET theory, and became
fuzzy logic through the mathematical isomorphisms between (common
lattice structures of) set inclusion and classical logic. The term
"fuzzy logic" has been popularized by Zadeh to the point of
faddishness. I'll stress again: fuzzy theory is about INFORMATION, and
only to the extent that that is about intelligence or logic then there
is crossover.

But fuzzy THEORISTS (as opposed to the engineers) work in a hybrid
world involving Dempster-Shafer evidence theory, capacity theory,
fuzzy and belief measures, possibilistic information, and even (gasp!)
probability! Part of my program is to proselytize (sp?) about this
broad world of information theories outside the narrower view of just
fuzzy, not to mention just fuzzy LOGIC.

So what's wrong with sci.math.fuzzy, or sci.fuzzy?

>By the way, since fuzzy is a relatively new field, my hope is that
>the newsgroup will be a place where we can share, teach and help 
>each other in a constructive and amicable manner.  (And, I'm
>confident that's how it'll end up.)

Amen. 

O----------------------------------------------------------------------------->
| Cliff Joslyn, Cybernetician at Large, 327 Spring St #2 Portland ME 04102 USA
| Systems Science, SUNY Binghamton      NASA Goddard Space Flight Center
| cjoslyn@bingsuns.cc.binghamton.edu    joslyn@kong.gsfc.nasa.gov
V All the world is biscuit shaped. . .
Newsgroups: comp.ai,comp.ai.genetic,rec.games.programmer
From: ginsberg@t.Stanford.EDU (Matthew L. Ginsberg)
Subject: Re: How to pick a grad school
Organization: Computer Science Department, Stanford University.
Date: Mon, 16 Nov 1992 16:50:25 GMT

In article <1992Nov15.233702.11813@CSD-NewsHost.Stanford.EDU> I wrote:

>Of Stanford's recent graduates for whom I know what's happened, one
>has a post doc at UCLA.  One got a temporary job at SRI, another is
>going to Siemens.  A variety of Asian students have faculty jobs in
>the Pacific Rim.  The reason Stanford did poorly on my list is that I
>would have hoped our students had fared better in the job market.

I've been reminded that one of Stanford's recent grads is now faculty
at Brown.  Sorry (especially to the individual involved!) for the
oversight --

						Matt Ginsberg

Newsgroups: comp.ai
From: ginsberg@t.Stanford.EDU (Matthew L. Ginsberg)
Subject: How to pick a grad school
Organization: Computer Science Department, Stanford University.
Date: Sun, 15 Nov 1992 23:37:02 GMT


As I might have expected, I've gotten a lot of grief about my AI grad
school ranking.  So let me try and give people some higher-level advice.

If you're looking for a grad school in AI, get a copy of the recent
proceedings of a large conference like AAAI, IJCAI, or KR.  Look
through the proceedings and find a few articles that you like, by
people you think it would be interesting to work for or around.  Then
find out (somehow) when the authors of those articles got their
Ph.D.'s, and:

1.  If more than 7 years ago, think about attending the school where the
author is faculty.

2.  If between 4 and 7 years ago, be careful.  By the time you apply
and are admitted, the author will be in the middle of a tenure
decision.  He or she may well not have a great deal of time to devote
to new students, and may fail to get tenure as well.

3.  If less than 4 years ago, consider attending the school where the
author *went*.  Papers published soon after graduation often represent
more the quality of the advisor than the quality of the author.  Of
course, the author gets some credit too, so you might want to consider
the author's school as well.

The other thing you should do when selecting a school is to ask for
specific information about the current status of their recent AI
graduates.  I personally would discount any graduates who are employed
at the school where they received their degree.

Of Stanford's recent graduates for whom I know what's happened, one
has a post doc at UCLA.  One got a temporary job at SRI, another is
going to Siemens.  A variety of Asian students have faculty jobs in
the Pacific Rim.  The reason Stanford did poorly on my list is that I
would have hoped our students had fared better in the job market.

All that said, I believe that my original list reflected this advice
fairly well.  CMU and Toronto were at the top because their students
have been getting the best jobs recently.  The two schools on my list
that *didn't* follow the advice were the University of Washington,
which has three young faculty members whom I respect very much, and
the University of Oregon, whose AI faculty is about to improve
substantially.

Good luck!

						Matt Ginsberg

Xref: sparky comp.ai:4313 sci.math:15089 sci.math.stat:2362
From: f175003@wilma.ucdavis.edu
Newsgroups: comp.ai,sci.math,sci.math.stat
Subject: Looking for Good Intro to Bayesian Classifiers
Date: 16 Nov 92 21:25:27 GMT
Followup-To: comp.ai
Distribution: usa
Organization: Computing Services, UC Davis
Originator: f175003@wilma.ucdavis.edu

I am looking for a book or paper with a good introduction into using 
Bayesian Classifiers preferably with a few examples showing how to 
determine the probabilities.  I understand the idea behind a Bayesian 
Classifier, but I have looked at a couple of examples of Bayesian 
Classifiers and they appeared to use maximum likelihood estimators to 
determine the values for the various probabilities.  According to my 
statistics book, this method provides excellent estimates if the sample 
size is large, but in the cases I hope to be dealing with I will only 
have a few samples and want to get as much information from them as I can.

There has also been some discussion here about whether 
there exist some values for the probabilities of the classes and the 
probabilities of the various attributes given the class, which tells 
you as much as possible from the given samples.  The methods I have 
seen require a prior distribution and show you how to determine the 
posterior distribution after seeing each example.  One then chooses a value 
from this distribution using their favorite function, such as mean, median, 
or mode, or equivalently by using some loss function.  It seems that their 
is no value for the probabilities which will give you as much
information as possible about the samples without chosing some
type of loss function.  Is this correct and is there some way to 
prove if it is or is not correct?

Please reply via email.  I'll appreciate any help I can get.

Robert Davis
Department of Computer Science
University of California, Davis
email:  davisr@cs.ucdavis.edu
Newsgroups: comp.ai
From: jdooley@urbana.mcd.mot.com (John Dooley)
Subject: Re: How to pick a grad school
Organization: Motorola Computer Group, Urbana Design Center
Date: Wed, 18 Nov 1992 19:16:40 GMT

ginsberg@t.Stanford.EDU (Matthew L. Ginsberg) writes:

>Yes,
>graduate school will teach you (hopefully) to organize your time,
>teach, write papers and present them.  But those are all things that
>you can, if need be, learn elsewhere (albeit perhaps with some
>difficulty).  What graduate school teaches you that you can't learn
>anywhere else is to be a scientist.  And the person you learn that
>from, more than anyone else, is your faculty advisor.

>						Matt Ginsberg

I'd like to disagree about graduate schools teaching you how to
_teach_.  If the two graduate schools I attended as a TA are any
example, teaching you to teach is the farthest thing from their minds.
One of them gave first year students a 1/2 day seminar on teaching
run by the senior grad students. You then got a textbook, a syllabus,
two course sections and a cheery "See you in December".  In the other,
TA's rarely got to actually teach anything. Mostly we graded papers,
and if you were lucky got to run a lab section or substitute for the
prof on occasion.  IMHO grad school is about _research_, not teaching.

I would love to see a grad program in CS (pick any sub-discipline)
that is geared toward putting it's graduates into the classroom -
especially the undergraduate classroom.  I learned to teach during my
first full-time teaching job at a small four-year college.  My
department chair, who'd been teaching for 20 years at that point was
my mentor, source of problems and examples, sounding board, critic, 
etc, etc.

I learned a lot in grad school, but I certainly didn't learn to teach
there.

cheers,
john

-- 
John F. Dooley                   jdooley@urbana.mcd.mot.com
(217) 384-8591                   ...uiucuxc!udc!jdooley
Motorola Urbana Design Center, 1101 E. University Ave. Urbana, IL 61801
             "These certainly aren't Motorola's opinions..."
Newsgroups: comp.ai
From: s324615@twncu865.ncu.edu.tw
Subject: comp.ai.fuzzy
Organization: Computer Center, NCU, Taiwan, R.O.C.
Date: Mon, 16 Nov 1992 11:15:52 GMT

Vote: YES
Newsgroups: comp.ai
From: shanks@saifr00.cfsat.honeywell.com (Mark Shanks)
Subject: Re: Grad school comments
Organization: Honeywell Air Transport Systems Division
Date: Tue, 17 Nov 92 17:04:54 GMT

In article <2B0917E4.DC7@deneva.sdd.trw.com> shrdlu@willow.sdd.trw.com (Lynda L. True) writes:
>> Much in the same way you have to have a High School Diploma or a B.S.,
>> a graduate degree is pretty much required as proof of competency in
>> the field of AI.
>
>Hah! Again I say HAH! I've been working in the field of AI for ten (count 'em,
>ten) years, and I have a BA. Not even a BS, and not even in comp sci (although
>I DID minor in comp sci).
>
>>Bottom line: If you want to pursue a career in AI, then get the graduate degree
>>(even if you don't want to)... get it done... it's a "union" card.
>
>Nope. It's not only NOT a union card, but out of the productive people I've
>worked with, only one has had a doctorate (which was in psych), and a small
>handful have had master's degrees. Advanced degrees are for those who are
>serious about research. If you can't make it in research, don't think that
>industry wants you.
>
>>Added dislaimer: Of course, it is possible to have a career in AI without a
>>graduate degree, but it's just not very probable.
>
>Yeah, right. In the past ten years, I've worked with lots and lots of people.
>They didn't have graduate degrees for the most part, and they have had great
>careers. In fact, the only person that I've known who has an AI background and
>is also out of work has a doctorate.

Mmmmmm, I disagree with you, Lynda, at least as far as the larger corps.
You are quite fortunate - *most* large engineering-oriented corporations
(at least in my experience) won't even TALK to you without a BSEE/BSCS,
and, as is largely the case with Human Factors, for AI an advanced degree
is de rigueur. Mind, I'm not saying that's the way it OUGHT to be, but
I think your experience is more the exception than the rule. I would
be prepared to do a LOT of fancy tap-dancing if I wanted to get my foot
in the door of a serious AI lab without at least an MSCS. Maybe not
a "union card"; more like a ticket or a coupon good for 90% reduction
in harrasment during interviews.

Mark Shanks
shanks@saifr00.cfsat.honeywell.com
Newsgroups: comp.ai,comp.ai.shells
From: gabetzos@rodan.acs.syr.edu (Betzos)
Subject: Info needed : expert system shells, companies
Summary: expert system shells
Keywords: expert system shells, companies, industrial applications
Organization: Syracuse University, Syracuse, NY
Date: Wed, 18 Nov 92 14:49:46 EST


Dear netnews readers,

A friend asked me to find out some information about companies that
have developed expert system shells.
He is overseas and has limited access to the network.
Please send your replies to me and I will forward them to him.
My email address is listed at the end of this message.

I would appreciate very much if you could provide me with the following
information about the companies listed below:

      Mail address
      Telephone number (800 and non 800 - to call from Europe)
      FAX number

1.  Inference Corporation (Expert System Shell ART)

2.  GOLDHILL Expert System Shell GoldWorksII (1-800-242-5477 ?)

3.  Texas Instruments (Expert System Shell Personal Consultant Plus 3.0
                       1-800-527-3500 ?)

Also my friend is interested in contacting other companies that provide
Expert System Shells (BIG systems for industrial applications). In
addition, a comparative evaluation or information about the systems would
be greatly appreciated. Pointers to where to find such information are also
welcome.

My friend has already contacted the following companies:

1. GenSym  (G2).
2. Intellicorp (KEE).
3. Neuron Data (Nexpert Object).

Again, please send your replies to me to the address listed below. Please
do not post because I don't read these groups. If there is enough interest
I will post a summary.

Thank you very much,

George Betzos

gabetzos@mailbox.syr.edu
From: jwkim@ece.arizona.edu (Jinwoo Kim)
Newsgroups: comp.ai
Subject: Reasoning Method for Object-Oriented KB
Date: 23 Nov 92 07:30:31 GMT
Distribution: world,local
Organization: U of Arizona Electrical and Computer Engineering

Dear Netters,

Hi,

I am looking for papers/references about Object-Oriented 
Knowledge-based Reasoning method. Is there any significant
difference non O-O KB reasoning and O-O KB reasoning. 

Maybe it depends on its knowledge representation scheme.
If there is enough replies, I'll post the summary.

Any comments will be very much welcomed!

--- jkim      email :: jwkim@helios.ece.arizona.edu
From: chenowet@rd1632.Dayton.NCR.COM (Steve Chenoweth)
Newsgroups: comp.ai
Subject: Re: Grad school comments
Date: 23 Nov 92 16:05:19 GMT
Reply-To: chenowet@rd1632.Dayton.NCR.com (Steve Chenoweth)
Organization: NCR Technology & Development, Dayton, Ohio

In article <1992Nov16.150247.3613@aisb.ed.ac.uk> e.reiter@ed.ac.uk () writes:
>...   Also, realize that very few of the people who start Ph.D programs end up
>20 years later as tenured professors at major research institutions; I suspect
>that the `ultimate success' rate even for students at the best universities
>is less than 10%. ...

It would be amusing to determine from more careful statistics what these odds
are, of a new grad student's making it eventually into a career position in
the academic world.  The universities themselves certainly are eager to have
the best students compete for these long-term goals, and sometimes make it
sound like the old advice that "if everyone works hard, they can all be
valedictorian."

As Prof. Reiter suggests, anyone pondering our recommendations should, above
all, have a realistic view of what they will get from the venture.


-- 
Steve.Chenoweth@Dayton.NCR.com
Newsgroups: comp.ai
From: MACDONAN@UK.AC.BHAM.IBM3090
Subject: art and technology
Date: Wed, 18 Nov 1992 13:54:18 GMT
Organization: The University of Birmingham, United Kingdom

Any ideas for a mini-conference on art and technology with special
emphasis on performing arts????
Newsgroups: comp.ai,comp.ai.genetic,rec.games.programmer
From: krulwich@zowie.ils.nwu.edu (Bruce Krulwich)
Subject: Re: Games and genetic algorithms
Followup-To: comp.ai,comp.ai.genetic,rec.games.programmer
Organization: The Institute for the Learning Sciences, Evanston, IL
	<1992Nov11.131739.19137@athena.mit.edu>
	<1992Nov16.175215.29411@versyss.com>
	<1992Nov18.210045.19530@Princeton.EDU>
	<PAULSON3-201192153909@kip2-11.apple.com>
	<PJA.92Nov23154818@neuron.cis.ohio-state.edu>
Date: Mon, 23 Nov 1992 21:34:49 GMT


Intuitively, does anyone really think that strategies for game playing are
learned in a random-permutation  evolutionary sort of way?  My intuition is
that people employ alot of reasoning, such as explanation, in learning new
strategies and in modifying old ones.  

Think, say, of a typical strategy in game-playing, such as the "fork" in
tic-tac-toe of chess.  It doesn't make sense to me that this would be learned
through random permutations, rather through a player explaining the ways in
which the enabled moves interact with the opponent's ability to respond.

For such an explanation-based approach to learning game strategies, see the
following papers:

	"Plan debuging an intentional system" (IJCAI91)
	Collins, Birnbaum, Krulwich, and Freed

	"Determining what to learn in a multi-component planning system"
	(CogSci91)  Krulwich

They can be FTP'ed anonymously:

Site:	ftp.ils.nwu.edu
Login:	anonymous
Pass:	anonymous
Dir:	pub/papers
Files:	gc_ijcai91.ps.Z and bk_cs91.ps.Z (respectively)
Newsgroups: comp.ai
Subject: Racter!
Date: Sun, 22 Nov 1992 12:30:12 -0500

Hello Ed!

 ES> I've been looking for ages for what I believe is "Racter"...an AI
 ES> program that supposedly composed fictional text (albeit somewhat
 ES> disjunct and bizarre).  I read about it in Omni and I guess it wrote a
 ES> book called "The Policeman's Beard Is Half Constructed".

 ES> Is there anyone out there that knows about it?  Was it a fake?

I'm not sure what you mean by a 'fake'.  The AI component of Racter was pretty
minimal -- better, perhaps, than 'Eliza', but still simpleminded.  I think what
it mostly did was search for keywords in user input, and plug them into
mostly-canned comments and responses.  It did occasionally generate a story, but
judging from its output (which was indeed 'disjunct and bizarre') it had no
world knowledge or reasoning; it was simply linking together sentences into
which it inserted words that it had picked up on.

 ES> Is it possible to still get a copy of this program?

I don't think so, but I'm not sure.  I used to have a copy of it for Macintosh;
I'm not sure where it went.

 ES> Are there similar or better programs available?

There's a program called 'TailSpin', which was a legitimate AI effort at Yale
during the 70's.  It wrote stories about fictional animal characters, based on
their goals and personalities; its language, which was generated from a
knowledge representation (unlike Racter), was clumsier and much simpler than
Racter's.  I don't know if source code is available anywhere.

Bruce