http://www.youtube.com/watch?v=bYYonyqHIoc
Where does this fit into the AI progression?
Does anyone know the underlying technology base. (01)
Ron (02)
John F. Sowa wrote:
> From time to time, I let loose a little rant about the Semantic Web.
> It's not that I'm opposed to the SemWeb. On the contrary, the goals
> are wonderful. But I'm frustrated by seeing another repetition of
> a phenomenon that has plagued the field of artificial intelligence
> since its inception over half a century ago.
>
> AI is dominated by brilliant people who are totally out of touch
> with anything and everything that goes on in the field of commercial
> data processing. There is no question that many of their ideas
> could, if properly implemented, revolutionize commercial systems.
>
> But that little qualifier "if properly implemented" is the major
> hurdle. Most of the AI researchers over the past half century have
> had little or no conception of how to implement anything that the
> commercial market could use. Conversely, few of the people in
> the commercial field have any idea of how to use anything that
> the AI researchers have produced.
>
> Since I worked at IBM for 30 years, I gained an appreciation for
> both sides of the divide, and I tried to do my part in helping to
> bring them together. But I was painfully aware of the great many
> developments that widened it.
>
> In the first decade of AI (mid 1950s to mid '60s), most of the
> cutting edge research was done on IBM hardware. Art Samuels,
> for example, was a pioneer in both game-playing programs and
> machine learning. At 3 o'clock in the morning, he would run
> multiple versions of his checker-playing programs on IBM 704
> computers on the assembly line in Poughkeepsie. Nat Rochester,
> who had been the head engineer for the IBM 701, also did early
> research on neural nets. Nat was one of the four organizers of
> the founding meeting for AI in 1956 (along with John McCarthy,
> Marvin Minsky, and Claude Shannon).
>
> The first split with commercial DP was also one of the most
> brilliant. John McCarthy designed the LISP language, which he
> tailored to run on the IBM 704. Although it ran on IBM hardware,
> it was so remote from commercial languages like FORTRAN and COBOL,
> that the LISP culture was disjoint from the commercial directions
> and applications. However, the fact that LISP ran on the same
> hardware meant that some sharing was possible.
>
> The total split occurred in 1964, when IBM announced the System/360
> line of compatible computers. Since the AI groups at MIT and Stanford
> needed to buy new hardware, they agreed to buy compatible machines so
> that they could share programs. Around that time, the new DEC PDP-6
> cost about the same as an IBM 360 Model 50, but it was as fast as
> the Model 65. Both MIT and Stanford bought PDP-6s, and most other
> AI centers followed suit. Of course, the MIT and Stanford systems
> became incompatible with the first lines of code written for each,
> but at least they belonged to the same culture.
>
> The next opportunity to bring AI into the mainstream of commercial
> systems came in the 1980s. The Japanese Fifth Generation Project
> spurred interest in AI around the world, and many commercial companies,
> including IBM, thought that the time was ripe to bring AI into the
> mainstream. But most of the AI community was still running on DEC
> equipment, which was not in the mainstream of commercial software.
> The rest of the AI community had migrated to LISP machines, which
> were so far removed from the commercial community that any kind
> of collaboration was unimaginable.
>
> But 1981 also brought the IBM PC, and many entrepreneurs developed
> expert systems (and versions of LISP) to run on the PC. At that
> time, IBM France had implemented an outstanding version of Prolog
> that ran on both the PC and the mainframes. On the mainframes,
> IBM Prolog reached the performance goals of the Japanese Fifth
> Generation: One MEGALIPS (Millions of Logical Inferences per
> Second), and it it was well integrated with relational databases.
> It provided an excellent platform for building deductive systems
> as adjuncts to commercial databases.
>
> I tried to persuade IBM developers who were interested in AI
> to build their software on top of Prolog, which was IBM's only
> world-class AI product. But instead, they decided to build
> half-vast imitations of EMYCIN from Stanford and OPS5 from
> Carnegie Mellon. Those products failed miserably in the
> marketplace, and they richly deserved to do so.
>
> Some of the AI companies founded in the 1980s still survive,
> and they continue to produce useful AI software. The biggest
> is Symantec, which had the goal of developing software for
> natural language processing. After a couple of years, the
> VCs put their own people in charge, who made money by selling
> the utilities that were intended to support NLP. The most
> famous AI company from the 1980s is Cyc, which survived on
> research grants rather than profitable products.
>
> In the late 1980s, the AI hype machine dried up, and the hype
> shifted to Object Oriented Programming Systems (OOPS), another
> technology from the 1960s -- Simula 67, which also inspired
> Smalltalk and many other languages. The AI gang responded
> with the Common Lisp Object System (CLOS), which was ignored
> by the commercial community because it looked like LISP.
>
> In the 1990s, however, Sun produced a version of CLOS with
> a notation that looked like C, and named it Java. Fortunately,
> Sun had enough people who understood both commercial DP and
> AI software that they were able to make Java successful.
>
> When I look at the Semantic Web, the original goals as outlined
> by Tim B-L, and the kinds of software they have implemented,
> it's "deja vu all over again".
>
> Following is an excerpt from a previous note I sent to this forum.
>
> John
> __________________________________________________________________
>
> My major complaint about the Semantic Web is that they ignored all
> the development techniques that worked successfully for years, and
> they failed to provide a migration path.
>
> Following are some of the most egregious blunders:
>
> 1. Ignoring the fact that every major web site is built on top
> of a relational database. The major sites use big commercial
> databases. Smaller sites are based on LAMP -- Linux, Apache,
> MySQL, and Perl, Python, or PHP.
>
> 2. Building RDF on top of triples, instead of the SQL n-tuples.
>
> 3. Failing to integrate their notations with UML diagrams, which
> include type hierarchies and various notations for constraints.
>
> If the Semantic Web had addressed these three issues from the beginning,
> it would have been integrated into the mainstream of data processing in
> about 3 or 4 years. Today, we would have seen some truly spectacular
> applications.
>
> The SemWeb still has a chance, but it has to be integrated with the
> mainstream of data processing before it can become the mainstream.
>
>
> _________________________________________________________________
> Message Archives: http://ontolog.cim3.net/forum/ontolog-forum/
> Config Subscr: http://ontolog.cim3.net/mailman/listinfo/ontolog-forum/
> Unsubscribe: mailto:ontolog-forum-leave@xxxxxxxxxxxxxxxx
> Shared Files: http://ontolog.cim3.net/file/
> Community Wiki: http://ontolog.cim3.net/wiki/
> To join: http://ontolog.cim3.net/cgi-bin/wiki.pl?WikiHomePage#nid1J
> To Post: mailto:ontolog-forum@xxxxxxxxxxxxxxxx
>
>
> (03)
_________________________________________________________________
Message Archives: http://ontolog.cim3.net/forum/ontolog-forum/
Config Subscr: http://ontolog.cim3.net/mailman/listinfo/ontolog-forum/
Unsubscribe: mailto:ontolog-forum-leave@xxxxxxxxxxxxxxxx
Shared Files: http://ontolog.cim3.net/file/
Community Wiki: http://ontolog.cim3.net/wiki/
To join: http://ontolog.cim3.net/cgi-bin/wiki.pl?WikiHomePage#nid1J
To Post: mailto:ontolog-forum@xxxxxxxxxxxxxxxx (04)
|