Fifth Generation Computer Systems: Difference between revisions

Revision as of 14:18, 17 October 2022

Revision as of 22:23, 30 November 2022

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== Results ==

The belief that parallel computing was the future of all performance gains generated by the Fifth-Generation project produced a wave of apprehension in the computer field. After having influenced the [[consumer electronics]] field during the 1970s and the [[automotive]] world during the 1980s, the Japanese in the 1980shad developed a strong reputation. The launch of the FGCS project spread the belief that parallel computing was the future of all performance gains, producing a wave of apprehension in the computer field. Soon parallel projects were set up in the US as the [[Strategic Computing Initiative]] and the [[Microelectronics and Computer Technology Corporation]] (MCC), in the UK as [[Alvey]], and in Europe as the [[European Strategic Program on Research in Information Technology]] (ESPRIT), as well as the [[European Computer‐Industry Research Centre]] (ECRC) in [[Munich]], a collaboration between [[International Computers Limited|ICL]] in Britain, [[Groupe Bull|Bull]] in France, and [[Siemens]] in Germany.

The project ran from 1982 to 1994, spending a little less than ¥57 billion (about US$320 million) total.<ref name=Odagiri/> After the FGCS Project, [[Ministry of International Trade and Industry|MITI]] stopped funding large-scale computer research projects, and the research momentum developed by the FGCS Project dissipated. However MITI/ICOT embarked on a neural-net project{{which|reason=which project exactly?|date=July 2022}} which some called the Sixth Generation Project in the 1990s, with a similar level of funding.<ref>{{cite book |last1=MIZOGUCHI |first1=FUMIO |title=Prolog and its Applications: A Japanese perspective |date=14 December 2013 |publisher=Springer |isbn=978-1-4899-7144-9 |page=ix |url=https://www.google.com/books/edition/Prolog_and_its_Applications/Uxv3BwAAQBAJ?hl=en&gbpv=1&pg=PR9 |language=en}}</ref> Per-year spending was less than 1% of the entire R&D expenditure of the electronics and communications equipment industry. For example the project's highest expenditure year was 7.2 million yen in 1991, but IBM alone spent 1.5 billion dollars (370 billion yen) in 1982, while the industry spent 2150 billion yen in 1990.<ref name=Odagiri/>

Five running [[Parallel Inference Machine]]s (PIM) were eventually produced: PIM/m, PIM/p, PIM/i, PIM/k, PIM/c. The project also produced applications to run on these systems, such as the parallel [[database management system]] Kappa, the [[legal reasoning system]] ''[[HELIC-II]]'', and the [[automated theorem prover]] ''[[MGTP]]'', as well as applications to [[bioinformatics]].

After the FGCS Project, [[Ministry of International Trade and Industry|MITI]] stopped funding large-scale computer research projects, and the research momentum developed by the FGCS Project dissipated. However MITI/ICOT embarked on a neural-net project{{which|reason=which project exactly?|date=July 2022}} which some called the Sixth Generation Project in the 1990s, with a similar level of funding.<ref>{{cite book |last1=MIZOGUCHI |first1=FUMIO |title=Prolog and its Applications: A Japanese perspective |date=14 December 2013 |publisher=Springer |isbn=978-1-4899-7144-9 |page=ix |url=https://www.google.com/books/edition/Prolog_and_its_Applications/Uxv3BwAAQBAJ?hl=en&gbpv=1&pg=PR9 |language=en}}</ref>

=== Concurrent logic programming ===

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=== Commercial failure ===

Five running [[Parallel Inference Machine]]s (PIM) were eventually produced: PIM/m, PIM/p, PIM/i, PIM/k, PIM/c. The project also produced applications to run on these systems, such as the parallel [[database management system]] Kappa, the [[legal reasoning system]] ''[[HELIC-II]]'', and the [[automated theorem prover]] ''[[MGTP]]'', as well as applications to [[bioinformatics]].

The FGCS Project did not meet with commercial success for reasons similar to the [[Lisp machine]] companies and [[Thinking Machines Corporation|Thinking Machines]]. The highly parallel computer architecture was eventually surpassed in speed by less specialized hardware (for example, Sun workstations and [[Intel]] [[x86]] machines).

A primary problem was the choice of concurrent logic programming as the bridge between the parallel computer architecture and the use of logic as a [[knowledge representation]] and problem solving language for AI applications. This never happened cleanly; a number of languages were developed, all with their own limitations. In particular, the committed choice feature of [[concurrent constraint logic programming]] interfered with the logical semantics of the languages.<ref>Carl Hewitt. [https://arxiv.org/abs/0904.3036 Inconsistency Robustness in Logic Programming] ArXiv 2009.</ref> The project found that the promises of [[logic programming]] were largely negated by the use of committed choice.{{Citation needed|date=August 2011}}

Another problem was that existing CPU performance quickly pushed through the barriers that experts perceived in the 1980s, and the value of parallel computing dropped to the point where it was for some time used only in niche situations. Although a number of [[workstation]]s of increasing capacity were designed and built over the project's lifespan, they generally found themselves soon outperformed by "off the shelf" units available commercially.

The project also failed to maintain continuous growth. During its lifespan, [[GUI]]s became mainstream in computers; the [[internet]] enabled locally stored databases to become distributed; and even simple research projects provided better real-world results in data mining.{{Citation needed|date=September 2008}} Moreover, the project found that the promises of [[logic programming]] were largely negated by the use of committed choice.{{Citation needed|date=August 2011}}

At the end of the ten-year period, the project had spent over ¥50 billion (about US$400 million at 1992 exchange rates) and was terminated without having met its goals. The workstations had no appeal in a market where general purpose systems could now replace and outperform them. This is parallel to the Lisp machine market, where rule-based systems such as [[CLIPS]] could run on general-purpose computers, making expensive Lisp machines unnecessary.<ref name='HendlerEditorial'>{{cite journal|last=Hendler|first=James|title=Avoiding Another AI Winter|journal=IEEE Intelligent Systems|date=1 March 2008|volume=23|issue=2|pages=2–4|doi=10.1109/MIS.2008.20|s2cid=35914860|url=http://csdl2.computer.org/comp/mags/ex/2008/02/mex2008020002.pdf|url-status=dead|archive-url=https://web.archive.org/web/20120212012656/http://csdl2.computer.org/comp/mags/ex/2008/02/mex2008020002.pdf|archive-date=12 February 2012}}</ref>

=== Ahead of its time ===

In summary, the Fifth-Generation project was revolutionary, and accomplished some basic research that anticipated future research directions. Many papers and patents were published. MITI established a committee which assessed the performance of the FGCS Project as having made major contributions in computing, in particular eliminating bottlenecks in parallel processing software and the realization of intelligent

Albeit not having produced much success, many of the approaches seen in the Fifth-Generation project, such as logic programming have been distributed over massive knowledge-bases, and are now being re-interpreted in current technologies. For example, the [[Web Ontology Language]] (OWL) employs several layers of logic-based knowledge representation systems. It appears, however, that these new technologies reinvented rather than leveraged approaches investigated under the Fifth-Generation initiative.

Ininteractive summary,processing itbased ison arguedlarge thatknowledge thebases. Fifth-GenerationHowever, projectthe committee was revolutionary,strongly biased to produce a positive howeveroutcome, stillso hadthis areasoverstates ofthe actual downfallresults.<ref name=Odagiri>{{Cite journal|last1=Odagiri|first1=Hiroyuki|last2=Nakamura|first2=Yoshiaki|last3=Shibuya|first3=Minorul|date=1997|title=Research consortia as a vehicle for basic research: The case of a fifth generation computer project in Japan|url=https://linkinghub.elsevier.com/retrieve/pii/S0048733397000085|journal=Research Policy|language=en|volume=26|issue=2|pages=191–207|doi=10.1016/S0048-7333(97)00008-5}}</ref>

Many of the themes seen in the Fifth-Generation project are now being re-interpreted in current technologies. In the early 21st century, many flavors of [[parallel computing]] began to proliferate, including [[multi-core]] architectures at the low-end and [[massively parallel|massively parallel processing]] at the high end. When [[clock speed]]s of CPUs began to move into the 3–5&nbsp;GHz range, [[CPU power dissipation]] and other problems became more important. The ability of [[Private industry |industry]] to produce ever-faster single CPU systems (linked to [[Moore's Law]] about the periodic doubling of transistor counts) began to be threatened. Ordinary consumer machines and [[game console]]s began to have parallel processors like the [[Intel Core]], [[AMD K10]], and [[Cell (microprocessor)|Cell]]. [[Graphics card]] companies like Nvidia and AMD began introducing large parallel systems like [[CUDA]] and [[OpenCL]]. Again,On however,another itline isof notdevelopment, clearthe that[[Web theseOntology developmentsLanguage]] were(OWL) facilitatedemploys inseveral anylayers significantof waylogic-based byknowledge therepresentation Fifth-Generation projectsystems.{{cn}}

It appears, however, that these new technologies do not cite FGCS research. It is not clear if FGCS was leveraged to facilitate these developments in any significant way. No significant impact of FGCS on the computing industry has been demonstrated.{{cn}}

In summary, it is argued that the Fifth-Generation project was revolutionary, however, still had areas of downfall.<ref>{{Cite journal|last1=Odagiri|first1=Hiroyuki|last2=Nakamura|first2=Yoshiaki|last3=Shibuya|first3=Minorul|date=1997|title=Research consortia as a vehicle for basic research: The case of a fifth generation computer project in Japan|url=https://linkinghub.elsevier.com/retrieve/pii/S0048733397000085|journal=Research Policy|language=en|volume=26|issue=2|pages=191–207|doi=10.1016/S0048-7333(97)00008-5}}</ref>

== References ==