Fifth Generation Computer Systems: Difference between revisions

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The '''Fifth Generation Computer Systems ''' ('''FGCS'''; {{lang-ja|第五世代コンピュータ|daigosedai konpyūta}}) was a 10-year initiative begun in 1982 by Japan's [[Ministry of International Trade and Industry]] (MITI) to create computers using [[massively parallel computing]] and [[logic programming]]. It aimed to create an "epoch-making computer" with supercomputer-like performance and to provide a platform for future developments in [[artificial intelligence]]. FGCS was ahead of its time, and its excessive ambitions led to commercial failure. However, on a theoretical level, the project spurred the development of [[concurrent logic programming]].

The term "fifth generation" was intended to convey the system as being advanced: In the [[history of computing hardware]], there were four "generations" of computers. Computers using [[vacuum tube]]s were called the first generation; [[transistor]]s and [[diode]]s, the second; [[integrated circuit]]s, the third; and those using [[microprocessor]]s, the fourth. Whereas previous computer generations had focused on increasing the number of logic elements in a single CPU, the fifth generation, it was widely believed at the time, would instead turn to massive numbers of CPUs to gain performance{{Citation needed|date=October 2023}}.

== Background ==

In the late 1960s until the early 1970s, there was much talk about "generations" of computer hardware, then usually organized into three generations.

# First generation: Thermionic vacuum tubes. Mid-1940s. IBM pioneered the arrangement of vacuum tubes in pluggable modules. The [[IBM 650]] was a first-generation computer.

# Second generation: Transistors. 1956. The era of miniaturization begins. Transistors are much smaller than vacuum tubes, draw less power, and generate less heat. Discrete transistors are soldered to circuit boards, with interconnections accomplished by stencil-screened conductive patterns on the reverse side. The [[IBM 7090]] was a second-generation computer.

# Third generation: Integrated circuits (silicon chips containing multiple transistors). 1964. A pioneering example is the ACPX module used in the IBM 360/91, which, by stacking layers of silicon over a ceramic substrate, accommodated over 20 transistors per chip; the chips could be packed together onto a circuit board to achieve unprecedented logic densities. The IBM 360/91 was a hybrid second- and third-generation computer.

Omitted from this taxonomy is the "zeroth-generation" computer based on metal gears (such as the [[IBM 407]]) or mechanical relays (such as the Mark I), and the post-third-generation computers based on Very Large Scale Integrated ([[VLSI]]) circuits.

There was also a parallel set of generations for software:

# [[First-generation programming language|First generation]]: [[Machine language]].

# [[Second-generation programming language|Second generation]]: [[Low-level programming language]]s such as [[Assembly language]].

# [[Third-generation programming language|Third generation]]: Structured [[high-level programming language]]s such as [[C (programming language)|C]], [[COBOL]] and [[FORTRAN]].

# [[Fourth-generation programming language|Fourth generation]]: "Non-procedural" [[high-level programming language]]s (such as object-oriented languages).<ref>{{Cite web|url=http://www.rogerclarke.com/SOS/SwareGenns.html|title = Roger Clarke's Software Generations}}</ref>

Throughout these multiple generations up to the 1970s, Japan built computers following U.S. and British leads. In the mid-1970s, the Ministry of International Trade and Industry stopped following western leads and started looking into the future of computing on a small scale. They asked the [[Japan Information Processing Development Center]] (JIPDEC) to indicate a number of future directions, and in 1979 offered a three-year contract to carry out more in-depth studies along with industry and academia. It was during this period that the term "fifth-generation computer" started to be used.

Prior to the 1970s, MITI guidance had successes such as an improved steel industry, the creation of the oil [[supertanker]], the automotive industry, consumer electronics, and computer memory. MITI decided that the future was going to be [[information technology]]. However, the [[Japanese language]], particularly in its written form, presented and still presents obstacles for computers.<ref>J. Marshall Unger, ''The Fifth Generation Fallacy'' (New York: Oxford University Press, 1987)</ref> As a result of these hurdles, MITI held a conference to seek assistance from experts.

The primary fields for investigation from this initial project were:

* Inference computer technologies for knowledge processing

* Computer technologies to process large-scale data bases and [[knowledge base]]s

* High-performance workstations

* Distributed functional computer technologies

* Super-computers for scientific calculation

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== Project launch ==

The aim was to build parallel computers for artificial intelligence applications using concurrent logic programming. The project imagined an "epoch-making" computer with supercomputer-like performance running on top of large [[database]]s (as opposed to a traditional [[filesystem]]) using a [[logic programming language]] to define and access the data using massively [[Parallel computing|parallel computing/processing]]. They envisioned building a prototype machine with performance between 100M and 1G LIPS, where a LIPS is a ''[[inference|Logical Inference]] Per Second.'' At the time typical workstation machines were capable of about 100k LIPS. They proposed to build this machine over a ten-year period, 3 years for initial R&D, 4 years for building various subsystems, and a final 3 years to complete a working prototype system. In 1982 the government decided to go ahead with the project, and established the '''Institute for New Generation Computer Technology''' (ICOT) through joint investment with various Japanese computer companies. After the project ended, MITI would consider an investment in a new "sixth generation" project. Pararell circuits used for interesting reasons.

[[Ehud Shapiro]] captured the rationale and motivations driving this project:<ref name="EhudTrip">{{Cite journal|doi = 10.1145/358172.358179|title = The fifth generation project — a trip report|year = 1983|last1 = Shapiro|first1 = Ehud Y.|journal = Communications of the ACM|volume = 26|issue = 9|pages = 637–641|s2cid = 5955109|doi-access = free}}</ref>

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The target defined by the FGCS project was to develop "Knowledge Information Processing systems" (roughly meaning, applied [[Artificial Intelligence]]). The chosen tool to implement this goal was [[logic programming]]. Logic programming approach as was characterized by Maarten Van Emden – one of its founders – as:<ref>Van Emden, Maarten H., and Robert A. Kowalski. [https://www.researchgate.net/profile/Maarten-Emden/publication/234779982_The_Semantics_of_Predicate_Logic_as_a_Programming_Language/links/0c96052857d2634345000000/The-Semantics-of-Predicate-Logic-as-a-Programming-Language.pdf "The semantics of predicate logic as a programming language."] Journal of the ACM 23.4 (1976): 733-742.</ref>

]] to produce ever-faster single CPU systems (linked to [[Moore's Law]] about the periodic doubling of transistor counts) began to be threatened.

* The use of logic to express information in a computer.

* The use of logic to present problems to a computer.

* The use of logical inference to solve these problems.

More technically, it can be summed up in two equations:

* ''Program'' = ''Set of axioms''.

* ''Computation'' = ''Proof of a statement from axioms''.

The Axioms typically used are universal axioms of a restricted form, called [[Horn clauses|Horn-clauses]] or [[Definite clause|definite-clauses]]. The statement proved in a computation is an existential statement.{{Citation needed|date=February 2021}} The proof is constructive, and provides values for the existentially quantified variables: these values constitute the output of the computation.

Logic programming was thought of as something that unified various gradients of computer science ([[software engineering]], [[databases]], [[computer architecture]] and [[artificial intelligence]]). It seemed that logic programming was a key missing connection between [[knowledge engineering]] and parallel computer architectures.

== Results ==

After having influenced the [[consumer electronics]] field during the 1970s and the [[automotive]] world during the 1980s, the Japanese had 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://books.google.com/books?id=Uxv3BwAAQBAJ&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/>

=== Concurrent logic programming ===

In 1982, during a visit to the ICOT, Ehud Shapiro invented Concurrent [[Prolog]], a novel programming language that integrated logic programming and concurrent programming. Concurrent Prolog is a [[Process-oriented programming|process oriented language]], which embodies [[dataflow]] synchronization and guarded-command [[Indeterminacy in concurrent computation|indeterminacy]] as its basic control mechanisms. Shapiro described the language in a Report marked as ICOT Technical Report 003,<ref>Shapiro E. A subset of Concurrent Prolog and its interpreter, ICOT Technical Report TR-003, Institute for New Generation Computer Technology, Tokyo, 1983. Also in Concurrent Prolog: Collected Papers, E. Shapiro (ed.), MIT Press, 1987, Chapter 2.</ref> which presented a Concurrent Prolog [[Interpreter (computing)|interpreter]] written in Prolog. Shapiro's work on Concurrent Prolog inspired a change in the direction of the FGCS from focusing on parallel implementation of Prolog to the focus on [[Logic programming#Concurrent logic programming|concurrent logic programming]] as the software foundation for the project.<ref name="EhudTrip"/> It also inspired the concurrent logic programming language Guarded Horn Clauses (GHC) by Ueda, which was the basis of [[KL1]], the programming language that was finally designed and implemented by the FGCS project as its core programming language.

The FGCS project and its findings contributed greatly to the development of the concurrent logic programming field. The project produced a new generation of promising Japanese researchers.

=== 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 bioinformatics applications.

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 benefits 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 overcame the barriers that experts anticipated 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 incorporate outside innovations. 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}}

The FGCS workstations had no appeal in a market where general purpose systems could 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

interactive processing based on large knowledge bases. However, the committee was strongly biased to justify the project, so this overstates the actual results.<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, as the hardware limitations foreseen in the 1980s were finally reached in the 2000s. 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.

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. 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]].