Fifth generation computers

Fifth generation computers

Fifth generation computers are mainly future computers. Of course some modern computers also belong to this generation. The aim of these computers is to develop devices that respond to natural language input and are capable of learning and self-organization. In these computers massive numbers of CPUs are used for more efficient performance. Voice recognition is a special feature in these computers. By using superconductors and parallel processing computer geeks are trying to make artificial intelligence a reality. Quantum computing, molecular and nanotechnology will change the face of computers in the coming years.

In the late 1960s till the early 1970s, there was much talk about "generations" of computer hardware — usually "three generations".

1. 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.
2. 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.
3. 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 unheard-of 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:

1. First generation: Machine language.
2. Second generation: Low-level programming languages such as Assembly language.
3. Third generation: Structured high-level programming languages such as C, COBOL and FORTRAN.
4. Fourth generation: Domain-specific high-level programming languages such as SQL (for database access) and TeX (for text formatting)

Throughout these multiple generations up to the 1990s, Japan had largely been a follower in the computing arena, building computers following U.S. and British leads. The Ministry of International Trade and Industry (MITI) decided to attempt to break out of this follow-the-leader pattern, and in the mid-1970s started looking, on a small scale, into the future of computing. 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, in both written and spoken form, presented and still presents major obstacles for computers. These hurdles could not be taken lightly. So MITI held a conference and invited people around the world to help them.

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 bases
• High performance workstations
• Distributed functional computer technologies
• Super-computers for scientific calculation

The project imagined an "epoch-making computer" with supercomputer-like performance using massively parallel computing/processing. The aim was to build parallel computers for artificial intelligence applications using concurrent logic programming. The FGCS project and its vast findings contributed greatly to the development of the concurrent logic programming field.

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:^[2]

• 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 or definite-clauses. The statement proved in a computation is an existential statement. The proof is constructive, and provides values for the existentially quantified variables: these values constitute the output of the computation.

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

In 1982, during a visit to the ICOT, Ehud Shapiro invented Concurrent Prolog, a novel concurrent programming language that integrated logic programming and concurrent programming. Concurrent Prolog is a logic programming language designed for concurrent programming and parallel execution. It is a process oriented language, which embodies dataflow synchronization and guarded-command indeterminacy as its basic control mechanisms. Shapiro described the language in a Report marked as ICOT Technical Report 003,^[3] which presented a Concurrent Prolog 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 concurrent logic programming as the software foundation for the project. 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 project imagined a parallel processing computer running on top of massive databases (as opposed to a traditional filesystem) using a logic programming language to define and access the data. They envisioned building a prototype machine with performance between 100M and 1G LIPS, where a LIPS is a 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.

Implementation

So ingrained was the belief that parallel computing was the future of all performance gains that the Fifth-Generation project generated a great deal of apprehension in the computer field. After having seen the Japanese take over the consumer electronics field during the 1970s and apparently doing the same in the automotive world during the 1980s, the Japanese in the 1980s had a reputation for invincibility. 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 ECRC (European Computer Research Centre) in Munich, a collaboration between ICL in Britain, Bull in France, and Siemens in Germany.

Five running Parallel Inference Machines (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.