What is fifth generation computing?
By Argonne National Laboratory's Flickr page [CC BY-SA 2.0 (https://creativecommons.org/licenses/by-sa/2.0)], via Wikimedia Commons
The Fifth Generation Computer Systems [Present and Beyond] (FGCS) was an initiative by Japan's Ministry of International Trade and Industry, begun in 1982, to create a computer using massively parallel computing/processing. It was to be the result of a massive government/industry research project in Japan during the 1980s. It aimed to create an "epoch-making computer" with supercomputer-like performance and to provide a platform for future developments in artificial intelligence. There was also an unrelated Russian project also named as a fifth-generation computer (see Kronos (computer)).
As we can see, in the early 80s the concept of fifth generation computing was a major buzzword similar to how we have buzzwords today such as "cloud computing". Just as EOS is being build for parallel processing in a blockchain context the fifth generation computers were designed for massively parallel processing. Japan and Russia both made attempts but the Japanese attempt is the one which triggered a reaction from the United States in particular which is relevant even today.
During this time the concept of blockchains were not yet invented and the discussion around this time was about AI. In essence this in my opinion indicates than an AI arms race was taking place even as far back as 1982 and shows at least in my opinion the relevance of the discussion today about weaponization of AI. In particularly Elon Musk has warned about the potential of an AI arms race and it appears that governments have funded the construction of super computers all along with AI dominance in mind.
The term "fifth generation" was intended to convey the system as being a leap beyond existing machines. In the history of computing hardware, computers using vacuum tubes were called the first generation; transistors and diodes, the second; integrated circuits, the third; and those using microprocessors, 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 for added performance.
The birth of Microelectronics and Computer Technology Corporation in response
The United States responded to Japanese government interest in AI with the facilitation of a consortium known as Microelectronics and Computer Technology Corporation (MCC). This particular company was gigantic by measures of it's time and focused on conducting cutting edge research into super computing and AI. In fact this organization even pioneered a move toward decentralized computing in it's time:
Distributed Information Technology (managing and maintaining physically distributed corporate information resources on different platforms, building blocks for the national information infrastructure, networking tools and services for integration within and between companies, and electronic commerce).
In addition MCC did not take government funding even though it was founded by former CIA/NSA.
Despite this purpose and the background of Inman and his senior staff, MCC accepted no government funding for many years and was a refuge for some avoiding work on Strategic Defense Initiative projects. MCC was part of the Artificial Intelligence boom of the 1980s, reportedly the single largest customer of both Symbolics and Lisp Machines, Inc. (and like Symbolics, was one of the first companies to register a .com domain). In the 1980s its major programs were Packaging, Software Engineering, CAD, and Advanced Computer Architectures. The latter comprised Artificial Intelligence, Human Interface, Database, and Parallel Processing, the latter two merging in the late 1980s.
The birth of Cyc
As we can see, MCC was a very important company in the 1980s in the technology and AI domains. In addition MCC is also the company responsible for one of the biggest AI projects ever launched known as Cyc:
The project was started in 1984 by Douglas Lenat at MCC and is developed by the Cycorp company. Until early 2017, parts of the project were released as OpenCyc, which provided an API, RDF endpoint, and data dump under an open source license.
Cyc is important to note because the design of the AI setup for Tauchain is what some could call a decentralized Cyc. Cyc was a symbolic style AI which relies on an inference engine, a shared knowledge base, and a knowledge representation language named CycL. Cyc was supposed to be an AI designed to run on the best supercomputers of it's time, as a sort of thinking machine which could use it's vast knowledge base and inference engine to generate common sense outputs.
Tauchain by design is intended to take some of the best concepts from Cyc combined with new concepts such as blockchain, Nomic, and more. The essence of what makes Tauchain possible is the Tau-MetaLanguage (TML) which some have described as an "Internet of languages". In essence it allows a user to create their own formal language using the processes to make that possible, such your own context free grammar so that you can determine the reserved symbols (syntax) for use in your programming language and the selection of your logic.
To be more specific and clear, any programming language must have it's syntax represented by it's reserved symbols which have meaning to programmers in that language, and "phrase names" are used to define the syntax. Syntax are the phrases and sentences necessary for your programming language (code). So what we have with TML for developers is an ability to use TML to define your own programming language and compiler. In other words, developers can code for Tau in any language they want.
Of course what also will make Tauchain special is the stuff which can be built once you have the most basic element (TML) in place. It then becomes possible to use TML to build Tauchain itself and to also take advantage of some of the unique powers seen in Cyc while building Tauchain. For example if the inference engine capabilities are in place then developers for Agoras will be able to rely on not only a shared knowledge base but a potentially decentralized shared knowledge base. This shared knowledge base if it works well could allow for a level of precision wisdom in development that the world has never seen before. Of course just as with EOS, these are nothing more than promising ideas which may take computing to the next level but which aren't going to build themselves.
While EOS promises us a high performance operating system so that possibly Steem and other platforms can scale, Tauchain is a different value proposition. EOS being an operating system, and Tauchain being a general purpose meta language with interfence engine and other features. Both are in my opinion necessary infrastructure for next level computing but to put it into perspective I see EOS like building a next generation space shuttle while I see Tauchain more like working on the atomic scale or quantum scale. The difference being that theoretically TML would let you write code in any formal language, so it should be possible to build a compiler and port EOS over if this were desired.