The Fifth Generation Computing Project
The Fifth Generation Computing project

		This article by Dominic Connor  reminds me of that marvelous artifact of the second AI winter (the one everyone talks about), “Fifth generation computing.”  I was not fully sentient at the time, though I was alive, and remember reading about “Fifth generation computing” in the popular science magazines.
It was 1982. Let’s not rely on vague recollections of what happened this year; some familiar things which happened that year. Tylenol scare, mandated breakup of the Bell System  and the beginning of the hard fade of Bell Labs, Falklands war, crazy blizzards, first artificial heart installed,  Sun Microsystems founded, Commodore 64 released. People were starting to talk about personal robotics; Nolan Bushnell (Atari founder) started a personal robot company. The IBM PC was released the previous year, somewhere mid year they had sold 200,000 of them, and MS-DOS 1.1 had been released. The Intel 80286 came out earlier in the year and was one of the first microprocessors with protected memory and hardware support for multitasking. The Thinking Machines company, attempting to do a novel form of massively parallel computing (probably indirectly in response to the 5thgen “threat”), would be founded in 1983.
Contemporary technology
The “AI” revolution was well underway at the time; expert system shells were actually deployed and used by businesses; Xcon, Symbolics, the Lisp Machine guys were exciting startups. Cyc -a sort of ultimate expert systems shell, would be founded a few years later. The hype train for this stuff was even more  lurid than it is now; you can go back and look at old computer and finance magazines for some of the flavor of it. If you want to read about the actual tech they were harping as bringing MUH SWINGULARITY, go read Norvig’s PAIP book. It was basically that stuff, and things that look like Mathematica. Wolfram is really the only 80s “AI” company that survived, mostly by copying 70s era “AI” symbolic algebra systems and re-implementing a big part of Lisp in “modern” C++. 
Japan was dominating the industrial might of the United States at the time in a way completely unprecedented in American history. People were terrified; we beat those little guys in WW-2 (a mere 37 years earlier) and now they were kicking our ass at automotive technology and consumer electronics. The Japanese, triumphant, wanted to own the next computer revolution, which was still a solidly American achievement in 1982. They took all the hyped technology of the time; AI, massive parallelism, databases, improved lithography, prolog like languages, and hoped by throwing it all together and tossing lots of those manufacturing-acquired dollars at the problem, they’d get the very first sentient machine. 
1) The fifth generation computers will use super large scale integrated chips (possibly in a non Von-Neumann architecture).
2) They will have artificial intelligence.
3) They will be able to recognize image and graphs.
4) Fifth generation computer aims to be able to solve highly complex problem including decision making, logical reasoning.
5) They will be able to use more than one CPU for faster processing speed.
6) Fifth generation computers are intended to work with natural language.
Effectively the ambition of Fifth generation computers was to build the computers featured in Star Trek; ones that were semi-sentient, and that you could talk to in a fairly conversational way.


People were terrified. While I wasn’t even a teenager yet, I remember some of this terror. The end of the free market! We’d all be Japanese slaves! The end of industrial society! DARPA dumped a billion 1980s dollars into a project called the Strategic Computing Initiative in an attempt to counter this (amusingly one of the focuses was … autonomous vehicles -things which are still obviously over the rainbow). Most of the US semiconductor industry and main frame vendors began an expensive collaboration to beat those sinister Japanese and prevent an AI Pearl Harbor. It was called the Microelectronics and Computer Technology Corporation (MCC for some reason), and it’s definitely ripe for some history of technology grad student to write a dissertation on it beyond the Wikipedia entry.  The Japanese 5th gen juggernaut was such a big deal, the British (who were still tech players back then) had their own copy of this nonsense, called the “Alvey Programme” -they dumped about a billion pounds in todays money into it. And not to be left out, the proto-EU also had their own version of this called ESPIRIT with similar investment levels. 

Prolog was of course the programming language of this future technology. Prolog was sort of the deep learning of its day; using constraint programming, databases (Prolog is still a somewhat interesting if over -lexible database query language), parallel constructs and expert system shell type technology, Prolog was supposed to achieve sentience. That’s not worked out real well for Prolog over the years: because of the nature of the language it is highly non-deterministic, and it’s fairly easy to pose NP-hard problems to Prolog. Of course in such cases, no matter how great the parallel model is, it still isn’t going to answer your questions.

One of the hilarious things about 5th generation computers is how certain people were about all this. The basic approach seemed completely unquestioned. They really thought all you had to do to build the future was take the latest fashionable ideas, stir them together, and presto, you have brain in a can AI. There was no self respecting computer scientist who would stand up and say “hey, maybe massive parallelism doesn’t map well onto constraint solvers, and perhaps some of these ambitions, we have no idea how to solve.” [1] This is one of the first times I can think of an allegedly rigorous academic discipline collectively acting like overt whores, salivating at the prospects of a few bucks to support their “research.” Heck, that’s insulting to actual whores, who at least provide a service.



Of course, pretty much nothing in 5th generation computing turned out to be important, useful, or even sane. Well, I suppose VLSI technology was all right, but it was going to be used anyway, and DBMS continue to be of some utility, but the rest of it was preposterous, ridiculous wankery and horse-puckey. For example; somehow they thought optical databases would allow for image search. It’s not clear what they had in mind here, if anything; really it sounds like bureaucrats making shit up about a technology they didn’t understand. For more examples:
“The objective stated (Moto-oka 1982 p.49) is the development of architectures with particular attention to the memory hierarchy to handle set operations using relational algebra as a basis for database systems. “
“The objective stated (Moto-oka 1982 p.53) is the development of a distributed function architecture giving high efficiency, high reliability, simple construction, ease of use, and adaptable to future technologies and different system levels.”
“The targets are: experimental, relational database machine with a capacity of 100 GB and 1,000 transactions a second; practical, 1,000 GB and 10,000 transactions a second. The implementation relational database machine using dataflow techniques is covered in section 8.3.3.”
“The objective stated (Moto-oka 1982 p.57) is the development of a system to input and output characters, speech, pictures and images and interact intelligently with the user. The character input/output targets are: interim, 3,000-4,000 Chinese characters in four to five typefaces; final, speech input of characters, and translation between kana and kanji characters. The picture input/output targets are: interim, input tablet 5,000 by 5,000 to 10,000 by 10,000 resolution elements; final, intelligent processing of graphic input. The speech input/output targets are: interim, identify 500-1,000 words; final, intelligent processing of speech input. It is also intended to integrate these facilities into multi-modal personal computer terminals.”
“The Fifth Generation plan is difficult and will require much innovation; but of what sort? In truth, it is more engineering than science (Fiegenbaum & McCorduck 1983 p 124). Though solutions to the technological problems posed by the plan may be hard to achieve, paths to possible solutions abound.” (where have I heard this before? -SL)
The old books are filled with gorp like this. None of it really means anything.  It’s just ridiculous wish fulfillment and word salad.  Like this dumb-ass diagram:


There are probably lessons to be learned here. 5thGen was exclusively a top down approach. I have no idea who the Japanese guys are who proposed this mess; it’s possible they were respectable scientists of their day. They deserve their subsequent obscurity; perhaps they fell on their swords. Or perhaps they moved to the US to found some academic cult; the US is always in the market for technological wowzers who never produce anything. Such people only seem to thrive in the Anglosphere, catering to the national religious delusion of whiggery.
Japan isn’t to be blamed for attempting this: most of their big successes up to that point were top-down industrial policies designed to help the Zaibatsus achieve national goals. The problem here was … no Japanese computer Zaibatsu worth two shits which had the proverbial skin in the game -it was all upside for the clowns who came up with this, no downside.  Much like the concepts of nanotech 10 years ago, quantum computing or autonomous automobiles now; it is a “Nasruddin’s Donkey bet” (aka scroll to bottom here) without the 10 year death penalty for failure.
Japan was effectively taken for a ride by mountebanks. So was the rest of the world. The only people who benefited from it were quasi-academic computer scientist types who got paid to do wanking they found interesting at the time.  Sound familiar to anyone? Generally speaking, top down approaches on ridiculously ambitious projects, where overlords of dubious competence and motivation dictate a  R&D direction that don’t work so well; particularly where there is software involved. It only works if you’re trying to solve a problem that you can decompose into specific tasks with milestones, like the moon shot or the Manhattan project, both of which had comparatively fairly low risk paths to success. Saying you’re going to build an intelligent talking computer in 1982 or 2019 is much like saying you’re going to fly to the moon or build a web browser in 1492. There is no path from that present to the desired outcome. Actual “AI,”  from present perspectives, just as it was in 1982, is basically magic nobody knows how to achieve. 
Another takeaway was many of the actual problems they wanted to solve were done in a more incremental way while generating profits. One of the reasons they were trying to do this was to onboard many more people than had used computers before. The idea was instead of hiring mathematically literate programmers to build models, if you could have smart enough machines to talk to people and read charts and things the ordinary end user might bring to the computer with questions, more people could use computers, amplifying productivity. Cheap networked workstations with GUIs turned out to solve that in a much simpler way; you make a GUI, give the non spergs some training, then ordinary dumbasses can harness some of the power of the computer. This still requires mentats to write GUI interfaces for the dumbasses (at least before our glorious present of shitty electron front ends for everything), but that sort of “bottom up, small expenditures, train the human” idea has been generating trillions in value since then.
The shrew-like networked GUI equipped microcomputers of Apple were released as products only two years after this central planning dinosaur was postulated. Eventually, decades later, someone built a mechanical golem made of microcomputers which achieves a lot of the goals of fifth generation computing, with independent GUI front ends. I’m sure the Japanese researchers of the time would have been shocked to know it came from ordinary commodity microcomputers running C++ and using sorts and hash tables rather than non-Von-Neumann Prolog supercomputers. That’s how most progress in engineering happens though: incrementally[2]. Leave the moon shots to actual scientists (as opposed to “computer scientists”) who know what they’re talking about. 

1988 article on an underwhelming visit to Japan.
1992 article on the failure of this program in the NYT.

[1] Some years later, 5 honest men discussed the AI winter upon them; yet the projects inexorably rolled forward. This is an amazing historical document; at some point scholars will find such a thing in our present day -maybe the conversation has already happened. https://www.aaai.org/ojs/index.php/aimagazine/article/view/494 … or PDF link here.
[2] Timely Nick Szabo piece on technological frontiersmanship: https://unenumerated.blogspot.com/2006/10/how-to-succeed-or-fail-on-frontier.html


	