In predicting the future from the past, it would be foolish to look only at past successes. So here is another important basis for the Technology Predictor Success Matrix: a list of technologies that, at one important level or another, are failures. I’m sure that any number of people will protest over one or the other of these, citing their influence on later technologies or people or companies. But consider, for those on the this list, the answers to two questions: Are people using them? Did anyone make serious money based on them? And you’ll generally get two negatives.
OODBMS · For those who don’t remember, this stands for Object-Oriented Database Mangement System. I remember being informed in superior tones, sometime around 1990, when I wanted to use boring old Sybase for some problem or another, that anyone who went to the big database conferences knew that the debate was over and that object-oriented had won.
Well, it wasn’t and it hadn’t. None of the pure OODBMS vendors are still alive, in that line of business anyhow; and if you proposed an OODBMS as part of a large mainstream aplication these days, you’d get some funny looks indeed.
Yes, conventional relational databases these days have some features gleaned from OODBMS field, but that the end of the day, this was a technology that just didn’t fly.
Spelled out in full, that would be Fourth-Generation Language.
This was super hot stuff back when I was getting into the business in the
The notion was that instead of writing detailed procedural programs full of
messy and easy-to-get-wrong
if statements and loops, you’d write
declarative programs that just generated the output from the input.
This went over big-time with the management community, which was (and
remains) sick of paying high-priced temperamental programmers to write code
that’s full of nasty little detail-level bugs.
Unfortunately, it turned out that with a 4GL, you could write 90% of your
application in no time at all (making managers wonder why these things
normally take so long) but you couldn’t get the last 10% done at all.
The fact is, life has
if statements and loops and so on, and
programming systems that pretend these things don’t exist are at best
There were dozens of these things (my personal demon was DATATRIEVE), now mostly relegated to the technology graveyard or at least to niche roles. The two mainstream technologies today that retain some flavor of 4GL are Visual Basic and XSLT.
AI · To a farmer this is artificial insemination, but for a few years a decade or two back, Artificial Intelligence was the white-hot center of the technology universe. It was all VCs wanted to invest in, it was how the “Star Wars” ballistic-missile-defense system was going to be made to work, and it was the next step in our all being left in the dust by the Japanese. The level of hype and enthusiasm and just general bullshit exceeded anything that I have seen around any technology trend, before or since.
I clearly recall how at one point everyone decided that AI was going to be done in Prolog, and devised a measure of how many LIPS (Logical Inferences Per Second) a computer running Prolog could do, and were seriously worried because the Japanese were building systems that they claimed would do GigaLIPS.
Some good algorithms were cooked up, and Marvin Minsky wrote The Society of Mind, and Doug Hofstadter wrote Gödel, Escher, Bach, both of which are worth reading, but at the end of the day the world didn’t get noticeably changed.
VRML · I’m personally connected with this one; in late 1995 I attended the First Annual Virtual Reality Modeling Language conference, in 1996 published the heavily-cited Measuring the Web which included a VRML visualization, and even contributed in a small way to the design discussions around VRML 2.0 (A.K.A. VRML 97). That conference was a blast; there were maybe 150 people there, at least a third VCs, and we thought we had discovered the Next Web, and it was going to be 3D, you betcha.
Well, it didn’t happen (but they haven’t given up hope).
Interactive TV · Back when the Internet was going to be the “Information Superhighway,” a lot of smart people wasted a lot of time and a lot of money on this. The put-down was “500 channels and a ‘BUY’ button” but near as I can tell this was mostly video-on-demand. I can remember an incredibly-arrogant presentation from Oracle about how they’d acquired and assembled this highly-parallel ultra-fast technology that could stream thousands of video feeds in parallel and so the game was pretty well decided in their favor before it even started.
Only it never started. It turned out that people wanted more interaction, and seemed to like going to video stores, and that large-scale video streaming couldn’t be done cheaply enough.
Ada · Ada was a programming language whose development was funded by the US military; at a time when the competition was COBOL, FORTRAN, and K&R C, it wasn’t hard to imagine that a better programming language could be designed.
The design was savaged by many Computer Scientists and although the early implementations were pretty good, Ada survives pretty well only as a footnote; although there’s still enough of a community to keep a web site going.
SGML · Standard Generalized Markup Language has roots dating back into the Sixties, and became ISO Standard 8879 in 1986. I had my Road-to-Damascus moment in 1987 when I saw the electronic text of the Oxford English Dictionary with nearly-SGML markup. I eventually asked “Why not real SGML?” and got a sheepish explanation about how that seemed to be awfully complicated and difficult.
SGML was a succesful in a narrow niche: the niche of people with huge, expensive, publishing problems, for example Boeing and the European Parliament. But it never touched the lives of most computer users or programmers. When HTML came along, it was occasionally advertised as being an application of SGML, but that claim was deeply bogus on a bunch of levels.
On the other hand, it did prove out a whole bunch of good ideas that were shamelessly stolen by the designers of XML, including me, and will live forever for that reason alone.
Next... · I’ll introduce our candidate Technology Success Predictors, then it’s on to evaluating them with these lists of winners and losers as a tool.