December 12, 2015

Abstract datatypes and extensible RDBMS

In my recent Stonebraker-oriented post about database theory and practice over the decades, I wrote

I used to overrate the importance of abstract datatypes, in large part due to Mike’s influence. I got over it. He should too. They’re useful, to the point of being a checklist item, but not a game-changer. A big part of the problem is [that] different parts of a versatile DBMS would prefer to do different things with memory.

and then left an IOU for a survey of abstract datatypes/RDBMS extensibility. Let’s get to it.

Perhaps the most popular term was actually object/relational DBMS, but I’ve never understood the etymolygy on that one.

Although I call RDBMS extensibility a “checklist item”, the list of products that can check it off is actually pretty short.

Surely there are more, but at the moment I can’t really think of which they are.

Read more

December 3, 2015

AI memories — expert systems

This is part of a four post series spanning two blogs.

As I mentioned in my quick AI history overview, I was pretty involved with AI vendors in the 1980s. Here on some notes on what was going on then, specifically in what seemed to be the hottest area at the time — expert systems. Summing up:

First, some basics.  Read more

December 1, 2015

Historical notes on artificial intelligence

This is part of a three post series spanning two blogs.

0. The concept of artificial intelligence has been around almost as long as computers — or even before, if you recall that robots were imagined by the 1920s. But for a while it was mainly academic and perhaps military/natural security research. There’s been a robotics industry for over 50 years. But otherwise, when I first became an analyst in 1981, AI commercialization efforts were rather new, and were concentrated in three main areas:

1. If I’ve ever gotten too close to a group of companies, it was probably the 1980s AI vendors. I unfortunately earned investment banking fees by encouraging people into money-losing investments in all three areas cited above, in Teknowledge, Artificial Intelligence Corporation and Symbolics respectively. I dated women who worked for Symbolics and Teknowledge. I wrote and performed a satirical song about Inference at an employee party for Intellicorp. Accordingly, when I write about individual companies in the sector, I fear that I may go on at self-indulgent length. So I’ll save all that for another time, and content myself now with a brief and dry survey that does little more than establish some context.

2. The 1980s also saw military-funded research into autonomous vehicles, as well as continued efforts in robotics and machine vision. Frankly, there wasn’t a lot of commercial overlap between these areas and the rest of AI at that time, and the rest of AI is what I tracked more closely.

But in one counterexample, a machine vision company named Machine Intelligence spun off a company that was building a PC DBMS with some natural language query capability. The spin-off company was Symantec. (Obviously, Symantec his pivoted multiple times since.) Machine Intelligence cofounder Earl Sacerdoti also wound up at expert system vendor Teknowledge for a while. So maybe there was more overlap in theory than there was in commercial practice.  Read more

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