Today's bit of randomness:
When I was a young programmer I worked for an AI company on a text-categorization project -- for a commercial client, all hush-hush for a while to preserve their competitive advantage and such, apparently really innovative (didn't realize then; I was just writing code to solve a problem, y'know?). Then somebody accidentally published the training dataset. And apparently it's gotten quite a lot of use in the research community, which I was completely unaware of, having never really been that kind of researcher.
For 30+ years there's been a mystery in that dataset that people have noticed, commented on, and apparently never tried to track down...until now. This podcaster got in touch with me and some others last week, and here's the result: Underunderstood: The Case of the Blah Blah Blahs. (36 minutes; has transcript).
It was neat to hear this trip down memory lane, and also to hear other parts of the story I'd never known about before, including the discussion from a researcher from the "other side" of one of the big arguments in AI in the 80s.