During Personify’s heyday, we were featured in a Business 2.0 article. It doesn’t seem to exist on the Web anymore, but the main thing I remember was a sentence that talked about Personify’s “algorithm-based software”—a phrase as useless as describing a car engine as “moving-parts-based.”
Certainly no one fed the author that phrase, and I doubt he or she invented it. More likely, the author wrote something that actually described our software, which an editor took the liberty of simplifying—to the point of pointlessness—for Business 2.0’s audience. Such things happen. It generated some smirks around the office, and that was that.
I tell this story because this weekend’s New York Times Magazine has a welcome counterpoint: an article about the Netflix Prize that could easily have hand-waved the details, per “algorithm-based software,” but instead made the details approachable and interesting for an audience even more general than Business 2.0’s.
Ironically, the algorithmic star of the article is singular value decomposition (SVD), a core component of, you guessed it, Personify’s algorithm-based software. Author Clive Thompson and his editor deserve credit for explaining SVD in everyday language, sprinkling plenty of movie examples from the Netflix contest. I’ll let you read it in the article (link below), but understanding SVD matters to Thompson’s larger questions of how predictable human tastes are and whether humans have limits to comprehending why certain predictions work.
A final irony: The New York Times Company may be running SVD to analyze behavior related to, among other things, Thompson’s article. I say that because The Times was a Personify customer, and last I heard (as of mid-2008), they were still running it at terabyte scale, six years after we discontinued official support. Just goes to show, many weird connections exist out there.
Now, onto the main attraction: Thompson’s If You Liked This, You’re Sure to Love That in The New York Times Magazine. Enjoy.