There was a very curious car outside my building this afternoon.
So bright!
This post's theme word is jehu, "a fast driver; the driver of a cab." That jehu had a rockin' electric blue ride!
Wednesday, June 15, 2011
Friday, June 10, 2011
Netflix overfitting
How can you tell that I've been watching movies on R.'s Netflix account? One glance at this screen should explain it:
That's right: the top two recommended categories are "British period pieces featuring a strong female lead" and "critically-acclaimed mind-bending movies." This screen made me laugh for several minutes. Netflix is parodying my own preferences back to me with a straight face!
My comments are thus: (1) machine learning should be applied to more areas of my life. It is obviously useful, hilarious, and interesting. Also, (2) I am not terribly worried about the filter bubble so bemoaned on BoingBoing. Partially because I am aware of the automated personalization that is happening around me, I'm not worried about being trapped in a bubble with only my own viewpoints mirrored back at me. I constantly tweak my catalogued "browsing behavior" to see what sort of changes it induces in automated systems. For example, I rated a lesbian romantic comedy/thriller (season 5) as five stars on Netflix just to see how that would affect the action/adventure/scifi/British-period-...-strong-female-lead balance of recommendations. (This was also a joke on R., who didn't know I had done this and was quite puzzled by the temporary diversion of his Netflix recommendations.)
I think Netflix overfitting is an interesting case of the filter bubble. As long as Netflix's genre suggestions are interesting, I always find something I'd like to watch before I get to the point of browsing all videos, or looking one up by search. So most of the time, Netflix's suggestions are good and I watch them and like them and so Netflix is working me into an overfitted profile. Hence "British period pieces featuring a strong female lead."
This post's theme word is prolepsis, "anticipating and answering objections in advance" or, apparently, "the literary device of referring to a thing by its future state." Certain applications of predictive machine learning seem to evince prolepsis.
That's right: the top two recommended categories are "British period pieces featuring a strong female lead" and "critically-acclaimed mind-bending movies." This screen made me laugh for several minutes. Netflix is parodying my own preferences back to me with a straight face!
My comments are thus: (1) machine learning should be applied to more areas of my life. It is obviously useful, hilarious, and interesting. Also, (2) I am not terribly worried about the filter bubble so bemoaned on BoingBoing. Partially because I am aware of the automated personalization that is happening around me, I'm not worried about being trapped in a bubble with only my own viewpoints mirrored back at me. I constantly tweak my catalogued "browsing behavior" to see what sort of changes it induces in automated systems. For example, I rated a lesbian romantic comedy/thriller (season 5) as five stars on Netflix just to see how that would affect the action/adventure/scifi/British-period-...-strong-female-lead balance of recommendations. (This was also a joke on R., who didn't know I had done this and was quite puzzled by the temporary diversion of his Netflix recommendations.)
I think Netflix overfitting is an interesting case of the filter bubble. As long as Netflix's genre suggestions are interesting, I always find something I'd like to watch before I get to the point of browsing all videos, or looking one up by search. So most of the time, Netflix's suggestions are good and I watch them and like them and so Netflix is working me into an overfitted profile. Hence "British period pieces featuring a strong female lead."
This post's theme word is prolepsis, "anticipating and answering objections in advance" or, apparently, "the literary device of referring to a thing by its future state." Certain applications of predictive machine learning seem to evince prolepsis.
Labels:
humor,
movies,
science,
technology,
TV
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