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That's true. Let's say in machine learning then.

Let's not, because it's still wrong on the order of thirty counterexamples.

Let's say we'll stop making broad proclamations about the global best in a field we know very little about.

Andrew Ng has set many state of the art results on various data sets using similar approaches as the one described in the paper.

Here is a reasonably approachable talk he gave about it. http://www.youtube.com/watch?v=ZmNOAtZIgIk

This is a very interesting talk.

Thank you for sharing with me. :)

In return, I will offer you two interesting non-sequiturs, because I don't have anything topical and a non-sequitur seems like it's worth half what something germane would be.

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Bret Victor, "Inventing on Principle." First 5 minutes are terribly boring. Give him a chance; it's 100% worth it.

http://vimeo.com/36579366

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Damian Conway, "Temporally Quaquaversal Virtual Nanomachine."

It's as funny as it sounds.

http://yow.eventer.com/events/1004/talks/1028

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