Hunch Co-Founder Chris Dixon Releases Forage

written by: Richard Kastelein

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Gigaom is reporting that Hunch co-founder Chris Dixon has released a new product called Forage Thursday night that utilizes the Hunch API to build personalized YouTube playlists based on the people you follow on Twitter.

So how does it work? Dixon told me via email that Hunch uses preferences from existing users to predict recommendations for users not known to the system. “Basically we have about one million people who have Twitter (or) Facebook connected into Hunch and told us about their music preferences,” he said. “We use this ‘known’ data to make inferences about unknown users based on who they follow, who follows them, and other signals.”

Dixon also emphasized that Forage is exploratory by nature — it won't necessarily list your favorite bands, but rather music you may want to try. And I gotta say, it actually works pretty well for that purpose. Not only does it serve up an interesting selection of videos, users can also link to the resulting playlists. Unfortunately, it struggles with one of the issues many music-focused YouTube mashups are facing: Some major labels aren't allowing third party sites to embed their clips.

Paul Johnson from previously covered Hunch in a piece last year:

According to Caterina Fake of, the type of Recommendation Engine used by Netflix and other Connected TV players do not work because they are vertically challenged and they dont know what socks you wear.

Thats right… socks. Eh?!

If you dont know Caterina Fake, she sold Flickr to Yahoo a few years ago, after growing it into one of the most popular photo sharing sites around.

If you don’t know, it is a company we first came across when they launched their beta at the beginning of 2009, and since then, they have been attracting consumers and collecting a huge number of answers to the broadest range of random questions I have come across. They have been building a recommendation tool that gets smarter the more their users use it.

So what relevance does have to the future of Connected TV, could they improve the recommendation engines currently in use by content providers, and does it actually matter? believes they will be part of the Connected TV future, because of the masses of data they have been capturing on consumers, and what they are now turning into a new set of views on likes and dis likes across a vast range of different products and services...including Film and TV.





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