Comment Re:Standard Missing Option Gripe (Score 1) 708
Haaha. I second that!
Submission + - Going Head To Head With Genius on Playlists (ucsd.edu)
brownerthanu writes: (This is a re-submit with the second paragraph revised to include an important part of the story.)
Engineers at the University of California, San Diego are developing a system to include an ignored sector of music, deemed the 'long tail', in music recommendations. It's well known that radio suffers from a popularity bias where the most popular songs receive an inordinate amount of exposure. In Apple's music recommender system, iTunes' Genius, this bias is magnified. An underground artist will never be recommended in a playlist due to insufficient data. It's an artifact of the popular collaborative filtering recommender algorithm, which Genius is based on.
In order to establish a more holistic model of the music world, Luke Barrington and researchers at the Computer Audition Laboratory have created a machine learning system which classifies songs in an automated, Pandora-like, fashion. Instead of using humans to explicitly categorize individual songs, they capture the wisdom of the crowds via a Facebook game, Herd It, and use the data to train statistical models. The machine can then "listen to", describe and recommend any song, popular or not. As more people play the game, the machines get smarter. Their experiments show that automatic recommendations work at least as well as Genius for recommending undiscovered music.
Engineers at the University of California, San Diego are developing a system to include an ignored sector of music, deemed the 'long tail', in music recommendations. It's well known that radio suffers from a popularity bias where the most popular songs receive an inordinate amount of exposure. In Apple's music recommender system, iTunes' Genius, this bias is magnified. An underground artist will never be recommended in a playlist due to insufficient data. It's an artifact of the popular collaborative filtering recommender algorithm, which Genius is based on.
In order to establish a more holistic model of the music world, Luke Barrington and researchers at the Computer Audition Laboratory have created a machine learning system which classifies songs in an automated, Pandora-like, fashion. Instead of using humans to explicitly categorize individual songs, they capture the wisdom of the crowds via a Facebook game, Herd It, and use the data to train statistical models. The machine can then "listen to", describe and recommend any song, popular or not. As more people play the game, the machines get smarter. Their experiments show that automatic recommendations work at least as well as Genius for recommending undiscovered music.
Submission + - Going Head To Head With Genius on Playlists (ucsd.edu)
brownerthanu writes: Engineers at the University of California, San Diego are developing a system to include an ignored sector of music, deemed the 'long tail', in music recommendations. It's well known that radio suffers from a popularity bias, the most popular songs receive an inordinate amount of exposure. In Apple's music recommender system, iTunes' Genius, this bias is magnified. An underground artist will never be recommended in a playlist due to insufficient data. It's an artifact of the popular collaborative filtering recommender algorithm, which Genius is based on.
In order to establish a more holistic model of the music world, Luke Barrington, and researchers at The Computer Audition Laboratory have created a system which classifies songs in an automated, Pandora-like, fashion. Instead of using humans to explicitly categorize individual songs, they capture the wisdom of the crowds via a Facebook game, Herd It, and use the data to train statistical models. The algorithm can then "listen to", classify and recommend any song, popular or not.
In order to establish a more holistic model of the music world, Luke Barrington, and researchers at The Computer Audition Laboratory have created a system which classifies songs in an automated, Pandora-like, fashion. Instead of using humans to explicitly categorize individual songs, they capture the wisdom of the crowds via a Facebook game, Herd It, and use the data to train statistical models. The algorithm can then "listen to", classify and recommend any song, popular or not.
Comment Brownerthanu (Score 1) 386
There are two other things I would test for:
- Generalization. There is experimental evidence which suggests that occupying perceptual resources creates a greater ability to generalize.
- Awareness of the distractor data. Who does better at gathering info from the distractor objects?
Comment chess AI (Score 1) 378
would something like this work? instead of crippling the AI, do enough move calculations so that the AI is guaranteed to blow almost any human opponent out of the water. rank the possible moves, and have the AI play one of the "less optimal" moves, depending on the chosen difficulty level.
Comment Re:Precious Snowflakes (Score 1) 1316
You are partly right. Narcissistic people are definitely trying to hide low self esteem through a grandiose front and flashy accomplishments. But it's not true that it's incurable. I can say through experience that I, and a lot of friends of mine, entered the workplace as self-centered hyper-achievers. We were narcissistic to the max and thought it was awesome. As time passed we mellowed out quite a bit, and realized that trying to look cool was a poor substitute for true peace of mind (which I still haven't completely found btw).
I think a more interesting question to ask is, why do do these kids have such low self esteem and why do they have such a burning need to look cool? I disagree with the linked article. It is not because of self esteem boosts that students are narcissistic, it's because they are scared, scared of not being as cool as they feel they should. It's a self defense mechanism to protect a fragile ego.
Personally, I just feel sympathy for these kids. They've been programmed to feel they are not sufficient, and have to put on a front to make others believe they are more badass than they actually are.
I think a more interesting question to ask is, why do do these kids have such low self esteem and why do they have such a burning need to look cool? I disagree with the linked article. It is not because of self esteem boosts that students are narcissistic, it's because they are scared, scared of not being as cool as they feel they should. It's a self defense mechanism to protect a fragile ego.
Personally, I just feel sympathy for these kids. They've been programmed to feel they are not sufficient, and have to put on a front to make others believe they are more badass than they actually are.
Comment Re:Wait a minute... (Score 1) 923
actually, there will be far more heat deaths prevented cold deaths. the people who end up suffering the most will those least equipped to adapt. study of the last "hot" period in history reveals massive deaths along the equator from drought. it's ironic that the people who will pay most dearly for global warming are the ones who have barely contributed to it.
