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Leveraging the Transformer Architecture for Music Recommendation on YouTube
Google has described an approach to use transformer models, which ignited the current generative AI boom, for music recommendation. This approach, which is currently being applied experimentally on YouTube, aims to build a recommender that can understand sequences of user actions when listening to music to better predict user preferences based on their context.
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Google Announces New DeepMind Model, Lyria, to Generate High-Quality Music
Google has introduced Google DeepMind's Lyria, an AI music generation model able to generate vocals, lyrics, and background tracks mimicking the style of popular artists. The model is experimentally available on YouTube through two distinct AI experiments.
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How YouTube's Recommendation Algorithm Works
In a recent paper published by Google, YouTube engineers analyzed in greater detail the inner workings of YouTube’s recommendation algorithm. The paper was presented on the 10th ACM Conference on Recommender Systems last week in Boston. In this news item we analyze how YouTube uses deep learning to operate one of the largest and most complex recommendation systems in industry.
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YouTube Switches to HTML5 Video Player
After many years of working on HTML5 support, YouTube has decided to use their HTML5 video player as the default for modern browsers, using the old Flash-based player only for legacy browsers. Using MPEG-DASH and W3C Media Source Extensions, YouTube can use Adaptive Bitrate streaming to reduce buffering and improve initial playback speed.