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      <title>Leveraging the Transformer Architecture for Music Recommendation on YouTube</title>
      <link>https://www.infoq.com/news/2024/09/transofrmer-based-recommender/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=YouTube</link>
      <description>&lt;img src="https://res.infoq.com/news/2024/09/transofrmer-based-recommender/en/headerimage/transformer-based-recommender-1725612187233.jpeg"/&gt;&lt;p&gt;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.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Machine Learning</category>
      <category>YouTube</category>
      <category>Artificial Intelligence</category>
      <category>Google</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Fri, 06 Sep 2024 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2024/09/transofrmer-based-recommender/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=YouTube</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2024-09-06T09:00:00Z</dc:date>
      <dc:identifier>/news/2024/09/transofrmer-based-recommender/en</dc:identifier>
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