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      <title>DoorDash Builds DashCLIP to Align Images, Text, and Queries for Semantic Search Using 32M Labels</title>
      <link>https://www.infoq.com/news/2026/03/doordash-semantic-search/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Products</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/03/doordash-semantic-search/en/headerimage/generatedHeaderImage-1772917454999.jpg"/&gt;&lt;p&gt;DoorDash has launched a multimodal machine learning system that aligns product images, text, and user queries in a shared embedding space. Trained on 32 million labeled query-product pairs using contrastive learning, the system improves semantic search, product ranking, and advertising relevance. Embeddings also support other machine learning tasks across the marketplace.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Online Learning</category>
      <category>Machine Learning</category>
      <category>Embedded-Databases</category>
      <category>commercial-off-the-shelf</category>
      <category>vector databases</category>
      <category>Offline-First</category>
      <category>Search</category>
      <category>E-Commerce</category>
      <category>Rankings</category>
      <category>Products</category>
      <category>Architecture &amp; Design</category>
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      <pubDate>Mon, 16 Mar 2026 14:25:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/03/doordash-semantic-search/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Products</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-03-16T14:25:00Z</dc:date>
      <dc:identifier>/news/2026/03/doordash-semantic-search/en</dc:identifier>
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