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      <title>Efficiently Applying LLMs to Transform Semi-Structured Data</title>
      <link>https://www.infoq.com/news/2023/05/data-transformation-using-llms/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Data+Wrangling-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2023/05/data-transformation-using-llms/en/headerimage/transforming-data-using-llms-1683142735234.jpeg"/&gt;&lt;p&gt;LLMs can be an effective way to generate structured data from semi-structured data, although an expensive one. A team of Stanford and Cornell researchers claim to have found a technique to reduce inference costs by 110x while improving inference quality.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Data Wrangling</category>
      <category>Python</category>
      <category>AI, ML &amp; Data Engineering</category>
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      <pubDate>Wed, 03 May 2023 20:00:00 GMT</pubDate>
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      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2023-05-03T20:00:00Z</dc:date>
      <dc:identifier>/news/2023/05/data-transformation-using-llms/en</dc:identifier>
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