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Unlocking Unstructured Data with LLMs
Manage episode 492366609 series 2570898
Content provided by Ben Lorica. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ben Lorica or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
Shreya Shankar is a PhD student at UC Berkeley in the EECS department. This episode explores how Large Language Models (LLMs) are revolutionizing the processing of unstructured enterprise data like text documents and PDFs. It introduces DocETL, a framework using a MapReduce approach with LLMs for semantic extraction, thematic analysis, and summarization at scale.
Subscribe to the Gradient Flow Newsletter 📩 https://gradientflow.substack.com/
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Detailed show notes - with links to many references - can be found on The Data Exchange web site.
291 episodes
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Manage episode 492366609 series 2570898
Content provided by Ben Lorica. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ben Lorica or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
Shreya Shankar is a PhD student at UC Berkeley in the EECS department. This episode explores how Large Language Models (LLMs) are revolutionizing the processing of unstructured enterprise data like text documents and PDFs. It introduces DocETL, a framework using a MapReduce approach with LLMs for semantic extraction, thematic analysis, and summarization at scale.
Subscribe to the Gradient Flow Newsletter 📩 https://gradientflow.substack.com/
Subscribe: Apple · Spotify · Overcast · Pocket Casts · AntennaPod · Podcast Addict · Amazon · RSS.
Detailed show notes - with links to many references - can be found on The Data Exchange web site.
291 episodes
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