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Software Engineering Daily

Unstructured Data and LLMs with Crag Wolfe and Matt Robinson

Jun 4, 2024
00:00
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Crag Wolfe and Matt Robinson from Unstructured discuss the challenges of cleaning unstructured data for large language models. They explore data normalization, document processing for NLP tasks, and data transformation techniques for tables, PDFs, and images. The podcast highlights the importance of preprocessing data for machine learning applications and enhancing information retrieval with structured data processing.
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Quick takeaways

  • Large language models require clean, curated data for training, posing a significant data cleaning challenge with heterogeneous formats.
  • Unstructured focuses on extracting and transforming complex data for vector databases and LLM frameworks.

Deep dives

Data cleaning challenges in large language models

Large language models require clean, curated data for training, leading to a major data cleaning challenge when dealing with heterogeneous data formats like HTML, PDF, PNG, and PowerPoint. Unstructured focuses on transforming complex data for vector databases and LLM frameworks, with Craig Wolf and Matt Robinson discussing data cleaning and the LLM age.

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