Contextual understanding using Generative Artificial Intelligence
summary
Pipeline converts uploaded documents to text, produces high-dimensional embeddings, stores vectors in a vector DB, and runs semantic similarity search to pull context into a prompt for a chat model; claims include improved domain-specific accuracy, sentiment-aware and empathetic replies, and a demo using an English science textbook. Transcript and description list text embedding models, fine-tuning, and retrieval integration, but no quantitative results or error rates are given.
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chapters (6)
- 0:00Introduction to Con 42 Cy Engineering Event 2025
- 0:41Challenges with Data Abundance and Contextual Understanding
- 1:25Solution Architecture Overview
- 1:35Document Analysis and Embedding Process
- 2:06Generating Contextual Responses
- 2:45Practical Application and Demonstration
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