AI's Memory Upgrade: Max Rumpf on how to build advanced RAG systems
High Agency: The Podcast for AI Builders
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Enhancing AI Information Retrieval with Dynamic Processes and Advanced Re-ranking Models
The chapter delves into the importance of dynamic information retrieval processes for AI systems, contrasting traditional static approaches like BM25. It discusses the implementation of re-ranking stages to enhance context filling and improve system performance, with significant accuracy gains seen in tasks like semantic retrieval. The conversation also covers evaluating AI models, utilizing prompted LLMs, human labeling services, and synthetic datasets to test accuracy and optimize performance.
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