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Learn to build sophisticated AI agents capable of handling complex data challenges in this conference talk from AIQCON 2024. Explore how Large Language Models are transforming content search, interaction, and generation while examining the evolution from basic Retrieval-Augmented Generation (RAG) systems to advanced agentic architectures. Discover the limitations of straightforward RAG-powered question-answering systems when dealing with large volumes of complex data, and understand the new data, retrieval, and LLM architectures required to overcome these challenges. Gain insights into the opportunities these agentic systems unlock, practical approaches for building them, and the remaining technical challenges in the field. The presentation addresses the ongoing relevance of data quality for AI agents one year after initial implementations, providing valuable perspectives from the co-founder and CEO of LlamaIndex on the current state and future direction of context-augmented LLM applications.
Syllabus
Building Advanced Agents Over Complex Data // Jerry Liu
Taught by
MLOps.community