Building High-Performance AI Literature Processing

Learn to build scalable AI systems for processing vast amounts of research literature through this 13-minute conference talk from Conf42 Platform Engineering 2025. Discover how to tackle the challenge of keeping up with rapidly growing research publications by implementing Retrieval-Augmented Generation (RAG) systems. Explore the architecture and implementation of distributed vector databases for efficient document storage and retrieval, and understand how to design efficient Large Language Model (LLM) inference pipelines for processing literature at scale. Master real-time knowledge synchronization techniques and learn to implement entity extraction and knowledge graphs for better information organization. Gain insights into horizontal scaling strategies and cost optimization approaches for AI literature processing systems. Understand monitoring, observability, and reliability practices essential for production AI systems, along with Infrastructure as Code principles and deployment strategies. Examine the cross-domain applicability of these techniques beyond literature processing, making this knowledge valuable for various AI-powered information processing applications.