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How AWS’s Suman Debnath Is Advancing AI Architectures with RAG | |
In this insightful Discover Dialogues episode, TechDogs speaks with Suman Debnath, Principal Developer Advocate for Machine Learning at AWS, to unpack how Retrieval-Augmented Generation (RAG) is transforming enterprise AI. With over 100 global talks at events like PyCon, ODSC, and AWS re:Invent, Suman bridges deep technical expertise with real-world business insights, making this episode essential for anyone scaling AI. His central message? AI hallucinations are not just model issues—they’re retrieval problems. Suman compares poor data retrieval to a librarian handing you the wrong book: no matter how smart the reader, the answer won’t be there. That’s why grounding AI with accurate, context-rich data is critical. RAG solves this by combining real-time data retrieval from sources like internal documents, PDFs, databases, or sensor feeds with generative AI. The result? Smarter, more reliable AI responses. But the future goes beyond text. Suman introduces Agentic RAG—where AI agents leverage multimodal inputs like images, charts, and text to make decisions. He shares Colpali, an approach designed for enterprises blending structured and unstructured data. Industries such as healthcare, finance, and logistics are already adopting these intelligent, multimodal agents to streamline processes and improve decision-making. Why This Episode Matters: ✔ Learn how RAG boosts AI accuracy with relevant, real-time data ✔ Explore multimodal AI combining text, visuals, and audio ✔ Gain practical insights on building scalable, production-ready AI ✔ Understand the evolving role of AI agents in modern enterprises Suman’s leadership in AI at AWS, using platforms like Bedrock and SageMaker, makes this a must-watch for technical teams, product leaders, and executives. Catch the full conversation at TechDogs.  | |
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CANetAds > Computers > Information Technologies > Item ID 3824554
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2025-06-30 (0.579 sec)