"Generative AI (GenAI) and Traditional (or classical) AI differ fundamentally in how they consume and rely on data, creating a massive challenge for financial firms. In this segment, Robert Hryniewicz, Director, Product Marketing - Enterprise AI at Cloudera, breaks down the two distinct AI models and explains why a simple switch from one to the other won't work without a robust data architecture. He details the importance of real-time data access and the Retrieval-Augmented Generation (RAG) architecture to ensure LLMs are grounded in your proprietary organizational data—not just public internet knowledge. Learn how to manage data lineage across your entire enterprise, from ingestion at the edge to the final model output, ensuring consistent security, governance, and observability to maximize ROI and minimize the risk of ""hallucinations."" CHAPTERS: 0:00 - Intro: GenAI vs. Traditional AI 0:22 - Does GenAI Require Different Data? 0:34 - The Key Differentiator: Model Size and Training 0:44 - Why Financial Firms Need RAG (Retrieval-Augmented Generation) 1:24 - The Need for Real-Time and Fresh Data 1:39 - Ensuring Data Lineage and Traceability End-to-End 2:36 - The Unified Platform: Security, Governance, and Consistency 3:02 - The Ultimate Goal: Maximizing ROI and Minimizing Hallucinations Robert Hryniewicz - Director, Product Marketing - Enterprise AI, Cloudera Adam Green - Technology Industry Expert, Moderator Presented by Cloudera in partnership with AWS. Watch all the videos in the series: What Financial Services Leaders Must Know Before Developing a GenAI Practice [Link to Video 1] Have GenAI Investments Paid Off for FinServ Firms? (The Real ROI of AI in Finance) [Link to Video 2] Get Your Data Pipeline Ready for AI (The Data Strategy FinServ Needs Now) [Link to Video 3] Learn how to build, run, and scale secure enterprise AI—across on premises and cloud—with full control over your data, models, and infrastructure: https://shorturl.at/5Z01O #GenAI #TraditionalAI #DataArchitecture #FinancialServices #RAGArchitecture #DataGovernance #LLM #Cloudera #AWS #EnterpriseAI"

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