Explore a comprehensive podcast episode featuring QuantumBlack AI by McKinsey's Principal Data Engineer, Anu Arora, and Associate Partner, Anass Bensrhir, discussing the management of data for effective Generative AI applications. Delve into the challenges organizations face when scaling GenAI, with a focus on data as a primary inhibitor. Learn about strengthening data foundations, managing unstructured data, and navigating data lakes and ETL processes. Gain insights on data privacy concerns in the context of Large Language Models (LLMs), balancing LLM adoption risks, and implementing effective LLM strategies. Discover the heavy workload of data engineers and the decision-making process between creating or waiting for AI solutions. Perfect for professionals interested in the intersection of data management and Generative AI applications across industries.
Managing Data for Effective GenAI Application - MLOps Podcast #216
Overview
Syllabus
[] Anass and Anu's preferred coffee
[] Takeaways
[] Please like, share, leave a review, and subscribe to our MLOps channels!
[] Huge shout out to our sponsor QuantumBlack!
[] Anu's tech background
[] Anass tech background
[] The landscape of data
[] Dealing with unstructured data
[] Data lakes and ETL processes
[] Data Engineers' Heavy Workload
[] Data privacy and PII in the new LLMs paradigm
[] Balancing LLM Adoption Risk
[] Effective LMS Implementation Strategy
[] Decisions: Create or Wait
[] Wrap up
Taught by
MLOps.community
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MLOps at the Age of Generative AI - Podcast Episode 169
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MLOps at the Crossroads - Challenges and Future Directions
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RAG Quality Starts with Data Quality - Enhancing Retrieval-Augmented Generation Systems
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