Data lineage and AI: Ensuring quality and compliance with Matt Barlin

The AI Fundamentalists

Ready to uncover the secrets of modern systems engineering and the future of AI? Join us for an enlightening conversation with Matt Barlin, the Chief Science Officer of Valence. Matt's extensive background in systems engineering and data lineage sets the stage for a fascinating discussion. He sheds light on the historical evolution of the field, the critical role of documentation, and the early detection of defects in complex systems. This episode promises to expand your understanding of model-based systems and data issues, offering valuable insights that only an expert of Matt's caliber can provide.
In the heart of our episode, we dive into the fundamentals and transformative benefits of data lineage in AI. Matt draws intriguing parallels between data lineage and the engineering life cycle, stressing the importance of tracking data origins, access rights, and verification processes. Discover how decentralized identifiers are paving the way for individuals to control and monetize their own data. With the phasing out of third-party cookies and the challenges of human-generated training data shortages, we explore how systems like retrieval-augmented generation (RAG) and compliance regulations like the EU AI Act are shaping the landscape of AI data quality and compliance.
Don’t miss this thought-provoking episode that promises to keep you at the forefront of responsible AI.

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章节

1. Data lineage and AI: Ensuring quality and compliance with Matt Barlin (00:00:00)

2. Matt's comments on systems engineering practices in AI (00:01:05)

3. What is data lineage? (00:05:28)

4. Why should you care about data lineage? (00:08:49)

5. Verified credentials, techniques, and what they enable (00:10:55)

6. Exploring benefits of data lineage (00:17:32)

7. Additional techniques and 3rd party cookies (00:18:00)

8. Modeling and responsible AI (00:22:19)

9. Governed modeling systems (00:24:03)

10. Resetting the foundation for data lineage (00:26:01)