The AI landscape often pulls us between the allure of cutting-edge models and the quiet necessity of foundational work—yet how do these extremes actually connect to deliver value?

Join Conor Bronsdon as he welcomes Denny Lee, a self-proclaimed "data nerd" and Product Management Director, Developer Relations at Dataricks, to unpack this very spectrum, from AI's core infrastructure to its most advanced applications. Denny explains why robust logging, tracing, and data lineage are indispensable for credible AI evaluation and feedback, ultimately making AI systems more affordable, accessible, and impactful.

The discussion ventures into strategies for democratizing AI, exploring the "GenAI ladder" from efficient inference and retrieval-augmented generation to deciding when to fine-tune or pre-train models. Denny also tackles the industry's pressing hardware bottlenecks, the critical role of open standards, and the imperative of navigating data privacy in an increasingly AI-driven world. Listen for grounded advice on moving beyond the hype and making practical, value-driven decisions in your AI journey.

Chapters

00:00 Introduction and Guest Welcome

01:31 Diving into AI Foundations

02:25 Importance of Logging and Tracing

08:40 Challenges in Data Quality and Lineage

14:49 Strategies for Cost-Effective AI

19:52 Partnerships and Collaborative Opportunities

22:10 Hardware Bottlenecks in AI

24:56 China's Power and Networking Advantage

25:26 Nvidia's Super Chip and Network Fabrics

26:39 The Growing Demand for Power in AI

29:26 Practical Advice for Data Governance

35:47 Understanding Privacy in AI

36:25 Differential Privacy and Its Challenges

41:57 Conclusion

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Follow Today's Guest(s)

Website: Databricks.com

Podcast: Data Brew by Databricks (available on major podcast platforms)

YouTube: @Databricks

LinkedIn: Denny Lee

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