205: How To Make LLMs Boring (Predictable, Reliable, And Safe), Featuring Nicolay Gerold The Data Stack Show podcast

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205: How to make LLMs Boring (Predictable, Reliable, and Safe), Featuring Nicolay Gerold

15h ago 48:52

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Highlights from this week’s conversation include:

Nicolay’s Background and Journey in AI (0:39)
Milestones in LLMs (4:30)
Barriers to Effective Use of LLMs (6:39)
Data-Centric AI Approach (10:17)
Importance of Data Over Model Tuning (12:20)
Capabilities of LLMs (15:08)
Challenges in Structuring Data (18:28)
JSON Generation Techniques (20:28)
Utilizing Unused Data (22:36)
Importance of Monitoring in AI (34:11)
Challenges in AI Testing (37:40)
Error Tracing in AI vs. Software (39:24)
The AI Startup Landscape (40:53)
Marketing for Technical Founders (42:41)
Generative AI Hype Cycle (44:33)
Connecting with Nicolay and Final Takeaways (47:59)

The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.

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