This week on The Data Stack Show, John and guest host Matthew Kelliher-Gibson welcome Nicolay Gerold, CEO and Founder of Aisbach, and host of How AI is Built podcast. The group delves into the evolution, strengths, and challenges of language models (LLMs) and AI. Nicolay shares insights on data-centric AI approaches, practical applications like data extraction and content generation, and the importance of aligning LLMs with user preferences. The conversation also explores the current AI startup landscape, the hype around generative AI, the necessity of thorough testing and monitoring in AI applications, and so much more.
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)
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205: How to make LLMs Boring (Predictable, Reliable, and Safe), Featuring Nicolay Gerold