LLMs in Focus: From One-Size-Fits-All to Verticalized Solutions - MLOps Podcast #196

Explore the evolving landscape of large language models (LLMs) in this 55-minute MLOps podcast featuring Numbers Station's Venky Ganti and Laurel Orr. Delve into the comparison between general-purpose and verticalized LLMs, examining their applications in data analytics through real-world customer stories. Investigate the implications of ownership structures on transparency and trustworthiness, focusing on open-source versus proprietary models. Learn about NSQL foundation models and the critical role of diverse, high-quality training data in addressing enterprise challenges. Gain insights into the future of LLMs, including hosting solutions and the trend towards specialized applications. Benefit from the expertise of Venky Ganti, with over two decades of experience in software engineering and technical leadership, and Laurel Orr, a Principal Engineer specializing in foundation model technology for enterprise data stacks.

[] Venky's and Laurel's preferred coffee
[] Takeaways
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[] Venky's background
[] Laurel's at background
[] Data wrangling
[] Sequel query
[] One size-fits-all LLMs vs Verticalized and Specific LLMs
[] Model Choice Trade-offs
[] NSQL Foundational Models
[] LLM Trends in 12 Months
[] Data recipes being democratized
[] Claude and 100,000 Context
[] Exploring Varieties of LLMs
[] AI Gateway
[] Text-to-SQL Model Evaluation
[] Wrap up