Alex Gold on DevOps for Data Science and Open Source Practices

Frank La Vigne sits down with Alex Gold, Head of Solutions Engineering at POSIT and author of "DevOps for Data Science." Together, they explore the fascinating intersections of DevOps, MLOps, and generative AI, shedding light on the importance of social norms, innovation, and practical impact in open-source development.Show NotesLinksDevOps for Data Science (Online Version) https://do4ds.com DevOps for Data Science (Amazon) Moments02:14 Marylander love their state flag06:09 PBC prioritizes diverse responsibilities beyond shareholder value.08:17 Chose Python for its versatility across fields.12:15 Choose the right language for each pipeline stage.16:14 Deploying software for enterprise use requires oversight.19:26 Most data scientists rarely focus on machine learning.23:18 Machine learning misunderstood; majority use simple models.26:46 Generative AI in big companies, production challenges.28:30 DevOps for data science needs unique practices.31:28 Focus on quick wins for business value.34:05 Focus on relationships; people problems require empathy.37:17 Technical people focus on solving technical problems.42:53 Companies exploring gen AI strategies, co-pilot model prioritized.45:01 Exploring gen AI for effective customer data use.49:32 Progress continues despite leveling off in horsepower.52:40 AI needs deeper integration for life-changing impact.55:39 Upload content; create NPR-style podcast summary.58:38 Thanks for tuning in! Stay data driven.