[] Register for the Data Engineering for AI/ML Conference now!
5
[] The Life Cycle of AI Executives Course
6
[] MLOps as a term
7
[] Tooling vs Process Culture
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[] Open source benefits
9
[] End goal flexibility
10
[] Hybrid Cloud Strategy Overview
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[] ROI for tool upgrades
12
[] Long-term projects comparison
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[29:02 - ] SAS Ad
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[] AI and ML Integration
15
[] Hybrid AI Integration Insights
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[] Tech trends vs Practicality
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[] Gen AI Tooling Debate
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[] Vanity metrics overview
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[] Tech business alignment strategy
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[] Aligning teams for ROI
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[] Communication mission effectively
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[] Enablement metrics
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[] Prioritizing use cases
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[] Wrap up
Description:
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Explore design and development principles for LLMOps in this insightful podcast episode featuring Andy McMahon, Director - Principal AI Engineer at Barclays Bank. Delve into fundamental software engineering practices and new techniques as the industry transitions from MLOps to LLMOps. Gain valuable insights on topics such as tooling vs. process culture, open source benefits, hybrid cloud strategies, and ROI for tool upgrades. Learn about AI and ML integration, hybrid AI integration insights, and the debate surrounding Gen AI tooling. Discover strategies for aligning tech with business goals, effective team communication, and prioritizing use cases. This comprehensive discussion covers essential aspects of LLMOps, providing practical knowledge for professionals in the field of machine learning operations.
Design and Development Principles for LLMOps - MLOps Podcast #254