MLOps vs ML Orchestration // Ketan Umare // #183

MLOps podcast #183 with Ketan Umare, CEO of Union.AI, MLOps vs ML Orchestration, co-hosted by Stephen Batifol.// AbstractLet's explore the relationship between Union and Flyte, emphasizing the significance of community-driven development and the challenge of balancing feature requests with security considerations. This conversation highlights the importance of real-time data and secure data handling in orchestrating machine learning models. The Flyte community's empathy and support for newcomers underscore the community's value in democratizing machine learning, making it more accessible and efficient for a broader audience.// BioKetan Umare is the CEO and co-founder at Union.ai. Previously, he had multiple Senior roles at Lyft, Oracle, and Amazon ranging from Cloud, distributed storage, Mapping (map-making), and machine-learning systems. He is passionate about building software that makes engineers' lives easier and provides simplified access to large-scale systems. Besides software, he is a proud father and husband, and enjoys traveling and outdoor activities.// MLOps Jobs board jobs.mlops.community// MLOps Swag/Merchhttps://mlops-community.myshopify.com/// Related LinksWebsite: https://union.ai/Flyte: https://flyte.org/ ⁠--------------- ✌️Connect With Us ✌️ -------------Join our Slack community: https://go.mlops.community/slackFollow us on Twitter: @mlopscommunitySign up for the next meetup: https://go.mlops.community/registerCatch all episodes, blogs, newsletters, and more: https://mlops.community/Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/Connect with Stephen on LinkedIn: https://www.linkedin.com/in/stephen-batifol/Connect with Ketan on LinkedIn: https://www.linkedin.com/in/ketanumare/Timestamps:[00:00] Ketan's preferred coffee[01:05] Takeaways[03:08] Please like, share, and subscribe to our MLOps channels![03:15] Shout out to Ketan and UnionAI for sponsoring this episode![04:23] Orchestration of recent changes[07:51] Community with Flyte[11:26] ML orchestration [15:40] 50/50 is generous[20:06] Real-time ML[21:15] Over-engineering without benefits[23:20] Balancing everything[27:40] Union verse Flyte[32:52] High-value features of Union AI at the back of Flyte[40:18] Building LLM infrastructure[45:30] Traditional ML is the whole prompting[46:46] LLMs for evaluating prompts[48:55] Wrap up