As you start developing an AI/ML based solution, you quickly figure out that you need to run workflows. Not only that, you might need to run those workflows across various kinds of infrastructure (including GPUs) at scale. Ville Tuulos developed Metaflow while working at Netflix to help data scientists scale their work. In this episode, Ville tells us a bit more about Metaflow, his new book on data science infrastructure, and his approach to helping scale ML/AI work. Join the discussionChangelog++ members save 2 minutes on this episode because they made the ads disappear. Join today!Sponsors:RudderStack – Smart customer data pipeline made for developers. RudderStack is the smart customer data pipeline. Connect your whole customer data stack. Warehouse-first, open source Segment alternative. SignalWire – Build what’s next in communications with video, voice, and messaging APIs powered by elastic cloud infrastructure. Try it today at signalwire.com and use code AI for $25 in developer credit. Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com Featuring:Ville Tuulos – LinkedIn, XDaniel Whitenack – Website, GitHub, XShow Notes: Metaflow Books “Effective Data Science Infrastructure” by Ville Tuulos Use code podpracticalAI19 for 40% off! Something missing or broken? PRs welcome!

Ville Tuulos, co-founder and CEO of Outerbounds, has a rich background from Netflix and AdRoll. He discusses the inception of the open-source framework Metaflow, designed to facilitate machine learning collaboration. The conversation highlights the importance of AI compute clusters and the distinction between large foundation models versus smaller specialist ones. Ville also explores trends in industrial and multimodal AI, and emphasizes the need for innovative AI infrastructure solutions. Dive into the future of AI with insights from his extensive experience!