Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, computer science, data science and more.
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episode 653: Delivering AI Systems in Highly Regulated Environments with Miriam Friedel
Today we’re joined by Miriam Friedel, senior director of ML engineering at Capital One. In our conversation with Miriam, we discuss some of the challenges faced when delivering machine learning tools and systems in highly regulated enterprise environments, and some of the practices her teams have adopted to help them operate with greater speed and agility. We also explore how to create a culture of collaboration, the value of standardized tooling and processes, leveraging open-source, and incentivizing model reuse. Miriam also shares her thoughts on building a ‘unicorn’ team, and what this means for the team she’s built at Capital One, as well as her take on build vs. buy decisions for MLOps, and the future of MLOps and enterprise AI more broadly. Throughout, Miriam shares examples of these ideas at work in some of the tools their team has built, such as Rubicon, an open source experiment management tool, and Kubeflow pipeline components that enable Capital One data scientists to efficiently leverage and scale models.
The complete show notes for this episode can be found at twimlai.com/go/653.