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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, deep learning, computer science, data science and more.
27 Aug 2020 • 44 mins
Today we’re joined by Dillon Erb, Co-founder & CEO of Paperspace. We’ve followed Paperspace since their origins offering GPU-enabled compute resources to data scientists and machine learning developers, to the release of their Jupyter-based Gradient service. Our conversation with Dillon centered on the challenges that organizations face building and scaling repeatable machine learning workflows, and how they’ve done this in their own platform by applying time-tested software engineering practices. We also discuss the importance of reproducibility in production machine learning pipelines, how the processes and tools of software engineering map to the machine learning workflow, and technical issues that ML teams run into when trying to scale the ML workflow. The complete show notes for this episode can be found at twimlai.com/go/404.