739: AI is Eating Biology and Chemistry, with Dr. Ingmar Schuster

AI Protein design, machine learning and cancer care, and pharmaceuticals: At Exazyme, CEO and Co-Founder Ingmar Schuster uses AI to design proteins. He speaks with Jon Krohn about their wider applications in pharmaceuticals and chemistry, how Kernel methods make the design of synthetic biological catalysts more efficient, and when to use shallow machine learning over deep learning. This episode is brought to you by Gurobi (https://gurobi.com/sds), the Decision Intelligence Leader. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • On designing proteins with AI [03:14] • Designing proteins at Exazyme [08:22] • About the kernel methods [18:10] • The importance of human-led approaches in protein research [35:44] • Europe’s focus on AI regulation [43:45] • Deep vs shallow in AI [59:35] • How a background in academia helps with entrepreneurship [1:09:17] Additional materials: www.superdatascience.com/739

Om Podcasten

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast. As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact. Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy. We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.