The Physics of Data with Alpha Lee

800 800 The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Today we’re joined by Alpha Lee, Winton Advanced Fellow in the Department of Physics at the University of Cambridge, and Co-Founder of data-driven drug discovery startup, PostEra.

Our conversation centers around Alpha’s research which can be broken down into three main categories: data-driven drug discovery, material discovery, and physical analysis of machine learning. We discuss the similarities and differences between drug discovery and material science, including the parallels in the design test cycle, and the major differences in cost.

We also explore the goals associated with uncertainty estimation, why deep networks are easier to optimize than shallow networks, the concept of energy landscape, and how it all fits into his research. We also talk about his startup, PostEra which offers medicinal chemistry as a service powered by machine learning.

The Discussion Series is Back!

Join us for the latest in the TWIML Discussion Series, this time focused on Advancing Your Data Science Career During the Pandemic, next Tuesday, May 26th, at 12pm PT.

I’ll be joined by Hilary Mason, who you know from her time at Fast Forward Labs, Cloudera, and this podcast, Caroline Chavier, data science recruiting maven and Co-Founder of Paris Women in Machine Learning and Data Science, Jacquline Nolis, co-author of Build a Career in Data Science, which is hot off the presses, and Ana Maria Echeverri of IBM and the OpenDS4All project.

With the help of your questions, this amazing panel and I will explore best practices, tips, advice, and direction for those affected by layoffs, new to the job market, or ready to accelerate your careers. To register for this panel, visit twimlai.com/advancingds.

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“More On That Later” by Lee Rosevere licensed under CC By 4.0

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