In this episode I’m joined by Greg Mulholland, Founder and CEO of Citrine Informatics, which is applying AI to the discovery and development of new materials.
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Greg and I start out with an exploration of some of the challenges of the status quo in materials science, and what’s to be gained by introducing machine learning into this process. We discuss how limitations in materials manifest themselves, and Greg shares a few examples from the company’s work optimizing battery components and solar cells. We dig into the role and sources of data used in applying ML in materials, and some of the unique challenges to collecting it, and discuss the pipeline and algorithms Citrine uses to deliver its service. This was a fun conversation that spans physics, chemistry, and of course machine learning, and I hope you enjoy it.
Interested in the Fast.AI Deep Learning course?
This Saturday we discuss lesson one, “Recognizing Cats and Dogs” of the Fast AI Practical Deep Learning for Coders course via the Meetup. This is a great course and Fast.ai co-founder Jeremy Howard encouraged our group on twitter noting that groups that take the course together have a higher success rate, so let’s do this!
Three simple steps to join:
1. Sign up for the Meetup, noting fast.ai in the “What you hope to learn” box
2. Using the email invitation you’ll receive to join our Slack group, and
3. Once you’re there joining the #fast_ai channel.
Mentioned in the Interview
- Citrine Informatics
- Join us in celebrating our 2nd Birthday!
- TWiML Presents: Series page
- TWiML Events Page
- TWiML Meetup
- TWiML Newsletter
“More On That Later” by Lee Rosevere licensed under CC By 4.0