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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.

Aug 15, 2019

Today we are joined by Anubhav Jain, Staff Scientist & Chemist at Lawrence Berkeley National Lab. Anubhav leads the Hacker Materials Research Group, where his research focuses on applying computing to accelerate the process of finding new materials for functional applications. With the immense amount of published scientific research out there, it can be difficult to understand how that information can be applied to future studies, let alone find a way to read it all. In this episode we discuss:

- His latest paper, ‘Unsupervised word embeddings capture latent knowledge from materials science literature’

- The design of a system that takes the literature and uses natural language processing to analyze, synthesize and then conceptualize complex material science concepts

- How the method is shown to recommend materials for functional applications in the future - scientific literature mining at its best.

Check out the complete show notes at