Abstract: From improving medical diagnosis to optimizing supply chains, AI holds the promise of transforming every industry. However, many companies and teams--particularly ones outside the consumer internet industry--are still struggling to take research breakthroughs or promising proof-of-concept demonstrations and turn them into practical production deployments. How can researchers and AI professionals help bridge this gap? In this talk, I’ll describe some key challenges facing AI deployments, and also discuss some solutions, ranging from techniques for working with small data, to improving algorithms’ robustness and generalizability, to systematically planning out the full-cycle of machine learning projects.
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Co-Chairman and Co-Founder of Coursera; and an Adjunct Professor at Stanford University.