Episode Summary: “Artificial intelligence (AI) can be seen as a progression in our scalability of labor.” This quote comes from this week’s guest, Naveen Rao, who received his PhD in Neuroscience from Brown before becoming CEO at Nervana Systems, which works on full stack solutions to help companies solve machine learning (ML) problems at scale. In this week’s episode, Rao speaks about certain domains in industry where he feels optimistic about machine learning (ML) making a difference in the next five to 10 years, providing interesting perspectives that include advances in the areas of agriculture and oil & gas.

 

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Expertise: Neuroscience and machine learning

Recognition in Brief: Naveen Rao, PhD, co-founded Nervana Systems with the goal of changing the way the world thinks about computation based on deep learning technologies. Prior to Nervana, Naveen was a researcher neural computation and artificial systems at Qualcomm, Assistant VP at ITG specializing in transactional cost analysis, and also served a number of engineer roles, including as Principal Engineer at W&W Communications. He received his PhD in Neuroscience from Brown University and a BSEE in Electrical Engineering and Computer Science from Duke University.

Current Affiliations: CEO at Nervana Systems

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Interview Highlights:

(1:41) In the next 5 to 10 years, what areas do you think will grow the most (in applying ML)?

(5:54) What is it about agriculture that makes it ripe for that kind of disruption and why do you feel it’s going to grow more than any other industry?

(7:35) What other sort of robotic applications might artificial intelligence (AI) weasel into in the agriculture world?

(10:50) In terms of personalized experiences…with respect to enterprise leading this domain, did you mean AI, that applications in a digital environment is normally led by bigger B2B companies?

(12:38) What are some of the other spaces that tend to be far out in front…finance, B2B applications for enterprise, where else does the cutting edge development sell?

(14:39) When you’ve been speaking to the investor community…what did you find as the sentiment for AI in today’s day and age and what were the common misconceptions?

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