Instructor Akash Levy Is Helping Design the Future of the Internet of Things by Making AI Applications Run Faster

Akash Levy is a 3rd year Ph.D. student studying Electrical Engineering at Stanford University. He is also working on new hardware for AI applications.

How did you choose what you studied in college? How did you end up studying AI?

“I was broadly interested in computer science and physics, so I decided to do a major somewhere in the middle: Electrical Engineering! I ended up minoring in both CS/physics, so I really got the trifecta. I first got into AI with a summer internship after my freshman year at Harvard, where I was using deep learning to predict petroleum well production. Since then, my interest has grown, and I am now studying how we can build tailor-made hardware for AI applications!”

What research/industry work within AI have you been focused on? What excites you about the future of AI?

“I have been interested in making hardware accelerators for AI applications! I think making AI applications run faster and more energy-efficiently is going to be really exciting for enabling the Internet of Things.”

What has been the highlight of your teaching experience with Inspirit AI?

“I love hearing students ask great questions. Learning is always a two-way street, and I feel like I have learned so much from my students throughout my time teaching.”

What advice would you give to young people who are interested in studying AI or pursuing a career in AI in the future?

“I highly recommend it. It is crazy to think that we might be part of the next revolution in computer science!”