Instructor Jake Kaplan Knows the Power of AI, and the Burden of Responsibility for Those Who Study It

Jake Kaplan is a junior at Stanford University studying Mathematics and Theoretical Computer Science. However, he is currently taking a year off to work at a growing startup, Hebbia.AI, creating a reinvented Ctrl-F that understands queries and finds the best answers on a page in seconds. Back on campus, Jake is especially interested in the interface of math and computer science, and how mathematical problem solving and proofs can be used to draw powerful conclusions in complexity theory (studying how hard a problem can be to solve) and machine learning.

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

“I came into college dead set on a chemical engineering degree. I really enjoyed math, physics, and organic chemistry in high school. However, after exploring courses in college, I realized that I was not nearly as interested in engineering and the applications of math as I was in the theory of it. I ultimately chose to study math because I really enjoyed the courses and found them the most engaging. Similarly, I chose to pursue a combined Master's in CS theory because I found the material and the way of thinking required for it had a lot in common with and built off of math very well. Naturally, the study of math and CS theory led me toward AI as a particularly interesting application of the two.”

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

“This year, I've had the phenomenal opportunity to work with a growing startup in the NLP space where I've been able to focus on how cutting edge transformer models can transform (no pun intended) the productivity space. Specifically, I work on a product designed to interpret queries using NLP techniques and find relevant information in documents within seconds. It is especially exciting to witness how recent developments in ML have allowed machines to accomplish tasks, one by one, that have long been thought of as benchmarks for cognition meant to distinguish human from machine. We have something very powerful at our hands, and though it requires a great burden of responsibility, there is just so much beauty that it can bring to the world. I am truly excited to see how AI can be used over the next few decades to solve some of the biggest problems we face as a society today.”