Zac Kriegman

Zac Kriegman

Director of Data Science

Zac Kriegman, J.D.

Director of Data Science


Deep Learning and NLP

How did you get into this area of work? (Was there a specific moment where you said this is what I want to do?)
I’ve been interested in Artificial Intelligence (AI) since I was a kid. In college, the field was moving very slowly, and I followed my interest in economics instead of computer science. After college I worked as software engineer for a while, but eventually decided I wanted to go to law school, earning my J.D. from Harvard. I practiced law for a few years at a top national law firm, doing venture funding for tech startups. Eventually I melded my law and economics backgrounds, and got a gig as an economist doing econometric analysis for anti-trust litigation. It was around that time that Deep Learning was starting to make breakthroughs in image recognition, so I followed my longstanding interest in AI and undertook an independent study of Deep Learning. I discovered that many of the core concepts were closely related to the econometrics I had learned in college. I entered a Kaggle competition to automatically identify plankton, and when my algorithm got better than me at distinguishing all the weird organisms, I was hooked.

What kind of projects do you work on?
I work exclusively on deep learning projects, and mostly focus on natural language understanding and composition. I’m particularly interested in problems that have traditionally been considered to require the unique intelligence of a human — for example, identifying the key legal points in a document, or writing summaries of the key facts in a legal complaint.

What is one interesting fact you’ve come across while performing your work?
AI is developing very quickly.

How would you apply AI/ML to improve some aspect of everyday life?
Are there any chores you have to do, but don’t like doing? That’s going to change… talking robots doing serious every day work won’t be science fiction that much longer.

Last thing you attended/ate/drank – and how would you apply AI/ML to improve that experience?
This doesn’t quite fit the question, but I’ve been learning piano recently. And I think there is an opportunity for an AI piano teacher that dynamically adapts lessons, notes, and music to optimally walk students through the process of learning piano. The AI would analyze your playing to identify key areas for improvement, and then select exercises and music based on your tastes to keep you hooked. It would learn to pace you at just the right speed to keep breakthroughs coming and keep you motivated, but not so fast that you get discouraged by the difficulty.

Any AI/ML related predictions in the next couple of years?
AI will transform every aspect of our business. It will take a little bit more than a couple years, but it will touch every corner of the company.

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