Stacked non-linearities: unusual career paths in AI

July 15, 2022 · ~4 min read

Some time ago, I wanted to create a podcast interviewing people who have taken varied, unconventional, or unexpected routes in (or even out) of the AI field.

The working name was "Stacked non-linearities". The deep learning reference is obvious, and I wanted to make sure to include "stacked" to emphasize how taking forks compound into interesting payoffs.

One motivation was to help folks with non-traditional backgrounds to enter AI, and provide inspiration in the spirit of Roadtrip Nation or 80000 Hours. I also always enjoyed efforts that highlight the random walk nature of research, such as the "I Can't Believe It's Not Better" Neurips workshops, or the Thesis Review podcast, which provides technical retrospectives.

For the majority of my PhD, most ML grad students targeting industry were interested in the few major research labs. That's changed a bit, and when I graduated, I ended up interviewing widely across roles (industry labs, stealth startups, post-docs) and domains (pure research, applied products, drug discovery and health, alignment).

I think this signals, hopefully, less of a need for such a podcast. We're trending towards many more opportunities, and varied entry points.

Since I likely won't be making the podcast, I thought I'd still share a few of the categories and interview candidates I had in mind, in case you'd like some inspiration:

  • Field Switchers: Thomas Wolf (physics PhD, patent attorney, co-founding Huggingface), David Ha, Nathan Benaich, Leonard Mlodinow, (physics post-doc, wrote Feynman's rainbow, screenwriter and author), David X. Cohen, Ted Chiang
  • Interdisciplinary Backgrounds: Yul Kwon (Yale Law, Survivor contestant, FBI instructor, Google VP research), Matthew Botvnick (art history Master's, medical school, deep learning and neuroscience PhD, DeepMind, law school), Tom White, Zachary Lipton, Martin Wattenberg and Fernanda Viégas, Demis Hassabis
  • Research without a PhD: Chris Olah, Eric Jang, Neel Nanda, Demi Guo, Google Brain residents
  • Academia, Industry, Startups transitions Kyunghyun Cho, Hugo Larochelle, David Luan, David Bau, Colin Raffel, Austin Henley, Pete Warden, Rewon Child, Paige Bailey, Deb Roy, Doug Beeferman, Lisha Li, Regina Barzilay, William Fedus