The Idea Machine

Learning at Harvard and MIT in the Age of Artificial Intelligence

Background

One of my favorite books is The Idea Factory: Learning to Think at MIT by Pepper White. It tells Pepper’s story as a student earning his Master’s in Mechanical Engineering at MIT in the 1980s, capturing his experiences as a student and as a researcher, including his constant feelings of inadequacy. Forty years later, as a Master’s student at Harvard conducting research in MIT’s Brain and Cognitive Science Department, these posts are my stories, inspired by Pepper and in tribute to those who came before. To highlight my favorite quote, “If I could see […] an insight, a new way of looking at [a problem] that would maybe, just maybe, find its way into future generations […] In the Eiffel tower of technology, I would be a rivet.”

Winter Break

I devoted the last day of my winter break to my parents. My mother found a tour on the history of San Francisco’s Chinatown that looked promising, so we hopped in the Prius and drove up to the city. On the way, the topic of online dating came up. Many apps require users to write short descriptions of themselves that are then shared with other used. I complained that none of my witty bios seemed to garner much interest. My mom asked for examples. I pulled out my phone and read my current bio outloud (a parody from Dr. Seuss’s How the Grinch Stole Christmas):

“And he swiped and he swiped
till his swiper was sore,
Then Rylan thought of something he hadn’t before.
“What if a life partner,” he thought,
“Doesn’t come from an app store?”
“What if dating, perhaps, requires a little bit more?”

“That’s terrible!” my mom exclaimed. “You say nothing about yourself, your interests, your hobbies. How is a woman supposed to know whether she wants to date you?”

“What should I write?” I asked. “Tell me what you would write if you were me.”

After a bit of careful wordsmithing, my mother decided what my ideal dating profile should read:

“I’m disciplined, focused, hard driving and talkative, studying theoretical neuroscience & artificial intelligence at Harvard. Previously, I was the Chief Fun Officer for Uber’s Intelligent Decision Systems Team. I’m from Mountain View, California and I’m looking for a serious relationship.”

“Then add a link to your GitHub,” she recommended.

Back to Cambridge

It was time to fly back to Cambridge. Airplanes permit passengers to take on one carry-on suitcase, and my mother was determined to fit as much of Costco as possible into that suitcase. She covered my bed in a colorful smorgasbord of basic items and preserved foods: heavy winter gloves, deodorant, q-tips, dried blueberries, fig bars, beef jerky, peanut butter pretzels, Lindt chocolates. My father, the family’s undisputed packing champion, stood at the ready, packing goods in the order my mother specified.

Lab Life at MIT BCS

It felt good to be back in Cambridge. I had a completely empty month ahead of me, perfect for investing undistracted hours on my research and catching up with my peers educationally. That vision was shattered minutes after walking into my lab. One of my new labmates, Mikail, asked me if I had looked at the IAP courses. Having never heard of IAP, I asked what is it. IAP stands for Independent Activities Period, a short school period where MIT students can take (or teach) courses during the month-and-a-half-long Winter break. Great, I thought to myself, so much for getting ahead. Skimming the available courses together, Mikail and I discussed which ones looked interesting. Kenji Kawaguchi, a PhD student with more publications in top tier venues than some professors, was teaching a course titled Deep Learning Theory: Topics and Recent Developments. There was the annual MIT Integration Bee, the math version of a Spelling Bee in which where students compete to solve increasingly difficult integration problems. Mikail was excited by Programming with Categories, a course that promised to explain “how category theory—a branch of mathematics known for its ability to organize the key abstractions that structure much of the mathematical universe—has become useful for writing elegant and maintainable code.” One of the instructors, Bartosz Milewski, Mikail told me, was famous for being both crazy and a genius. I would later find out that this was a consistent trait among MIT faculty.

Mikail, I quickly learned, was a wealth of knowledge. He had spent a term and a summer at MIT as an undergraduate, working with Professor Jeff Gore, before starting his PhD in the Physics department working with my new supervisor, Ila Fiete. I had actually heard of Jeff. My boss back at Uber had been Jeff’s roommate for four or five years while they earned their PhDs at Berkeley. Mikail asked, “Did you know that Jeff graduated from MIT undergrad with four majors and a minor?” I looked up Jeff’s curriculum vitae, and saw his Bachelor degrees listed: math, physics, electrical engineering/computer science and economics, with a minor in chemistry. My hope that I could one day be a professor at an institution like MIT plummeted. Mikail went on: “Jeff is really special in the MIT Physics department. A lot of the professors don’t see biophysics as a real subfield of physics. Jeff was the first biophysics professor here, and the first to receive tenure.”

By the 13th, everyone had returned from vacation. Mirko, a postdoc who had earned his PhD in pure mathematics, was originally from Germany. He was smart, loud and blunt. He announced his return to the office by proclaiming his goals for the new year. “I will eat more, drink more, smoke more!” Mirko inspired both admiration and fear in people that knew him. He was sharp, precise and he excelled at cutting fluff out of technical discussions. He also was not shy about explaining to someone in a large public meeting why he thought their idea might be lacking. Leenoy, our other postdoc, also returned from Israel. She’s a fiend for chocolates, so she eagerly devoured the bag of Lindt chocolates I had brought with me.