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30 May 2020

# 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.”

### Coronavirus Career Development

My parents and I have often discussed the two of them trying to become more familiar with quantitative topics. This past term, I was a teaching fellow for Harvard’s Data Science 10, and since I’m back at home due to Coronavirus, I proposed that I could teach them using the lectures, Jupyter notebooks and assignments. They both agreed and since then we’ve had an absolute blast. The two of them have complementary strengths, with my father having an edge at coding and my mother having an edge with algebra. Here are the two of them, pair programming on a Jupyter notebook.

I was expecting teaching the two of them to be uneventful, but we’ve made so many enjoyable memories. During one lecture, my father fell asleep. My mother and I couldn’t believe it. Most of the time, he’s a very good student. I’m a big fan of students teaching me, so here he is, teaching us.

During another lecture, I was teaching conditional probability and introduced them to the formula:

$P(A|B) = \frac{P(A, B)}{P(B)}$

I then gave them a practice problem and five minutes to solve it. Halfway through, my mother exclaimed “I’ve been using the wrong formula!” Here she is laughing at her mistake.

My favorite story concerns our cabin. We’re legally required to remove the flammable debris surrounding it, so once a year, we typically head up where we rake and burn the pine needles. However, this year was going to need extra work. The winter had been dry, and had been followed by a heavy snowstorm that wrecked havoc on the weakened trees; three trees had fallen on our cabin. My mother sent me the following email, asking for a break from our lectures to take care of the cabin.

She then showed up in my office and told me that I was misreading the academic calendar. I asked, “How’s that?” She then wrote the following on the whiteboard.

One of my friends, V, has agreed to be a guest lecturer and we’re so excited. If you’re interested in joining us or doing something similar with your family, get in touch!

### Hosting Trivia

My supervisor Ila was promoted to full professor at MIT, so my lab decided to host a remote celebration. My labmate Su, who was coordinating the celebration, was a bit concerned that we might benefit from having an activity to do together, so I volunteered to put together a round of trivia. We ended up not using any of the questions I put together because we ended up listening to Ila tell us her life’s story. She spoke about wanting to pursue philosophy, but being advised that it wasn’t a promising career. She told us she discovered neuroscience almost by accident, and that she met her husband (another professor) relatively early in their academic trajectories. At the end, she made a vulnerable confession, which I appreciated tremendously. She said that after being a professor for ten years (and in academia for much, much longer), this was the first year where she didn’t ask herself if she was wasting her time and if she was fail to measure up to her own expectations. She said not even becoming a full professor at MIT quelled those concerns.