2022 in Review

life learning progress

03 Jan 2023

15 minute read

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Table of Contents #

Sequel to 2021 post, 2021, 2020, and 2019.

If you want to talk to me about any of this, chat, or have any recommendations on anything, email me or DM me on Twitter.

Doing yearly recaps helps me observe my progression in many areas, and keeps me accountable for next year. I share things I’ve done, learned, read, and often sprinkle in some introspection on recurring motifs that have animated my year. I also included a best of twitter.

General Goals #

These are not directly learning/project-related, just random stuff I’d like to do/did.

Last year’s goals #

2023 Goals #

College #

One of the main themes this year was college, applying, choosing where I want to go, and then actually doing my first semester. I decided to go to MIT, instead of my second choice which was a good preparatory school in Paris. I have trouble making decisions and honestly hesitated a lot on this one, both options having drawbacks and advantages. I think I need to learn to accept the decisions I make and become less anxious about optimization errors of past decisions, but I’m not sure how.

The first semester of college has been interesting. I’ve met many very cool people and have started doing some theory of deep learning research with a grad student. My courses had high variance in quality, but I think next semester will be more consistent. The transition to the US was hard in terms of moving to a new country far from friends/family. I had spent time in the US but it took getting used to.

Thread with first impressions:

Projects #

What I wanted to do #

From last year:

What I did #

Research #

I did ML research this semester with Eric Michaud in the Max Tegmark lab! Based on hypotheses set forth in In-context learning and induction heads and A mechanistic interpretability analysis of grokking, we ran experiments to get a better grasp on the relationship between phase changes (rapid decreases in test loss) over time and the formation of algorithmic circuits in models.

Doing research in an official context for the first time was really interesting. It was cool to see my internal models of how these neural networks learn get more and more accurate (I think?) although there’s still a ways to go. I’m happy with the paper-reading/experimentation/ML engineering skills I’ve been building here.

Espial #

I worked a lot on my project Espial but have yet to actually publish anything, sadly. I think this is because of a set of things, notably:

I did share online and got lots of people interested in and setup a waiting list, and overall actually built out a project I can be proud of, but I didn’t do things all the way.

However, I started working on it again with a friend recently and am quite excited/hopeful that I can get something out there related to this in 2023. Time will tell!

Miscellaneous #

What I want to do #

Learning #

Courses #

I took 5 courses:

Format is (<MIT course #>) (rating).

Overall, my takeaways here are to be very thoughtful about which classes I take, and to shop for classes at the beginning of the semester.

What I wanted to learn #

Didn’t do that well on the stuff I wanted to learn here, in part because I was quite busy with intense French graduation exams in philosophy/literature. More for next year!

From last year:

What I learned #

What I want to learn #

Writing #

What I wanted to write #

What I wrote #

I only wrote two posts on my blog this year, coming in at ~5.5k words:

I have too many drafts and struggle to make time for writing long-form posts I’m happy with. I probably need to be less perfectionist and just output stuff.

I’ve started a newsletter where I post semi-frequent updates (in theory it was weekly), and am quite happy about what I write up on there (link). I wrote 4k words on there. I really enjoy this format, where I kind of speak my mind and introspect, on a more regular basis than with what I do here.

I also wrote stuff on my wiki, publishing some notes on books I read this year, and agency. Also added to my favorite music

Books read #

Non-Fiction #

Fiction #

People #

I’ve been much more social this year generally, and quite extraverted. My MBTI has gradually shifted from I to E, and I’m becoming much more proactive in terms of reaching out to people. I think this is good: people are super interesting and I’ve been making many good friends. I also believe it’s important to leave a big amount of time to actual object-level projects and deepening my understanding of the content I want to master. I want to find my balance regarding this in 2023.

Tweets #

I used Twitter a lot more this year, meeting and scheduling one-on-ones with many cool people, especially in the knowledge management space. Here are my most interesting tweets this year: (note: I’m mostly putting this here for myself because Twitter search is bad and I want to be able to compare my thoughts on the scale of years)

Conclusion #

Overall, 2022 has been a year of heavy change. I’ve kind of been all over the place (physically and in terms of my thoughts), and now am living in a new country. I worked a lot on my projects but didn’t publish much yet, however I look forward to making updates soon. I’d say it’s been a year of discovery, in terms of people and ideas. Many of those discoveries are already precious to me, and I hope the others flourish into more things I can be grateful for.

Have a happy new year!