10x Researcher
I had a note on 10x Developer. It’s now time to make the 10x researcher note.
Becoming Expert in Robot Learning
This is a thought experiment that I am going through.
With the rate of how many papers are coming out every day, and to stay on top, how much do I need to read to develop this taste?
- How fast are robot learning papers coming out every day?
From my arxiv search, there were 2661 papers tagged with
cs.ROandcs.AIin the past 12 months, so 2661 / 365 = 7.3 papers per day
- I will not keep up with 7.3 papers a day
The good news is that how many of those papers are actually useful though? Not that many.
- For example, this paper self-claims to be groundbreaking… any paper that claims to be groundbreaking is a huge red-flag. That is up to the readers to judge.
First, you can quickly filter out just by looking at school. The top robot learning is really consolidated in 2 schools: stanford and berkely. So you can just read those papers. And then, there are extra benchmark papers like Bridge (lol those also came out of stanford/berkeley).
So action plan:
- RoboPapers is a pretty good signal since they hand-pick the authors
- ~20 papers right now
I think if I read ~100 papers deeply, I can get a really strong grasp of the field. I think future lifetime goal is 1-2 papers a day. You will be able to read more papers faster once you can quickly identify the new ideas. For example, for you, Flow Matching is a really new idea, so the math doesn’t make sense. Perhaps it’s worthwhile to skip the math.
https://www.reddit.com/r/MachineLearning/comments/f4oxuj/discussion_what_are_some_habits_of_highly/
You need to relentlessly pursue
https://www.instagram.com/entrepreneurarchived/reel/DMAczQHxxk0/
- kevin o’leary on steve jobs in the diary of a ceo
Sigi There are a few things to read:
- Opiniated guide to research
- You and your research