I started my PhD around the same time as Emmy (2021), and very much agree with Emmy's take here. I told myself at the time when I started my PhD that I'd write something akin to "The PhD Grind"––a book I was really inspired by––but as I was trying to pen down my thoughts/advice for incoming PhD students last month, I felt that I really don't know what to say. One thing imo you should take away here is that: you should downweight the advice from whoever tells you *confidently* you should or should not do PhD based on their experiences––without expressing any thoughtful musing about what it means to be a researcher in academia in both next year and 5 years ahead. I remember around late 2023 (right before I started my first AI safety paper), I had a discussion with my PhD roommates that I'm afraid AI is going to eat researcher jobs like mine. I would like to believe that I have been doing good research, but man at that time, I already found a lot of my own experimental workflows are mid-to-low-intellectual tasks (the "mechanics" Emmy talked about). Most of my value was on deciding what ideas and directions to best spend my limited time/energy/compute on, and continuously verifying that my findings and conclusions are indeed robust and can hopefully stand the test of time. In a future world of expanding compute and where LLM can "jump" because of interconnected knowledge, researchers would really have to think twice about our own roles.

pre-registering my first wild take, written while on flight to SF! I argue that "LLM can jump", where I touched upon the potential (re)discovery of General Relativity, and what "LLM can jump" means for safety as well as continual learning.