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[D] (“Soft”) Life compartmentalization and practical aspects of working in ML

Some background on myself: I just finished my phd doing ML research, and I’ll soon begin a postdoc. My apologies if this is not the right subreddit, but I feel many of you may be dealing with the same issues as me, and I think we could benefit from a discussion of this.

I’ve noticed that essentially all the time, I feel I should be working. This is clearly no way to live my life, so I’m trying to identify all the factors in this. One factor is I often stay up late trying to get code to work so I can train it while I sleep. So I go to bed thinking about work, and I wake up thinking about work because the first thing I do is check the results. Since I also work during the day, I never stop thinking about how things are going, etc. This mentality makes me very moody: if I’m getting bad results, I feel like what I’m working on is doomed. In short, I identify my life situation and self-worth with simulation results that are relatively arbitrary.

Does anyone else feel the same way? How might we fix this issue? I think part of a solution is to work on more ‘conceptual’ problems in which things like hyperparameter tuning carries less weight, requiring less amounts of training time. But even though I work on pretty conceptual stuff anyway (no classification problems which often become quite industrialized), small changes in the model do make a difference in quantitative results, which must be there for publication.

I’ve toyed with the idea of a hard cutoff for work, e.g., 8 or 9 pm. But I often find that when I have to train during the day, I feel like I lose a day and just piddle that day away, waiting for the results to finish so I know what to think about or do next.

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.