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Do you have any pointer to search for that?


You can see aggregated results on `stats` [1] for every year. In general, half the people drop in the first 3-4 days. For last year, by day 12 there is less than 1/5 of day 01. While the stats do count people that completed later, the shape appears to track well with what I saw during the events since 2021.

[1] https://adventofcode.com/2024/stats


I am not aware of Eric saying something about that alternative, but this comment on reddit[1] makes a lot of sense to me:

> Given that part 2 is often a very simple modification of part 1, this could lead to many of the days being total letdowns. I can enjoy a simple puzzle, but I'd be a bit disappointed if one day is a single line change to the previous day.

I'd also add that not having to be worried everyday about something makes a lot of sense. He can have fewer days "on call" in December with.

[1]https://www.reddit.com/r/adventofcode/comments/1ocwh04/chang...


Plus, I like doing Part 2 immediately after Part 1, cause then I don't have to remember how my solution worked.


You could think about how most people can get away without doing anything physical to survive, so we must artificially exercise to be healthy. The question then is if this analogy hold for mental capacities, and I think it does.


hard, and expensive, but doable as long as carbon credits are a thing: https://re.green/en/?force_locale=1

there are a few others in Brazil, like Biomas and Mombak


>2. be very careful when using rm command (use alias rm='rm -i' )

and treat mv/cp/rsync like rm



There is a multitude of applications leveraging parts of the spectra different than the visible. I come from an agricultural background, and you can see examples from improving classification of land use, detection and classification of diseases, nutritional status assessment, indirect measurements of properties of plants and soil... it is endless, and every time any part of the tool stack gets cheaper, you have more and more potential applications. This comment [1] have a nice description for the library.

[1] https://news.ycombinator.com/item?id=42507805


If anything, OCaml's error messages are something that sucks, especially for newcomers. The `Error: Syntax Error` message that points to an empty last line in the file leaves you doing the parser work, in a language that you don't understand.


I'd guess that you can equate "screen time" to "smartphone use" in most of the population but here. Similar to what people are using the screen for.

To include so many variations of screen would complicate a lot the study, and without a prior about why it should matter, you are probably safer starting with something more homogeneous.


> I'd guess that you can equate "screen time" to "smartphone use" in most of the population but here. Similar to what people are using the screen for.

I'm fairly confident this is not a safe assumption.

> To include so many variations of screen would complicate a lot the study

How so, though?

> without a prior about why it should matter, you are probably safer starting with something more homogeneous.

That's not very scientific, is it? There's no prior as to why it shouldn't matter, which is what the authors seem to think.


A huge number of people are professional screen-users. Almost every office job, and quite a few otherwise. I probably spend more time on my work laptop than my phone, and I'm pretty bad for using my phone a lot.


> smartphone use" in most of the population but here

Presumably you don’t think that all the white collar workers who aren’t in tech spend all of their work-hours scrolling tiktok/etc.?


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