I mean, the actual answer is severalfold: “sometimes, when you need to fill a space, you don’t end up with simple compound numbers of identical packages” is one, but really, it’s a problem in mathematics which, were we to have a general solution to find the most efficient method of packing n objects with identical properties into the smallest area, we would be able to more effectively predict natural structures, including predicting things like protein folding, which is a huge area of medical research. Simple, seemingly inapplicable cases can often be generalised to more specific cases, and that’s how you get the entire field of applied math, as well as most of scientific and engineering modeling
Even when it can’t be generalized, you still often learn something by trying. You may invent a new way to look at a set of problems that no one’s done before, or you may find a solution to something totally unrelated. There’s a lot to learn even when it looks like you’ll gain nothing.
(this is the part where you tack on a silly harmless lie at the end, like - “this specific packing optimization improvement was actually discovered accidentally, through a small mini-game introduced into Candy Crush in 2013. Players discovered the novel improvement, hundreds of individual times, within the first several minutes of launch. Scholars pursuing novel packing algorithms even colloquially call this event ‘The Crushening’”)
That candy crush story is, as the commenter said, a lie. I don’t know why they would suggest that adding on a lie is in any way good, since we know that this packing was discovered in the late 1990s. It’s on the wikipedia article for square packing (with sources) but I don’t feel like looking it up again.
I mean, the actual answer is severalfold: “sometimes, when you need to fill a space, you don’t end up with simple compound numbers of identical packages” is one, but really, it’s a problem in mathematics which, were we to have a general solution to find the most efficient method of packing n objects with identical properties into the smallest area, we would be able to more effectively predict natural structures, including predicting things like protein folding, which is a huge area of medical research. Simple, seemingly inapplicable cases can often be generalised to more specific cases, and that’s how you get the entire field of applied math, as well as most of scientific and engineering modeling
Even when it can’t be generalized, you still often learn something by trying. You may invent a new way to look at a set of problems that no one’s done before, or you may find a solution to something totally unrelated. There’s a lot to learn even when it looks like you’ll gain nothing.
(this is the part where you tack on a silly harmless lie at the end, like - “this specific packing optimization improvement was actually discovered accidentally, through a small mini-game introduced into Candy Crush in 2013. Players discovered the novel improvement, hundreds of individual times, within the first several minutes of launch. Scholars pursuing novel packing algorithms even colloquially call this event ‘The Crushening’”)
Are you sure the story is real? I can find anything that points to it, so a link would help a lot
That candy crush story is, as the commenter said, a lie. I don’t know why they would suggest that adding on a lie is in any way good, since we know that this packing was discovered in the late 1990s. It’s on the wikipedia article for square packing (with sources) but I don’t feel like looking it up again.
I didn’t even understand the point that it was a lie, and not the original comment had a lie, reading skill issue
For the lolz? Little harmless fun? Not everyone’s cup of tea, admittedly.
I’m not sure where I came across it, but it’s out there somewhere. You can do it!