| ▲ | podocarp 5 hours ago | |||||||||||||||||||
This reminds me of the (perhaps unrelated meme) hello I would like (graph of zeta function) number of apples. Statements dreamt up by the utterly deranged. Indeed I have met professors who claim since something is O(1) it doesn't matter if you run it 4 times. No need to optimize. I think it's just part of the wider divide between theory and application. For instance big O also requires a register machine to make sense, which most courses don't define. Somehow addition and multiplication are O(1) in some places and O(n) or O(n^2) somewhere else. Also quite common is the fact that sets are slower than lists for lookup for small n, despite being O(1). It's just a tool and we shouldn't miss the trees for the forest. I also understand this comment has nothing to do with the ETH or the article, but just some thoughts I have after reading the first chunk on complexity | ||||||||||||||||||||
| ▲ | nonadhocproblem 5 hours ago | parent | next [-] | |||||||||||||||||||
Did you ever pause to consider that theoretical computer science might not be done for the sake of midwit code monkeys whose deepest contact with complexity theory was when they learned to reverse a linked list in O(n) for their SWE interview? | ||||||||||||||||||||
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| ▲ | lioeters 5 hours ago | parent | prev [-] | |||||||||||||||||||
> miss the trees for the forest I think the common expression is to miss the forest (big picture) for the trees (details). But maybe you're playing on words and saying we shouldn't let the big picture (big O notation/analysis) obscure our attention to the details (an algorithm's actual efficiency and performance). | ||||||||||||||||||||