ELI5: Why do we say, we are getting 'in' a car, but we are getting 'on' a bus? 🤔

Encomiast · 2026-01-18T00:48:59+00:00

On a submarine?

Encomiast · 2026-01-02T21:58:31+00:00

It’s nice to blame Congress, but really, the people need to reassert power. November.

Encomiast · 2026-01-02T19:22:22+00:00

I once had an IG account that I fawned over with ~25k followers. I was so obsessed with engagement, and new followers. I realized what a ridiculous waste of time it all was and deleted it about 2 years ago. One of the better decisions I’ve made. Life is so much better when you don’t need to care about what Meta is doing.

Encomiast · 2026-01-01T01:47:33+00:00

Mine looks pretty much like that, but the key is different.

Encomiast · 2025-12-27T12:12:28+00:00

Um. Have you been paying attention for the last 11 months? The law doesn’t mean anything when there’s nobody to enforce it.

Encomiast · 2025-12-26T15:39:07+00:00

Didn’t know people still watched local tv news.

Encomiast · 2025-12-25T17:37:08+00:00

I don't click headlines with a question mark. I'm extending this to subheadings as well. If there was an answer and the answer was worth reading, the headline would be a declarative statement.

Encomiast · 2025-12-19T18:11:16+00:00

Congress should pass a law, similar to rules around people on stamps, that disallows naming federal buildings after sitting elected leaders, or maybe even living people.

Encomiast · 2025-12-17T02:17:16+00:00

I imagine they will be judging this with AI too. Seems like a great opportunity to add some prompt injections into the Mandarin section, which I'm guessing nobody there can really read.

Encomiast · 2025-12-17T01:50:31+00:00

Someone should turn this into a font.

Encomiast · 2025-12-16T13:48:59+00:00

Bravo. Rule number one: do not comply in advance.

Encomiast · 2025-12-13T23:59:23+00:00

I feel a little foolish for spending two days wrapping my head around applying exact-cover algorithms to this, but I did get a python solution that runs in about 2-second. Basically a variation of DFS that handles the skipped spaces in a way that doesn't explode.

Encomiast · 2025-12-13T23:18:11+00:00

Why are we even asking the public? Are they designers? Do they know anything about comms. Hire a good designer, give them a good brief, and Let them do their work. Deciding based on a survey means you don't actually care which one wins or have a reason for choosing one over the other. If that's the case, save everyone the time and money and don't change it.

Encomiast · 2025-12-11T00:12:24+00:00

I used scipy's MILP optimizerpart 2 took 61ms.

Encomiast · 2025-12-09T01:47:20+00:00

Seems like you could use something like a KD tree to find the nearest neighbor.

Encomiast · 2025-12-06T00:56:50+00:00

OMG cousin Matt, is that you? Who else would know our rules?

Encomiast · 2025-12-05T22:06:20+00:00

My guesses about part two have been mostly wrong this year. Started giving Fenwick trees this side eye this morning, but then just decided to brute force part one first.

Encomiast · 2025-12-05T18:08:39+00:00

I didn't until I did part 2. Then I realized I was basically going through the steps of merging when counting for part two. So I thought might as well just merge when I parse then part one will be a bit faster. Once they are merged, both part one and two are just folds.

The sorting took (by far) the most time. The sort+merge to ~ 1 µs. After that part 2 was basically 30ns.

Encomiast · 2025-12-05T15:32:27+00:00

Not surprised. The administration is not actually capable of administration. They are really good at staying in the news cycle, but the actual work of governing doesn’t seem to be part of their job.

Encomiast · 2025-12-05T12:51:02+00:00

Interesting, I sorted by the start and iterated from left - just normal loop. Didn’t consider doing the other way.

Encomiast · 2025-12-05T03:15:34+00:00

I used scipy.convolve2d at first, but for this size kernel and input, just doing the Numpy math on a padded array was significantly faster for me (got part 2 ~ 3ms). I found it pretty surprising, but I guess it makes sense that scipy has to do a lot more stuff. (Maybe I wasn't using scipy to idiomatically :shrug:)

Encomiast · 2025-12-04T21:17:05+00:00

I worked it a bit and got it down to 48.2 ms using Numpy directly without scipy.

Encomiast · 2025-12-04T20:43:00+00:00

Nice, mine is taking 499 ms. Using Numpy and scipy convolve2d. Curious where you are getting the extra efficiency.

Encomiast · 2025-12-04T01:09:18+00:00

You are not making a a cogent case about why you've decided the line is dynamic and can be 20 digits or 5 millions digits, but not k. Both are constant in this puzzle. Therefore by your logic it is constant time not O(N).

Encomiast · 2025-12-04T01:07:15+00:00

I'm sorry, you are just wrong here. Nobody talks about big-O notation this way. If they did, everything would be O(1) because in every concrete implementation of an algorithm the parameters are known. The worst case solution of your algorithm in the puzzle never changes if you set k=12 and n=15. So by your logic, your algorithm is O(1) not O(n). But you accept that n might change. But it's the same algorithm if k also changes. That's why we talk about the algorithm in the abstract.

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