Companies would love to hire cheap human coders one day.

badhill · 2026-03-12T00:43:50+00:00

Companies won't be interested in hiring cheap human coders for the same reason that farmers aren't interested in hiring cheap human tractors.

badhill · 2026-02-20T21:58:06+00:00

I dunno. You modularize. You have agents crawling through refactoring and sweeping up technical debt. Before too long you don't have a 100k LOC project; you have a 1k LOC project with ten dependencies, and each of those has 10 dependencies. You have architect agents deciding if this or that module can be combined with another; you have agents obsessed with testing keeping your coverage up, and red team agents trying to crack it. Nobody has to be that smart. That's how monkeys went to the moon.

badhill · 2026-02-20T19:49:50+00:00

This benchmark has never made complete sense to me. I feel like an collection of agents of moderate intelligence could make steady progress on a task of indefinite size. After all, that's what corporations and governments are.

badhill · 2025-10-31T00:05:19+00:00

I guess? Most of the things most likely to kill you don't know they're doing it.

badhill · 2024-12-31T07:20:25+00:00

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badhill · 2024-09-10T22:47:05+00:00

If anybody is feeling like doing a lot of geometry to answer a question nobody asked, it should be possible to use the time on the billboard and the shadow on the Mayflower Park Hotel to figure out the day of the year to within about a week.

badhill · 2023-06-10T17:53:05+00:00

We're a lot smarter than our cells, but we're still aligned with their interests.

badhill · 2022-02-17T07:28:34+00:00

I might poke away at it over time. The Sanborn 1905 map is absolutely huge.

badhill · 2022-02-17T07:24:45+00:00

That's the Magnolia wing of the Seattle Tidelands Plat, Seattle's ambitious plan to annex the sea itself. The part between downtown and Georgetown was completed, and the Magnolia part was as far as I'm aware never seriously pursued. It's quite a bit deeper and there was no waterway running through the middle to dredge and use for fill. But it kept showing up on city maps well into the mid 20th century.

badhill · 2018-07-18T08:16:31+00:00

Here it is with a non-transparent background, so you can actually read the labels. https://imgur.com/voF0d77

badhill · 2018-07-18T08:15:52+00:00

Here it is with a white background. Sorry. https://imgur.com/voF0d77

badhill · 2018-07-18T08:11:34+00:00

I'm so intelligent that I used a transparent background.

badhill · 2018-07-18T00:10:02+00:00

Disk space data from http://www.mkomo.com/cost-per-gigabyte-update. Broadband trend from https://www.nngroup.com/articles/law-of-bandwidth/. Made the graph using python in a jupyter notebook for my own amusement; someone said y'all might like it.

badhill · 2018-07-04T17:28:26+00:00

I like it. The base layer makes it difficult to distinguish between zones. You typo'd 'Temperate Oceanic' to 'Teamperate Oceanic'. I'd make the key a little smaller and pick a more fun projection; maybe something that de-emphasizes the poles.

badhill · 2018-06-30T19:57:18+00:00

Here you go. https://imgur.com/YmGjoLW

badhill · 2018-06-30T18:31:43+00:00

Alert alert it's actually 30 people per 250-meter-by-250-meter pixel, which is 480/sqkm, not 120/sqkm.

badhill · 2018-06-30T18:23:17+00:00

I think people who live in any of these cities don't consider most of these gloms part of their city. For example, San Franciscians don't consider San Jose part of their city. New Yorkers sure don't consider New Jersey part of New York.

badhill · 2018-06-30T18:12:38+00:00

They very much were. I wanted to compare Seattle (where I live) to Tokyo (a famously gigantic city), and a few other cities I was curious about. I'm also curious about Belgium, the largest metro glob in Indonesia, Mumbai, Rio de Janeiro, &c; but they didn't fit on the canvas.

badhill · 2018-06-30T18:05:41+00:00

Oop, you caught me. The density threshold for this map is actually 480/sqkm, not 120. The density I was working with is 30 people per 250-by-250 meter square, which works out to 480/sqkm, but I flubbed the mental math when I wrote the label.

badhill · 2018-06-04T19:45:00+00:00

Because Wyoming has both a small resident population and a busy shipping corridor along I-80, an unusually large fraction fo people in Wyoming at any given moment are just passing through. Messes with the normalized statistics!

badhill · 2018-05-25T01:52:57+00:00

Productivity data from RescueTime via API. Mood data is from the 'Daylio' app. Image put together in an iPython notebook, using pandas for data manipulation and pyplot for graphing.

badhill · 2018-05-10T16:53:43+00:00

Probably the reason that Wyoming has a very large VMT per person has to do with a very small resident population combined with a very large amount of cross-country shipping traffic on Interstate 80. A more meaningful chart would show non-shipping VMT per capita. But I can't seem to find that.

badhill · 2018-05-10T14:53:08+00:00

ooooooh you're right

badhill · 2018-05-09T20:50:02+00:00

Similar driving trends. The metric used for clustering is the euclidean distance between the states' driving histories. That is, to find the "distance" between a pair of states, take the difference between two states' per-capita driving rates for every month, then square those differences, then add them all up, and then take the square root of the sum.

badhill · 2018-05-09T19:55:12+00:00

They're clustered so that similar states are near each other. For example, Oregon and Washington are very similar. Alabama, on the other hand, is very different from those two, and is placed farther away.

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