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Cake day: November 19th, 2023

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  • That estimate is based on assuming that the ratio of matter to light output is the same between galaxies 10 billion years apart in age. The high light output of these young galaxies could also be supermassive stars that burn out very quickly, larger stars typically forming faster than smaller stars, or many other things.

    Blindly assuming a linear relationship between two things, then extrapolating is how you get the Windows loading bar circa 2000.

    Separately, but just as big a potential issue, the data itself may be incorrect. Previous galaxies measured at extreme redshift values were remeasured, and found to have less extreme values. This can be as simple as there aren’t that many photons from these galaxies reaching us, so a short measurement period might not be enough to get an accurate picture.





  • I’ve known a lot of math people, and /on average/ I think they’re more capable of programming useful code than the other college graduate groups I’ve spent a lot of time working with (psychology, economics, physics) /on average/.

    That said, the best mathematicians I’ve known were mostly rubbish at real programming, and the best programmers I’ve known have come out of computer engineering or computer science.

    If you need a correct, but otherwise useless implementation, a mathematician is a pretty good bet. If you need performance, readability, documentation, I’d look elsewhere most of the time.


  • I don’t think anyone will actually make it, but it would be cool to have an arrangement of accelerometers and microphones that you can put on the side of a packaged gift, shake it, and get a guess about what it is.

    A harvesting robot that can tell how many days from ripe an avocado is, so the grocery store can have like… “ripe today” avocados, “ripe tomorrow” avocados, “ripe in 2 days” avocados. They’d come in small cardboard boxes, and they could just shift the boxes or signs over by one each day, and have more boxes if they get avocado deliveries less often.

    Machine learning clothing/hairstyle/general fashion advice would be neat, but probably too open to manipulation to sell certain brands to be practical.

    Tools to help developers put houses at the best spot on a lot, for things like water mitigation, tree safety, garden space in good sunlight, wind noise, and privacy.

    Search tools that aren’t terrible on shopping sites, and news sites, and research journals and things. The days of “we asked Google to do it for us” being good enough are long over.