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Cake day: June 14th, 2023

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  • not exactly because of pairs unless you’re talking about 1 and 0 being a pair… it’s because the maximum number you can count in binary doubles with each additional bit you add:

    with 1 bit, you can either have 0 or 1… which is, unsurprisingly perhaps, 0 and 1 respectively - 2 numbers

    with 2 bits you can have 00, 01, 10, 11… which is 0, 1, 2, 3 - 4 numbers

    with 3 bits you can have 000, 001, 010, 011, 100, 101, 110, 111… which is 0 to 7- 8 numbers

    so you see the pattern: add a bit, double the number you can count to… this is the “2 to the power of” that you might see: with 8 bits (a byte) you can count from 0 to 255 - that’s 2 (because binary has 2 possible states per digit) to the power of 8 (because 8 digits); 8^2

    the same is true of decimal, but instead of to the 2 to the power, it’s 10 to the power: with each additional digit, you can count 10 x as many numbers - 0-9 for 1 digit, 00-99 for 2 digits, 000-999 for 3 digits - 10^1, 10^2, 10^3 respectively

    and that’s the reason we use hexadecimal sometimes too! we group bits into groups of 8 and call it a byte… hexadecimal is base 16, so nicely lets us represent a byte with just 2 characters - 16^2 = 256 = 2^8




  • kinda the same reason people suggest something like linux mint over slackware, gentoo, arch, etc… mint is easy to install and is preconfigured to be an easy to use user desktop environment. you can configure any other option to be have like that, but they tend to be a bit more “DIY”, which is great if you know what you’re doing!

    dedicated NAS OSes will have good software out of the box that make it easy to configure and manage various common disk-related configurations (RAID, SMB, NFS, etc). you can certainly do all this yourself, but it might not have a pretty, unified user interface, or you might have to deal with software that isn’t compatible with some version of a library that’s in your distro of choice… all resolvable things, but they take time to solve: anywhere from installing a package manually to applying a kernel patch and recompiling the kernel to get something to work




  • a healthy democracy requires others to have privacy. people like investigative journalists need to be able to blend in with the crowd and expose government wrongdoing

    blending in the the crowd is the important part: if everyone cares about privacy, nobody sticks out for caring about privacy… but if nobody cares about privacy, the investigative journalist suddenly looks really obvious and can be targeted much more easily

    if someone doesn’t think they have anything to hide, that’s fine (wrong, but fine) however they can help to make sure the government acts appropriately simply by not splashing data around everywhere for all to see






  • afaik activitypub/fediverse doesn’t have to be fully open… there’s private messages and followers only profiles on mastodon… sure, any server admins of your followed would be able to see anything you post (and thus in this case for threads for example, if you accept any follower from threads then meta can see your stuff) but this also doesn’t grant them a license to use the content

    also, bluesky will eventually be the same: it only doesn’t have those issues now because they haven’t opened up their software… it’ll have federation in the future, which means it has to be somewhat programmatically open to others



  • i feel like i need to preface this comment with the fact that this is undeniably a bad thing and no amount of “but on the flip side” will change that, but it’s interesting to express regardless…

    this could lead to a few interesting situations:

    • more ubiquitous ML could lead to enforcement of laws more evenly… ML doesn’t make “oh sorry sir i didn’t know who you were” decisions, and if that’s coupled with transparency then maybe we will be left in less of a “laws for thee and not for me” situation as it becomes more difficult to break laws for people in power
    • more ubiquitous ML, as long as it’s fairly openly available, will absolutely be used by media to piece together complex structures and do investigative journalism. it could help to hold people to account
    • more ML in tax could mean less tax evasion? or setting it to task on suggesting fixes for tax loop holes if it can see a lot more invasive data?

  • i don’t agree with that definition of creative… there’s lots of engineering work that’s creative: writing code and designing systems can be a very creative process, but doesn’t involve feeling… it’s problem solving, and thats a creative process. you’re narrowly defining creativity as artistic expression of emotion, however there’s lots of ways to be creative

    now, i think thats a bit of a strawman (so i’ll elaborate on the broader point), but i think its important to define terms

    i agree we should be skeptical of marketing hype for sure: the type of creativity that i believe ML is currently capable of is directionless. it doesn’t understand what it’s creating… but the truth lies somewhere in the middle

    ML is definitively creating something new that didn’t exist before (in fact i’d say that its trouble with hallucinations of language are a good example of that: it certainly didn’t copy those characters/words from anywhere!)… this fits the easiest definition of creative: marked by the ability or power to create

    the far more difficult definition is: having the quality of something created rather than imitated

    the key here being “rather than imitated” which is a really hard thing to prove, even for humans! which is why our copyright laws basically say that if you have evidence that you created something first, you pretty much win: we don’t really try to decide whether something was created or imitated

    with things like transformative works or things that are similar, it’s a bit more of a grey area… but the argument isn’t about whether something is an imitation; rather it’s argued about how different the work is from the original


  • that’s a lack of understanding of concepts though, rather than a lack of creativity… curation requires that you understand the concept that you’re trying to curate: this looks more like a dog than this; this is a more attractive sunset than this

    current LLMs and ML don’t understand concepts, which is their main issue

    id argue that it kind of does “think about its own thoughts” to some degree: modern ML is layered, and each layer of the net feeds into the next… one layer of the net “thinks about” the “thoughts” of the previous layer. now, it doesn’t do this as a whole but neither do we: memories and neural connections are lossy; heck even creating a creative work isn’t going to turn out exactly like you thought it in your head (your muscle memory and skill level will effect the translation from brain to paper/canvas/screen)

    but even we hallucinate in the same way. don’t look at a bike, and then try and draw a bike… you’ll get general things like pedals, wheels, seat, handlebars, but it’ll be all connected wrong. this is a common example people use to show how our brains aren’t as precise and we might like to think… drawing a bike requires a lot of very specific things to be in very specific places and that’s not how our brain remembers the concept of “bike”