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Cake day: September 27th, 2023

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  • Mirodir@discuss.tchncs.detoProgrammer Humor@programming.devSus
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    5 days ago

    Sure. You have to solve it from inside out:

    • not()…See comment below for this one, I was tricked is a base function that negates what’s inside (turning True to False and vice versa) giving it no parameter returns “True” (because no parameter counts as False)
    • str(x) turns x into a string, in this case it turns the boolean True into the text string ‘True’
    • min(x) returns the minimal element of an iterable. In this case the character ‘T’ because capital letters come before non-capital letters, otherwise it would return ‘e’ (I’m not entirely sure if it uses unicode, ascii or something else to compare characters, but usually capitals have a lower value than non-capitals and otherwise in alphabetical order ascending)
    • ord(x) returns the unicode number of x, in this case turning ‘T’ into the integer 84
    • range(x) creates an iterable from 0 to x (non-inclusive), in this case you can think of it as the list [0, 1, 2, …82, 83] (it’s technically an object of type range but details…)
    • sum(x) sums up all elements of a list, summing all numbers between 0 and 84 (non-inclusive) is 3486
    • chr(x) is the inverse of ord(x) and returns the character at position x, which, you guessed it, is ‘ඞ’ at position 3486.

    The huge coincidental part is that ඞ lies at a position that can be reached by a cumulative sum of integers between 0 and a given integer. From there on it’s only a question of finding a way to feed that integer into chr(sum(range(x)))



  • after leaving can’t join another for a year

    Can you fix this? There was enough misinformation floating around about this already when this feature went into beta.

    Adults can leave a family at any time, however, they will need to wait 1 year from when they joined the previous family to create or join a new family.

    it should say something like: “After joining, can’t join another for a year”




  • I’d argue that with their definition of bots as “a software application that runs automated tasks over the internet” and later their definition of download bots as “Download bots are automated programs that can be used to automatically download software or mobile apps.”, automated software updates could absolutely be counted as bot activity by them.

    Of course, if they count it as such, the traffic generated that way would fall into the 17.3% “good bot” traffic and not in the 30.2% “bad bot” traffic.

    Looking at their report, without digging too deep into it, I also find it concerning that they seem to use “internet traffic” and “website traffic” interchangeably.


  • Without knowing any specifics of the TOS or the exact setup beyond what I could gather in this thread: generally speaking they could still send you a bill through email or otherwise.

    After that, if you’re not paying up, they might be able to successfully get the money out of you through court regardless, depending on a few factors. What’s more likely for smaller sums is that they’ll just drop it and ban you though.

    IANAL of course.


  • I think the humor is meant to be in the juxtaposition between “reference” in media contexts (e.g. “I am your father”) and “reference” in programming contexts and applying the latter context to the former one.

    What does “I’m your father” mean if the movie is jaws?

    I think the absurdity of that question is part of said humor. That being said, I didn’t find it funny either.


  • It’s not as accurate as you’d like it to be. Some issues are:

    • It’s quite lossy.
    • It’ll do better on images containing common objects vs rare or even novel objects.
    • You won’t know how much the result deviates from the original if all you’re given is the prompt/conditioning vector and what model to use it on.
    • You cannot easily “compress” new images, instead you would have to either finetune the model (at which point you’d also mess with everyone else’s decompression) or do an adversarial attack onto the model with another model to find the prompt/conditioning vector most likely to create something as close as possible to the original image you have.
    • It’s rather slow.

    Also it’s not all that novel. People have been doing this with (variational) autoencoders (another class of generative model). This also doesn’t have the flaw that you have no easy way to compress new images since an autoencoder is a trained encoder/decoder pair. It’s also quite a bit faster than diffusion models when it comes to decoding, but often with a greater decrease in quality.

    Most widespread diffusion models even use an autoencoder adjacent architecture to “compress” the input. The actual diffusion model then works in that “compressed data space” called latent space. The generated images are then decompressed before shown to users. Last time I checked, iirc, that compression rate was at around 1/4 to 1/8, but it’s been a while, so don’t quote me on this number.

    edit: fixed some ambiguous wordings.




  • I think it’s much more likely whatever scraping they used to get the training data snatched a screenshot of the movie some random internet user posted somewhere. (To confirm, I typed “joaquin phoenix joker” into Google and this very image was very high up in the image results) And of course not only this one but many many more too.

    Now I’m not saying scraping copyrighted material is morally right either, but I’d doubt they’d just feed an entire movie frame by frame (or randomly spaced screenshots from throughout a movie), especially because it would make generating good labels for each frame very difficult.



  • no where near Reddit yet on niche subjects

    I’m always saddened by how not-active some of those subjects are. For example: Even many large games struggle to have dedicated, active communities on Lemmy (assuming I’m not terrible at finding them, which is sadly also possible). Even some of the largest games have only completely dead communities here. A huge draw of Reddit for me was to be able to talk about the games I play with other people who do too. And mostly, the games I’d love to talk about aren’t in the top 10 most played games list.

    Now I could try to (re)vitalize those communities I would love to see around, and I have done so shortly after the exodus (on my previous account that died with the instance it was on). However, there’s only so much talking into the void I can do until it gets boring.

    I also feel like that might be a big issue for people coming over. After I manage to explain to my friends how federation works, they ask me to help them find the [topic of their interest] community, and all I can show them is a community with 10 threads, all over 3 months old and with 0 comments. Sadly it shouldn’t surprise anyone they’re not sticking around after that.



  • This exact image (without the caption-header of course) was on one of the slides for one of the machine-learning related courses at my college, so I assume it’s definitely out there somewhere and also was likely part of the training sets used by OpenAI. Also, the image in those slides has a different watermark at the bottom left, so it’s fair to assume it’s made its rounds.

    Contradictory to this post, it was used as an example for a problem that machine learning can solve far better than any algorithms humans would come up with.