Trying to find it funny, but in 2026 it’s way too close to the bone and just makes me sad.
Had Sam Altman personally vocalized this article in full sincerity, I would not have been surprised.
Yeah. I first thought it’s about jpeg, then i read ai and i wasnt sure if its worrying stupidity reporting or bad satire. Edit: i thought '92 i mean
Yeah, like how they are destroying rare books.
I mean, you don’t get that back just by asking the content theft machine.
Amateur. I can compress entire seasons of a TV series to a few bytes. All I have to do is type its title in Netflix and then BAM, gigabytes of video come out.
Sure, but Netflix has a lot of cache misses for my favorite shows. I found a random website that has compressed matches for thousands more shows and movies than Netflix
I pirate my shit.
Back in the day we had this neat trick to do 100% compression on photos. Just print them out on pieces of paper, for completely byte-free storage!
brilliant satire that critiques all of magazine journalism.
i love going to [insert publication here] and reading another article about ‘so and so is ready for their next chapter in life.’ the so and so always an uninteresting, overly wealthy fuckwit that hasn’t accomplished anything other than going to college and having a wealthy parent.
I suppose they weren’t worth a 1000 words after all
Lossless -> lossy -> mindless.
-> mindy?
mindly?
Probably not very.
It’s basically just tricking the AI model to be your cloud storage provider.
I’ve read that the Trump administration is hiring him to archive all of the Epstein files using that format.
Compressing the Epstein files is easy: “Donald Trump raped children.” What’s my Weissman score?
Could have just stored those in PiFS https://github.com/philipl/pifs
That’s nice, albeit I want to point out for anyone wondering that this is only conjectured and not guaranteed:
One of the properties that π is conjectured to have is that it is normal, which is to say that its digits are all distributed evenly, with the implication that it is a disjunctive sequence, meaning that all possible finite sequences of digits will be present somewhere in it.
There is no guarantee for any specific sequence to appear in π, but for short chunks chances are better (it’s not really a probability, but it’s simpler to say and I can’t explain in details anyway). That’s because (from wiki):
It is widely believed that the (computable) numbers √2, π, and e are normal, but a proof remains elusive.
It’s pronounced “Piff Es” for anyone wondering
Idk if it’s irony, but the real pronounce is probably /paɪ ɛf-ɛs/ (english)
or /'pi fs/ in every other language that readsletters as they are writtennormally
It’s humorous, but last I checked, the best general-purpose compressors with the highest levels of compression—even lossless, which is probably not what most people think of when they think of neural nets—are neural net based.
Neural net-based compressors are computationally expensive, which is why we don’t normally use them for most day-to-day tasks, but they really can produce really small outputs.
I’m going to take the text of the US Constitution and stick it in a text file.
$ wget https://www.gutenberg.org/cache/epub/5/pg5.txt $ stat -c %s pg5.txt 48326Okay, so 48326 bytes.
Let’s do lzo. You’d expect a limited amount of compression — LZO is “fast” compression, usually only used where compression speed is really important, like where you want to be compressing stuff that’s going to be decompressed once and your bottleneck is throughput to disk:
$ lzop <pg5.txt >pg5.txt.lzo $ stat -c %s pg5.txt.lzo 24843Okay, how about gzip? That’s Deflate, an older, but pretty-widely-used general-purpose compression algorithm.
$ gzip <pg5.txt >pg5.txt.gz $ stat -c %s pg5.txt.gz 16660Okay, what about LZMA? That’s a newer, more-CPU-intensive thing that’s probably a good general-purpose choice that’ll generally give better compression ratios. It’s the kind of thing that I’d probably use in a lot of cases. (Personally, these days, I tend to use
pixz, which provides both indexed access for tarballs and parallel compression and decompression, which is important for modern processors.)$ xz <pg5.txt >pg5.txt.xz $ stat -c %s pg5.txt.xz 15488Okay, now PAQ, a neural-net-based compressor:
$ zpaq a pg5.txt.zpaq a pg5.txt -method 5 $ stat -c %s pg5.txt.zpaq 13063I did not know about PAQ actually, thats cool. :)
“Neutral net based” compression isn’t even in the same universe as “compressed to a prompt” via LLM
This is so sad, Chat GPT generate me an email responding to this article
The sad thing is that this has been possible for decades using convolutional autoencoders, but with LLMs we forgot that AI architectures other than transformers still exist.
Yeah, it’s really awful. With any luck, AI winter will follow AI summer, like usual, and the serious people can come out again. Although, aren’t CNNs more of a this century thing? I guess two decades is still decades…
IIRC autoencoders actually produce the same image to within our ability to notice, as well.
Lmfao “tears of joy”
Precisely! We human people all know that tears definitely do not express joy.
Correct?
On a similar note, I saw a story a bit back of someone saving input tokens by feeding the bot an image of a wall of text rather than the text itself and having it read the image via OCR.
Satire and reality are too hard too distinguish these days.
Saves input tokens and uses more output because of OCR, and output is priced way higher.
I mean, back in my days (👴) people sent a photo pasted into a word document, so things haven’t change that much…
They still do
This reminds me of IPoAC
