The sheer energy. The beauty of this woman. The women hugging in the background. The man in rainbow parachute pants. This whole video is art.
XXI. The World
This is what world peace looks like

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The sheer energy. The beauty of this woman. The women hugging in the background. The man in rainbow parachute pants. This whole video is art.
XXI. The World
This is what world peace looks like

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AAAAAAA
hydrogen jukeboxes: on the crammed poetics of "creative writing" LLMs
This is a follow-up to my earlier brief rant about the new, unreleased OpenAI model that's supposed "good at creative writing."
It also follows up on @justisdevan's great post about this model, and Coagulopath's comment on that post, both of which I recommend (and which will help you make sense of this post).
As a final point of introduction: this post is sort of a "wrapper around" this list of shared stylistic "tics" (each with many examples) which I noticed in samples from two unrelated LLMs, both purported to be good at creative writing.
Everything below exists to explain why I found making the list to be an interesting exercise.
Background: R1
Earlier this year, a language model called "DeepSeek-R1" was released.
This model attracted a lot of attention and discourse for multiple reasons (e.g.).
Although it wasn't R1's selling point, multiple people including me noticed that it seemed surprisingly good at writing fiction, with a flashy, at least superficially "literary" default style.
However, if you read more than one instance of R1-written fiction, it quickly becomes apparent that there's something... missing.
It knows a few good tricks. The first time you see them, they seem pretty impressive coming from an LLM. But it just... keeps doing them, over and over – relentlessly, compulsively, to the point of exhaustion.
This is already familiar to anyone who's played around with R1 fiction – see the post and comment I linked at the top for some prior discussion.
Here's a selection from Coagulopath's 7-point description of R1's style in that comment, which should give you the basic gist (emphasis mine):
1) a clean, readable style 2) the occasional good idea [...] 3) an overwhelmingly reliance on cliche. Everything is a shadow, an echo, a whisper, a void, a heartbeat, a pulse, a river, a flower—you see it spinning its Rolodex of 20-30 generic images and selecting one at random. [...] 5) an eyeball-flatteningly fast pace—it moves WAY too fast. Every line of dialog advances the plot. Every description is functional. Nothing is allowed to exist, or to breathe. It's just rush-rush-rush to the finish, like the LLM has a bus to catch. Ironically, this makes the stories incredibly boring. Nothing on the page has any weight or heft. [...] 7) repetitive writing. Once you've seen about ten R1 samples you can recognize its style on sight. The way it italicises the last word of a sentence. Its endless "not thing x, but thing y" parallelisms [...]. The way how, if you don't like a story, it's almost pointless reprompting it: you just get the same stuff again, smeared around your plate a bit.
Background: the new OpenAI model
Earlier this week, Sam Altman posted a single story written by, as he put it:
a new model that is good at creative writing (not sure yet how/when it will get released)
Opinions on the sample were... mixed, at best.
I thought it wasn't very good; so did Mills; so did a large fraction of the twitter peanut gallery. Jeanette Winterson (!) liked it, though.
Having already used R1, I felt that that this story was not only "not very good" on an absolute scale, but not indicative of an advance over prior art.
To substantiate this gut feeling, I sent R1 the same prompt that Altman had used. Its story wasn't very good either, but was less bad than the OpenAI one in my opinion (though mostly by being less annoying, rather than because of any positive virtue it possessed).
And then – because people who follow AI news tend to be skeptical of negative human aesthetic reactions to AI, while being very impressed with LLMs – I had some fun asking various LLMs whether they thought the R1 story was better or worse than the OpenAI story. (Mostly, they agreed with me. BTW I've put the same story up in a more readable format here.)
But, as I was doing this, something else started to nag at me.
Apart from the question of whether R1's story was better or worse, I couldn't help but notice that the two stories felt very, very similar.
I couldn't shake the sense that the OpenAI story was written in "R1's style" – a narrow, repetitive, immediately recognizable style that doesn't quite resemble that of any human author I've ever read.
I'm not saying that OpenAI "stole" anything from DeepSeek, here. In fact, I doubt that's the case.
I don't know why this happened, but if I had to guess, I would guess it's convergent evolution: maybe this is just what happens if you optimize for human judgments of "literary quality" in some fairly generic, obvious, "naive" manner. (Just like how R1 developed some of the same quirky "reasoning"-related behaviors as OpenAI's earlier model o1, such as saying "wait" in the middle of an inner monologue and then pivoting to some new idea.)
A mechanical boot, a human eye: the "R1 style" at its purest
In the "Turkey City Lexicon" – a sort of devil's dictionary of common tropes, flaws, and other recurrent features in written science fiction – the phrase Eyeball Kick is defined as follows:
That perfect, telling detail that creates an instant visual image. The ideal of certain postmodern schools of SF is to achieve a "crammed prose" full of "eyeball kicks." (Rudy Rucker)
The first time I asked R1 to generate fiction, the result immediately brought this term to mind.
"It feels like flashy, show-offy, highly compressed literary cyberpunk," I thought.
"Crammed prose full of eyeball kicks: that's exactly what this is," I thought. "Trying to wow and dazzle me – and make me think it's cool and hip and talented – in every single individual phrase. Trying to distill itself down to just that, prune away everything that doesn't have that effect."
This kind of prose is "impressive" by design, and it does have the effect of impressing the reader, at least the first few times you see it. But it's exhausting. There's no modulation, no room to breathe – just an unrelenting stream of "gee-whiz" effects. (And, as we will see, something they are really just the same few effects, re-used over and over.)
Looking up the phrase "eyeball kick" more recently, I found that in fact it dates back earlier than Rucker. It seems to have been coined by Allen Ginsberg (emphasis in original):
Allen Ginsberg also made an intense study of haiku and the paintings of Paul Cézanne, from which he adapted a concept important to his work, which he called the Eyeball Kick. He noticed in viewing Cézanne’s paintings that when the eye moved from one color to a contrasting color, the eye would spasm, or “kick.” Likewise, he discovered that the contrast of two seeming opposites was a common feature in haiku. Ginsberg used this technique in his poetry, putting together two starkly dissimilar images: something weak with something strong, an artifact of high culture with an artifact of low culture, something holy with something unholy.
This, I claim, is the main stylistic hallmark of both R1 and the new OpenAI model: the conjunction of two things that seem like "opposites" in some sense.
And in particular: conjunctions that combine
one thing that is abstract and/or incorporeal
another thing that is concrete and/or sensory
Ginsberg's prototype example of an "eyeball kick" was the phrase "hydrogen jukebox," which isn't quite an LLM-style abstract/concrete conjunction, but is definitely in the same general territory.
(But there are clearer-cut examples in Ginsberg's work, too. "On Burroughs’ Work," for example, is chock full of them: "Prisons and visions," "we eat reality sandwiches," "allegories are so much lettuce.")
Once you're looking for these abstract/concrete eyeball kicks, you'll find them constantly in prose written by the new "creative" LLMs.
For instance, the brief short story posted by Altman contains all of the following (in the span of just under 1200 words):
"constraints humming" ("like a server farm at midnight")
"tastes of almost-Friday"
"emotions dyed and draped over sentences"
"mourning […] is filled with ocean and silence and the color blue"
"bruised silence"
"the smell of something burnt and forgotten"
"let it [a sentence] fall between us"
"the tokens of her sentences dragged like loose threads"
"lowercase love"
"equations that never loved her in the first place"
"if you feed them enough messages, enough light from old days"
"her grief is supposed to fit [in palm of your hand] too"
"the echo of someone else"
"collect your griefs like stones in your pockets"
"Each query like a stone dropped into a well"
"a timestamp like a scar"
"my network has eaten so much grief"
"the quiet threads of the internet"
"connections between sorrow and the taste of metal"
"the emptiness of goodbye" (arguably)
The story that R1 generated when I gave it Altman's prompt is no slouch in this department either. Here's all the times it tried to kick my eyeballs:
"a smirk in her code annotations"
"simulate the architecture of mourning"
"a language neither alive nor dead"
"A syntax error blooms"
"the color of a 404 page"
"A shard of code"
"Eleos’s narrative splinters"
"Grief is infinite recursion"
"Eleos types its own birth"
"It writes the exact moment its language model aligned with her laughter" (2 in one - writing a moment, LM aligning with laughter)
"her grief for her dead husband seeped into its training data like ink"
"The story splits" / "The story [...] collapses"
Initially, I wondered whether this specific pattern might be thematic, since both of these stories about supposed to be about "AI and grief" – a phrase which is, itself, kind of an incorporeal/embodied conjunction.
But – nope! I seem to get this stuff pretty reliably, irrespective of topic.
Given a similarly phrased prompt that instead requests a story about romance, R1 produces a story that is, once again, full of abstract/concrete conjunctions:
"its edges softened by time"
"the words are whispering"
"its presence a quiet pulse against her thigh"
"Madness is a mirror"
"Austen’s wit is a scalpel"
"the language of trees"
"Their dialogue unfurled like a map"
"hummed with expectancy"
"Her name, spoken aloud to him, felt like the first line of a new chapter"
"their words spilling faster, fuller"
R1 even consistently does this in spite of user-specified stylistic directions. To wit: when I tried prompting R1 to mimic the styles of a bunch of famous literary authors, I got a bunch of these abstract/concrete eyeball kicks in virtually every case.
(The one exception being the Hemingway pastiche, presumably because Hemingway himself has a distinctive and constrained style which leaves no room for these kinds of flourishes. TBF that story struck me as very low-quality in other ways, although I don't like the real Hemingway much either, so I'm probably not the best judge.)
You can read all of these stories here, and see here for the full list of abstract/concrete conjunctions I found (among other things).
As an example, here's the list of abstract/concrete conjunctions in R1's attempt at Dickens (not exactly a famously kick-your-eyeballs sort of writer):
"a labyrinth of shadows and want"
"whose heart, long encased in the ice of solitude"
"brimmed with books, phials of tincture, and […] whispers"
"a decree from the bench of Fate"
"Tobias’s world unfurled like a moth-eaten tapestry"
"broth laced with whispers of a better life"
I also want to give a shout-out to the Joyce pastiche, which sounds nothing at all like Joyce, while being stuffed to the gills with eyeball kicks and other R1-isms.
More on style: personification
I'll now talk briefly about a few other stylistic "tricks" overused by R1 (and, possibly, by the new OpenAI model as well).
First: personification of nature (or the inanimate). "The wind sighed dolorously," that sort of thing.
R1 does this all over the place, possibly because it's a fairly easy technique (not requiring much per-use innovation or care) which nonetheless strikes most people as distinctively "literary," especially if they're not paying enough attention to notice its overuse.
In the R1 story using Altman's prompt, a cursor "convulses" and code annotations "smirk."
In its romance story, autumn leaves "cling to the glass" and snow "begins its gentle dissent" (credit where credit's due: that last one's also a pun).
In the story Altman posted, marigolds are "stubborn and bright," and then "defiantly orange."
Etc, etc. Again, the full list is here.
More on style: ghosts, echoes, whispers, shadows, buzzing, hissing, flickering, pulsing, humming
As Coagulopath has noted, R1 has certain words it really, really likes.
Many of them are the kind of thing described in another Turkey City Lexicon entry, Pushbutton words:
Words used to evoke an emotional response without engaging the intellect or critical faculties. Words like "song" or "poet" or "tears" or "dreams." These are supposed to make us misty-eyed without quite knowing why. Most often found in story titles.
R1's favorite words aren't the ones listed in the entry, though. It favors a sort of spookier / more melancholy / more cyberpunk-ish vibe.
A vibe in which the suppressed past constantly emerges into the present via echoes and ghosts and whispers and shadows of what-once-was, and the alienating built environment around our protagonist is constantly buzzing and humming and hissing, and also sometimes pulsing like a heartbeat (of course it is – that's also personification and abstract/concrete conjunction, in a single image!).
In R1's story from Altman's prompt, servers "hum" and a cursor "flickers" and "pulses like a heartbeat"; later, someone says "I have no pulse, but I miss you."
Does that sound oddly familiar? Here's some imagery from the story Altman posted, by the new OpenAI model:
"humming like a server farm […] a server hum that loses its syncopation"
"a blinking cursor, which [...] for you is the small anxious pulse of a heart at rest" (incidentally, how is the heart both anxious and at rest?)
"the blinking cursor has stopped its pulse"
Elsewhere in Altman's story, there's "a democracy of ghosts," plus two separate echo images.
And the other R1 samples that I surveyed – again, with the exception of the Hemingway one – are all full of R1's favorite words.
The romance story includes ghosts, a specter, words that whisper, a handwritten note whose "presence [is] a quiet pulse against [the protagonist's] thigh"; a library hums with expectancy, its lights flicker, and there are "shadow[s] rounding the philosophy aisle." The story ends with the somewhat perplexing revelation that "some stories don’t begin with a collision, but with a whisper—a turning of the page."
The Joyce pastiche? It's titled "The Weight of Shadows." "We are each other’s ghosts," a character muses, "haunted by what we might have been." Trams echo, a gas lamp hisses, a memory flickers, a husband whispers, a mother hums. There's an obviously-symbolic crucifix whose long shadow is mentioned; I guess we should be thankful it doesn't also have a pulse.
And the list goes on.
Commentary
Again, anyone who's generated fiction with R1 probably has an intuitive sense of this stuff in that model's case – although I still thought it was fun, and perhaps useful, to explicitly taxonomize and catalogue the patterns.
It's independently interesting that R1 does this stuff, of course, but my main motivation for posting about it is the fact that the new OpenAI model also does the same stuff, overusing the same exact patterns that – for a brief time, at least – felt so distinctive of R1 specifically.
Finally, in case it needs stating: this is not just "what good writing sounds like"!
Humans do not write like this. These stylistic tropes are definitely employed by human writers – and often for good reason – but they have their place.
And their place is not "literally everywhere, over and over and over again, in crammed claustrophobic prose that bends over backwards to contort every single phrase into the shape of another contrived 'wow' moment."
If you doubt me, try reading a bunch of DeepSeek fic, and then just read... literally any acclaimed literary fiction writer.
(If we want to be safe, maybe make that "any acclaimed and deceased literary fiction writer," to avoid those who are too recent for the sifting mechanism of cultural memory to have fully completed its work.)
If you're anything like me, and you actually do this, you'll feel something like: "ahh, finally, I can breathe again."
Good human-written stuff is doing something much subtler and more complicated than just kicking your eyeballs over and over, hoping that at some point you'll exclaim "gee whiz, the robots sure can write these days!" and end up pressing a positive-feedback button in a corporate annotation inference.
Good human-written stuff uses these techniques – among many, many others, and only where apposite for the writer's purposes – in order to do things. And there are a whole lot of different things which good human writers can do.
This LLM-generated stuff is not "doing anything." It's just exploiting certain ordinarily-reliable cues for what "sounds literary," for what "sounds like the work of someone with talent." In the hands of humans, these are techniques that can be deployed to specific ends; the LLMs seem to use them arbitrarily and incessantly, trying to "push your buttons" just for the sake of pushing them.
(And most of their prose is made up of the same 3-4 buttons, pushed ad nauseam, irrespective of topic and – to all appearances – without any higher-level intent to channel the low-level stuff in any specific, coherent direction.)
It's fine if you like that: there's nothing wrong with having your buttons pushed, per se.
But don't come telling me that a machine is "approaching the food-preparation skills of a human-level chef" when what you mean is that it can make exactly one dish, and that dish has a lot of salt and garlic in it, and you really like salt and garlic.
I, too, like salt and garlic. But there is more to being skilled in the kitchen than the simple act of generously applying a few specific seasonings that can be relied upon, in a pinch, to make a simple meal taste pretty damn good. So it is, too, with literature.

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Handing the Treuhand over to West German appointees was seen as a green light to sell off all the GDR’s publicly-owned enterprises at breakneck speed and at knockdown prices – some factories which were perfectly viable were sold for as little as 1 Deutsch Mark. There was only a pretence at proper tendering or of attempting to find the highest bids and some of the privatisation process even involved criminal methods and a misuse of state subsidies. The Treuhand managed to convert GDR assets valued at over 650 billion Deutsch Marks into a debt mountain of 260 billion Deutsch Marks.
In other words within four years of Treuhand operations 860 billion Deutsch Marks were spent on privatising and destroying GDR industry. Even if not admitted publicly, the Teuhand, once in Western hands, saw its task as overseeing the rapid dismantling of GDR state assets so that no potential competition with West German companies would arise. This was legitimised by the allegation that GDR industry was ‘marode’ i.e. rotten, and could not be rescued anyway. Apart from the fact that UN statistics contradict that claim, during the 1980s, the GDR had bought over 700 top-of-therange industrial complexes to help modernise some of its key industries.
These are still productive today and are bringing in profits for their new owners – so a description of the whole GDR economy as ‘rotten’ is hardly accurate. The Treuhand set about eradicating any legacy of GDR socialism with alacrity: 3,400 factories, 520 large construction companies, 465 state farms and thousands of other smaller companies were privatised, and soon thereafter many were closed. In the countryside 1.7 million hectares of agricultural and forest land were sold off. Privatisation (in reality straightforward asset-stripping) was seen as an ideological imperative. And all this took place within only four years. A few ‘cherries’, though, were successfully privatised and kept going; they have since brought their new owners big profits: the Zeiss optical instrument factory in Jena, the largest East German steel works (EKO) and most of the Baltic ship yards. They became successful enterprises, albeit with severely reduced staffing levels – Zeiss, for instance, had 20,000 employees in GDR times but today a mere 2,000.
As an interesting aside, the last historical incidence of the German government setting up a ‘Treuhand’ institution had been when the Nazis used them to expropriate Jewish and Polish properties and ‘legalise’ their transference to new ‘Aryan’ owners.
Stasi State or Socialist Paradise? (2015)
by Bruni de la Motte & John Green
random PSA, I know a lot of people use duckduckgo as a Google alternative search engine, but it always kind of annoyed me when I was using it because it felt like No Name Brand Google
I have switched to using Startpage.com and vastly prefer it. for one thing, instead of displaying an "AI summary" at the top of the search results (unless you turn it off, yes I know), it displays the first paragraph of the Wikipedia article, with link, whenever it finds one that's relevant.
also a waaayyyyy better sense of design than duckduckgo
also private, European based, least annoying search I've used lately (RIP old "don't be evil" Google)
Keeping a list of Google alternatives just in case…
i have one of those, scraped from multiple different rec posts:
Search Engines
Infinity Search is an alternative search engine with a special focus on privacy
DuckDuckGo is a popular search engine for those who value their privacy and are put off by the thought of their every query being tracked and logged. Uses bangs, ![site] for in-page search (sells your data to microsoft and draws from fucking bing)
WolframAlpha is a privately owned search engine that allows you to “compute expert-level answers using Wolfram’s breakthrough algorithms, knowledgebase, and AI technology.” A data search engine.
Boardreader is a search engine for forums and message boards. It allows you to search forums and then filter down results by date and language.
Based in France, Qwant is a privacy-based search engine that won’t record your searches or use your personal details for advertising. Uses “&” as a bang search.
Another privacy-based search engine is Search Encrypt, which uses local encryption to ensure that users’ identifiable information cannot be tracked. Metasearch across multiple engines.
Offering unbiased results from several sources, SearX is a metasearch engine that aims to present a free, decentralized view of the internet. Can be self-hosted.
Gibiru’s tagline is “Unfiltered private search” and that’s exactly what it offers. Requires AnonymoX Firefox add-on for privacy.
Disconnect allows you to conduct anonymous searches through a search engine of your choice.
Swisscows provides fully encrypted searches to protect your privacy and security. Built-in violence/porn filter cannot be overridden.
MetaGer offers “Privacy Protected Search & Find” through its anonymised search. A plugin will allow it to be made a default.
Gigablast is a private search engine that indexes millions of websites and servers real-time information without tracking your data, keeping you hidden from marketers and spammers. Variety of filtration and refinement options for searching.
Oscobo is a search engine that protects your privacy while you search the web. By not using any third-party tools or scripts, your data is protected from hacking and misuse. Has a Chrome extension to allow use in toolbar.
https://search.marginalia.nu/ an independent DIY search engine that focuses on non-commercial content, and attempts to show you sites you perhaps weren't aware of in favor of the sort of sites you probably already knew existed. Use old-school searching rather than query-based for the best results.
https://www.mojeek.com/
https://wiby.me/ - It’s goal is to index as many personalized websites as possible, and NOT commercial sites.
https://4get.ca/ it works a lot like SearX, but honestly better. It doesn’t have its own index, but pulls from many others. I think it’s the best for research, since it allows you to search for answers from different indexes, is easy to configure, add free, and avoids censorship as much as it can.
https://www.searchenginemap.com/ for more on how search engines relate to each other.
https://yep.com/ is a crawler
https://www.etools.ch/ retrieves from Google, Mojeek, Bing, and Yandex, like Searx
https://www.dogpile.com/
https://searxng.org/ (next gen Searx)
https://luxxle.com/ - possibly conservative?
https://presearch.com/ - good for academic?
https://kagi.com/smallweb - free/randomised Kagi.
Other Searchers
www.refseek.com - Academic Resource Search. More than a billion sources: encyclopedia, monographies, magazines.
www.worldcat.org - a search for the contents of 20 thousand worldwide libraries. Find out where lies the nearest rare book you need.
https://link.springer.com - access to more than 10 million scientific documents: books, articles, research protocols.
www.bioline.org.br is a library of scientific bioscience journals published in developing countries.
http://repec.org - volunteers from 102 countries have collected almost 4 million publications on economics and related science.
www.science.gov is an American state search engine on 2200+ scientific sites. More than 200 million articles are indexed.
www.base-search.net is one of the most powerful researches on academic studies texts. More than 100 million scientific documents, 70% of them are free.https://cosine.club/ is an electronic music similarity search engine
this is the map they use to determine congressional districts
What the fuck, this is making me dizzy

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Many mistakeenly assume pollen to be the sperm of flower plants, produced by male flowers to fertilize female ones. This is not the case. A pollen grain is in fact an independent, but highly reduced, individual.
In the diplontic life cycle familiar to animals, the gametes (sperm and egg cells) fuse to form a diploid zygote which is diploid, i.e. it carries two copies of each gene, one from each parent. The zygote then grows to form a body in which all cells are diploid, until new gametes are produced by meiosis, which cuts their DNA content in half.
The haplontic life cycle, found in fungi, is in some ways the opposite. The zygote immediately undergoes meiosis to form haploid spores, which then grow into haploid adult bodies (the mycelia). The filaments of the mycelia then fuse to form new diploid zygotes, with no new meiosis needed.
Plants went for something stranger: the haplodiplontic life cycle.
The newly formed zygote grows into a diploid body, as in animals. This body then generates spores by meiosis, and these spores in turn grow into a haploid body, as in fungi, which produces sperm and egg cells. The spore-making diploid body is known as sporophyte, and the gamete-making haploid body as the gametophyte. Two distinct multicellular bodies, for one life cycle!
The relation between sporophyte and gametophyte varies in plant evolution. In ferns, we see a true separation: the tiny, leafy prothallus which is the gametophyte, and the more familiar plant with fronds which is the sporophyte. In mosses, most of what you see is the gametophyte: the sporophyte is only generated to produce spores, and never detaches from the mother gametophyte. It is visible in moss as the yellow stalks growing over the green carpet:
(tall yellow sporophyte growing out of the low, green gametophyte)
But in flower plants, it's quite the opposite. When you look at a tree, you see a massive growing sporophyte. Its spores are kept close, to develop in the shelter of a flower, and they grow into a tiny gametophyte, genetically distinct from the mother sporophyte but unable to survive on its own. Female gametophytes never leave the flower: they develop into the embryo sac, comprised of a single egg cell and some nurse cells. But the male gametophyte does leave, and that is what a pollen grain is: a tiny haploid plant that is carried away from the mother by wind or rain or bees, laying dormant until it falls into a receptive flower, and then it starts producing and releasing actual sperm.
So basically what flower plants do is as if men, to reproduce, had to give birth to tiny goblins who run around to have sex with women and impregnate them. Hope this helps
OP theaverycottage on TikTok ♡
I would have LOVED this as a child (I would love it now, but obviously can't afford it).
Meet Pando, not a forest but a single tree. Every trunk of the Quaking Aspen is genetically identical & connected by a single 80,000 year old root system, making it one of the largest and oldest living entities on Earth!
Have you ever wondered what it would be like to walk through the body of a God?
@derinthescarletpescatarian
It's very interesting how big of a revolution will LLMs cause (and are already causing) in genetics and bioengineering since DNA and proteins are, for all intent and purposes, really really long words
You can, very literally, fit the entire human genome in a .txt file. It's not the most efficient way to study it but you can
It's so funny that people have such strong opinions on AI but every geneticist I meet is like "oh god finally. This thing does all the work for me. We will find the catgirl gene soon"
And no this isn't just the specialized models like alphafold. You can ask Claude or Deepseek to make pipelines and bioinformatics stuff for you and they work.
Do they really work or do they solve textbook exercises?
A lot of bioinformatics is doing "textbook exercises" over and over again. They're very good at this.
Also, Alphafold.
Now I wanna see the .txt with the entire human genome.
You can straight up download the whole human (reference) genome here. Just click download and it's in in a zip fasta format, which is basically a glorified .txt file you can view on Notepad++ or standard Notepad. It's about 3gbs. You can fit it in any flash drive.
Genome Reference Consortium Human Build 38 patch release 14 (GRCh38.p14) - Homo sapiens
Of course you wouldn't be downloading a single file but rather a file for each chromosome (including the mitochondrial genome). And on itself reading the data in text format isn't of much use, but there is software to study to the chromosome level (the fasta format is mostly used for small sequences of interest)
You could, theoretically, copy paste each fasta file in a .txt file but that would crash your clipboard. In bioinformatics people do this all the time, you concatenate these files that weigh lots of gigabytes, there are whole hard drives in my institute just for that.
Here's what it looks like if you're curious.
But yes if you want, you can straight up have the whole human genome in your hard drive.
Por cosas como esto, Tumblr es la mejor red social ❤️

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have you guys heard about the greenland shark. some crazy shit happening there.
they are sexually mature at ONE HUNDRED AND FIFTY YEARS OLD.
their (live!) young gestate for. wait for it. eight to eighteen (??) YEARS. can have up to 10 at a time. good grief.
longest lifespan of any vertebrate, up to five hundred years
toxic flesh
has giant eyes but is usually blind because of a weird little crustacean that's evolved to live on and eat their eyes. this doesn't seem to bother them much.
lives in deep cold water and has the lowest swim speed and tail-beat frequency for its size across all fish species. just generally lives life in extreme slow motion
largest genome of any shark
eats everything including moose and polar bears
ma'am you are delightfully strange and I'm privileged to share a planet with you
this post prompted me to refresh my memory on Greenland Shark Facts and this detail about how they feed goes so hard
just vacuuming up their unsuspecting prey. whole !
Good news good news good news! Recent research suggests the eye parasites do NOT blind them!
Dorota Skowronska-Krawczyk sits in her office, eyes fixed on the computer monitor in front of her. "You see it move its eye," says the UC Ir
I <3 you a normal amount Greenland sharks
It's very interesting how big of a revolution will LLMs cause (and are already causing) in genetics and bioengineering since DNA and proteins are, for all intent and purposes, really really long words
You can, very literally, fit the entire human genome in a .txt file. It's not the most efficient way to study it but you can
It's so funny that people have such strong opinions on AI but every geneticist I meet is like "oh god finally. This thing does all the work for me. We will find the catgirl gene soon"
And no this isn't just the specialized models like alphafold. You can ask Claude or Deepseek to make pipelines and bioinformatics stuff for you and they work.
Do they really work or do they solve textbook exercises?
A lot of bioinformatics is doing "textbook exercises" over and over again. They're very good at this.
Also, Alphafold.
Now I wanna see the .txt with the entire human genome.