sleepwalking-moose

expect a lot of political statements here. i mostly use this to post things i want to show family and friends.

[mapsontheweb]

US climate with equivalent cities from around the world.

Keep reading

[shabbytigers]

This is the greatest map I have ever seen. I want an interactive version where you can click on any city in the world and get a pop-up list of all the climate-equivalent cities.

[shabbytigers]

so it turns out this exists and it makes a fine rabbit hole for passing the time during a conference call

[queenbookwench]

OK, this is super neat and also a great tool for writers’

[liveleaker-deactivated20250423]

[oneheadtoanother]

[tachyon-log]

(USAmerican trying to imagine a societal environment) Okay, so picture a highway,

[fishmech]

inability to correctly perceive 3d objects is in fact far more dangerous when someone is driving a car next to you then when they're like, sending emails to you.

[mervynbunter]

You said something in “Smith” which I hope I grasped, and there was a feeling almost of recognition. An odd feeling of grief overcame me when I read it. I cannot explain my feelings any clearer. It was like hearing a piece of music from way back, except that it was nearer poetry by Graves’ definition. Thank you very much for writing it.

Terry Pratchett, in a letter to J. R. R. Tolkien, 22 November 1967

Thank you very much for your letter. The first one that I have received with regard to Smith of Wootton Major. You evidently feel about the story very much as I do myself. I can hardly say more.

J. R. R. Tolkien, in reply to Pratchett’s letter, 24 November 1967

[thesetwoutes]

This is the first I've ever seen this and it makes me wonder if it's why Pratchett was always so conscientious about responding to letters from kids.

[vaspider]

If you were wondering: in November 1967, Terry Pratchett was 19 years old.

[rock-n-roll-fantasy]

And he did in fact say on at least one occasion that it was this that pushed him to always engage with his own fans in the same kind and conscientious manner.

[depsidase]

[barkingbarghest]

Here is an article from NPR about it (May 22, 2026):

Carolina Milanesi, an independent technology analyst, said Google is trying to make its cash cow business — search — richer and more personalized, and it will make shopping easier. But there is a risk that users may have fewer choices about what to click. "Right now it's: I ask a question, I get a bunch of answers and I feel that I'm in control as to which answer I take, or if I'm looking for something, which product I'm going to end up buying. That is going to be less so going forward," she said. Milanesi envisions AI-enabled search and agents proposing products to consumers — perhaps even those they have requested — but with less clarity or choice around where it's coming from. "If you're going to say: 'I want a pair of Jordans, go find them,' you're not necessarily sure what steps have been taken and whether the AI has used a source or a store that was paid for and therefore came up in the search results," she said, "or if AI actually went and did their due diligence and picked the best for me as a customer."

And here's one from Time magazine (May 20, 2026):

While Google already has “AI Mode,” the company will now power the whole search bar through its new Gemini 3.5 Flash model.  Instead of the classic list of blue links, Google Search will now also generate a custom page with an AI-generated summary of what you’re searching about, which will then trigger a conversation with AI Mode on the main page, allowing users to ask follow-up questions—similar to the kind of layout you would see when opening ChatGPT.

And a little more from Time's article on how this may affect the websites that we are trying to search for:

When Google first started implementing AI-assisted results, news publishers warned of “catastrophic” impacts on the industry, much of which relies on Google search to drive users to their websites.  Last year, news websites saw significant traffic declines as chatbots increasingly replaced Google search as the primary way to find sites and ask questions.  Small businesses also noted drops in traffic to their sites from Google, which has traditionally delivered customers.   Lily Ray, vice president of SEO strategy & research at Amsive, a digital marketing agency, warned as early as last year that Google’s planned changes to search are “going to have a devastating impact on the Internet.”  “It will severely cut into the main source of revenue for most publishers and it will disincentivize content creators who rely on organic search traffic, which is millions of websites, maybe more,” she told Technology Magazine.  

[anarchopuppy]

noai.duckduckgo.com blocks all AI content in search results automatically

[smol-blue-bird]

all STEM students should have to take humanities courses, and all humanities students should have to take STEM courses

[smol-blue-bird]

@caesarsaladinn I had a whole discussion with a history major who was extremely confident that smallpox is a “common childhood illness” with a very low death rate. Therefore, she believed that historical smallpox outbreaks were either massively exaggerated or used as a cover-up for something else (since “smallpox isn’t that bad.”) I eventually asked if she was possibly confusing smallpox with chickenpox, at which point she said, “aren’t they the same thing?”

[the-grey-tribe]

The English language really whiffed on that one. Should have called it largepox or at least regularsizepox.

[myfootyrthroat]

The whole "-pox" making system could use some work. Are we doing sizes? Animals? Get it together.

[imjustusingthistolikeartists]

One of the less deadly variants of smallpox was called cowpox, and the fact that dairy maids who contracted it tended to avoid the worst affects of smallpox is part of the development of vaccination

[smol-blue-bird]

Cowpox is actually a separate (but very similar!) virus!

There's a lot of confusion about different "poxes" in this post (which wasn't my intention, and now I feel bad), so here's a general overview (also, obligatory apology for messiness, this was written at like 1 AM):

Smallpox:

Smallpox, caused by variola virus, was a massive problem historically. It existed in the Western hemisphere for thousands of years (genetic evidence of smallpox has been found in Egyptian mummies from ≈1500 BCE, but it was probably around long before then), and it was introduced to the New World during the Columbian exchange, which had devastating consequences for indigenous populations (which were already suffering from colonialist violence, which made epidemics much worse than they already would've been). Historically, smallpox had a case fatality rate between 30-50%, and survivors were often left disfigured or permanently disabled (you've probably seen pictures of smallpox scars, but smallpox can also cause blindness and other complications). Importantly, smallpox only affects humans—it has no animal hosts—which is why it's one of the few infectious diseases to have been completely eradicated. As of May 8, 1980, it officially no longer exists outside of certain designated American and Russian laboratories. (There are, however, concerns that it could be used as a bioweapon, which is why the government still stockpiles smallpox vaccines and antivirals. I wrote my bioethics term paper on this exact issue, and incidentally, it's one of the major reasons why I believe that STEM majors should take ethics courses!)

There were two strains of variola virus: variola major and variola minor. Variola major was much more dangerous, with a much higher mortality rate; variola minor typically didn't cause severe disease. Fortunately, infection with one strain conferred immunity against the other. Both strains are now eradicated. (People sometimes confuse variola minor with other viruses like cowpox and horsepox, but they're different things.)

There were four clinical forms of smallpox: ordinary (classic smallpox, associated with the rash you usually see in pictures), modified (less severe, often occurred in vaccinated people who got infected anyway), malignant (caused a flat rash instead of the usual pustules, associated with immune dysfunction, almost always fatal), and hemorrhagic (caused severe bleeding, and also near-universally fatal.) All of the non-ordinary forms could be difficult to diagnose because they looked so different from typical smallpox. The less serious "modified" form was often confused with chickenpox, and the hemorrhagic form was sometimes assumed to be a completely different disease. Occasionally, historical sources will refer to hemorrhagic smallpox as "black pox," with or without an understanding that it's caused by the same virus as ordinary smallpox.

Other relevant viruses:

Cowpox, caused by cowpox virus (an orthopoxvirus similar to smallpox) causes mild disease in cows, humans, and several other animals. Infection with cowpox virus confers immunity to variola—Edward Jenner noticed this relationship and used material from cowpox lesions to inoculate people against smallpox.

Vaccinia virus, another orthopoxvirus, is the source of the modern smallpox vaccine. It's closely related to both cowpox and horsepox (weirdly, it's actually closer to horsepox), but it's distinct enough to be its own species. Infection usually causes mild symptoms, and, of course, confers immunity to smallpox.

Chickenpox is an entirely different thing. It's caused by the varicella-zoster virus, which is a herpesvirus, not a poxvirus at all! Infection with varicella-zoster does not confer immunity to smallpox or any other poxvirus—chickenpox is from a totally different family.

So why are the names so weird and confusing? Why is everything about all of this so weird and confusing?

There are multiple reasons for this, so bear with me.

Historically, a "pox" was any disease that caused a bumpy rash of pustles/blisters. Chickenpox, smallpox, and the other "poxes" all cause superficially similar rashes—thus the similar names. (Even though we know now that chickenpox comes from a completely different family, this wouldn't have been apparent before the dawn of modern medicine.)

Smallpox was given that name to differentiate it from syphilis, which was known as the "great pox" when it first appeared in Europe. (Fun[?] microbiology fact: There are debates about the origins of syphilis, but the most common theory holds that it originated in the New World, and Christopher Columbus brought it back to Spain. In that way, it's kind of the inverse of smallpox.) Historically, smallpox was also known by a variety of other names in different European, Asian, and African cultures. Again, this gets murky, because historical physicians sometimes struggled to distinguish between similar-looking-but-different diseases.

Other poxviruses are often named after the animals in which they were first identified. This is not a hard-and-fast rule, though, and it can sometimes be misleading (for example, monkeypox virus was first discovered in laboratory monkeys, but it more often affects rodents and other small mammals. The disease formerly known as "monkeypox" was recently renamed "mpox" because the name wasn't accurate.) Also, some poxviruses aren't named after animals at all! It's a weird and inconsistent system (but a lot of virus names are kinda weird and inconsistent).

Related to the above: We don't even know where the name "chickenpox" comes from. I mean, we know it was called a "pox" because it causes a pox-y rash, but we don't know where the "chicken" part originated. There are multiple theories about this, none of which are definitive. The disease itself has nothing to do with chickens.

Basically, a lot of the weirdness is a result of historical naming practices—people identified and named these diseases before modern virology existed, and those names stuck, so now we have similar names for superficially-similar-but-ultimately-different viruses, and names whose origins have been completely lost to time. Later, virologists muddied the waters further by naming newly-discovered poxviruses after the animals in which they were first seen, even when these animals aren't natural hosts or reservoirs of those viruses. It's a mess! And, again, all of this is complicated by the fact that some of these diseases were very hard to diagnose (or distinguish from one another) before modern medicine existed. Now, we can sequence viral DNA and figure out what's actually going on—which viruses caused which symptoms, whether those viruses were closely related, and whether being infected with one disease conferred immunity to another—but historical doctors and scientists didn't have those tools, so they were doing they best they could with very limited information, and that led to a lot of weirdness in terms of how these viruses were named and classified. Our current system inherited some of that weirdness, so here we are.

TL;DR: Poxvirus names are messy. Smallpox is caused by variola virus, which has two strains: variola major (the more severe one) and variola minor (less severe). Cowpox and vaccinia are different viruses in the same family, and being infected with one of them confers immunity to smallpox. Chickenpox isn't a poxvirus at all, but a herpesvirus—it just happens to cause a pockmark-y rash that looks superficially similar to smallpox pustules (and mild forms of smallpox were historically confused with chickenpox).

(P.S. none of this is super relevant to the average person, so don't feel bad if you didn't know any of it. Unless you are a history major inventing new conspiracies about smallpox, in which case you definitely should feel bad.)

Sources & further reading under the cut!

Edward Jenner and the history of smallpox and vaccination

The History of Smallpox (CDC)

The Triumph of Science: The Incredible Story of Smallpox Eradication

Scientific Background on Smallpox and Smallpox Vaccination (from Scientific and Policy Considerations in Developing Smallpox Vaccination Options: A Workshop Report) <- this article is like 20 years old, but it has some interesting information about the clinical forms of smallpox and how difficult they would be to diagnose accurately

Phasing out monkeypox: mpox is the new name for an old disease <- discusses the renaming of monkeypox to mpox, also mentions issues with other poxvirus names and virus names in general

Poxes great and small: The stories behind their names

[revangerang]

Unrelated but there should be more “art appreciation” and “film appreciation” type courses for non majors.

I would love to take a “sports appreciation” class. Tell me what all the straights find so entertaining lol

[professorwetware]

We will all die someday. But not from smallpox. Think about it.

[onion-souls]

[tiralatele]

[finofilipino]

Wait for the master.

[thebroccoligoblin]

The amount of confidence oozing from this dude

[jumpingjacktrash]

i re-watched it several times, looking for what he does differently. finally i spotted it. look at the line of motion in his strike. it’s not especially fast, he doesn’t wind up more than the others, and it’s not a matter of strength – the guy who knocked over the stand probably put more muscle into it. but there’s a unity of movement he has that the others lack. his body and sword are all one curve. everything moves at once along the same line.

from a physics perspective, that means all the force he’s applying is concentrated at the point of contact between his sword’s edge and the target, and it moves at just the speed that breakage propogates through the material. too slow and it wouldn’t have enough force; too fast and he’d get ahead of the break, shoving the target over instead of cutting it.

from a writing perspective, that means that i should focus on describing a master swordsman’s smoothness more than their strength or speed, and can also have witnesses be confused at the effectiveness of strikes that don’t actually seem all that fast.

[giuliaciulia89]

Martial arts are all about physics, my karate sensei is has a mechanic/physics diploma and he loves to explain the biomechanics of human body and how this was turned into fight via martial arts. It’s a very good way to teach. The sword master has a larger stance of the feet, much more than the others, allowing his barycenter to lower and thus giving more stability. This, united with the movement of the sword that follows the angle of his body increases the power of the blow without actually using too much muscle strength. Pretty sure he’s also just tending (not contracting) the muscles under the armpits, near the rib cage, the serratus anterior. That makes a huge difference.

[patentlyabsurdrpgideas]

Above: The science of moving like a master of martial arts.

[meret118]

What was most interesting to me is size has no correlation to success for any of the people.

[hoursofreading]

“I feel it in my work as a teacher, where I recognize that we are so close — so, so close — to a world where teaching looks like AI-generating lesson plans and delivering those lesson plans using AI-generated slides, and then assessing the skills of those lessons using AI-generated tests, and then grading those tests using a form of AI. The content of AI producing student work that is then fed back to AI for AI to assess. And for what? And at what cost? It pains me. It pains me deeply. And then I sit down and I read about clams. And it’s not just that I am reading about clams. It’s that I am reading the perspective of someone who thought that it was worth paying attention to clams. There. Remind me again why we read? I think that’s part of it. You pick up a book and someone has you by the arm. There, they are saying, look over there. They are pointing now. They are holding something in their hand. Little clam in the palm, refusing to open. Look at that thing that loves being alive, how it resists the same sun we turn our cheek towards. Crazy world, beautiful place. Down in the deep somewhere, a clam smaller than my hand is withstanding the pressure of a few dozen full-size trains just hanging out on top of its body.”

— Mary Oliver’s “Clam” - by Devin Kelly

[likeafieldmouse-deactivated2015]

Luis Camnitzer - The Photograph (1981)

[gastronauticsyd]

The Screenshot (2014)

[fredersen]

The Reblog (2014)

[toratiger-deactivated20211204]

Bahahahaha love this

[processintegrated]

The Unnecessary Comment (2014)

[greatmountainfloofsquatch]

The Delayed Reblogging (2026)

[madeline-the-bisexual-samurai]

The Astonishment of a Wild Encounter (2026)

[animentality]

[mjalti]

[david-goldrock]

Smart woman next to an unbelievable achievement is a picture niche that will never get old

[awnerd]

Then you’re gonna love this photo of Annie Jump Canon.

Working at Harvard in the late 1800’s and early 1900’s as a “Computer”, Annie Jump Cannon cataloged stars using their spectra from photographic plates, in an effort to understand the mysteries and peculiarities of stellar spectra.

This was hard, detailed, nuanced work. By 1889, three years into her work, she had classified over 1,000 stars. By 1913, she could classify 200 stars an hour. She could classify three stars a minute, just by sight. Using a magnifying glass, she could classify stars down to 9th magnitude, 16 times fainter than the human eye can see. And she did this all with exceptional accuracy.

Over the course of her career, she personally classified more than 350,000 stars, accounting for a mind-boggling 98% of all contemporary stellar spectra classifications, a feat that wouldn’t be bested until the 1990’s with automated digital sky surveys.

Cannon used these classifications to develop the Harvard spectral classification system (O–B–A–F–G–K–M), organizing stars by surface temperature and physical properties.

It is hard to overstate just how foundational her work was to modern astronomy and astrophysics. Her classifications have enabled more than a century of breakthroughs in stellar structure and evolution, including the understanding of how stars change over time and how temperature, luminosity, and composition are related. The system underpins the Hertzsprung–Russell (HR) diagram, one of the most important tools in astrophysics, and remains embedded in modern research, from stellar population studies to galaxy evolution.

The immense scale of her work was itself a massive contribution to astronomy. For comparison, before Cannon, star catalogs contained between 600 and 4,000 stars. Her work single-handedly proved that large-scale stellar classification was both feasible and scientifically valuable. She helped establish systematic star catalogs as a core method of modern astronomy and laid the groundwork for astrophysical research on stellar structure, evolution, and populations that continues today.

[justalurkr]

Text of tweet under the cut because it is loooong.

But... Stochastic Parrots.

Timnit Gebru was fired from Google in December 2020 for refusing to retract a research paper, and every single warning that paper made about large language models has now happened at a scale the industry spent 4 years trying to make people forget about.

Her name is Timnit Gebru.

She co-led the Ethical AI team at Google. She co-wrote a paper called "On the Dangers of Stochastic Parrots" with Emily Bender at the University of Washington and two other researchers. The paper was 14 pages long. It was submitted to a top AI ethics conference. And it was the reason Google decided that one of the most senior Black women in AI research could no longer work there.

The story Google told publicly was that she resigned. The story she told, confirmed by 2,695 of her colleagues in an open letter, was that she was fired by email while on vacation because she refused to either retract the paper or remove her name from it.

The paper had not even been published yet.

Here is what she actually wrote, and why every prediction inside it has now come true.

The first warning was about scale itself. Bender and Gebru argued that training ever-larger models on ever-larger scrapes of the internet would produce systems that appeared fluent but had no actual understanding of language. They called these systems stochastic parrots because they would repeat patterns from training data with statistical confidence and zero comprehension. The paper predicted that this apparent intelligence would fool both users and developers into trusting outputs that were structurally incapable of being reliable.

This was 2020. GPT-3 had just come out. The paper predicted the hallucination problem before anyone had a word for it.

The second warning was about bias amplification. The paper documented in detail that internet-scale training data contains systematic overrepresentation of dominant viewpoints and underrepresentation of marginalized ones. The models would not just absorb this bias. They would amplify it, because the optimization process rewards confident outputs, and confidence in language patterns tracks frequency in the training set.

The prediction was that hiring tools built on these models would discriminate against women. That healthcare triage tools would underperform on Black patients. That loan approval systems would entrench inequality while presenting their decisions as neutral algorithmic judgment.

Every one of those things has now been documented in deployment.

Amazon's hiring algorithm penalized resumes that contained the word "women" in any context. Healthcare risk scoring algorithms used by major US hospitals were found to systematically underestimate the medical needs of Black patients. Apple Card's credit algorithm gave wives credit lines 10x lower than their husbands for the same financial profile.

The third warning was about environmental cost. The paper calculated that training a single large language model produced emissions equivalent to the lifetime output of 5 cars. The prediction was that the race to scale would create an environmental footprint that would eventually rival entire industries.

In 2024, Google's emissions were up 48% from 2019, and the company explicitly blamed AI infrastructure. Microsoft's were up 29%, same reason. Both companies have now quietly abandoned the climate commitments they were publicly celebrating the year Gebru was fired.

The fourth warning was about documentation. The paper argued that the training datasets being assembled were too large for anyone to actually audit. Nobody at Google, OpenAI, Meta, or any other lab could tell you with confidence what was in the data their models were trained on. This was not a temporary problem to be solved later. It was a permanent feature of the approach.

In 2023, researchers discovered that the LAION-5B dataset, used to train Stable Diffusion and other major image models, contained thousands of images of child sexual abuse material. The companies that had trained on the dataset had no way of knowing. The paper predicted that category of failure 3 years before it was found.

The fifth warning was the one Google cared about most.

Bender and Gebru argued that the deployment of these systems would centralize linguistic and cultural power in the hands of the small number of companies that could afford to train them. The internet would become a place where the dominant voice was a statistical average of dominant voices, presented as a neutral assistant. Languages underrepresented in the training data would degrade over time as more web content was generated by these systems and fed back into the next training run.

This is now happening in real time. A 2024 study found that 57% of new web content in English is AI-generated or AI-assisted. Researchers studying low-resource languages have documented active degradation in translation quality, because the synthetic content fed back into training is itself worse in those languages.

The paper Google fired her for predicted the model collapse problem before model collapse had a name.

The mechanism behind why this all happened is the part of her work that nobody quotes.

Gebru's argument was not that AI is dangerous in some abstract sci-fi sense. Her argument was that AI is dangerous in a very specific structural sense. The technology was being built by a small group of researchers who shared similar backgrounds, worked at similar companies, and were rewarded for shipping products faster than competitors. The incentive structure made it impossible for safety, ethics, and bias concerns to slow anything down. Anyone inside the system who raised those concerns was either ignored, sidelined, or removed.

She was making that argument from inside Google.

Then Google proved her right by removing her.

The team Google had built to make sure their AI was safe was dismantled in 90 days because they did the job they had been hired to do. Margaret Mitchell, the other co-lead of the Ethical AI team, was fired two months after Gebru for searching through her own emails for evidence of how Gebru had been treated.

Gebru did not stop. She founded DAIR, the Distributed AI Research Institute, in 2021. The mission is to do AI research outside the control of the companies that have a financial interest in not hearing the answers.

Every prediction in the Stochastic Parrots paper has now been validated by deployment. Hallucinations are an industry-wide problem the largest labs cannot solve. Bias amplification has been documented in hiring, healthcare, lending, and criminal justice. Environmental costs are larger than entire small countries. Training data audits remain impossible. Model collapse is an active research crisis at every major lab.

The question worth sitting with is the one almost no one in the industry will say out loud.

Every researcher with the technical credibility to call out these problems watched what happened to her in December 2020 and made a calculation about their own career. The number of people willing to speak publicly about safety and ethics issues inside the major AI labs collapsed after that firing and has not recovered.

The researcher Google fired for warning about exactly what is now happening was right.

The company that fired her is now the second-largest deployer of the technology she warned about.

And the people inside that company who agree with her are not allowed to say so.

[mckitterick]

definitely read under the cut for the full overview

essentially, everything Gebru warned about LLMs in her paper has come to pass, including "model collapse," the issue where LLM datasets grow worse as more of their training data - the internet - becomes AI-generated slop, degrading the LLMs more and more as time goes on

because LLMs aren't really artificial intelligence and cannot understand anything - they're just really good at sounding like the dominant language - their "hallucinations" (nonsense and lies) will continue to worsen. they're not even really algorithms anymore, just "Stochastic Parrots"

the human, cultural, and environmental cost is awful and building. when these LLMs become unusable and all the hundreds of billions of dollars invested evaporate, the economic collapse will be unimaginable

[pisboy]

does anyone have the gamer dance gif because i need it

[hollowtones]

This? 

[pisboy]

Hmm…………….. not quite. try again

[hollowtones]

Only gif I got, boss.

[vladtheunfollower]

[animentality]

[beardedmrbean]