"aww yiss look at all these social media sites my friend is forcing me to participate in i'm so thank" - said the owner of this blog, probably. you're welcome, humble citizen. you're welcome.
I'm a big fan of wizards-as-programmers, but I think it's so much better when you lean into programming tropes.
A spell the wizard uses to light the group's campfire has an error somewhere in its depths, and sometimes it doesn't work at all. The wizard spends a lot of his time trying to track down the exact conditions that cause the failure.
The wizard is attempting to create a new spell that marries two older spells together, but while they were both written within the context of Zephyrus the Starweaver's foundational work, they each used a slightly different version, and untangling the collisions make a short project take months of work.
The wizard has grown too comfortable reusing old spells, and in particular, his teleportation spell keeps finding its components rearranged and remixed, its parts copied into a dozen different places in the spellbook. This is overall not actually a problem per se, but the party's rogue grows a bit concerned when the wizard's "drying spell" seems to just be a special case of teleportation where you teleport five feet to the left and leave the wetness behind.
A wizard is constantly fiddling with his spells, making minor tweaks and changes, getting them easier to cast, with better effects, adding bells and whistles. The "shelter for the night" spell includes a tea kettle that brings itself to a boil at dawn, which the wizard is inordinately pleased with. He reports on efficiency improvements to the indifference of anyone listening.
A different wizard immediately forgets all details of his spells after he's written them. He could not begin to tell you how any of it works, at least not without sitting down for a few hours or days to figure out how he set things up. The point is that it works, and once it does, the wizard can safely stop thinking about it.
Wizards enjoy each other's company, but you must be circumspect about spellwork. Having another wizard look through your spellbook makes you aware of every minor flaw, and you might not be able to answer questions about why a spell was written in a certain way, if you remember at all.
Wizards all have their own preferences as far as which scripts they write in, the formatting of their spellbook, its dimensions and material quality, and of course which famous wizards they've taken the most foundational knowledge from. The enlightened view is that all approaches have their strengths and weaknesses, but this has never stopped anyone from getting into a protracted argument.
Sometimes a wizard will sit down with an ancient tome attempting to find answers to a complicated problem, and finally find someone from across time who was trying to do the same thing, only for the final note to be "nevermind, fixed it".
If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:
Over the weekend, I did an interview about my forthcoming book The Reverse Centaur's Guide to Life After AI (a book about being a better AI critic), and the interviewer said she was surprised that I wasn't an AI booster, based on my demographics and work history:
I could see where she was coming from. I encountered computers in the mid-seventies, as a small child. My first computer was a CARDIAC, a working, Turing-complete, mechanical computer made entirely of cardboard, that I spent endless hours with:
Then I graduated to a teletype terminal and acoustic coupler connected to a minicomputer at the University of Toronto. My mom, a kindergarten teacher, used to smuggle home 1,000' rolls of paper towel from the kids' bathroom. I'd get 1,000' feet of computing up one side, then another 1,000' down the other side, then I'd carefully re-roll the paper towel so she could put it back in the bathroom for the kids to dry their hands on.
After that, I got an Apple ][+ in 1979, and shortly thereafter acquired a modem, and that was it: I was hooked for life. I became an amateur programmer, then a professional programmer. I hosted forums on dial-up BBSes where I distributed software and offered support to strangers who wanted to connect their computers to the internet. I got a job as a gopher developer, then a web developer, then a CIO-for-hire, helping wire up small businesses and connect them to the net. Eventually, I co-founded a free/open source software startup, before transitioning to 25 years as a digital rights activist with the Electronic Frontier Foundation. And for most of that time, I was energetically writing science fiction, eventually becoming associated with a school sometimes called "post-cyberpunk":
The force that energized all this work was a dialectical one, the contradiction that powered cyberpunk literature itself. For all that cyberpunk was undeniably enamored with the coolness and combustibility of new technology, it was also terrified of how technology could be a force for oppression, surveillance and control. As William Gibson says, "cyberpunk was a warning, not a suggestion."
Gibson's more famous quote, of course, is "the street finds its own use for things." In Gibson's novels (and in my own life in technology) all the most interesting things happen when users of technology (often without formal training or credentials) find ways to adapt the technology they use to suit their needs:
This is why I remain an ardent fan of Hypercard, Scratch and other meta-tools that are designed to allow non-programmers to write software that exactly conforms to their desires. Whatever the apps produced by these tools lack in sophistication and efficiency is more than offset by the fact that they give everyday people the power to directly control the tools they rely upon.
If "epistemic humility" means anything, it means acknowledging that no amount of "requirements gathering" can capture the needs of people totally unlike yourself as faithfully as those users can capture their own needs. Giving people the tools to produce their own software is always going to make tools – vernacular, idiosyncratic, homespun – that are more suited to their own hands and minds than anything a technologist working on their behalf could make.
The ancient dictum of "nothing about us without us" – born in 16th century Poland and taken up by the modern disability rights movement – asserts the right of people to control their own living conditions, and also the unique capacity of people to understand their own needs. You know what's even better than being consulted on the design of the technology you use? Having direct control over that technology!
This is why I was so suspicious of the iPad. The iPad's much-lauded "ease of use" was entirely about how easy it was to use an iPad to consume technology. But the iPad remains the single most user-innovation-hostile technology in modern history, a device designed to make it impossible to produce technology without permission from a remorseless multinational corporation. This is cyberpunk as a demand, not a warning:
The technology I've championed all my life is technology that gives more control to its users. One of my immutable precepts is that people who are different from me know things I can't know, and the only way I can get the benefit of their unique knowledge and perspective is if they are free to make and share things that matter to them. As Dan Gillmor said, back when he was inventing the study of citizen journalism, "My readers know more than I do":
And while I am broadly very skeptical of AI, and deeply alarmed by the proliferation of "vibe coded" software in production environments, vibe coding for personal projects is a useful and exciting addition to the lineage of tools that let computer users decide how their computers will work. For people making personal projects, vibe coding extends the power of shell scripting, cron jobs, Applescript, and other desktop automation tools to a wider audience.
One of the journalists I spoke to last week about my book described how he had vibe coded an app that showed him an alert every time a plane flew over his house, giving the tail number and other details of the flight. This is information that I have no need for, no interest in, and that I'm therefore excited to learn about, because its very existence affirms that the world is full of people who are delightfully, irreducibly, amazingly different from me, and moreover, that their unique needs can be directly met using their imaginations and their personal computers.
I recently sat down with my colleague Naomi Novik, a brilliant author who also co-founded Archive of Our Own. Naomi demoed her followup to AO3 for me: Wreccer, a system to help you find small groups of people with taste similar to your own, in order to facilitate media recommendations within that group – a kind of personal, relationship-driven alternative to massive, centralized, monolithic algorithmic recommendation systems:
https://github.com/wreccer
Naomi told me that Wreccer was being built using the same design ethos that the original Twitter embraced. When Twitter launched, it was an API first, and the official Twitter front end was built on that API – but anyone could build their own front end for Twitter that worked in the way they wanted it to. Now, the word "anyone" is doing a lot of work in that sentence, because most people don't even know what an API is, and of the people who do, most of them were not capable of writing their own software front end for Twitter.
But Wreccer is being designed for the age of vibe coding, and the API will really allow anyone who uses the service to design their own interface to the system, one that elevates and centers the features they find useful and tucks away the ones they're not interested in. Your personal, custom front end could also bring in other data-sources – pulling in your Mastodon messages, for example, or even showing you an alert with the tail-number of any plane flying over your home.
This is the part of vibe coding that I'm quite excited about, but it's not the part the industry focuses on. Instead of hearing about how personal, homemade software utilities can be an end unto themselves, we hear about vibe coded projects as prototypes for commercial production code. We hear about clueless bosses vibe coding software products and services that run fine for one user on a siloed desktop computer, and then demanding to know why it takes 50 engineers a year to make the same thing work for millions of users on the public internet. We hear about people who vibe code and submit patches to free/open-source software projects with millions of users, overwhelming project maintainers with slop code that is riddled with security vulnerabilities.
Of course, there's an obvious reason why the industry wants to focus on the potential for vibe coded software to replace production code. The AI bubble has burned up $1.4t to date, while bringing in mere tens of billions of dollars per year, even as its unit economics grow steadily worse:
To keep the bubble inflated, AI hucksters must promise massive economic returns to the technology. They want investors to believe that vibe code is about to replace working programmers, who are skilled, high-waged, high-demand workers. Their pitch is that for every million dollars' worth of programmers that an AI salesman and a boss conspire to fire, half a million dollars will go to the AI company whose bots shit out that vibe code.
That's par for the course with the AI bubble, whose focus is entirely on how AI can centralize, control and homogenize our lives. Whereas early desktop publishing, web publishing and social media gave us a glorious higgledy-piggledy of chaotic, weird and transgressive hobbyist media and retina-searing designs, AI art and design are instantly recognizable at a thousand yards, and it all looks the same, boring, and washed:
AI companies have released open weight/open source models that can run on your own computer, but these are treated as side-shows and toys and demos. The real action, we're told, is in "frontier models," which is industry-speak for "a piece of software whose running costs exceed the GDP of most countries":
Perhaps this is why the dynamics of AI are so different from the early dynamics of the web. Early web users were workers, who demanded that their bosses allow them to use the web and so devolve more power to people doing their jobs. By contrast, today's most ardent AI boosters are bosses, who threaten workers who don't use AI enough in the course of their duties:
Where we do see idiosyncrasy emerging from AI usage, it's often terrible. AI can help you create a folie-a-un in which you and a chatbot team up to reinforce your delusions and drive you deeper into a world of dangerous mirage:
There's a (false) story that's told about people who championed the early internet: that we were blithely certain that technology could only be a force for good, and negligently disinterested in the possibility that technology could control, extract and harm. That's demonstrably untrue: recall cyberpunk's dualism of "the street finds its own use for things" and "cyberpunk is a warning, not a suggestion."
More true is to say that early internet champions were alive to the importance of the internet, and therefore both excited about the possibilities of the internet to deliver a world of connection, idiosyncrasy, love and solidarity; and about the danger of the internet as a dystopian system of surveillance and manipulation:
History isn't finished. Long after the AI bubble pops, there will be local models and people vibe coding homemade software that respond directly to their needs. The stuff we make on our own computers, for ourselves, is deplatformed from its inception. It's part of the life we can build in technology's "shadowy corners" that we used to just call "technology." The fact that this stuff is utterly unsuited to be production code makes it inherently unmonetizable. It's how the street finds its own use for things:
so i feel the urge to add a bit of context here because i find the vague on-screen text deeply underwhelming.
this is not just "a picture", it's Pale Blue Dot, one of the most famous works of astrophotography ever made public. and it was not just "a dying spacecraft", it was Voyager 1, a probe launched in 1977 to study the atmosphere and moons of Jupiter and Saturn, among other things. both Voyager probes carried on them a golden record meant as an introduction to humanity for any alien species that might discover them (if you saw Kane Parsons' Backrooms, you've heard the contents of that record coming out of a cardboard caveman standee). they did this because NASA planned to sundown these probes by letting them drift out of the solar system to parts unknown. Voyager 1 is currently 16 billion miles away, the farthest any manmade object has ever traveled from earth.
AND it's not even dead! despite supposedly being a "dying spacecraft" all the way back in 1990, Voyager 1 is not expected to be fully out of commission until 2036. to keep the probe alive they've switched off unneeded tools, adjusted its trajectory, even essentially updated the firmware, and through all that time it's basically never stopped sending back priceless data for scientists to analyze.
this is the original Pale Blue Dot, by the way:
it's relevant because "a single point of light smaller than one pixel" makes a lot more sense in the context of the original than it does in the heavily corrected version up top, where our pale blue dot looks more like a vibrant dwarf star. the difficulty of spotting earth in these waving curtains of space IS the entire impact of the picture! the blue dot is "pale" because it's hard to see! by making earth stand out so brilliantly, Terribly Interesting have inadvertently created the impression that earth is this vibrant glowing pearl, bright for all to see for billions of miles around. and it just isn't! the point is not that we can see earth from far away, but that we almost can't, because we aren't the center of the universe! when science educators past have used this image they often referred to one where the earth is circled in bright red, which only further emphasizes how small and fragile our home really is.
but hey, if you DO want an improved version of Pale Blue Dot you don't even need photoshop:
this is Pale Blue Dot Revisited, released by NASA in 2020. this is a reinterpretation of the original data using modern image processing techniques to create a more realistic or at least more high-definition rendering of the scene. it's important to understand that this is not the original image dropped into photoshop and airbrushed. strictly speaking, there isn't an "original" Pale Blue Dot the way there are negatives of traditional photography. astrophotography is almost always the product of raw data being deliberately interpreted by scientists, so the same data can produce many different images (ie if they want to emphasize the infrared spectrum vs visible light). similar work was done by Don P. Mitchell in ~2005 to enhance images taken by Soviet Venera probes of the surface of Venus to be less noisy.
here's an original:
and here's Mitchell's version:
i'm not here to argue which is "better" (and i highly recommend you read the source for this one because it's quite fascinating), just to give another example of the process in action and hopefully clarify how it's distinct from editing a jpeg in photoshop. also i just think it's neat!
which is the real reason i went to the trouble of making this post. Terribly Interesting may indeed find all of this to be terribly interesting, but it appears to be interest for the sake of a vague transient feeling of having been interested and little else. it doesn't name the probe, the photo in question, nor does it give historical context for the mission it was part of. the only substantial thing it says about the probe, that Voyager 1 is a "dying spacecraft", is so frustratingly oversimplified it may as well just be a lie.
so what's actually learned here, if you're someone who knows none of this history? that one time there was a thing and it did a thing? earth tiny from far away?? obviously it's just one image macro but i see this kind of thing making the rounds SO often, a screenshot with like two sentences on it explaining the image with as little descriptive text as possible. it's like there's a space-themed inspiration-posting rulebook that says you can't imply the existence of information not contained within the image. mention NASA? mention Voyager 1? mention Pale Blue Dot? nope! "a dying spacecraft" took "one last photograph", and here's a photoshopped version to make earth more visible.
and it might not even get to me nearly as much if this was any other space photo. i could accept that space stuff is complicated and this kind of fast-food image can only say so much if we were talking about Cassini or JWST's role in helping us find exoplanets. but this is Pale Blue Dot, the brainchild of arguably THE science communicator Carl Sagan! he wrote a book about Pale Blue Dot, he was on TV to announce the image personally! it's arguable that no astrophotograph exists whose context has been more digestibly packaged for laymen than Pale Blue Dot, which just makes it that much more egregious when someone doesn't go to the trouble.
so much of what i love about astronomy and studying the past & future of space travel is that everything you can learn is a doorway to learning more. you can't earnestly read about Voyager or Cassini or Venera or any other mission without finding some odd searchable detail and going "wait, what is that" and immediately falling down an hourslong rabbit hole to find an answer. and you'll never reach the bottom! i love reading articles about cutting edge astrophysics written for people in, like, early grad school, because i fully comprehend maybe 10% of it, vaguely understand 20% (on a good day), can kind of wrap my head around 30%, and find the rest totally inscrutable... but that's still a solid 60% scrutability rating even at the lowest-quality end of the spectrum! i'm no expert and i never will be, but in scouring the written expertise of others i almost always find one or two ideas that end up sticking with me forever. and it starts, every time, from questions about a photograph.
the sin of the above image is that it's solipsistic. it doesn't give you anywhere to put your curiosity or interest, doesn't invite you to leave their website and learn more than they have space to share, it doesn't even tell you anything useful about its subject! it reduces the entire history of Pale Blue Dot down to a vague and nondescript wonder that's just a pale imitation of the highly specific and ideologically driven wonder that Carl Sagan wanted us to feel.
here, feel it for yourself:
----
[P.S.: before you lament that this is an "AI" problem, while yes "AI" has radically increased the volume of low-value (often negative-value) inspiration bait like this, know that this has been a problem in online science education for a LOT longer than chatgpt's been around. this example isn't extraordinary, just close to my heart. nothing new under the sun and all that]
lmao someone else got their knocks in on this post before i could finish writing mine. clearly we are hand in hand re: Talk About How Cool Voyager 1 Is You Fucks
💬 0 🔁 109 ❤️ 245 · Okay, I need to add some clarification and correction to this.
This photo is known as The Pale Blue Dot. It was take
Thank you to @securityunit-ese for the excellent prompt and to @emily-e-draws for making me want to immediately draw mb at the rainforest cafe when I saw your art 💖
Possibly my spiciest take is that it's actually good to have people you respect and like that have some dogshit takes.
I think part of what is making young people lonelier, in discussing why they're increasingly isolated, is that they're so afraid of meeting someone who doesn't hold their same beliefs, and instead of being just core beliefs it is kinda ancillary shit.
It's actually okay to disagree even on social topics! Even on some political ones! But I mean, online you can start with "i love this mutual but they have a really bad/uninformed opinion about x media"
I know this is IMMEDIATELY going to be taken in bad faith, and yes babygirl, you are so right, I DO want you to go make best friends with both the KKK grand wizard AND your nearest nazi leader.
But seriously, as someone who has spent two decades doing community organization: finding ways to connect with different people is so so so important. There are people i follow here who ate 80% smart and their brain falls out of their head 20% of the time and that is GOOD FOR MY MENTAL ECOSYSTEM AND GOOD FOR LEARNING HOW TO BE A PERSON
today's reason I fucking love the open source community: Ageless Linux, a brand new Debian-based operating system specifically designed to break the law by giving children access to computers that explicitly refuse to track their age.
As of June 29, 2026 the law discussed here is a recently passed California state law (AB 1043) that requires age validation before using a computer connected to the internet. This is expected to happen at the operating system level, when you login to Windows, MacOS, Linux, etc.
Ageless Linux intends to force the issue before the California state supreme court, then ultimately (probably) the Supreme Court of the United States (SCOTUS). It's a stupid, dangerous law, voted into place by legislators who either don't understand the core issue OR knowingly voted for it because they're assholes.
California is an influential state in the US. Many laws & regulations passed there eventually trickle out to most states. That's why it's worrisome to see this kind of thing rammed through, and why it's important to fight it.
Also, it doesn't matter if you use Linux or not. Or whether you live in California or not. Visit their site, read the text, learn what's going on with access to computing in this hellscape timeline.
AO3 does not live in “the cloud” because that is other people’s computers, and other people’s computers are vulnerable to censorship.
AO3 is on its own computers. It does still have to be housed somewhere, and I suppose a determined enough hater could try to find that place and go after it, but it’s a lot harder than sending spurious complaints to Amazon or whomever going “BadWrong things are hosted on your cloud service!”
When people involved with AO3 talk about “the cost of servers” they don’t mean “the cost to pay Amazon for space on their servers.” They mean, like, the cost to physically own them, and eventually replace them with new ones. And the operating costs to run them.
AO3 is not “in the cloud.” AO3 is stored on physical machines that the OTW owns.
While this is not a solution that can work for everyone who wants to deal with controversial content, it is why AO3ple sneer at alt-righters who complain about getting thrown off hosting platforms.
Because I want us to own the goddamned servers, ok? Because I want a place where we can’t be TOSed and where no one can turn the lights off or try to dictate to us what kind of stories we can tell each other.
Yang Yang as Zhan Zhao, Zhang Ruonan as Huo Linglong and Alen Fang as Bai Yutang in ZHAN ZHAO ADVENTURES (2026)
I still have the two of you. That's enough for me. It feels like I've won.
You are lucky you met the two of us. With us by your side, you won't have to suffer anymore.
I don't want to be a burden. Burden? Strange word between the three of you.
Of course we are going together.
Okay so I was all done with these for today, but then this mad genius, @avoid-avoidance came up with the most incredible idea. I couldn't stop til I got this down.
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.
I just went looking for the post on X and got a message that it didn't exist
I searched for Guri Singh and got search results showing his account existed, but when I clicked on it I got a message his account did not exist
Does anyone know if he made his account private or if he got nuked by Elon? Or do I just suck at X (because I never go there)?
Sometimes it’s hard to read fanfic when you’re studying herbalism.. when they have the character preparing a tincture to use that same DAY!!?
Baby those dried herbs need to sit in that jar with high proof alcohol for at LEAST a month!
That’s why before the use of calendars ppl use to prepare their tinctures either on the new moon or full moon. A a full moon cycle is usually 28 days or so. And they would give the moon names so it’s easier to remember when/what month said tincture was bottled.
This is also why herbal medicine is prepare in small batches. You have to take your time preparing your bottles. Making sure everything is clean so you don’t end up with mold. Diluting your grain alcohol. Heckkk knowing when to pick your herbs for max potency! Drying your herbs! That takes a lot of time too!
If you're writing anything involving cons, scams, heists, or morally questionable characters who are very good at lying, here are some free resources I've been using for research. Saving you the "why is this in my search history" anxiety.
1. The FBI's Famous Cases & Criminals archive (fbi.gov/history/famous-cases) has detailed breakdowns of real fraud cases, Ponzi schemes, and confidence operations. The language they use is clinical and precise, which is perfect for getting the procedural details right.
2. The FTC Consumer Sentinel Network publishes annual reports on the most common fraud tactics in the US. Great for understanding how modern scams actually work and what makes people fall for them.
3. The Smithsonian's American Art Museum has a free digital collection of forgery case studies. If your character forges documents or art, this is gold.
4. Court Listener (courtlistener.com) is a free legal database where you can read actual court transcripts from fraud trials. Want to know how a real con artist talks under oath? This is where you find out.
5. The Internet Archive's collection of old newspaper crime sections. Search for "confidence man" or "swindle" in papers from the 1920s through 1960s and you'll find incredible real stories that would feel too dramatic for fiction.
Bonus: The Psychology of Fraud section on the Association for Psychological Science website has accessible articles about why people trust, how deception works cognitively, and what makes someone a convincing liar. Essential reading if you want your con artist characters to feel psychologically real.
Reblog to save for later. Your WIP will thank you.
Chat, is it considered “abusive roommate behavior” to release a raccoon into the living space after you have asked your roommate for months to please clean up their messes (they do not pay any of the mortgage)
For context, when I used to live alone I would do something called “Princess Time” where I would do an initial sweep (to remove any significant hazards) and then I would release a raccoon into the living area and clean. This helped because I would 1) feel like a princess and 2) the raccoon would bring attention to things my ADHD brain had decided to ignore and I’d quickly clean that stuff up.
So like, if I’m expected to clean the house now, I will be doing it in the way that is most effective for me. And anything that has not been cleaned up after months of having sit-down talks and sending reminders and being promised things will change, might be deemed “trash” by the trash panda and thrown away.
We haven’t done since we moved into the house, because I didn’t want to cause my roommate or their cats destress or have their things destroyed by a raccoon
I am a raccoon biologist and one of the few people in the state allowed to take in captive bred raccoons that had been possessed illegally. The raccoon in the photos is Moonshine, but she is currently at the animal sanctuary where I work as I had been quarantining multiple new intakes from an abuse case. I still have two males (Rum Tum Tugger and Electra) left in my home enclosure as we are getting them neutered and then hopefully sending them to an AZA accredited zoo.
I wanna make things very clear that underneath all the whimsy, I am a trained professional.
