⬝ ⬝ ⬝ Dead Dove Eat Your Heart Out ⬝ ⬝ ⬝ Main fandom currently The Clone Wars, also Downton Abbey/Thomas Barrow, anime, One Piece, European musicals.
My fanfic is hosted on AO3: One Piece, Hungarian Musicals (#SparklyHungarianFandom), Les Miserables, Hetalia etc. #myfic is for my writing here on Tumblr..
Honestly, Tvyek is pretty miraculous. It’s permeable to water vapor but not to water, it’s nearly impossible to tear, but can be easily cut. It’s cheap and made entirely without binding chemicals. In addition to being used for wristbands, it’s used to wrap construction sites to keep out water during construction, for tear-resistant envelopes at Fed-Ex, coveralls for mechanics, and my wallet, actually.
Fun tip, though it looks like paper, Tyvek is plastic, and cannot be recycled with paper.
Its also very commonly used in museums! It is dust and waterproof but still breathes really well, with is great for wrapping things like textiles, its non-woven, which means it is less likely to cause tension issues from shrinking/growing with humidity, my conservation prof uses it sometimes as backing for paintings with tears. It is durable, and inert (ph neutral, wont have weird chemical reactions with stuff). Very cool material.
Anya is live and ready to show you everything. Watch her strip, dance, and perform exclusive shows just for you. Interact in real-time and make your fantasies come true.
✓ Live Streaming✓ Interactive Chat✓ Private Shows✓ HD Quality
Anya is LIVE right now
FREE
Free to watch • No registration required • HD streaming
inspired by my running into a codywan fic posted in 2017 for the star wars rarepair exchange last night, i graphed the growth of codywan on ao3
[Image ID: A graph of Codywan works on AO3. The horizontal axis shows the years from 2009 to 2023, and the vertical axis shows the total number of Codywan works from 0 to 6000. From 2009-2015, there are nearly no Codywan works. From 2015-2019, there is a slow gradual growth to about 350 works. From 2019-2023, there is a huge growth of 1000-2000 works per year ending in nearly 6000 works in 2023. /End ID]
you can see the sudden growth of codywan in 2020 in the following graph:
[Image ID: A graph of Codywan works per year. The horizontal axis shows the years from 2009 to 2023, and the vertical axis shows the number of Codywan works posted. From 2009-2015, there are nearly no Codywan works. From 2016-2019, there are about 50-100 works posted each year. From 2020-2022, each year there is an increase in Codywan works posted from 900 to 1400 to 2000. In 2023, there are a little more than 2000 works posted*. /End ID]
*the number of codywan works posted in 2023 was extrapolated from the number of works posted this year so far. at the time of this post (2023/07/31), there have been 1179 codywan works posted in 2023
it's wild to think about how just a few years ago, what is now the 7th largest star wars ship was a rarepair. now there are redditors running into it and screenshots making the rounds on twitter. so uh congratulations codywans?
notes: works from the "CC-2224 | Cody/Obi-Wan Kenobi" tag on ao3 were filtered by date. no other filters were used. each year shows the number of works at the end of that year (i.e., 2022/12/31, 2021/12/31, etc). technically, the graphs show the number of works updated, not posted, as i could not find any option to filter works on ao3 by date posted. however, i don't think this really makes a difference in the overall trend of growth
I feel a sudden need to bring some important, clarifying information to people. Mostly artists who love drawing murder shrimp.
There are two kinds of crustaceans that are called "shrimp" that use concussive force via cavitation bubbles as a weapon.
These are Pistol Shrimp, a group of actual shrimp, and Mantis Shrimp, which are not actually shrimp but they are the ones you probably think of when you hear "murder shrimp" and "shrimp colors" (specifically the Peacock Mantis, bc there's a lot of species for both.)
I'm not annoying enough to grumble about the mantis being called a murder shrimp, because "murder stomatopod" is objectively a less fun combination of words.
HOWEVER!! People keep drawing mantis murder shrimp with pistol shrimp claws. They are not the same claws!! They are not used the same way!!! I will explain!!!!
Pistol shrimp: A number of shrimp species which have one big megachad claw and one dinky normal one.
The dactyl, or movable part of the large claw, is snapped shut with so much force that it shoots a cavitation bubble out with a very loud snap that can stun prey or scare off predators. It's very fucking cool.
As cool as that is, there is a reason that the mantis shrimp is what most people think of when they read "murder shrimp."
This is the Peacock Mantis Shrimp. Which is not a shrimp, but a stomatopod.
(In a lot of pictures it appears like they're staring intently at the camera. They probably are, because they are alarmingly intelligent.)
Note that it doesn't seem to have the big classic claws, and that's becaus it doesnt. Please stop drawing a shrimp claw on them. Their "claw" appendages are kept tucked up, praying mantis style.
These are a raptorial appendage that do have a sharp bit, but that sharp point has adapted to add support to the club end. They use the club to punch the shit out of things. They do punch so hard that they create a cavitation bubble, but the punch is the main deal.
If you look up a mantis shrimp puncher you may find this image, but they rarely if ever fold out fully past the punching part.
The second common mistake on mantis drawings is from mixing up two types of mantis shrimp. There are punchers, which includes the peacock mantis, and stabbers. You can guess what they do.
Fun fact! The peacock mantis is the largest puncher species, maxing out at 6-7 inches. Some of the stabber species, such as a zebra mantis can get 11 inches. This is because the peacock mantis is as big as it can get before it would shatter itself with the force of its punch!
This has been the marine biologist PSA.
Please stop putting the wrong claw on a peacock mantis.
@robowarrior-god this is good and valid to suggest!
but also. in my very unscientific, pure vibes, anthropomorphizing opinion. Peacock mantis shrimp would be totally honored to be called a "murder shrimp" and they super super deserve it.
idk about other mantis species (there are LOTS of various sizes) but having worked with a few peacock mantis' every single one has had a distinct "punch first, ask questions later" approach to life. It never seems aggressive or defensive, to be clear. It's like. Part of their curiosity. So many I've worked with will see a new thing - like say, a scrubber or hose or tongs - approach it, examine it with their antennae/normal legs.
and as part of their examination they just. fucking punch it. like part of their exam method is "what will happen if I Do Violence upon it?"
I always, with pure fondness, said of the last mantis I had; "if he knew what war crimes were he would do war crimes."
PISTOL SHRIMP, however, are adorable delights who are the exemplary image of good neighbors!
They have fish roommates!! It's very cute!!!
This is what's called a mutualistic relationship between various species of pistol shrimp and various species of watchman gobies. The shrimp is good at making a burrow and is good at snapping at things. The goby is not as good at burrow making, but it has much better eyesight and field of vision. When they team up the shrimp will often keep an antennae touching the goby whenever it (the shrimp) is out of the burrow so that it can be alerted more easily to danger.
This happens with multiple species of pistol (aka snapping shrimp) and watchman gobies, and often they'll pair up with a species of similar size. And lots of them do very well in home aquariums with other animals! They're very polite. Absolutely lovely.
the most occidentalist cnovel I ever binged via MTL was about a chinese guy reincarnating into europe right before the black plague & teaching the savage europeans how to cook food and do agriculture and industry properly and inventing an innoculation for the plague and he wound up gay marrying the sexy young pope & collecting a really unreasonable number of magical animal companions along the way, including a tiger. the tiger's introduction led to my favorite author's note in the following chapter, which was basically "I've been informed Europe doesn't have tigers but I don't really give a fuck" ... that was kind of charming.
Definitely a tangent but for some reason the part of this that really snagged my suspension of disbelief was a pope being 'young' so I looked for that and found the following per Wikipedia:
Pope Benedict IX (Latin: Benedictus IX; c. 1012 – c. 1056), born Theophylact of Tusculum in Rome, was the bishop of Rome and ruler of the Papal States for three periods between October 1032 and July 1048 (1032–1044; 1045; 1047–1048).[1] Aged about 20 when first elected, he may have been the youngest pope in the history of the Catholic Church. He is the only person to have been pope more than once[a] and the only person ever accused of selling the papacy.
Anya is live and ready to show you everything. Watch her strip, dance, and perform exclusive shows just for you. Interact in real-time and make your fantasies come true.
✓ Live Streaming✓ Interactive Chat✓ Private Shows✓ HD Quality
Anya is LIVE right now
FREE
Free to watch • No registration required • HD streaming
In my experience, horror fans are by and large lovely people with a very healthy relationship to their genre of choice, but sometimes they fuck up and say something that in their ears sounds very affirmative of the movie of discussion and to everyone else sounds like the most sinister shit.
I mean the line that I think of first is “A kid dies in this movie.”
Which I suspect to horror fans is shorthand for “The director of this movie subverts horror tropes (wherein kids are usually immune to the monster/slasher/source of terror) to make something that is deliberately shocking. Seeing a child character die in this story is not a happy thing or a good thing, but for a horror story emphasizes that nobody is immune to the source of the terror, which makes the horror more serious and scarier.”
And to everybody else just sounds like “Oh this movie’s great! A kid dies in it!”
I don't really watch horror movies but i really enjoy watching analysis of them and i recently found a really interesting yt channel called the monster and the child that analyzes how horror and monsters show the place of children in society and the categories of children who get denied their innocence/childhood such as children who are disabled, queer or racial/ethnic minorities. It's very interesting analysis of ageism/adultism and how it intersects with other aspects of identity through the lens of monster stories/horror
Hello from the east coast! I have encountered these species in my travels (I don’t just cosplay a scientist! 😉) so I have prepared an informational slide for you.
The berries produced by the C. canadensis are edible, but not tasty. The lycopodium is a particularly fascinating vascular plant more closely related to ferns than real bryophytes. Their spores are very oily, hydrophobic and quite flammable. They were historically used in stage theatre (dramatic “explosions”) and to create the flash (tiny explosions) in early photography. Today the spores are still used as a coating on pills/tablets to prevent them from sticking together. 💫
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)
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
Anya is live and ready to show you everything. Watch her strip, dance, and perform exclusive shows just for you. Interact in real-time and make your fantasies come true.
✓ Live Streaming✓ Interactive Chat✓ Private Shows✓ HD Quality
Anya is LIVE right now
FREE
Free to watch • No registration required • HD streaming
This last moment was everything. Our Romeo couldn't stop smiling he was so excited, our Benvolio couldn't stop crying basically the whole time, and our Mercutio looked at both of them with the most love in his eyes you can imagine. It was beautiful.
for those who don't speak academia: "according to our MRI machine, dead fish can recognise human emotions. this suggests we probably should look at the results of our MRI machine a bit more carefully"
So basically, in the psych and social science fields, researchers would (I don't know if they still do this, I've been out of science for awhile) sling around MRIs like microbiolosts sling around metagenomic analyses. MRIs can measure a lot but people would use them to measure 'activity' in the brain which is like... it's basically the machine doing a fuckload of statistics on brain images of your blood vessels while you do or think about stuff. So you throw a dude in the machine and take a scan, then give him a piece of chocolate cake and throw him back in and the pleasure centres light up. Bam! Eating chocolate makes you happy, proven with MRI! Simple!
These tests get used for all kinds of stuff, and they get used by a lot of people who don't actually know what they're doing, how to interpret the data, or whether there's any real link between what they're measuring and what they're claiming. It's why you see shit going around like "men think of women as objects because when they look at a woman, the same part of their brain is active as when they look at a tool!" and "if you play Mozart for your baby for twenty minutes then their imagination improves, we imaged the brain to prove it!" and "we found where God is in the brain! Christians have more brain activity in this region than atheists!"
There are numerous problems with this kind of science, but the most pressing issue is the validity of the scans themselves. As I said, there's a fair bit of stats to turn an MRI image into 'brain activity', and then you do even more stats on that to get your results. Bennett et. al.'s work ran one of these sorts of experiments, with one difference -- they used a dead salmon instead of living human subjects. And they got positive results. The same sort of experiment, the same methodology, the same results that people were bandying about as positive results. According to the methodology in common use, dead salmon can distinguish human facial expressions. Meaning one of two things:
Dead salmon can recognise human facial expressions. OR
Everyone else's results are garbage also, none of you have data for any of this junk.
I cannot overstate just how many papers were completely fucking destroyed by this experiment. Entire careers of particularly lazy scientists were built on these sorts of experiments. A decent chunk of modern experimental neuropsychology was resting on it. Which shows that science is like everything else -- the best advances are motivated by spite.
The main problem addressed by this paper is the lack of correction for multiple comparisons. MRIs are acquired in hundreds of thousands of voxels (three-dimensional equivalent to pixels). In voxel-based analyses, you register the brain to a standardized template and then compare the signal intensity in each voxel coordinate from condition A to the same coordinate in condition B – a mass univariate analysis with hundreds of thousands of individual t-tests, regressions, or ANOVAs, with the signal intensity in a single individual voxel being the dependent variable in each test. Each of these tests has a predetermined significance level, i.e. "we'll interpret this as a significantly different signal intensity if the probability of a false positive is below X percent". In the past, they just slapped "α < .001" (0.1% accepted probability of a false positive, which would be a pretty strict nominal significance level in most other applications!) onto every test.
The problem is that the total probability of a false positive across the entire analysis accumulates with every single test. If you do 100 tests with α < .001, the false positive probability for each individual test is still lower than 0.1%, but the probability that at least one of the 100 tests is falsely positive jumps to 1-(1-0.001)¹⁰⁰ ≈ 0.095 ≈ 9.5%. And in voxel-based analyses, you don't do 100 tests – you usually do at least 500,000 if your resolution is relatively low, millions if your resolution is 1x1x1 mm. The probability for a false positive is so close to 100% that most calculators won't even bother displaying the result of 1-(1-0.001)⁵⁰⁰⁰⁰⁰ as anything other than " = 1". Obviously you will find correlates for emotion recognition in dead fish if the probability of at least one voxel with p < .001 (it'll usually be more than just one voxel) is practically 100% by design.
So modern studies started correcting for multiple comparisons. It's not that the entire methodology was thrown out of the window, it's that our nominal significance levels are far stricter now, so the probability of a false positive in the entire brain is in an acceptable range (usually the classic .05). But that still doesn't mean you can make conclusions like "The """""pleasure centers"""""" lights up when you eat chocolate, so chocolate is pleasurable". You can't just look into the literature, see that brain regions xyz are active in people who report feeling pleasure, and then go "oh, that means that you're always feeling pleasure if regions xyz are active, so my subjects were definitely feeling pleasure when that region lit up as they ate chocolate". And I don't mean "you can't make these conclusions because the literature still contains these old unreliable studies", I mean that this kind of reverse inference is literally not possible with standard univariate statistics.
The "pleasure centers", i.e. a region or a group of regions uniquely responsible for pleasure and nothing but pleasure, simply do not exist. If region x lights up during pleasurable experiences, that means it is involved in pleasure, but it'll be in a complex interplay with the rest of the brain to generate this feeling, and it will have other jobs than generating pleasure as well. Even if you know for a fact that pleasure is impossible without regions xyz (because people with lesions in these areas cannot feel pleasure anymore, or because a disturbance of the regions via transcranial magnetic/electric stimulation diminishes pleasure), that doesn't mean "you must be feeling pleasure if xyz are active". Other cognitive states could activate these brain regions as well. If you want to decode unknown cognitive states from MRI data rather than finding correlates for known cognitive states, you need statistical models that are a lot more complex (Bayesian rather than probabilistic frameworks, multivariate pattern analysis, usually machine learning, definitely some form of validation like cross-validation or two distinct datasets for training and testing your statistical model). And even then, it's iffy because validation can still not account for every single other cognitive state that could create this activity pattern. This point is really important to me because reverse inference is regularly used to hurt minorities, especially people with mental illness. Do not fucking believe any study that says "people with narcissistic personality disorder show less activity in The Caring About Other People Region™, so they're incapable of ever loving you".
And yeah, fMRI is not even a direct measure of brain activity. It measures the blood oxygenation in each voxel, and if the oxygenation in a specific timeframe follows a specific pattern (small dip below baseline first, then a rapid rise), you assume that neurons in the general area of this voxel are currently requiring more oxygen than usual due to their activity. But other factors can affect oxygenation as well. And measuring the oxygenation in the first place is not super straight-forward. Oxygenated hemoglobin has different magnetic properties than non-oxygenated hemoglobin, yes, but the difference is pretty subtle, and if you want a fast acquisition sequence (because changes in oxygenation obviously happen pretty quickly) as well as a decently small voxel size, you'll have a relatively low signal-to-noise ratio where you may confuse artifacts with real changes in oxygenation.
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.
In case you just skimmed the post above and missed it, I want to reiterate and highlight Gebru's current position as Executive Director of Distributed AI Research Institute. If you're curious about what AI technology might look like when not applied in the horrifically unethical and damaging way it's currently applied, please check them out.
If we want to have nice things, decentralization is essential, and if we want to decentralize, we need to have our eyes on things that are beyond the scope of the current Big Tech narrative.
The Distributed AI Research Institute is a globally distributed organization of academics, activists, and engineers conducting community-roo
Anya is live and ready to show you everything. Watch her strip, dance, and perform exclusive shows just for you. Interact in real-time and make your fantasies come true.
✓ Live Streaming✓ Interactive Chat✓ Private Shows✓ HD Quality
Anya is LIVE right now
FREE
Free to watch • No registration required • HD streaming