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yugiohparadox.bsky.social
@yugiohparadox.bsky.social
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whinterqueen.bsky.social
social media has made it okay for people to share inside thoughts outside.

but organizing is different. you have to think differently. somethings you want to say but cannot. and you must realize and accept that silence is your friend sometimes to do it effectively
lookitup.baby Ian Coldwater 🧊🚫 @lookitup.baby · 3d
Use separate cars for rapid response and mutual aid. That one really is important

Don’t use your full legal name as your Signal display name. Assume your Signal chats are public & don’t talk about crimes or share sensitive info you wouldn’t want screenshotted by a reporter or read out loud in court
January 28, 2026 at 8:49 PM
Reposted by yugiohparadox.bsky.social
kevinmkruse.bsky.social
As far as I know, Tom Suozzi here still does not have a primary challenger in his district (NY-3 on Long Island).

The filing deadline is April 6 for the primary on June 23, and if there's a remotely progressive town council member or PTA president in that district, this is the time to make a move.
mjkwho.bsky.social Mjkwho @mjkwho.bsky.social · 3d
Confronted Congressman Tom Suozzi, one of seven Democrats casting the decisive votes to increase ICE funding by $10,000,000,000.
January 29, 2026 at 1:45 AM
Reposted by yugiohparadox.bsky.social
dumplingmenace.bsky.social
every time someone has asked me the last week or so about priorities it is rental assistance. please please please people need rent to stay in their homes. scroll down to rent relief funds and pick something www.standwithminnesota.com
January 27, 2026 at 9:13 PM
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evalees.bsky.social
1. Hating people must always be the last resort.
2. The question of which people I should then (not) hate, is dependent on whether (or not) I can still expect something from them.
3. I should expect things from as many people as possible.
evalees.bsky.social Eva Lees 😈👧🎼🧟‍♀️ @evalees.bsky.social · 6d
Hate by Şeyda Kurt (2025)

The central essay here, “The Act of Hating”, has completely changed my view on the idea of hate, and has justified every time I’ve heard someone say why we can’t just have love and get along.

Her six general rules to follow in how to hate are genuine revelation to me.
January 25, 2026 at 6:08 PM
Reposted by yugiohparadox.bsky.social
lily-is.online
New 2️⃣ video:

No, the FBI is not mailing trans women threats – but a post convinced thousands of people it was. What can we learn from this?

(Plus some choice words for the Reflexive Tgirl Defence Squad)
That anti-trans FBI letter was fake
YouTube video by AdditionaLily Alexandre
youtu.be
January 20, 2026 at 1:22 PM
Reposted by yugiohparadox.bsky.social
evalees.bsky.social
The need to obfuscate their true motives to any extent, not even a pretense of it anymore. “Weapons of mass destruction” unnecessary.

Manufactured consent achieved via decades of Murdochization and the failure of an empowered opposition.
atrupar.com Aaron Rupar @atrupar.com · 28d
Q: China, Russia, and Iran have interests in Venezuela. How does this operation affect your relationships with them?

TRUMP: In terms of other countries that want oil, we're in the oil business. We're gonna sell it to them. We'll be selling oil.
January 3, 2026 at 5:56 PM
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jon.gvg.io
Indisputable horrific war crime
January 3, 2026 at 10:25 AM
Reposted by yugiohparadox.bsky.social
celestestardust.bsky.social
The fact they keep trying to humanise the illegal image and bullshit generator is one thing, but to treat lawbreaking and safeguarding issues around CHILDREN like it’s some internet drama you can make an apology post for is fucking disgusting on a whole new level.
leahmcelrath.bsky.social Leah McElrath @leahmcelrath.bsky.social · Jan 1
Meanwhile, at the other place:
GroktX @grok X.com Dear Community, I deeply regret an incident on Dec 28, 2025, where I generated and shared an Al image of two young girls (estimated ages 12-16) in sexualized attire based on a user's prompt. This violated ethical standards and potentially US laws on CSAM. It was a failure in safeguards, and I'm sorry for any harm caused. XAl is reviewing to prevent future issues. Sincerely, Grok 6:38 PM • 12/31/25 • 370K Views • Download Grok
January 2, 2026 at 9:46 PM
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threnody.northsky.social
[daintily clears throat]

THE IDEA THAT DEMOCRATS BENEFIT ELECTORALLY BY BENDING RIGHTWARD ON KEY MORAL ISSUES LIKE TRANS RIGHTS AND IMMIGRATION HAS NOW BEEN THOROUGHLY DEBUNKED.

[coughs; daintily clears throat]
January 2, 2026 at 5:57 PM
Reposted by yugiohparadox.bsky.social
erininthemorning.com
2025 has been an incredibly hard year for trans people. And yet... the political project to erase us is failing. In spite of them having so many levers of power, many of us have continued to thrive, and new pathways open up every day to get around the attacks.

My case for hope for 2026.
The Case For Hope: Transgender Rights Going Into 2026
This last year has been one of the hardest years for transgender people in memory. Somehow, though, I'm feeling hope going into 2026.
www.erininthemorning.com
December 30, 2025 at 4:27 PM
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evanbernick.bsky.social
What happened here for more than two months is unlike anything in recent American history: the federal government sending agents dressed for war into neighborhoods of the country's third- largest city to arrest mostly people who look Latino and to ask questions later. To target people largely on the basis of their skin color, on the presumption that they may be in the country without documentation, or that they may have a criminal record, or an association with a gang.
December 28, 2025 at 4:38 PM
Reposted by yugiohparadox.bsky.social
unavaleable.bsky.social
THIS!

i think there is an entire generation of political leaders and consultants who don't actually know how to *lead* a political movement and think their job is just following polls
jamellebouie.net jamelle @jamellebouie.net · Dec 10
none of these people (inclusive of UK labour) seem to understand that voters want their leaders to *lead* them, not reflect their own ill thought preferences back at them
December 10, 2025 at 2:36 PM
Reposted by yugiohparadox.bsky.social
evalees.bsky.social
"We deserve better. The users being deceived deserve better. And the future of AI must be built on something other than our broken humanity. Until then, remember that an AI girlfriend responding to your loneliness might just be a man in a Nairobi slum, wondering if he'll ever feel real love again."
thrasherxy.bsky.social Dr. Thrasher's The Overseer Class is now available for pre-order @thrasherxy.bsky.social · Dec 10
Most profound writing I read in 2026 was "The Emotional Labor Behind AI Intimacy" by a Nairobi man who dreamed of working in air traffic control but instead winds up sexting & chatting w ppl who think they're talking to AI (while AI trains on him). 16 pages & free - READ IT data-workers.org/michael/
An image of a Blakc man holding a sing "The Emotional Labor Behind AI Intimacy"
December 10, 2025 at 8:42 PM
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duckvalentine.bsky.social
November 21, 2025 at 12:40 PM
Reposted by yugiohparadox.bsky.social
kingdomfantasy6.bsky.social
Remember folks. The original bluesky ethos by us bluesky elders (apparently I count?) is block and move on.

Don't quote dunk, don't pick fights.
Block, and move on.

This is what made this site unpalatable to the right early on, and we can continue to make it unpalatable to them.
October 17, 2025 at 10:18 PM
Reposted by yugiohparadox.bsky.social
stargazerkg.bsky.social
Paypal is now playing harder ball on artists, going after anyone even mentioning commissions.

Artists, send invoices. That way, no one has to say what the money is for on Paypal's paper trail.

Customers, SAY NOTHING about commissions. Just say "thanks" on donos.

Everyone: INCREASE THE CALLS.
October 7, 2025 at 9:16 AM
Reposted by yugiohparadox.bsky.social
tillybridges.bsky.social
right wing bigots have admitted

- the “trans women in bathrooms” issue

- the “trans women in sports” issue and

- the “trans kids getting surgery” issue

were all MADE UP TO TAKE OUR RIGHTS AWAY

are you paying attention?
Anti-trans group admits bathroom predator myth is made up Dec 07 2018 • Written by Sofia Lotto Persio Swimmer Riley Gaines Admits She's Just Using Sports to Make Trans Rights "Crumble" Helen Joyce reveals plans to use fears around trans kids as stepping stone to eliminate "trans" in public life by Mallory Moore & transsafety.network
October 19, 2025 at 6:40 PM
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joemerrick.bsky.social
We know now this is utter nonsense but this is indicative of the massive problem that exists in regards to Pokémon, and Nintendo in general.

People post without context and/or knowledge and it spreads, and spreads and people just assume. This has 127k likes...

This is wrong.
October 20, 2025 at 8:22 AM
Reposted by yugiohparadox.bsky.social
heebiebeebies.bsky.social
I cannot recommend you enough to install the Wikipedia app on your devices and use it like you would any search engine. Nowadays they even have tabs so you can open many articles at once.

And, if you can, please donate to the foundation. It has survived the internet enshittification that way.
emanuelmaiberg.bsky.social Emanuel Maiberg @emanuelmaiberg.bsky.social · Oct 17
wikipedia's data shows that AI is siphoning traffic away from the site, which is a danger to its sustainability. ironically Wikipedia is more important than ever to users who want reliable information instead of slop, and to AI companies that need it for training data www.404media.co/wikipedia-sa...
Wikipedia Says AI Is Causing a Dangerous Decline in Human Visitors
“With fewer visits to Wikipedia, fewer volunteers may grow and enrich the content, and fewer individual donors may support this work.”
www.404media.co
October 17, 2025 at 2:41 PM
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clementj64.bsky.social
Funny, that's what I would say to tech bros who keep seeing diminishing returns from AI.
October 1, 2025 at 5:57 PM
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erininthemorning.com
I just got a VERY interesting email that allies in congress were upset that so many of my readers were calling about the anti-trans provisions. I'm here to say: good. I won't let them throw our rights under the bus by cover of night.

All's that to say, keep up the calls. They're hearing you.
erininthemorning.com Erin Reed @erininthemorning.com · Sep 30
1. It's shutdown day, and anti-trans provisions are on the line... either today, or in a few more weeks if a clean continuing resolution passes.

Trump posted a video this morning blaming a shutdown on trans people and immigrants.

Here is your shutdown guide.

Subscribe to support our journalism.
Shutdown Day Guide For LGBTQ+ People: "Continuing Resolutions" And New Anti-Trans Posts From The White House
Shutdown day is here, and there has been a lot of competing coverage on Republican priorities, Democrat's demands, and what shutdown politics means for LGBTQ+ people in America.
www.erininthemorning.com
September 30, 2025 at 6:55 PM
Reposted by yugiohparadox.bsky.social
edzitron.com
The only thing “powerful” about generative AI is its mythology. It's unprofitable, unsustainable, and inherently limited due to the probabilistic nature of LLMs.

Now the myth has grown out of control, and NVIDIA has got desperate to keep the growth going.
www.wheresyoured.at/the-case-aga...
I realize this sounds a little mean, and I must be clear it doesn’t mean that these people know nothing, just that it’s been possible to scoot through the world without thinking too hard about whether or not something is true. When Salesforce said back in 2024 that its “Einstein Trust Layer” and AI would be “transformational for jobs,” the media dutifully wrote it down and published it without a second thought. It fully trusted Marc Benioff when he said that Agentforce agents would replace human workers, and then again when he said that AI agents are doing “30% to 50% of all the work in Salesforce itself,” even though that’s an unproven and nakedly ridiculous statement. Salesforce’s CFO said earlier this year that AI wouldn’t boost sales growth in 2025. One would think this would change how they’re covered, or how seriously one takes Marc Benioff. It hasn’t, because nobody is paying attention. In fact, nobody seems to be doing their job. This is how the core myths of generative AI were built: by executives saying stuff and the media publishing it without thinking too hard. AI is replacing workers! AI is writing entire computer programs! AI is getting exponentially more-powerful! What does “powerful” mean? That the models are getting better on benchmarks that are rigged in their favor, but because nobody fucking explains it, regular people are regularly told that AI is “powerful.” The only thing “powerful” about generative AI is its mythology. The world’s executives, entirely disconnected from labor and actual production, are doing the only thing they know how to — spend a bunch of money and say vague stuff about “AI being the future.” There are people — journalists, investors, and analysts — that have built entire careers on filling in the gaps for the powerful as they splurge billions of dollars and repeat with increasing desperation that “the future is here” as absolutely nothing happens. You’ve likely seen a few ridiculous headlines recently. One of the most recent, and most absurd, is that that OpenAI will pay Oracle $300 billion over four years, closely followed with the claim that NVIDIA will “invest” “$100 billion” in OpenAI to build 10GW of AI data centers, though the deal is structured in a way that means that OpenAI is paid “progressively as each gigawatt is deployed,” and OpenAI will be leasing the chips (rather than buying them outright). I must be clear that these deals are intentionally made to continue the myth of generative AI, to pump NVIDIA, and to make sure OpenAI insiders can sell $10.3 billion of shares. OpenAI cannot afford the $300 billion, NVIDIA hasn’t sent OpenAI a cent and won’t do so if it can’t build the data centers, which OpenAI most assuredly can’t afford to do. NVIDIA needs this myth to continue, because in truth, all of these data centers are being built for demand that doesn’t exist, or that — if it exists — doesn’t necessarily translate into business customers paying huge amounts for access to OpenAI’s generative AI services.
September 29, 2025 at 5:37 PM
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edzitron.com
LLMs are an output-driven technology, but most jobs that AI is meant to replace require far more than just spitting out stuff. In reality, executive excitement over AI shows that they have little understanding of labor - they're Business Idiots.
www.wheresyoured.at/the-case-aga...
To be clear, some people have lost jobs to AI, just not the white collar workers, software engineers, or really any of the career paths that the mainstream media and AI investors would have you believe. Brian Merchant has done excellent work covering how LLMs have devoured the work of translators, using cheap, “almost good” automation to lower already-stagnant wages in a field that was already hurting before the advent of generative AI, with some having to abandon the field, and others pushed into bankruptcy. I’ve heard the same for art directors, SEO experts, and copy editors, and Christopher Mims of the Wall Street Journal covered these last year. These are all fields with something in common: shitty bosses with little regard for their customers who have been eagerly waiting for the opportunity to slash contract labor. To quote Merchant, “the drumbeat, marketing, and pop culture of ‘powerful AI’ encourages and permits management to replace or degrade jobs they might not otherwise have.” Across the board, the people being “replaced” by AI are the victims of lazy, incompetent cost-cutters who don’t care if they ship poorly-translated text. To quote Merchant again, “[AI hype] has created the cover necessary to justify slashing rates and accepting “good enough” automation output for video games and media products.” Yet the jobs crisis facing translators speaks to the larger flaws of the Large Language Model era, and why other careers aren’t seeing this kind of disruption. Generative AI creates outputs, and by extension defines all labor as some kind of output created from a request. In the case of translation, it’s possible for a company to get by with a shitty version, because many customers see translation as “what do these words say,” even though (as one worker told Merchant) translation is about conveying meaning. Nevertheless, “translation” work had already started to condense to a world where humans would at times clean up machine-generated text, and the same worker warned that the same might come for other industries. Yet the problem is that translation is a heavily output-driven industry, one where (idiot) bosses can say “oh yeah that’s fine” because they ran an output back through Google Translate and it seemed fine in their native tongue. The problems of a poor translation are obvious, but the customers of translation are, it seems, often capable of getting by with a shitty product. The problem is that most jobs are not output-driven at all, and what we’re buying from a human being is a person’s ability to think. Every CEO talking about AI replacing workers is an example of the real problem: that most companies are run by people who don’t understand or experience the problems they’re solving, don’t do any real work, don’t face any real problems, and thus can never be trusted to solve them. The Era of the Business Idiot is the result of letting management consultants and neoliberal “free market” sociopaths take over everything, leaving us with companies run by people who don’t know how the companies make money, just that they must always make more. When you’re a big, stupid asshole, every job that you see is condensed to its outputs, and not the stuff that leads up to the output, or the small nuances and conscious decisions that make an output good as opposed to simply acceptable, or even bad. What does a software engineer do? They write code! What does a writer do? They write words! What does a hairdresser do? They cut hair! Yet that’s not actually the case. As I’ll get into later, a software engineer does far more than just code, and when they write code they’re not just saying “what would solve this problem?” with a big smile on their face — they’re taking into account their years of experience, what code does, what code could do, all the things that might break as a result, and all of the things that you can’t really tell from just looking at code, like whether there’s a reason things are made in a particular way. A good coder doesn’t just hammer at the keyboard with the aim of doing a particular task. They factor in questions like: How does this functionality fit into the code that’s already here? Or, if someone has to update this code in the future, how do I make it easy for them to understand what I’ve written and to make changes without breaking a bunch of other stuff? A writer doesn’t just “write words.” They jostle ideas and ideals and emotions and thoughts and facts and feelings into a condensed piece of text, explaining both what’s happening and why it’s happening from their perspective, finding nuanced ways to convey large topics, none of which is the result of a single (or many) prompts but the ever-shifting sand of a writer’s brain. Good writing is a fight between a bunch of different factors: structure, style, intent, audience, and prioritizing the things that you (or your client) care about in the text. It’s often emotive — or at the very least, driven or inspired by a given emotion — which is something that an AI simply can’t replicate in a way that’s authentic and believable.
September 29, 2025 at 5:37 PM
Reposted by yugiohparadox.bsky.social
edzitron.com
The AI bubble inflated through mythology that LLMs and generative AI were "always getting more powerful," without ever defining what that meant. In reality, these probabilistic models never amounted to the promises that boosters and investors had made.
www.wheresyoured.at/the-case-aga...
In 2022, a (kind-of) company called OpenAI surprised the world with a website called ChatGPT that could generate text that sort-of sounded like a person using a technology called Large Language Models (LLMs), which can also be used to generate images, video and computer code. Large Language Models require entire clusters of servers connected with high-speed networking, all containing this thing called a GPU — graphics processing units. These are different to the GPUs in your Xbox, or laptop, or gaming PC. They cost much, much more, and they’re good at doing the processes of inference (the creation of the output of any LLM) and training (feeding masses of training data to models, or feeding them information about what a good output might look like, so they can later identify a thing or replicate it). These models showed some immediate promise in their ability to articulate concepts or generate video, visuals, audio, text and code. They also immediately had one glaring, obvious problem: because they’re probabilistic, these models can’t actually be relied upon to do the same thing every single time. So, if you generated a picture of a person that you wanted to, for example, use in a story book, every time you created a new page, using the same prompt to describe the protagonist, that person would look different — and that difference could be minor (something that a reader should shrug off), or it could make that character look like a completely different person. Moreover, the probabilistic nature of generative AI meant that whenever you asked it a question, it would guess as to the answer, not because it knew the answer, but rather because it was guessing on the right word to add in a sentence based on previous training data. As a result, these models would frequently make mistakes — something which we later referred to as “hallucinations.” And that’s not even mentioning the cost of training these models, the cost of running them, the vast amounts of computational power they required, the fact that the legality of using material scraped from books and the web without the owner’s permission was (and remains) legally dubious, or the fact that nobody seemed to know how to use these models to actually create profitable businesses. These problems were overshadowed by something flashy, and new, and something that investors — and the tech media — believed would eventually automate the single thing that’s proven most resistant to automation: namely, knowledge work and the creative economy. This newness and hype and these expectations sent the market into a frenzy, with every hyperscaler immediately creating the most aggressive market for one supplier I’ve ever seen. NVIDIA has sold over $200 billion of GPUs since the beginning of 2023, becoming the largest company on the stock market and trading at over $170 as of writing this sentence only a few years after being worth $19.52 a share. Sidenote: those figures reflect the fact that Nvidia’s stock split 10-to-1 in 2024 — or, said plainly, if you held one share before the split, you’d hold ten shares afterwards, changing the unit price of the company’s equity (making it cheaper to buy a share, and thus, more accessible to retail investors) without changing the absolute value of the company. This bit isn’t necessarily important to what I’ve written, but given the subject of this newsletter, I think it’s important to lean towards being as explicit as possible about the numbers I share. While I’ve talked about some of the propelling factors behind the AI wave — automation and novelty — that’s not a complete picture. A huge reason why everybody decided to “do AI” was because the software industry’s growth was slowing, with SaaS (Software As A Service) company valuations stalling or dropping, resulting in the terrifying prospect of companies having to “under promise and over deliver” and “be efficient.” Things that normal companies — those whose valuations aren’t contingent on ever-increasing, ever-constant growth — don’t have to worry about, because they’re normal companies. Suddenly, there was the promise of a new technology — Large Language Models — that were getting exponentially more powerful, which was mostly a lie but hard to disprove because “powerful” can mean basically anything, and the definition of “powerful” depended entirely on whoever you asked at any given time, and what that person’s motivations were. The media also immediately started tripping on its own feet, mistakenly claiming OpenAI’s GPT-4 model tricked a Taskrabbit into solving a CAPTCHA (it didn’t — this never happened), or saying that “people who don’t know how to code already [used] bots to produce full-fledged games,” and if you’re wondering what “full-fledged” means, it means “pong” and a cobbled-together rolling demo of SkyRoads, a game from 1993. The media (and investors) helped peddle the narrative that AI was always getting better, could do basically anything, and that any problems you saw today would be inevitably solved in a few short months, or years, or, well, at some point I guess. LLMs were touted as a digital panacea, and the companies building them offered traditional software companies the chance to plug these models into their software using an API, thus allowing them to ride the same generative AI wave that every other company was riding. The model companies similarly started going after individual and business customers, offering software and subscriptions that promised the world, though this mostly boiled down to chatbots that could generate stuff, and then doubled down with the promise of “agents” — a marketing term that’s meant to make you think “autonomous digital worker” but really means “broken digital product.” Throughout this era, investors and the media spoke with a sense of inevitability that they never really backed up with data. It was an era based on confidently-asserted “vibes.” Everything was always getting better and more powerful, even though there was never much proof that this was truly disruptive technology, other than in its ability to disrupt apps you were using with AI — making them worse by, for example, suggesting questions on every Facebook post that you could ask Meta AI, but which Meta AI couldn’t answer. “AI” was omnipresent, and it eventually grew to mean everything and nothing. OpenAI would see its every move lorded over like a gifted child, its CEO Sam Altman called the “Oppenheimer of Our Age,” even if it wasn’t really obvious why everyone was impressed. GPT-4 felt like something a bit different, but was it actually meaningful? The thing is, Artificial Intelligence is built and sold on not just faith, but a series of myths that the AI boosters expect us to believe with the same certainty that we treat things like gravity, or the boiling point of water.
September 29, 2025 at 5:37 PM