just saw a 'comments' tab on someones blog you know where the following and likes tabs would be if enabled and it was just showing all the replies theyve made on peoples posts. this is fascinating when did this feature come out
if you've made replies on posts there is now a tab on your blog showing every post youve replied to and your reply.
if this is not what you want, either go to your blog and click comments and disable it from there or just go to your individual blogs setting pages. just change it from blue to grey if you dont want everyone to see your replies AND the post you're replying to
PLEASE BE ADVISED that it is set to disabled for blogs that have not made any replies but it will turn ON if you reply with that blog in the future.! i just tested it with my main, which was greyed out but it turned on the moment i left a test reply
figured i'd get the word out bc i have not seen a single mention of this and i'm sure there are plenty of people who maybe comment on things they don't want on display for everyone to see on their blog lol. you can still look at your replies with it toggled off just no one else can, like locking the following and likes list
so for some reason this feature was actually announced on the tumblr engineering blog. interesting choice not to reblog it to the staff or tumblr blog, esp considering they asked for user input on how to implement it, but i suppose considering the response to the last update maybe the replies would be too overwhelming...
so couple of clarifications. comments are disabled as default for primary blogs that have their likes disabled. they are seemingly enabled for all other blogs that have replied to posts
posts you comment on may show on your followers 'for you' page if you leave your replies publically available. they may, in the future, show in on your followers dashboard if your follower goes to their dash settings and enables this. apparently, if your likes are enabled, your followers can already see those on the dash if they've gone into preferences and selected to do so, which I was unaware of, and that seems to be disabled at default, but it's possible i disabled it previously and forgot about it ig
just had a weird black spider the size of a nickel in my cup from last night and i didn't freak out or kill it, i lidded it and took it outside. i demand accolades. i am braver than any us marine.
Dead wife montage but it's all slow motion shots of your dead wife throwing grenades and doing backflips and oneshotting the enemy with their long range weapons
The Odyssey but retold as a low-stakes modern adventure of one guy out with his girlfriend leaving the bar with his buddies to do just one (1) simple thing real quick, it'll take like 15 minutes tops, he'll be right back, but then some bullshit happens and the trip keeps getting more complicated as more bullshit keeps happening while he just tries to get back to the bar because he promised his girlfriend that he'd get back and he knows that she's still there because she told him she'd wait there.
And by the time he finally gets back it's almost 3 am and the bar is about to close while she's sitting there stone cold sober, surrounded by 5 drunk guys unsuccessfully trying to convince her to give up on waiting for him and go home with one of them instead. And the guy shows up to proceed to beat the shit out of them before explaining himself to her like hey sorry bullshit kept happening, my phone fell into a storm drain and my wallet got stolen when I was trying to find someone who'd borrow me a phone so I could call and
His girlfriend had been fending off the 5 drunk guys for most of the evening by explaining that even if she was going to ditch her boyfriend, she can't possibly leave without finishing her beer, which she is keeping perpetually full via careful sleight of hand where she's just pouring it back and forth into and out of the pitcher.
However the drunk guys are also drinking, and eventually she can't afford to buy another pitcher for the table so she can't keep up the ever-full beer glass trick. At this point she has to resort to setting up the pool trick shot that she's never seen anyone but her boyfriend pull off, and says she'll leave with whoever manages the shot first.
That buys her another hour or so and then, finally, her boyfriend makes it back. He looks like shit, hair down and just a mess, he's wearing an entirely different jacket that he got from an alley, and barely recognizable—especially to 5 guys who've been drunk for hours now. He lurks for a minute, finds out what's going on, and proceeds to pull off the trick shot first try. Throws the jacket off, fixes his hair with a hair tie his girlfriend lends him, finally looks like himself again, and THEN beats the shit out of them with the pool cue.
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.
So. For those of you who didn't pay attention to the details of the legal spat between Krafton and Unknown Worlds, allow me to give you some details of the finest legal comedy of a generation.
Krafton CEO looks at the hype surrounding Subnautica 2, goes over the contract between Krafton and Unknown Worlds, realizes he'll have to pay out bonuses and freaks out because shelling out those bonuses will make him look like a pushover.
CEO goes to his legal department, asks them to come up with a plan to weasel out of paying bonuses. Legal tells him the contract is iron-clad and to accept the loss.
CEO refuses to take the loss, asks ChatGPT for a plan. ChatGPT says the exact same thing the legal department did.
CEO demands a plan from ChatGPT, which dutifully spits out a plan at this point because clearly the CEO is a goddamn idiot.
CEO deletes the chat logs, failing to understand that 'delete' doesn't permanently remove things.
CEO follows plan, and is surprised when Unknown Worlds sues for breach of contract despite being told by both humans and an LLM that is exactly what would happen.
Court does not go well for Krafton's legal department. It comes out that after ignoring the sound legal advice of human beings, the CEO went to ChatGPT and asked for a plan. When asked for the logs by the court, Krafton's legal team states they were deleted, thus that it's simply herersay. Judge goes "Oh, that's okay, we'll have our IT folks recover them." Krafton's legal team is astounded that's even possible.
The chat logs are recovered. It comes out that even ChatGPT was in agreement with Krafton's legal department, and only spat out a plan after being asked a second time.
The judge, now thoroughly done with the stupidity of Krafton's CEO at this point, rules in favor of Unknown Worlds. Her ruling doesn't simply undo the scheme, but effectively leaves all control over Subnautica 2's development in the hands of Unknown Worlds, including the early access release date, reducing Krafton to just publishing out of contractual obligation. Krafton must also return all social media platforms for Unknown Worlds and Subnautica 2 to Unknown Worlds' control. Financial damages will be determined at a later date.
Krafton proceeds to violate the court order in less than 72 hours by trying to set an early access release date before returning Unknown Worlds' social media platforms.
Summary: In trying not to look like a pushover, Krafton's CEO now looks like a complete idiot who's going to have to fork over bonuses, plus court-mandated damages, plus whatever comes out of violating the court's orders. Krafton's legal department may as well come to court dressed as clowns after this. I suspect Unknown Worlds might buy the rights to Subnautica back after all this and either relegate Krafton to just publishing or find a different publisher for future games altogether.
So much translation discourse just boils down to monolinguals not understanding that "coolness" doesn't translate across languages, and you need to re-add it manually on the other end.
No no, not literally the word "cool" I mean the [concept of coolness]. Things that sound cool, poetic, funny, dramatic, etc in one language will completely fail to land if you simply go 1-to-1 word equivalents.
In the Japanese version of Fullmetal Alchemist, the antagonists are named after the seven deadly sins, in English. As in, rather than the Japanese word, "Greed" is still Greed in the original.
Because loan words from English are often pretty "cool", as with your Spanish and French example.
But this presents a problem, because, to give them a bit of flair, the antagonists are sometimes given a proper Japanese adjective along with their name, to make a sort of title of sorts.
"Greedy Greed"
The italicized part would be a Japanese adjective, and the bolded part is an English loanword. This is fine in Japanese, but would be totally nonsense in an English translation.
After all, it's common sense to keep the names the same, duh, and obviously the whole point of what you're doing is to translate the Japanese.
Greedy Greed. You cannot call him that.
You can't go 1-to-1. To keep the [concept of coolness], you have to identify what made the original cool, and then recreate it in the new language.
And here, we have a foreign word, and a native word, both meaning the same thing, paired together to give an antagonist a cool sounding title. So how do we do that in English.
Well, the seven deadly sins, being Christian and Catholic and all, have fancy names in Latin. Or well, they just sound fancy in English, because Latin was the language of intellectuals for a long long time.
And in fact, while we also have the word "greed", English has a fancier sounding word that means the same thing, but whose etymology comes from the fancy Latin. That might give a similar cool-loanword feeling, right?
snowghoul
jbbartram-illu
titsay
annaxmalina
vaporwave
pixelskylines
