is world cup That Important for other countries too? i remember when i was in school that if our team was going to play, the class would be cancelled and now im wondering if that's just a brazil thing or no
My job will literally let us stop working a full hour before the brazilian games start so we can get home/to the bar we want. For some games thats 4 hours early. With no paycut of course.
Tau Sky Rays in Venom: Space Knight #6 (2016) you can even see a Tau symbol (on the weirdly shrunken door, possibly to try and hide the symbol?) in the second image, I think they might literally be this free 3D model
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.
The thing about the Clone Saga as it drags on is that there are so many places where you are like "oh this would make a great endpoint for the arc!" except no... it never ends... it just keeps going.
If I could ink like anyone, it would be Ronald Searle. His book, “Paris Sketchbook” is a personal journal he and his wife would keep when they would holiday in Paris. The book sits proudly on my bookshelf. And if you ever have a chance to pick it up, do so.
when pete accuses mj of not caring about gwen's death in 122, do we ever get to see the aftermath of that? is that ever brought up again in peter and mj's relationship? bc if i was mj in that situation, i probably would have slapped peter across the face, idc if that sob is grieving, so is mj
I think it’s pretty natural to look at Peter lashing out at Mary Jane at the end of Amazing Spider-Man #122 and to feel frustrated by his behavior, or that Mary Jane would have been justified in lashing out. After all, he not only accuses her of not caring about Gwen, but also (ignorantly on his part) sticks the knife in her ribs by saying she wouldn’t care if her own mother was dead, when Mary Jane’s mother is dead and when that death has informed a lot of Mary Jane’s behavior.
I think part of the success of this scene is Gil Kane’s art -- if you look at the last three panels, Peter’s head is hung low and then his face is buried in his hands. He’s not looking at Mary Jane while he verbally attacks her; he can’t see her face. We, the reader, know he’s being horribly unfair because we can, and no matter what you think Mary Jane’s relationship with Gwen was at this time -- and I think canon is pretty clear that they were friends, although I know this is a somewhat contentious view in parts of Spider-Man fandom -- you can see that’s real pain on her face. She’s crying, her posture is defeated. Peter doesn’t see that, but we do. So I think it’s very natural to sympathize with Mary Jane here and to feel like this is something that, ideally, at some point, they would talk about.
That being said, if they ever talk about it, it’s not on the page (as of the writing of this post anyway), and I personally don’t feel it’s something that canon ever needs to directly address. I think this scene serves a couple of points -- one is definitely that it bookends Peter’s earlier behavior with Harry, who begs him to stay with him, only for Peter to leave. This scene is a reversal of Peter’s abandonment of Harry: not only does Mary Jane stay, she stays in the face of Peter’s grief-stricken cruelty. I think the second thing here, though, is at this point in canon, neither Peter nor we the reader know very much about Mary Jane at all. One of the first things Mary Jane tells Peter is that she’s an actress, and that’s very much been true up until this point. She’s played flighty, the party girl, flirtatious with Peter even after he’s essentially engaged to Gwen but never very serious. We have a few hints scattered here and there: once, when Peter asked her what the bit was for, she says it’s a long story. So we know she has a past. We just don’t know anything about it. It’s important to note that that’s because Peter himself, as our viewpoint character here, hasn’t really thought much about that, either. Mary Jane at this point in canon is still very much an enigma. Even after we learn about Mary Jane’s past -- a whole 100 plus issues past this point, after Peter’s first marriage proposal to her -- Mary Jane is a very internal character. She plays her cards close to her chest. I think this is in contrast to Peter, who is very external with his feelings. Even when he’s locking them up tight inside and throwing him into Spider-Man, he’s still acting upon them, whereas Mary Jane can keep things locked up very tight inside.
So this glimpse of Mary Jane staying in the face of Peter lashing out is our first look into Mary Jane, minus the walls. It’s about her vulnerability, her kindness, her serious side. Mary Jane staying with Peter in her grief, while Peter left Harry in his. Peter’s face is still in his hands in this scene; he’s not seeing this, but the reader, as an observer, is. So I don’t think it’s necessarily something that has to be addressed in canon directly, because while it’s definitely a turning point in Peter and Mary Jane’s relationship, it’s also a new viewpoint for the reader into Mary Jane’s character. Because, his cruelty in his grief aside, and that’s something we’ve already seen in this issue, this one closing scene isn’t really about Peter. It’s not telling us anything new about him, but it is throwing open a whole new perspective on Mary Jane.
I really do like the Marvel 1000 throwback to this scene from Mary Jane’s perspective, written by Gerry Conway, the author of Amazing Spider-Man #122, which offers Mary Jane’s own thoughts on that night:
“My aunt, she knew how I was. And she asked me once. I guess she was surprised. “Why did you stay with Peter that night, honey?” What she meant was, why did you do that for him? She didn’t understand. Even Peter doesn’t understand. We never really talked about it. I didn’t stay for him. I stayed because she’d shown me how. I stayed for Gwen.”
She got a bit better looking when she joined the X-Men, and even more so when Alan Davis (who is physically incapable of not drawing a beautiful women) put Marrow through a beautifying machine to make her "normal".
I like these characters. There's nothing wrong with being unattractive.
okay of all the stupid things ai is used for i truly cannot wrap my head around why it appears to have replaced the search engine for a lot of people. it is functionally identical to using a search engine except sometimes it lies to you. and you guys prefer this because..??????
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