Blogging on my current hyper-fixations and bringing everyone else along for the ride! Latest obsession Stargate SG-1, 80s MacGyver, and everything RDA ☺️☺️☺️😈😈😈❤️❤️❤️
I know that I had somewhat unusually comprehensive sex ed but it still surprises me every time I'm reminded that some people genuinely think that losing your virginity is a capri sun kind of situation.
Every other site's algorithm: Here is an endless stream of content we have decided you might like. If you slip and forget to bookmark something, you will likely never encounter it again.
Tumblr's algorithm: Here is one post we have decided you WILL like. We are going to keep bringing it up, forever.
Find for me the execs who decided to pull the plug on the new Stargate show for fearing it would only appeal to Stargate fans & bring them to me, alive is preferable, but not required
Given the state of the future of the Stargate franchise, I know that for myself and many fans fan fiction is where we go for our Stargate fix.
In the spirit of this, here are some of the Stargate fan fiction archives, outside of AO3 and FF.net, that I have found on my travels. I will post more as I find them 😊
The Place of Our Legacy (great name): a fic archive from around the year 2000
Jackfic.net: a website focusing on Jack O'Neill fics from around 2004 to 2007
Samandjack.net: for all you Sam/Jack shippers. Fics from 1998 all the way to 2021
Heliopolis archive: an archive of SG1 and Atlantis fics. The main page has links to associated fic archives.
O'Neill's House: the website of the author BadgerGater who was a fan fic award winner back in the 2000s
Super disappointed about the cancellation of the new Stargate show, but then also not surprised. I have started enough good shows to just watch them get cancelled to never get my hopes up. Hell, I have been waiting for years for the new Jurassic Park Survival game and as far as I'm concerned, until it is in my hands, it doesn't exist.
Also, Amazon needs $400million to make another season of Rings Of Power, and who are we to question that?! 🫠
How many am I allowed? I have many! I will do in season order 😃
S1E11: Nightmares: it's whumpy and I enjoy Mac and Lisa's friendship.
S1E22: The Assassin: one of the better bad guys and poor Mac getting his butt kicked twice!
S2E8: Eagles: so wholesome, Mac saving wildlife from bad guys with the help of a little ginger kid.
S2E11: Pheonix Under Fire: MacGyver does Die Hard before Die Hard! And another cool baddie. I also like it when Harry shows up.
S2E21: DOA MacGyver: who doesn't love an good amnesia storyline? Such a classic 80s trope.
S3E4: Ghost Ship!: (I added the exclamation mark coz I feel like it needs it) A creepy abandoned boat, a legit jumpscare and Mac fights Big Foot!
S3E8: The Widowmaker: This and Ghost Ship are probably my legit faves! Mac is all sad as his friend dies, Nikki tries to snap him out of it, and Murdoch shows up. Quality!
S3E15: The Negotiator: she is so pretty and so evil!
(Am I taking the piss? You only asked for one. I will wrap this up, I promise!)
S4E1: The Secret of Parker House: Penny is back and her house is haunted!
S4E15: The Invisible Killer: who is the bad guy?! Just a great all round episode!
S6E19: Humanity: more whump. Mac makes friends with the guy who shot him in a way only Mac can.
S7E3: Obsessed: more Murdoch craziness, and RDA's hair just looks specifically good in this. I like season 7 hair!
There are a few honerable mentiones like the race driving one, the hockey coach one and the one where Mac fights an oil rig fire, but I had to stop 😂
You asked for my favourite and I gave you twelve 😃😃
“Where are the trans men in history?” See. When you're born a gender that was forcefully married off, who had to live most of their life indoors, when you had to raise children, and had a lobotomy if your family thought you were a tad too odd, it's kinda hard to come out as a trans man now ain't it.
‘A Matter of Time’ (2x16) is one of my favs episodes tbh I love it lots
-Sam and Jacks little convo at the beginning
-Her being so curious about the blackhole at first
-“Paradox the stargate was never designed for”
-Teal’c’s “do not concern yourself with my injury” while he can barely stand up and hunched over to Carter’s height. who is he fooling
-I love Carter in this episode sm
-Hi major davis!!
-O’Neill lore drop + angst.
-“Dont even pretend you understood that”
-both sam and teal’c and quantum gravity
-“way smart than we are, I know” this episode has a lot of great lines
-like that, even though it had in fact been several days, Teal’c still had marks/scarring from the electrical burn, nice detail.
-the piece of glass getting wedged in the rope thing kinda gives me final destination vibes.
-dramatic death of a character just introduced: ✅
-oh hi daniel
its always "what are your plans for the future, you should really be planning for the future" and never "wow that character you're obsessed with sounds so cool can you explain them to me. im sure you get them more than anyone else"
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
it fucking sucks how you can do all the therapy and self healing in the world and you still have to wake up living under a capitalist death cult that's killed community and crushes your soul
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