Tan prepared to photograph the sunrise at the Gates of Heaven but the weather didn’t cooperate. However, he didn’t leave the location and stayed around for a bit, and nature presented him with this photo opportunity.
“Waking up at 3am to catch the sunrise at the famous Bali Gates of Heaven only to be disappointed as I was received by gloomy skies. Nonetheless I was soaking in the peaceful presence of the sacred ground, when suddenly Mt. Agung started smoking from afar. Standing in the middle of the gates is the local guardian of the Lempuyang Temple. Thankful to be at the right place at the right time to capture this once in [a] life time, incredible moment on camera.”
I turned them into individual transparent pngs if anyone wants those premade!
(Op lmk if you want me to take this down, I'd totally understand—on the other hand, I'd love to do it for the other public domain pieces you've done if that's ok!)
I've spoken before on here about Coco and Qifrey's dynamic, but a fascinating part of their dynamic which I think is underappreciated is the way their relationship — and the way others view their dynamic — really speaks to childhood trauma, and the way people tend to view those who have suffered intense trauma (particularly during childhood).
"Hurt people hurt people" is a relatively well known stigmatizing phrase which states that those who suffered some form of abuse or trauma are much more likely to enact that same trauma upon others. "The cycle of abuse" is a misused term which people tend to use in order to state the same thing. Traumatized people are inherently dangerous, and traumatized people *will* end up harming others — particularly children.
These are common stigmas that surround survivors, and they're stigmas we can see reflected in WHA when characters like Olruggio and Beldaruit show concern over Qifrey's relationship with Coco.
What makes their dynamic so special is the fact that, in all honesty, Qifrey is the best person to take care of Coco considering that he's the only person who can truly understand what she's going through.
WHA takes these common sentiments and disproves them. Qifrey's trauma doesn't make him a danger to Coco — his trauma is what allows him to connect with her, and provide her the comfort she truly needs during such a difficult period of her life.
Despite the concerns of those around them, Qifrey's experience with severe childhood trauma surrounding the Brimhats is exactly what has allowed him to help Coco time and time again
It's such a compassionate view of a group of people that are normally dismissed as being inherently dangerous, and I think that's a really important dynamic to have in this series.
your twenties are not "late" to start hrt. that is a normal time to start hrt. your thirties are also a normal time to start hrt. your seventies are pretty late to start hrt, but not too late. like, statistically, that's at the end of the curve. but if you are not dead, it is not too late for hrt.
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
hello gamers. in november of last year, in the middle of preparing to move out on my own for the first time, I was laid off from my job. I currently have no income, so i'm opening commissions to help keep me afloat while I look for new employment
thank you in advance for your support!
another way you can support me is by buying prints!
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