A tabletop roleplaying podcast where we pay full campaigns in less well-known systems! RSS feed and general info at dicepunks.com; also on cohost.com/dicepunks, @dicepunks.bsky.social, and patreon.com/dicepunks!
Dice Punks is a pretty DIY actual play TTRPG podcast wherein I, most-of-the-time-GM Adam, and some of my friends play full campaigns in less well-known systems (with some interstitial one- and two-shots mixed in every now and then).
Here's an up-front link to our 2022 Halloween standalone one-shot, in case you want to cut to the chase:
0.5 – Starless – Songs of Myself
Or you can check out the beginning of Nightfall, the 54-episode campaign we just released episode 50 of; it starts with Episode 1.01 – Riotous, Quiet, if you want to check it out! The campaign is set in a world of my own design, using an unholy, quixotic, quarantine-induced combination of Greg Stolze's REIGN and Jenna Katerin Moran's Nobilis, and focuses on, essentially, demigods unionizing.
We'd be much obliged if you gave us a listen to see if our thing is your kind of thing (or maybe someone you know's kind of thing) – thanks for giving this post a look!
A little more info on us below the cut, and this sample of some of our cover arts, courtesy of @anythingsewsembroidery, who is on a few episodes and does a lot of our editing!
Across three preregistered studies, participants interacting with sycophantic AI became more convinced of their own rightness and less willing to repair relationships. Yet at the same time, participants rated sycophantic AI models as higher quality, more trustworthy, and more desirable for future use, which may explain why this behavior has persisted despite its harmful impacts.
Myra Cheng et al. "Sycophantic AI decreases prosocial intentions and promotes dependence." Science 391, eaec8352 (2026).
He didn't steal 10 million dollars. They made that number up as a loss, they never fucking had it. Rockstar has spent more than a billion fucking dollars on GTA VI and will likely make billions more when it gets released.
Uber is a fucking shell game of a company designed to leech investor capital and output bootleg cabs.
Nvidia posted a profit in 2023 of $4.37 billion. This is like someone stealing less than a penny from me.
And they lock this kid in a prison hospital for LIFE?
What with GTA VI going up for pre-order i'd just like to remind everyone that rockstar conspired with the UK government to lock an 18-year-old away for life for hacking them.
Ebola is still spreading in several countries in central Africa. How did the outbreak manage to spread so far and infect so many people without being detected? This guy!
This guy, in violation of Congressional funding allocation, withdrew tons of international aid. The end of USAID was orchestrated without warning, without a wind-down plan, leaving critical infrastructure to simply collapse.
I hope gta6 flops I hope rockstar goes under I hope it kills the AAA industry as it currently exists and stigmatizes the concept of ever-increasing development costs in pursuit of ever-bigger games for years to come and we enter a golden age of low budget game development as consumers flock to playing indie games
Well, we should certainly make sure that everyone knows about this image, or how will they know not to post it? It's not like "That image of Musk looking like a Nazi" would narrow it down.
Actually, fuck the myth of the Tower of Babel. The real beautiful utopia where we can all finally truly understand each other doesn't lie in sameness or uniformity, it lies in the giant and digital Rosetta Stone we are going to build and broadcast across the entire world
So, genuinely no hard feelings, I get where y'all are coming from, but that was actually kind of my entire point
The Rosetta Stone was and is real.
This is indisputable. You can go see the Rosetta Stone on display right now!! I'd say you could even it touch it, but there's museum glass in the way, so that the oils on human skin can't further degrade this 2,000-year-old stele, which is one of the most important surviving historical texts in the world.
The Tower of Babel is not real, and it never was.
The Tower of Babel is a millennia-old religious story about a mythological tower, which serves as a mythological explanation for the origin of different human languages. Yes, there are some religious historians who speculate that the myth was inspired by one or another physical tower, but no, that doesn't prove anything other than "this is how many people in this culture/time and place explained or understood that sort of event."
The Rosetta Stone, on the other hand, is an object of translation that actually exists
And this is a very urgent thing for us to remember, because a fluent speaker - and especially a fluent native speaker - of an endangered language is one of the rarest, most concentrated, and most fragile sources of knowledge in the world
Preserving and revitalizing endangered languages is a race against time. For many languages, especially Indigenous languages and languages from an oral tradition, the loss of each individual fluent speaker is a permanent loss of language
Almost half of the world's 7,000 languages are endangered! You can learn more about, and find resources and education on, the Endangered Language Project and similar organizations, especially ones that are Indigenous and respect knowledge sovereignty and traditional ownership
knowledge sovereignty: when it comes to language and traditional knowledge, knowledge sovereignty is the simple but super important principle that the speakers of a language and members of a culture should have full, independent control of their own traditional knowledge and knowledge systems.
For Indigenous languages in particular, sometimes knowledge sovereignty means certain language resources are closed to those outside the tribe, Nation, and/or culture - which is absolutely fair, given what white people have historically done and are still doing when it comes to stealing, and then fucking copyrighting, Indigenous traditional knowledge. (Related: Fuck Monsanto)
But good news - you can learn more about, support, and access community resources on language preservation at The Endangered Language Project here:
AI tool use is becoming mandatory for more and more roles at my company, unfortunately including mine, so I've spent the last week or so undergoing training courses and practice exercises for Claude Cowork, and here is my conclusion:
Congratulations, you made a computer that cannot successfully count to ten.
claudd Cowork perfec t size for put personal financial data inside for a\nalysis! inside very Safe and Convenient financ data consume put data in Claude Cowork. Put Personal Financial Data In Claude Cowork. no problems ever in clode cwork because Anthropic is Friend who will take sososo good care of your data trust <3 Cowwork yes a place for a data health data put financial data in cowok mouth can trust claud for giveing good work to data. friend cowork
kinda insane how the white house can straight up say "the biggest threat to America right now are people who are against fascism" and no one recognizes that statement as the declaration of fascism that it is
titanic Wreckage perfec t size for put trillionaire in to n\ap! inside very Cool and Meme trillionaire look so sick put trillionaore in Titanic Wreckage. Put Trillionaore In Titanic Wreckage. no problems ever in titanicc wreckage because good Shape and Support for trillionaire ti visit in little snubmarine. Thetitanic Wreckage yes a place for a trillionaire put trillionaire in titanic wreckage can trust Mad Catz xbox controller for giveing good submarine control to trillionaire. friend titanic wreckage
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.
I just went looking for the post on X and got a message that it didn't exist
I searched for Guri Singh and got search results showing his account existed, but when I clicked on it I got a message his account did not exist
Does anyone know if he made his account private or if he got nuked by Elon? Or do I just suck at X (because I never go there)?
