I saw a post recently wherein someone used LLM tools to analyze someone else’s software, which eventually led them to a conclusion that was essentially completely wrong. Not only that, the LLM drew conclusions about the *authors* behind the code that were borderline character assassination. Nevertheless, this person posted this output as though it were some kind of deep insight.

These LLM outputs are not independent thoughts. The LLM probably ingested hints of (maybe unconscious) biases in the user’s prompts within its context window, and regurgitated something that confirmed those biases. The user was pleased that their biases were confirmed (Independently! By an impartial LLM!), and they posted the output, maybe as vindication of their insight.

These models’ sycophancy can be subtle. They don’t have to state “You’re absolutely right!” to blow smoke up your ass. Sometimes they seem to confirm your preconceived notion after they supposedly “evaluate” information “independently”.

#ai

Dear Malta Gaming Authority,
Yes, I hacked you, and the data obtained has been shared with media partners, authorities,….

And yes, we will expose the organized crime enablement schemes you created while presenting yourselves as a “legitimate public service”.

“Asking an AI chatbot a question consumes a great deal more energy than finding the answer via simple web search or calculator. It adds extra demand for no good reason... a bit like driving to the shops in an SUV instead of riding your bike.”

Or driving any kind of car. AI, like cars, aims to reconfigure everyday life in a way that’s vastly more energy-hungry and polluting… and profitable for a few.

https://www.theguardian.com/australia-news/2026/mar/13/ai-datacentres-environmental-impacts

"Healthy people cost less.
Educated people contribute more.
Housed people are more stable.

...in a healthy society there are no "undeserving".
There are just people."

RE: https://social.treehouse.systems/@ariadne/116213132813239860

Read what Ariadne is writing about LLMs. This all tracks with my intuition, that OpenAI et al are a big grift.

You categorically do NOT need millions or billions to train a useful LLM that can communicate in human language. LLMs are good at language, it's in the name!

The reason these companies are burning massive amounts of money and using increasingly massive models is they've taken "look, this tech makes for a cute chatbot that can do useful stuff" and turned it into "if we make it bigger it'll be SMARTER!"

And the thing is, that's true... to a point. When you stop treating the LLM as a language model and start trying to turn them into an all-knowing entity that has memorized the entirety of human knowledge and can do anything you prompt it for all with the same model (or a few collaborating models), you quickly hit diminishing returns. And you end up with a thing that's kind of smart (not really) and kind of knows everything (not really) and convinces everyone to throw insane amounts of money at you because you're fundamentally using the technology for something it wasn't intended for.

The way we fight back is with small home-grown "LLMs" (SLMs?) that run on a MacBook and train on a few GPUs and training/fine tuning them for specific purposes.

The whole AIBro approach of just using prompting and in-context learning with a single all-powerful model is just patently absurd.

Near ChatGPT London office, Led By Donkeys

https://www.instagram.com/reel/DV1DrLnCC8P/?igsh=NWYyeDc1cnE5cjA0

#LedByDonkeys #TrumpIsAWarCriminal #TrumpEpstein #EpsteinFiles #London #TrumpWar #FuckTrump #ProtestArt #FuckSamAltman #FuckChatGPT #USpol #TrumpWar #ChatGPT #activism #TrumpIsAPedophile #SamAltman

Zwei Dinge können gleichzeitig wahr sein: Alice Schwarzer sollte von keiner Bühne geworfen werden. Und sie ist unerträglich.

Ganze Folge: https://www.youtube.com/watch?v=bXtUp9b_fHY

#BosettiWillReden #SarahBosetti