TheGodThing

Hard science, engineering, physics and open source data.
There are no privileged frames of reference. Empirical data trumps all. QED

[TheGodThing @TGodthing]

"All great systems work towards their own extinction."

Think about it......

#inequality #evolution #Evolve #evonomics #systemsthinking #evenitup #nature
#extinction #optimum

[Alex Veremeyenko @alex_verem]

🚨 BREAKING: Researchers at UW Allen School and Stanford just ran the largest study ever on AI creative diversity.

70+ AI models were given the same open-ended questions. They all gave the same answers.

They asked over 70 different LLMs the exact same open-ended questions.

"Write a poem about time." "Suggest startup ideas." "Give me life advice."

Questions where there is no single right answer. Questions where 10 different humans would give you 10 completely different responses.

Instead, 70+ models from every major AI company converged on almost identical outputs. Different architectures. Different training data. Different companies. Same ideas. Same structures. Same metaphors.

They named this phenomenon the "Artificial Hivemind." And the paper won the NeurIPS 2025 Best Paper Award, which is the highest recognition in AI research, handed to a small number of papers out of thousands of submissions.

This is not a blog post or a hot take. This is award-winning, peer-reviewed science confirming something massive is broken.

The team built a dataset called Infinity-Chat with 26,000 real-world, open-ended queries and over 31,000 human preference annotations. Not toy benchmarks. Not math problems.

Real questions people actually ask chatbots every single day, organized into 6 categories and 17 subcategories covering creative writing, brainstorming, speculative scenarios, and more.

They ran all of these across 70+ open and closed-source models and measured the diversity of what came back. Two findings hit hard.

First, intra-model repetition. Ask the same model the same open-ended question five times and you get almost the same answer five times.

The "creativity" you think you're getting is the same output wearing a slightly different outfit. You ask ChatGPT, Claude, or Gemini to write you a poem about time and you keep getting the same river metaphor, the same hourglass imagery, the same reflection on mortality.

Over and over. The model isn't thinking. It's defaulting to whatever scored highest during alignment training.

Second, and this is the one that should really alarm you, inter-model homogeneity. Ask GPT, Claude, Gemini, DeepSeek, Qwen, Llama, and dozens of other models the same creative question, and they all converge on strikingly similar responses.

These are models built by completely different companies with different architectures and different training pipelines.

They should be producing wildly different outputs. They're not. 70+ models all thinking inside the same invisible box, producing the same safe, consensus-approved content that blends together into one indistinguishable voice.

So why is this happening? The researchers point directly at RLHF and current alignment techniques. The process we use to make AI "helpful and harmless" is also making it generic and boring.

When every model gets trained to optimize for human preference scores, and those preference datasets converge on a narrow definition of what "good" looks like, every model learns to produce the same safe, agreeable output. The weird answers get penalized.

The original takes get shaved off. The genuinely creative responses get killed during training because they didn't match what the average annotator rated highly. And it gets even worse.

The study found that reward models and LLM-as-judge systems are actively miscalibrated when evaluating diverse outputs. When a response is genuinely different from the mainstream but still high quality, these automated systems rate it LOWER. The very tools we built to evaluate AI quality are punishing originality and rewarding sameness.

Think about what this means if you use AI for brainstorming, content creation, business strategy, or literally any task where you need multiple perspectives. You're getting the illusion of diversity, not the real thing.

You ask for 10 startup ideas and you get 10 variations of the same 3 ideas the model learned were "safe" during training. You ask for creative writing and you get the same therapeutic, perfectly balanced, utterly forgettable tone that every other model gives.

The researchers flagged direct implications for AI in science, medicine, education, and decision support, all domains where diverse reasoning is not a nice-to-have but a requirement.

Correlated errors across models means if one AI gets something wrong, they might ALL get it wrong the same way. Shared blind spots at massive scale.

And the long-term risk is even scarier. If billions of people interact with AI systems that all think identically, and those interactions shape how people write, brainstorm, and make decisions every day, we risk a slow, invisible homogenization of human thought itself. Not because AI replaced creativity.

Because it quietly narrowed what we were exposed to until we all started thinking the same way too.

Here's what you can actually do about it right now:
→ Stop accepting first-draft AI output as creative or diverse. If you need 10 ideas, generate 30 and throw away the obvious ones
→ Use temperature and sampling parameters aggressively to push models out of their comfort zone
→ Cross-reference multiple models AND multiple prompting strategies, because same model with different prompts often beats different models with the same prompt
→ Add constraints that force novelty like "give me ideas that a traditional investor would hate" instead of "give me creative ideas"
→ Use structured prompting techniques like Verbalized Sampling to force the model to explore low-probability outputs instead of defaulting to consensus
→ Layer your own taste and judgment on top of everything AI gives you. The model gets you raw material. Your weirdness and experience make it original

This paper puts hard data behind something a lot of us have been feeling for a while. AI is getting more capable and more homogeneous at the same time.

The models are smarter, but they're all smart in the exact same way. The Artificial Hivemind is not a bug in one model. It's a systemic feature of how the entire industry builds, aligns, and evaluates language models right now.

The fix requires rethinking alignment itself, moving toward what the researchers call "pluralistic alignment" where models get rewarded for producing diverse distributions of valid answers instead of collapsing to a single consensus mode.

Until that happens, your best defense is awareness and better prompting.

[TheGodThing @TGodthing]

@atRachelGilmore @westernstandard "Great causes start as movements,, then they become businesses and then they become rackets."

Eric Hoffer

[Tokyo Rosie @RosieRocks28]

These two headlines actually appeared on the same day.

There is perhaps no country on earth more disconnected from reality than Canada at the moment.

[Vesper @vesperdigital]

"I do not trust the current government in the type of content it tries to boost or tries to throttle... News media is dominated mostly by the CBC and it's not objective... It's ideological and consistent with the Liberal Party..."

Prof. Camden Hutchinson
Allard School of Law
🙃

[TheGodThing @TGodthing]

@SatireSquadHQ @KirkLubimov Mark Carney has 103 conflicts of interest in an over 500 page report written and submitted by a governmental ethics committee.
Ghilaine Maxwell had seven different numbers for Mark Carneys wife Diana. Id be very careful about defending them on anything.

[Humanspective @Humanspective]

"Game Over" - Robert F Kennedy.

Pfizer had the data their vaccine wasn't going to stop transmission and they knew 7 MONTHS BEFORE the mRNA injections entered the market.

RFK Jr: "When they gave the vaccine to monkeys, to macaques, and then they exposed them to wild virus, the vaccinated monkeys had the same amount of viral concentrations in their nasal pharynx as the unvaccinated monkeys"

"And right then, I said, "Game over." They can't, they cannot market this product 'cause it's not gonna end the pandemic. It's not gonna prevent transmission. And Pfizer knew it then, and Fauci knew it then."

[Drea Humphrey @DreaHumphrey]

BREAKING OSTRICH MASSACRE:

It appears the CFIA slaughtered the entire flock of healthy ostriches through the night.

This is a sad day for Canada.

Footage to follow & Background: https://t.co/ziF2wnLm2P

[Rebel News @RebelNewsOnline]

HEARTBREAKING: @KatiePasitney calls out to her ostriches by name as the CFIA prepares to cull her flock after the Supreme Court declined to hear Universal Ostrich Farms' case.

[Daniel Horowitz @RMConservative]

We need to start normalizing impeachment, particularly for judges, who violate the law

[TheGodThing @TGodthing]

@RealMattA_ @kwquinn @LichTamara That's a massive fallacy.
ALL of recorded human history is full of warriors, saints, poets, rebels, scientists etc, that were "convicted" by the extremely corrupt status quo. The list is endless & there are PhD thesis written on these topics. It's an aspect of human civilization

[TheGodThing @TGodthing]

@mapleblooded @chrisdacey The city's bylaw violates federal law and supreme court decisions.
When two rules/by laws/legislation collide the superior one takes effect and the lower one is null and void.
Aka cities cannot write nor enforce laws that violate the constitution or other federal legislation.

[TheGodThing @TGodthing]

@dewar_phil @EdDemastus @Dj_YQL @Tablesalt13 In martial arts, armed forces, spec ops units etc you're taught to neutralize the threat by any means necessary. Especially, when the scope and magnitude is unknown. This usually requires the threat, escalation and/or application of terminal force. This situation is textbook.

[Denis Rancourt @denisrancourt]

there was no spread
i don't know how else to say it
nothing was spreading
there was geostatic time evolution, not geotemporal

[Lyndsey, RN 💜🐭 @HouseLyndseyRN]

So the Yale Listen Study said 709 days per their testing of vaxinjured still having continuous spike production (which I am a participant in this study) and show T cell exhaustion etc

Well it’s actually longer than that:

My first injection was 12/23/2020 and I haven’t stopped producing spike and it’s now 02/21/2025

8 months after my 2 Moderna injections I still had large amounts of spike detected per antigen testing- & I’ve never had Covid( results below)

That’s 1,521 days - of continuous spike protein production with NO OFF SWITCH since my first injection & STILL in my body to date

Let that sink in!

(3 years worth of Cytokine 14 panels & S1 immune subset panels below)

I am a documented, confirmed & diagnoses Adverse reaction to MRNA vaccine ( T50.B95A)

[Eva Chipiuk, BSc, LLB, LLM @echipiuk]

https://t.co/n7NxtZrDmm

[TheGodThing @TGodthing]

@JonnyRichter_ @rwalker1072 @krassenstein "So, for the first 84 years of your life you can't be charged for anything you did."

This is not a pardon. This is a Godmode-Cheat.

Insane.

[TheGodThing @TGodthing]

@JonnyRichter_ @rwalker1072 @krassenstein You can't pardon someone who hasn't been charged with anything at all, yet alone convicted.

What he's doing is granting him blanket immunity. Which not only doesn't exist in any legal doctrine but is absurd prima facie.

[Liz Churchill @liz_churchill10]

Not a single person was held responsible for Fauci’s ‘HIV Pandemic’…nor has anyone been held accountable for ‘Covid’ which was HIV on steroids. All ‘Gain of Function’. The next ‘Pandemic’ will be no different than the others because the Medical Monsters aren’t sitting in prison.

[Ben Smith @bensmithlive]

This is Anthony Fauci.

His calculated COVID-19 response devastated billions of lives across the globe.

In his 492-page book, Robert F. Kennedy reveals how Fauci committed a crime against humanity.

Here is the shocking truth: 🧵

[Wall Street Mav @WallStreetMav]

If Washington DC is our richest area per capita, that tells you how important D.O.G.E. is.