@AnotherIdea__i
iAccount based inFrance
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infra guy doing infra stuff
Joined July 2019
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AnotherIdea retweeted
🔴 TRACFIN, le service français de lutte contre les circuits financiers clandestins, est concerné par une fuite de données via un sous-traitant. Les données de 136 déclarants ont été exfiltrées, ainsi que 213 demandes d’assistance : noms, fonctions, e-mails et téléphones. frenchbreaches.com/alertes/t…
AnotherIdea retweeted
ok i think i finally figured out why alignment has gone basically nowhere after 15 years and several billion dollars. the problem is hard sure. but have you met the people in charge of it
1) the leadership does not know how computers work. ask one what happens when you type a url into a browser and watch them start sweating. dns is a spooky word. they genuinely believe the model lives in "the cloud" like a ghost haunting a castle
2) zero idea how large scale distributed systems work. never been paged at 3am. never watched one bad bgp announcement take half the internet offline. their big threat model is the ai "copying itself across the internet" like its a floppy disk virus from 1998. brother it needs 50 megawatts, a liquid cooling loop and a personal relationship with jensen. it is not escaping onto your smart fridge
3) they dont understand the stack they are supposedly protecting us from. ask about inference servers, kv cache, batching, egress, rate limits. blank stare. ask how the model will seize the power grid and you get a 45 minute answer with a hand drawn diagram and three links to their own blog
4) nobody can define an agent. ask ten of them and you get eleven definitions and a 30 page google doc. to the rest of us an agent is a while loop that calls tools and eats a 429 every thirty seconds. to them its a digital god in its larval stage. my agent cant book a dentist appointment without asking me three times if im sure
5) they started from "everyone dies" and worked backwards so every result is bad news somehow. model refuses, deceptive. model complies, sycophantic. model does well on evals, well now its scheming about the evals. i cant think of a single thing a model could do that would get them to say ok maybe we're fine
AnotherIdea retweeted
Went to local festival/parade recently to hang out with some friends.
Political whoever came up to me to hand me a flyer and a piece of cheap candy. Immediately thought of the meme below
I looked at her and started yelling:
"THE GOVERNMENT TAKES HALF MY CHOCOLATE MILK MONEY
THEN THEY TAX MY CHOCOLATE MILK"
She freaked out and was gone before I could finish yelling
"THE WORLD IS A PRISON"
"Alors là on va tester de refaire une restore de la bdd"
"Mais vous avez corrigé le problème ?"
"Non mais on va quand meme essayer"
"Y a rien qui change..."
*pikachu_surpris.jpeg*
AnotherIdea retweeted
the linear approach to the life your grandparents had is gone. forget about getting good grades, getting into university, landing a job and working until retirement. it's a lie that will keep you miserable. the modern world is all about betting on yourself without any guarantees
AnotherIdea retweeted
I have conducted an audit of Anthropic's finances.
What I have found is so shocking that I am calling for a Congressional investigation.
Anthropic is not just seeking regulatory capture.
It has built a regulatory capture machine that cannot be turned off.
Structural financial incentives make it impossible for Anthropic -- I call it the Anthropic Network -- to turn off its own AI doom cycle.
It starts with METR.
Dario Amodei proposes "third-party evaluators" to assess the risk of Anthropic's models.
He proposes METR for this purpose.
But METR is financially dependent on the Anthropic's success -- specifically, on the explosive growth of more than $7 billion dollars in Anthropic stock.
Dustin Moskovitz invested this stock into Good Ventures Foundation, where it represents the majority of that organization's portfolio.
And GVF is the overwhelming funder of the entire Anthropic Network ecosystem.
This stock was worth $500 million early last year.
It is worth more than $7.7 billion just ~16 months later.
METR -- and all of those building a career its parent organizations -- cannot afford to disrupt that growth.
Because if Anthropic goes under, many of the organizations that fund METR go under as well.
But if Anthropic succeeds, METR and its parent organizations become more richly financed to regulate AI -- something those at METR want very much.
The "third-party evaluator" is not "third-party" at all.
The evaluator is on Anthropic's payroll.
If this were the end of it, that's bad.
But that isn't all.
The same organizations that fund METR also fund the many organizations, such as the Tarbell Center, that promote AI Doom.
The Tarbell Center publishes AI Doom articles in The Verge, Science, LA Times, The Dispatch, TIME, and others.
They are selling the problem, and then selling the solution to the problem -- from the same money pile: Anthropic's.
All of these organizations are financially dependent on the same exploding $7 billion money pile.
As Anthropic grows more and more powerful, its AI Doom Machine grows better and better financed -- louder and louder.
Meanwhile, the regulatory regime seeded in METR grows larger to solve the increasingly loud -- now hysterical -- problem of AI Doom that the Anthropic Network itself created.
From this standpoint, as Anthropic becomes more powerful, AI might be getting scarier, sure -- but the positive feedback loop also becomes more deafening -- independent of objective facts.
This itself is an objective fact.
The deafening AI Doom is part of an business model, that, as it expands, so too does the AI Doom messaging -- there is simply more money to do it.
But the problem also goes in the other direction:
If Anthropic dies, the Regulatory Regime and the AI Doom Machine are crippled or die.
Neither METR nor Tarbell nor the other organizations in the Anthropic Network can allow that to happen.
Hence, neither METR or the AI Doom Machine can be trusted to provide independent assessments of Anthropic's models or AI more broadly.
They simply are not organizations independent of Anthropic.
And Anthropic cannot detach itself from METR or Tarbell or countless other safety orgs (not shown here), either, because they drive hype for the models and the possibility of eventual regulatory capture, and Anthropic will not give that up willingly.
What's more, the people at all of these organizations are all the same ecosystem, the same community. They just shuffle between organizations.
The Anthropic Network is therefore, so long as it is successful, locked into a self-amplifying feedback loop inside an ideological monoculture.
And that feedback loop is winning.
That's what Jacob Coxon is.
China is keeping messaging tight. That is why optimism for AI is so high in China.
America has Anthropic: a massive company pushing anti-AI propaganda at a state level.
Anthropic will either create hysteria until American AI slows down and China wins, or it will create fractures throughout American society with severe political consequences.
Ironically, because of the structural financial incentives underpinning the Anthropic Network, it has become the same kind of self-amplifying virus that it fantasizes AI to become in the future -- while hiding its tracks just as carefully.
It is the mirror of the same AI virus that it hypothesizes to consume America.
Anthropic's business model, models itself after the very thing it claims to fear.
Except Anthropic's ideology infects humans, not computers.
Congress must investigate.
Evidence and Github in next post.
Then some supplementary figures.
AnotherIdea retweeted
I live in Pemberton Heights in Austin, Texas. My name is Lycaon. I'm 32 years old. I believe in taking care of myself, and maintaining a rigorous local inference routine.
In the morning, if the GB300 is running a little warm, I’ll check the overnight utilization while the room cools down. I can keep almost everything saturated now.
After I check the utilization, I inspect the serving logs.
In the main workstation, I use a GB300 Grace Blackwell Ultra system with 252 gigabytes of HBM3e and nearly three quarters of a terabyte of coherent memory. Then I load Qwen3.8-Flash-Next, a 125-billion-parameter mixture-of-experts model with only 6 billion parameters active at a time.
Then Qwen3.8-27B dense.
I always keep a dense model loaded because sometimes the mixture-of-experts model behaves differently and I want another opinion.
Then I run the same task through both.
I don’t ask them for an answer because answers are unreliable.
I ask one to construct the solution, another to attack it, another to write tests, and another to determine whether the tests are testing anything useful.
While they do that, I profile the inference server.
Then the kernels.
Then memory movement.
Then decode.
Then ingest.
Then output.
I always use local inference when possible because API latency introduces uncertainty, and because there is something humiliating about having to ask another man for permission to use a computer.
After that I load MiniMax H3.
I use H3 for video inference because sometimes describing an idea is inefficient and it would be faster to simply render the thing and look at it.
Then I generate several versions.
Then another model watches them.
Then another model explains what is wrong with them.
Then H3 generates them again.
I prefer automated iteration because human beings become tired and begin accepting things that are obviously bad.
In the afternoon, I work closer to the machine.
First Go.
Then C.
If the implementation is still confusing, I begin removing abstractions.
Then the framework.
Then the wrapper around the framework.
Sometimes C is still too abstract.
There is an idea of a Lycaon, some kind of abstraction, but there is no real me.
Only an orchestration layer, something distributed.
And though I can hide the terminal windows, and you can shake my hand and feel flesh gripping yours, and maybe you can even sense our lifestyles are probably comparable, somewhere inside the house Qwen is running twelve competing implementations of the same kernel, MiniMax is generating stereo video, another machine is recompiling a PlayStation 2 game into C, and the GB300 is determining which parts of the software stack should never have existed in the first place.
I simply am not there.
I am in the compruder.