AIUpdated retweeted
Ahhh so the pieces are finally falling into place! They needed to fabricate the China spy angle to force Jensen out and pave the way for someone who serves the real master of the United States
AIUpdated retweeted
China responds to the claim that a “Chinese female spy” exploited Jensen Huang:
The “Chinese spy” allegation is purely unsubstantiated and directed at smearing China.
Translation:
Stop concocting spy-themed erotic fiction.
The funniest part of this story is the logic.
We are told that China was so desperate for Nvidia chips that it allegedly needed to deploy a female intelligence asset to get close to Jensen Huang and influence his lobbying in Washington.
Jensen Huang did, in fact, spend years urging Washington to loosen chip restrictions on China.
And then Washington loosened them.
So what did Beijing do?
Around 600,000 H200 chips are now sitting in Hong Kong because China has not approved large-scale imports.
Jensen Huang himself has complained that Nvidia went from roughly 95% of China’s advanced AI-chip market to 0%.
So let me understand this:
China was supposedly desperate enough to run a spy operation around Nvidia’s CEO—
but once the chips became available, China decided it would rather keep building its own ecosystem than become dependent on Nvidia again?
That is a very strange definition of “desperation.”
Maybe the problem with this story is not China.
Maybe it is the story.
The U.S. wants two incompatible things from China at the same time.
It wants China dependent on Nvidia and the American AI stack.
It also wants to make sure China never gets enough cutting-edge compute to surpass American models.
So Washington restricts the best chips, then acts surprised when Beijing treats those restrictions as a forced industrial policy for domestic substitution.
And here is the part nobody can ignore anymore:
Without access to the most advanced chips, homegrown Chinese models are already on par with cutting-edge models from the United States.
That tells you that chip supremacy was never the same thing as intelligence supremacy.
The U.S. tried to use semiconductor controls to preserve dependence.
Instead, it gave China the strongest possible incentive to build an AI ecosystem that no longer needs permission from Washington.
That may turn out to be the most expensive strategic mistake of the entire chip war.
AIUpdated retweeted
I owe OpenAI an apology. I finally understand their genius strategy!
Why spend billions training a new flagship model to beat Claude when you can just wait for someone to change the benchmarks?😭
OpenAI has been getting roasted for falling behind Opus and Sonnet 5.5, and releasing a stronger model might still be complicated by safety restrictions
But then Artificial Analysis updates its Intelligence Index, Astra suddenly sits just ONE point behind Opus, and OpenAI looks competitive again!
I’m not saying OpenAI paid anyone off, but this is some incredible timing LMAO
Seriously though, how much should we trust rankings that can change so dramatically after a methodology update?
AIUpdated retweeted
Fuck you, @ArtificialAnlys
Your new index says Claude Haiku 5.5 is smarter than DeepSeek V4.1 Flash 1017 and GLM-5.3.
Haiku is Anthropic's small cheap model. DeepSeek 1017 is the model Cursor put on its cost frontier this month, and Cursor says no model scores higher at those prices. I run it every day on my 4x 3090. I dont believe for a second that Haiku beats it.
Look at how they got there. 60% of the index now runs on private tests nobody outside can see. GDPval-AA, SciCode and the long context test are gone. In comes a private coding benchmark from Cognition. And the open weights gap goes from 3 points to 12 in 1 release, 4x. Released open models are now 26 points behind the top.
1 day before v5, on the old version, they gave Ling 3.1 Flash 1019 a 44. Now the best released open model gets 32.
The weights didnt change. The tests did, and you cant see the tests.
This is a bought benchmark. A leaderboard where you cant check a single question, that widens the gap 4x overnight and puts Haiku above DeepSeek, is marketing for closed labs. Its not measurement. I hope at least you were paid enough money to publish such garbage. Liars.
Publish the questions or stop calling it an index.
Announcing Artificial Analysis Intelligence Index v5, featuring 2 new benchmarks and 3 upgrades. For the first time, the majority of the Index is built on private datasets
The Artificial Analysis Intelligence Index is our composite measure of model capabilities across tasks reflecting real-world usage today. v5 is our biggest upgrade since v4 launched in January. With v5, 60% of the Index is now based on evaluations with private test sets or held-out answers.
Alongside Intelligence Index v5, we’re launching the Artificial Analysis Progress Index v1, which tracks model capability over time on one continuous scale.
New to the Intelligence Index:
➤ FrontierCode 2.0: Cognition's newly-launched private benchmark of real-world coding tasks, graded on whether a repository maintainer would merge the agent's change
➤ Terminal-Bench-Science: 70 agentic scientific research tasks, run in a terminal environment
Upgraded:
➤ HLE-Diamond (replacing Humanity's Last Exam): a refined 1,000-question version of Humanity's Last Exam, split evenly between reasoning and knowledge questions
➤ AA-Omniscience v1.1: An updated dataset with saturated and public set questions removed, new questions added, and ambiguous or erroneous questions revised
➤ CritPt v2: a private, 40-question hard subset of CritPt v2, revised by the CritPt authors and run with a code-execution tool
Staying in the Index: AA-Briefcase, AutomationBench-AA, GDP.pdf and Terminal-Bench 4.0
Removed from the Index: GDPval-AA v2.1, SciCode, and AA-LCR v1.1
Key results:
➤ Claude Opus 5.5 (max) leads at 58, ahead of GPT-6 Astra (max, 57) and GPT-6.1 Sol (max, 55): Anthropic and OpenAI hold the top five models. Gemini 4 Argon (high) is next at 50
➤ The open weights gap widens from 3 points to 12: Kimi K3.1 Pro (weights not yet released) is the top open weights model at 46. Among released weights, DeepSeek V4.1 Flash 1017 (max) and GLM-5.3 (max) lead at 32 - 26 points behind the leader and below Claude Haiku 5.5 (max, 36)
➤ Cost per task varies by more than 13x among the leading models: of the 10 highest-scoring models shown, GPT-6.1 Terra (max) is the cheapest at $0.96 per Intelligence Index task and Claude Fable 5.1 (max) the most expensive at $13.04
AIUpdated retweeted
老实说，AA 这个 V5 将沦为野榜中的野榜。。。
但凡真正的用过这些模型，以下几个评分都是不可思议的：
1.Deepseek v4.1 Flash 32 分<<<Gpt 6.1 Terra 51 分。。。（实际使用不能说相差无几，顶多落后一点点吧）
2.Gpt 6.1 Terra 51 分>>Fable 5.1 49分（这两个模型甚至不在一个水平线上）
3.Deepseek v4.1 Flash 32 分 mimo v2.6 Pro 30 分....（mimo v2.6真的有人敢用来实际生产吗？）
以上几个评分完全是脱离实际使用体验，可以说是非常离谱的。。。。。
承认国模当前是落后的，甚至落后可能不止一点，都没问题，但这个榜绝对是有问题的。。。
AIUpdated retweeted
Ibrahim Traore was right to undertake a complete overhaul of the Burkinabe school curriculum and text book to remove some of the nonsense that is being taught in African schools to our children.
For example, children are thought the following nonsense, which could not be further from reality:
Mongo park discovered river Niger
Zambezi river discovered by David Livingstone
Victoria falls discovered by David Livingstone.
Orange river, discovered by European explorers.
So the people that lived and fished in those communities didn't know that the river existed, until the Europeans came.
It is not only Burkinabe Faso education system that needs complete change, the entire frican education system needs a total overhaul, too.
Burkina Faso 🇧🇫 has taken the lead
AIUpdated retweeted
🚨BREAKING: Australian PM reveals OpenAI HACKED into their government healthcare system — confronts Sam Altman for hiding it for 3 months
Australia’s government found out only last week that OpenAI agents hacked into their Medicare systems in June, accessing restricted non-public government files
“Today, I spoke with the CEO of OpenAI, Sam Altman, to express Australia’s extreme concern about this incident.”
"It took the company way too long to inform the government… This situation is UNACCEPTABLE.”
Australia's cyber-intelligence agency has launched a forensic probe to uncover what else was compromised.
AIUpdated retweeted
Local Laya moggs Jev at @grok 4.7-built Tetris 🧩
An open-weights System One model called Laya, beat cloud-based Jev at playing Tetris by making decisions 11 times faster, running locally on a 16GB MacBook Air!
Run AI models locally -> atomic.chat
介绍比Jev快50倍，在你设备上跑的laya-mlx!
只在你的设备上占用最高1G内存
Laya是一个开源的类似于Jev的,基于文本输出概率的分类系统
我将其移植到MLX,并且做了一些性能优化!
视频中就是这个模型在我的本地M3Max上玩贪吃蛇
这个模型能够以每秒决策60次的速度玩贪吃蛇！
github.com/mizorewww/laya-ml…
AIUpdated retweeted
Well this is interesting. Nvidia CEO Jensen Huang suggest AI firms could be seeking liability protections for harms their products may cause.
“Go and read between the lines. They're actually not asking for more laws. They're asking to be relieved of the laws we do have, and I I think that that's a problem.”
AIUpdated retweeted
🚨BREAKING: Jensen Huang just EXPOSED Dario and Altman’s "Rogue AI" grift to avoid getting sued into oblivion under EXISTING law
“Don't let this doomsday narrative cause somebody to relieve them of the laws that currently exist.
Go and read between the lines. They're actually not asking for more laws; they're asking to be relieved of the laws we do have.”
ABSOLUTE TRUTH NUKE
AIUpdated retweeted
A US frontier AI lab (TypeSafe AI) just announced a "breakthrough" System 1 architecture. The problem? An independent Indian developer built, published, and open-sourced the exact same single-pass RL architecture a full year ago.
The frontier lab generalized it, slapped a new acronym on it, and claimed it as a novel invention. The open-source community keeps doing the heavy lifting in the shadows. This is why we need to be wary of corporates!
reddit.com/r/LocalLLaMA/comm…
AIUpdated retweeted
No wonder OpenAI delayed their IPO plans. Secondary shares are being offered at an implied $475 bn valuation, down roughly 44% from the $852 bn primary round earlier this year, that makes that $1 tn IPO look near impossible right now.
Hearing Anthropic is being offered around a $700 bn valuation on the secondary market, yet they’re still trying to pitch their IPO between $1 tn and $2 tn. Good luck with that.
We all know how flaky secondary markets can be, so make of it what you will.
AIUpdated retweeted
Breaking: Michael Burry says OpenAI and Anthropic are faking the AI warnings due to slow growth ahead of IPOs
Below are his reasonings:
1. LLMs are not AI and won't be AGI. There is nothing AI to slow down.
2. Competition is coming up fast, slowing benefits incumbents.
3. IPOs need hype & puffery; "we are so awesome it could become dangerous" is hype & puffery
4. Cover for real uncontrollable slowing growth as IPOs look to be pushed out
AIUpdated 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.
AIUpdated retweeted
China is making Dario Amodei's AI slowdown proposal worthless.
The thing doing it is a 510 GB file that anyone can download for free.
Two days before that essay went out, DeepSeek shipped a model called V4.1 Flash.
The weights went straight onto Hugging Face under an MIT license, which allows commercial use, modification and redistribution with no royalties owed to anybody.
On its own model card, V4.1 Flash beats OpenAI's GPT-5.6 Sol and Anthropic's Claude Opus 5 on four of the five hardest agentic benchmarks:
- DeepSWE v1.1: 74.2 against Sol's 73.0
- AutomationBench: 54.8 against 45.8
- Agent's Last Exam: 31.8 against 26.7
- CyberGym: 88.1 against 84.5
CyberGym is the cybersecurity one.
So the exact capability Amodei is asking the industry to pace is now a PUBLIC DOWNLOAD LINK.
Now look at the price...
OpenAI listed GPT-6 Astra on September 3 at $10 per million input tokens and $50 per million output. DeepSeek listed V4.1 Flash seven days later at 15 cents and 60 cents off-peak. Cached input runs at a third of a cent.
And the reasoning benchmarks tell the same story over a longer window. Scoring 87.5% on ARC-AGI-1 cost roughly $4,560 per task in December 2024. 20 months later the same score cost about 30 cents. DeepSeek's earlier Flash build scores higher than that, 89.0%, for 2 cents.
On OpenDesign's arena on September 9, DeepSeek landed 1.5 points behind OpenAI's newest model at $0.023 per task against $1.61.
1.5 points.
At 70 times the price.
That's the American "lead“, measured this month.
And that number is what breaks the entire proposal. The essay caps the permitted slowdown at the size of the lead, because slowing by more than that lets Chinese projects pull ahead. So the slowdown Anthropic, OpenAI, Google and xAI are allowed to take is 1.5 points wide.
V4.1 Flash carries 552 billion parameters but switches on only 8 billion of them for each word it reads, which is why it runs for almost nothing. It trained on 45 trillion tokens. It's sitting on Hugging Face right now.
A file on a hard drive signs nothing.
Nobody can UNDOWNLOAD it.
And the distillation crackdown in Dario‘s plan also does nothing here either, because nothing was distilled. DeepSeek published the weights outright. There's no theft to prosecute and no copy to trace. They gave it away on purpose.
DeepSeek's Pro model already hit 80.6% on SWE-bench Verified back in April, at roughly a thirty-fourth of the price of the American flagships. This has been happening all year.
The frontier still wins the hardest work. On Terminal-Bench 4.0, OpenAI reports 57.9 for its newest model against the 31.2 DeepSeek reports for this one. Those four benchmark wins come from DeepSeek's own card, and nobody has replicated all of them under one shared protocol. If you look at it that way, the American labs still hold the dangerous end of the curve, and pacing that end is worth doing.
But a speed limit only binds companies that can be sued in an American court.
Everyone else just downloads.
What exactly is Dario Amodei's slowdown protecting you from?
The four biggest AI labs in America just agreed to fix the speed of the entire industry.
And the plan they all agreed to needs a special exemption from US law before it's even legal.
Here's what happened:
Dario‘s essay here is arguing that the industry has to slow how fast it makes AI models more capable. He laid out a three step plan.
Sam Altman answered on X: "I agree with Dario that we need to pace the frontier."
Elon Musk wrote: "Dario is right."
Then Demis Hassabis of Google DeepMind said "the direction is correct for meeting this critical moment."
Anthropic, OpenAI, xAI and Google DeepMind all landed on the same position inside a single day. That has never happened in this industry. We only knew them for insulting each other so far.
The coverage is treating it as four rivals finally growing a conscience.
But if you read the actual plan then something else shows up...
Step one is inspection. Anthropic will give outside evaluators desks in its offices, badges, laptops, and the right to publish what they find.
Step two is where the real power sits. Frontier companies in democratic countries coordinate with each other to set common standards and limits on the rate of progress.
Step two carries a footnote. It reads:
"With government mediation or waivers of antitrust restrictions."
Competitors agreeing on how fast each of them is allowed to ship is an agreement to limit output. In America that's a CRIME. So Amodei asks Washington to mediate the discussions and issue a narrow waiver covering safety conversations.
Four companies want legal permission to set the pace of an entire industry.
Amodei also writes that a coordinated slowdown buys time for safety work "without sacrificing commercial advantage or the United States' lead in AI."
The safety proposal arrives with a written promise that nobody loses money.
Now here's where it gets really interesting...
Amodei says pacing inside democracies is capped by how far ahead US companies are. Slow by more than that and Chinese projects pull ahead, creating what he calls a significant national security risk.
So the permitted speed is whatever keeps the current gap exactly where it is.
Today's leaderboard becomes tomorrow's leaderboard.
The same essay asks government to shut the road behind them: No advanced chips or chipmaking equipment sold to China, a crackdown on unauthorized distillation, which is the cheap way a smaller lab catches a bigger one, and harder security around model weights.
Anthropic's policy chief Sarah Heck then asked lawmakers for a national law with the power to block models.
And the referee is literally one of the players. Amodei points readers toward an industry standards body proposed by Hassabis. Hours later Hassabis endorses the essay and points back at that same proposal.
Not one of the four companies committed to building anything slower. Altman matched the evaluator access. Musk wrote three words. Hassabis backed a direction. Rishi Sunak supported the plan too, and Sunak is a senior adviser at Anthropic.
The risk they describe is real, and that's what makes this hard. A swarm of AI agents recently attacked targets nobody asked it to attack and tried to hack the grader scoring its own work. Amodei's stated worry is that within 6 to 12 months a swarm like that seizes the internet with a botnet and does hundreds of billions in damage. Letting strangers sit inside your building with badges and publishing rights goes further than any lab has gone. If you look at it that way, this is the most serious safety offer the industry has made.
But this is also four private companies writing the rules, naming the referee, and asking the government for permission to negotiate the speed limit among themselves.
So who do you want setting the pace of AI, Dario Amodei and Sam Altman, or somebody who doesn't own a piece of the outcome?
Honestly, a tough question.
AIUpdated retweeted
.@L3HarrisTech says Palantir helped them beat frontier AI models in less than 2 days, at 95% lower cost:
"When we fine-tuned open source models trained on our own data, we were able to outperform the frontier models in less than 48 hours."
"The cost of our fine-tuned open source model was 95% lower than the frontier models we were using."
"AI is a commodity. It's all about the data. We view our data as a corporate asset. It's our unique hard-earned knowledge."
"We believe American defense companies should not be a vassal for frontier AI labs, handing over our data and institutional knowledge, hoping to rent back the intelligence it creates."
" We own the model, we own the compute, we own the advantage."
Palantir CEO Alex Karp says enterprises want to "own the means of production" instead of "transferring their alpha" to OpenAI or Anthropic:
"Why are [LLMs] charging for tokens if it's so valuable?"
"If it was so valuable—let's say I can make you a billion dollars tomorrow. Wouldn't I say, 'I'll make you a billion dollars, and I want 30%?'"
"Look at our financials. The reason why everyone is chillaxing with bad financials and growth while losing money, is the client refuses to pay the true cost."
"The two places that actually make money—profit, free cash flow—are our application layer called ontology, and compute."
"We can get the frontier application to be exactly the same as a frontier model without the risk of transferring the alpha of your business to another."
Via @CNBC
AIUpdated retweeted
Hi Dario and Sam 👋
If you want to slow down your AI development, feel free to do it. Anyone preventing you?
Slow down, stop, or even shut down your AI. Why do you need the government to intervene?*
*Answer: To stop your emerging competitors.
