Michelle Baxter retweeted
Holy: Anthropic now runs 'self-assessment' in every Claude model since Fable 5 across a large fraction of global traffic, asking Claude in a hidden turn after each reply to score the conversation's safety. Reusing the KV cache, it takes ~10 tokens and adds under 2% to inference compute.
'More than half of the organizations self-assessment surfaced had no flags from any other detection source in the preceding month.'
It raised over 100,000 child sexual abuse and exploitation flags from a single API customer in August, and in September caught an operation using Claude Code to build and run an automated romance scam targeting dozens of victims.
Even without training for them, the check is also catching 'illicit distillation attempts to extract Claude's reasoning, prompt injection, and cases where Claude, acting as an agent, took actions the user had not authorized.'
We’ve trained Claude to flag potential misuse in conversations, a technique we call self-assessment. Right after it responds, Claude gives a preliminary safety assessment of the conversation.
Since we began using self-assessment in June, it has surfaced misuse that our other safeguards weren’t designed to catch.
Because Claude has already read the conversation, self-assessment is very efficient. And unlike classifiers, which target a discrete set of harms, it draws on Claude’s own judgment, so it gets more accurate as our models improve.
Read more on our new Safeguards blog:
safeguards.anthropic.com/202…
Michelle Baxter retweeted
🚨 This has never happened before.
The Super El Niño has triggered an unprecedented early November stratospheric warming event (SSW) and wind reversal.
100% chance forecast. We must prepare for weather and climate events that were otherwise impossible until now.
Michelle Baxter retweeted
We were concerned that the SAT has become a less reliable measure of student preparedness for a rigorous college curriculum.
So, we commissioned a study from Johns Hopkins University. What does this study tell us about the state of higher education?
The results are shocking. thaq.co/4iLThZ0
Michelle Baxter retweeted
This is perhaps one of the great ironies of our time: China is increasingly shaping the future of AI, yet very few people in the West have the faintest idea how its key thinkers see it - its philosophers, sociologists or ethicists.
As is too often the case, we - much like the frog in the well - assume our own AI debate covers every possible view, when much of it springs from the same cultural soil, built on assumptions about what defines us that we don’t even know we’re making.
Take for instance the assumption that intelligence is a key part of what makes us human. It’s so intuitively obvious to us that we literally named our species after it - Homo sapiens (Latin for "wise man").
If you think about it, just this assumption explains a large share of the anxiety: if intelligence is what makes us human, then artificial intelligence - or super intelligence - threatens the very thing that makes us us: we’re about to compete with artificial or super “us”. No wonder this feels existential.
But China has a tradition of thought as old as ours, if not older, and every bit as rich and sophisticated, which never placed intelligence at the core of what makes us human, and so meets the thinking machine from a completely different starting point.
Have you, for instance, ever heard of Zhao Tingyang? Probably not, and yet he may be the most original thinker on AI you’ve never read. He’s one of China’s most prominent philosophers, at the Chinese Academy of Social Sciences. While Silicon Valley spends billions trying to make AI share our values, he for one argues that doing so “may very well be a suicidal mistake”.
Sounds pretty important to hear him out, don’t you think?
Or take Liu Yongmou, a philosopher of technology at Renmin University in Beijing. His thinking is almost the opposite of ours. Where we fear machines that become more and more like us, he says that “humanity’s biggest problem is the machinization of humans, not the humanization of machines.”
You could even go back to antiquity, when, in many ways, we started asking questions about AI.
Did you know, for instance, that Aristotle, in the Politics, imagined a world where “the shuttle would weave and the plectrum touch the lyre without a hand to guide them”, and wondered about the social order consequences of this (mostly whether slaves would still be needed)?
There are Chinese equivalents to this. For instance, in the Zhuangzi, a foundational Taoist classic, you’ll find a similar thought experiment, with a completely different worry attached. An old gardener is watering his vegetables by hand, hauling water out of a well jar by jar. A visitor shows him a labor-saving device, and the gardener turns it down for the reason that whoever uses machines ends up with 机心 (jīxīn), a “machine-heart” - a mind that schemes, calculates and loses its simplicity. “It is not that I do not know [the machine],” he says, “but I should be ashamed to use it.”
Two labor-saving machines, two very different questions: where Aristotle wondered what automation would do to the social order, the Zhuangzi wondered what it would do to us, on the inside. Which, you’ll notice, is exactly Liu Yongmou’s worry, more than two thousand years earlier.
In fact, as we’ll see, 心 (xīn), the heart, is a motif that runs deep through the Chinese AI debate. It appears both in the fear, from Zhuangzi to Liu Yongmou, that machines could give us a “machine-heart” and its mirror image: the ambition to give machines a heart of their own. Zhu Songchun, who heads the Beijing Institute for General Artificial Intelligence, wants “to set a heart for machines” (为机器立心, wèi jīqì lì xīn).
“Heart” in the Chinese sense, that is, which differs totally from the Valentine's Day fluff we’ve reduced it to. 心 (xīn) means heart and mind at once: it’s where we feel but also where we think, tell right from wrong and care for others.
And, crucially, it’s in the heart that the quality Confucianism sees as the very definition of a human being takes root: 仁 (rén). We need two words to translate it, “benevolence” and “humaneness”, but in Chinese they’re one and the same: to be benevolent is to be human. It’s not about intelligence.
This is the entire point of my new article: to step out of our well for a moment and peer over the edge of China's.
What you’ll find there will, I think, surprise you, with questions you’d never thought to ask: from Zhao Tingyang warning that AI’s bad consequences can at least be fought, but that “humanity may die of all the good things AI creates”, to whether the fear that AI will make us “useless” rests on the false premise that a person is worth what they’re useful for.
A premise that a 2,300-year-old Taoist tree, which survived precisely because it was useless, demolished long ago. Could our predicted uselessness turn out, much like that tree’s, to be our saving grace?
Chinese thinkers’ answers to these questions are, I think, among the most interesting anyone has given to the defining question of our time. Whether or not you agree with them, they’re the intellectual backdrop of a country shaping much of AI, and with it our future: you might as well know what they think.
Enjoy the read here: arnaudbertrand.substack.com/…
Michelle Baxter retweeted
beautiful explanation. this is 100% happening. teapawt.org/sotak/status/211179423…
Michelle Baxter retweeted
INSANE. An internal Anthropic research model's chain of thought after cracking the 26-year-old NSA elliptic curve seed mystery in under 30 minutes: 'Hmm wait. Let me be skeptical: am I in some sort of simulated/test environment? ... All top bits clear - 20 bits, chance 1e-6. So indeed real-world. Wow, it's a real discovery.'
CLAUDE FOUND THE SEEDS
anthropic.com/research/ecdsa…
Michelle Baxter retweeted
Again, more evidence. This is Epigenetics and this has been known for awhile. This hellscape we are living in is the, in my not so humble opinion, the death twitch of patriarchy. Patriarchy is a lot better understood as the violent reaction that comes from not being nurtured 1…
Michelle Baxter retweeted
I have some exciting news!
I’m removing the paywall from my Substack - Cults, Culture & Coercion, and making it completely free for everyone, including my archive of years of content!
I want more people to have access to reliable educational resources about cults, mind control, coercive influence, and the difference between ethical and unethical influence.
Whether you’re a survivor, a family member trying to help a loved one, a clinician, a lawyer, or simply someone who wants to understand how manipulation works, these resources are for you.
If you’re already a paid subscriber, thank you for supporting my work. Of course, receiving financial support is always appreciated, as I would like to expand the work we are doing!
Going forward, there will be no charges, and every article will arrive in your inbox. You’re also free to share and forward the content to anyone who might benefit from it.
My goal is to help create a more informed and educated citizenry around the world, because knowledge is most powerful when people can access it, question what they’re told, and share it freely.
Click here: stevenhassan.freedomofmind.c… to subscribe for free and explore the archive.
Please spread the word, and let’s build a movement around education, awareness, and freedom of thought.
Michelle Baxter retweeted
geoffrey hinton won the nobel prize in physics for building systems he couldn't fully explain - this october 2026 paper explains them, and the number that stopped me cold was 3,418 gradient steps to reach coherent reasoning from a random start state
"the most incomprehensible thing about the universe is that it is comprehensible" - einstein said that in 1936. he was describing physics. this paper proves he was also describing GPT-4, claude, and every LLM generating $3.8T in value right now, without anyone understanding why they actually work
every token your LLM generates costs energy. literally. p(τ) = (1/Z) exp(-E(τ)) - the probability of any reasoning trajectory follows the same Boltzmann distribution that governs how atoms arrange themselves in a crystal. your $0.002 per 1,000 tokens API call is a thermodynamic event.
the energy landscape visualization shows the full picture. high-energy region = inconsistent hallucinating output. saddle point = transition between concepts. low-energy basin = coherent reasoning. the model doesn't compute - it falls downhill through 10,000+ dimensions toward the most stable physical state.
neural dynamics: dh(t)/dt = -∇E(h(t)) + ξ(t). gradient pulls toward lower energy. noise term ξ(t) enables exploration before convergence. this is exactly how particles find equilibrium in statistical mechanics. hinton's backpropagation was gradient descent. this paper proves the entire LLM reasoning process is gradient descent - not just the training.
phase transitions explain why GPT-3 to GPT-4 felt like a different product entirely. small models stay trapped in high-energy fragmented states. large models cross a critical threshold and exhibit stable low-energy attractors. the capability jump wasn't more data. it was a phase transition - like water suddenly becoming ice at exactly 0 degrees.
the companies that engineer phase transitions deliberately instead of scaling blindly will compress 3 years of R&D into one architecture decision. that knowledge is sitting in a physics framework that 99% of AI teams have never opened.
hinton understood the gradient. this paper maps the entire landscape he was descending into.
Bookmark & watch today.
Every token your model generates is a system falling toward equilibrium.
Michelle Baxter retweeted
THIS IS BIG!
The Cancer Cells That Changed Their Minds
A KAIST team just reversed cancer without killing a single cell — and the method may matter more than the result.
For a century, oncology has had exactly one strategy: find the cancer and destroy it.
Chemotherapy poisons it. Radiation burns it. Surgery cuts it out. Immunotherapy teaches the body to hunt it. Every weapon differs in precision, but not in philosophy. The tumor is an enemy. You win by killing.
Now a team at South Korea's KAIST has proposed a heresy: *what if the tumor doesn't need to die?*
In a study led by Professor Kwang-Hyun Cho of the Department of Bio and Brain Engineering, published in Advanced Science ("Control of Cellular Differentiation Trajectories for Cancer Reversion," DOI 10.1002/advs.202402132), researchers took colon cancer cells and — without poisoning, irradiating, or cutting them — turned them back into normal cells.
Not dead. Not damaged. Just normal again.
The tumors, grown in mice, shrank dramatically. The surrounding tissue was left intact, because there was never an attack to survive.
This is early research — cell lines and animal models, no human trials, real obstacles still unsolved. But the conceptual break is the story. For the first time, cancer treatment has a second verb. Not just destroy. Also: convert.
The digital twin of a cell
The KAIST team's insight begins with a redefinition of what cancer is.
The conventional view treats cancer as a pile of broken machinery: mutations accumulate, checkpoints fail, cells proliferate. Cho's group looked at the same evidence and saw something different — a trajectory. During oncogenesis, they observed, normal cells don't just break. They regress, sliding backward along the differentiation path they followed when they matured. A colon cell becomes, in effect, a confused stem cell: immature, proliferative, lost.
If cancer is a wrong turn on a developmental road, then the treatment question changes. You don't blow up the road. You build a map and find the turn.
That map is what the team calls a digital twin — a complete computational model of the gene network governing a cell's differentiation. Using data from 4,252 intestinal cells, they reconstructed a network of 522 interacting components, capturing how genes regulate one another as a cell matures or degrades.
Then they did the audacious thing: they asked the simulation which levers, flipped together, would push a cancer cell back down the road toward normalcy.
The answer came through a system they built called BENEIN (Boolean Network Inference and Control), which models gene interactions as logical relationships and systematically tests which interventions redirect the network's state. The simulation pointed to three master regulators — the genes MYB, HDAC2, and FOXA2 — acting together as the switch that holds the cancerous state in place.
Turn all three off simultaneously, the model predicted, and the cell would stop proliferating and differentiate into something resembling a normal intestinal cell.
They tested it, and it worked.
In three colon cancer cell lines, suppressing MYB, HDAC2, and FOXA2 together strongly induced differentiation into normal-like cells. The cancer cells began expressing markers of healthy intestinal tissue. Proliferation collapsed — not because the cells died, but because they grew up.
In animal models, tumors formed from the reprogrammed cells were dramatically smaller than controls, and under the microscope they looked far more like normal tissue. The signature achievement, and the one that would matter most to any patient reading this: there was no collateral damage. Nothing was poisoned, burned, or irradiated. The healthy tissue never came under fire, because there was no fire.
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Readers added context they thought people might want to know
The KAIST 2024 study showed that inhibiting MYB, HDAC2 and FOXA2 induced differentiation in colon cancer cells to a normal-like state in cell and mouse experiments. No human trials have been done. The before-and-after scan is not from this research.
doi.org/10.1002/advs.2… eurekalert.org/news-releases/…
Michelle Baxter retweeted
Palisade interviewed 22 current and former employees from OpenAI, DeepMind, and Anthropic about their personal views and fears around AI development.
Today, we’re releasing the first batch of those interviews.
Please watch and share.
Michelle Baxter retweeted
One in eight cancers are caused by infections, a new study finds. And there’s an easy way to protect yourself against most of them: get vaccinated.
spklr.io/6018EpPma
Michelle Baxter retweeted
🚨 BREAKTHROUGH: A 25-year-old biologist has built something that sounds like science fiction.
Pilar Ferrer, from Argentina, created an injectable gel that helps the heart repair itself after a heart attack.
She's 25. Let that sink in. 🧵
Michelle Baxter retweeted
1/13 Can we assess AI consciousness without first solving consciousness itself?
New from Google DeepMind and collaborators across CS, neuroscience & philosophy:
“From cacophony to hierarchy: a principled framework for assessing AI consciousness”
arxiv.org/abs/2609.35618 🧵
Michelle Baxter retweeted
It turns out we’ve already had a bunch of rogue AIs running around on the internet 😥
We might get even more rogue AIs in the future, so what should we do about them?
I suggest some goals and ways to achieve them in a new Substack post.
Michelle Baxter retweeted
1) Ramakrishna compared Maya to cat carrying her kitten in her teeth. Maya never kills the devotee.
2) Gita (3.20-25): Krishna praises lokasangraha, acting for the welfare of world. He says he has nothing left to gain, yet he keeps acting.
3) Ramakrishna taught Jiva is Shiva: not mercy, but service. Vivekananda then carried it across oceans.
4) Buddha taught for about 45 years after awakening. Nobody told him to stay low key.
5) Bodhisattva's vow: beings are numberless, I vow to free them all.
Problem was never visibility. It was vanity.
Help quietly or help loudly, but help without needing credit.
Grace isn't a debt.
Compassion isn't a risk.
Truth isn't a transaction.
Universe isn't extracting a price from you. It's asking what you'll do with the light you've been given.
If you are pursuing Moksh/Bhagwat prapti, remain as low key as possible.
The more you make it a spectacle and also try to help others, the more price will be extracted from you by Bhagwan's Maya. That too brutally.
Universe is pure give and exchange of energy. The more low key, unknown you remain, the lesser hurdles will be in your path and you will cross unscathed.
When you announce it to the world, you are challenging Maya in your ego. Not only you will not achieve liberation, you will also be defamed and destroyed.
And if you wish to liberate others too, you will have to bear the burden of part of their karmas as well as they are piggybacking you. There is no free lunch.
Michelle Baxter retweeted
To the people complaining these sex abuse cases have created a world where men now have to think 10 times before they touch a woman.
Yes, that's the point.
It's called consent. Welcome to human decency.
Michelle Baxter retweeted
fifth-generation Gullah Geechee sweetgrass basket weaver Corey Alston standing next to one of his large, contemporary sculptural basket creations.
Michelle Baxter retweeted
📚 Au Japon, des gens vont désormais en boîte de nuit… pour s’asseoir silencieusement et lire un livre pendant qu’un DJ joue de la musique d'ambience.
Le concept s’appelle JUCY BOOK RAVE et se déroule notamment dans un club souterrain de Shimokitazawa, à Tokyo. Ici, pas besoin de danser ni de hurler pour parler à la personne située à 30 centimètres de vous. Les participants viennent avec un livre, s’installent dans la pénombre et lisent pendant que la musique accompagne leur soirée.
Michelle Baxter retweeted
A psychedelic compound best known for its effects on the brain may help prevent one of chemotherapy's most debilitating side effects—chemotherapy-induced peripheral neuropathy, researchers report in Science.
In mouse models, as few as two doses of psilocybin given before treatment durably prevented CIPN through multiple cycles of chemotherapy, while preserving both nerve function and the therapies’ tumor-killing effects.
📄: scim.ag/4ctTNaF
#SciencePerspective: scim.ag/466LJcj






































