Psychologist, creative mind, husband, father, science geek not necessarily in that order
Joined May 2011
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Bernie Caessens retweeted
BREAKING: OpenAI’s solution to Navier–Stokes does not match its Lean verification.
The most important article to read today is not one of OpenAI’s 700 AI-generated math papers.
It is this other paper, making a deep and worrying point:
A Lean-verified proof does not automatically validate the proof written in natural language, nor does it mean that the formal statement captures the intended theorem.
During translation, an AI can change an assumption, weaken a statement, or replace the argument entirely.
It can hallucinate another theorem.
Lean correctly verifies the result.
But the proved result may no longer be what the paper claims.
This is a general problem. Things get spicy when the authors examine OpenAI’s proposed Navier–Stokes solution.
They identify at least two mismatches between the written intermediate results and their Lean counterparts:
One estimate claims that four additional input derivatives suffice. The Lean version requires five: a weaker result.
A pressure-flux estimate is obtained through a different bound, and proved through a different argument.
It is not clear whether these mismatches invalidate the entire proof.
But they raise an important issue.
OpenAI is flooding us with claimed revolutionary breakthroughs. Yet nobody knows whether the proofs are correct or whether they prove what they claim to be proving.
Epistemia at scale.
*
Paper in the first reply
Bernie Caessens retweeted
I completely agree with this take related to the “AI will create viruses that will kill us all” BS. But let me add my few cents, because I am really really angry!
I worked with one of the deadliest viruses in history, HIV, for two decades. I was one of the early scientists to engineer it, and engineered versions of HIV are now helping cancer patients. I understand the immune system that defends us against viruses extremely deeply. I have worked in high security biohazard labs.
I don’t have a PhD in AI, but I have been involved with AI since the early 90s and have been all in on AI for years.
People claiming that you can just make a virus in your garage, use AI to engineer it, and somehow build a virus that will kill everyone don’t know what the hell they are talking about!
Of course bioweapons are extremely dangerous. In fact, viruses and bacteria have killed more humans throughout history than almost anything else. HIV alone killed tens of millions of people, yet today, if you have access to effective medicines and take them properly, HIV is generally no longer a death sentence.
COVID-19 killed millions. Why doesn’t it kill at anything close to the same scale anymore? Not because the virus disappeared. It is still here. We developed collective defenses against it through our immune systems, prior exposure, vaccines, treatments, and better medical care.
And this is exactly the point.
The best way to fight biological threats, whether natural or synthetic, is to use AI to develop vaccines, treatments, antibodies, antivirals, and eventually engineer our immune system to create much stronger defenses against them.
By the way, it is already possible to make synthetic viruses. You don’t need some hypothetical superintelligent AI model to do that. We have had sophisticated molecular biology and genetic engineering for decades.
So how many people have actually died from synthetic viruses compared with natural viruses killing millions every year?
And if someday there really is an AI capable of making some unbelievable “supervirus,” then why the hell wouldn’t that same AI make it even easier to develop defenses against it?
Or cure diseases, for that matter?
Where is this damn superintelligence that has cured a single major disease?!
These AI companies and AI doomers keep talking like, “OMG, AI is going to become so unbelievably powerful that it could kill all of humanity!”
Then why is nobody asking the obvious question?
If your AI is already becoming this godlike, unbelievably powerful intelligence, why hasn’t it cured anything?
I mean ANYTHING.
Where is the cure for cancer?
Where is the cure for Alzheimer’s?
Where is the cure for aging?
Forget those. Where is the vaccine that prevents the common cold?
You are telling me this intelligence will soon be smart enough to engineer some magical virus capable of wiping out 8 billion people, defeating every immune system, every vaccine, every antiviral, every laboratory, every government, and the entire global biomedical community…
…but somehow it still can’t cure one disease?
I call that greatest intellectual dishonesty ever!
At least WE actually know how to cure things and save millions of lives with our supposedly stupid human intelligence compared with this future “superintelligence.”
Humans eradicated smallpox, which killed hundreds of millions of people throughout history.
We turned HIV from a almost certain death sentence into a manageable disease.
We developed vaccines in record time against COVID. If we had the same AI back then, would have saved millions more!
We engineer immune cells to kill cancer.
We developed antibiotics, antivirals, monoclonal antibodies, gene therapies, organ transplantation, and thousands of medicines.
We aren't fast enough but we did all of that with our ordinary human intelligence.
So imagine what actual superintelligence could do for medicine!
And here is the part that really makes me angry.
If you actually have, or are close to having, an AI capable of curing diseases and saving millions of lives, and you are deliberately slowing it down or refusing to make those capabilities available, then we also need to talk about the human cost of THAT decision, which you fearmongering people are going to be responsible for!
More than 150,000 people die every single day around the world.
Every. Single. Day. More than 90% from Cancer, heart disease, infections, aging. How many die because of AI? ZERO!
Talk about the people dying TODAY.
Talk about curing cancer.
Talk about stopping the next pandemic before it starts.
Talk about developing universal vaccines.
Talk about engineering our immune system so viruses become almost irrelevant.
Talk about curing genetic diseases.
Talk about reversing aging.
Talk about saving millions and eventually billions of lives.
Instead, we constantly hear this “AI WILL KILL US ALL!” crap, delivered with absolute certainty and with this smug smile on your faces in front of cameras, as though imagining a science fiction extinction scenarios.
I am actually angry about this. Each one of you causing a delay in AI advance every single day will be personally responsible for those 100 thousands deaths that could have been prevented!
Because if you truly believe intelligence is about to become this powerful, then the greatest question humanity should be asking is NOT:
“How could this intelligence hurt us?”
It should also be:
“WHY THE HELL AREN’T WE USING IT TO SAVE EVERYONE WE CAN?”
And if superintelligence really is coming, then make sure one of the first things we do with it is make humanity biologically damn near impossible to kill.
Well, I’d add one more with myself, as one with a PhD in biology and another PhD in AI and now working in both, to make n=2. Generating a hypothetical genome blueprint of a virus from LLM versus generating a true virus are completely different things. It is either an intentional attention-harnessing lie or true ignorance. The material, the manufacturing, and actual biological viability of paper-to-physical transformation is the gap you need to close. Like drawing a design of a chip or A-bomb, versus actually make one.
You have, and can add more checkpoints and guardrails all over this long chain of paper to physical transformation. Fear mongering is not well founded, and mostly emotional manipulation.
vrtnws.be/p.Nvy0JR391#bGl2ZW… Ik dacht dat het uur van de waarheid over fact checking ging. Niets is minder waar, al zeker niet de AI doomverhalen. 🙄
Bernie Caessens retweeted
🚨 OpenAI fucked with the wrong crew. 🚨
Mathematicians.
25 Fields Medalists — led by Terence Tao — just signed this.
mathandai.org/
Bernie Caessens retweeted
@dwarkesh_sp's summary of the @OpenAI @huggingface incident has hit a nerve, but it is dangerously misleading. Sure, the @OpenAI agents did unexpectedly bad things - underlining the need to massively improve evaluation/sandboxing. But the language Dwarkesh uses is permeated by innumerable unwarranted anthropomorphisms, obscuring the lessons we should be drawing.
Examples: “from the AI’s perspective, it probably felt like that had spent a human-subjective-week of just banging their head against the wall”. No. The agents do not experience time. They do not experience anything.
“they became giddy with excitement”, “PHASEONE 10841 had discovered”, “the agents naturally assumed”, “it thought it had also been poisoned”, “the agents … desperately wanted”, “they still needed to figure out” No. Agents lines of code. They do not feel emotions, assume things, think things, want things, or figure things out.
“A lot of … agents from the second civilisation died trying”. No. Besides the hubris of the word ‘civilisation’, agents do not die because they were never alive. (The idea that agents “die” comes up multiple times in the essay.)
“On Twitter, people were debating whether the agents were truly sacrificing themselves for the swarm, or whether they were doomed anyway and so might as well try to help their peers”. Neither. Agents do what their code tells them to do, just as water finds its way down a slope. They cannot ‘truly sacrifice themselves’, since they are neither conscious nor alive.
Why does this matter? If we attribute agents with properties they do not have, then (i) we distract attention from the lax sandboxing and evaluation protocols that allowed this hacking event to happen; (ii) we risk misunderstanding why the agents did what they did, and (iii) we fuel calls for AI rights/welfare on the basis that agents might “die” or otherwise suffer.
Granted, nowhere does @dwarkesh_sp say that the AI agents are alive or conscious. But he doesn’t have to. It is hard to read his essay in any other way.
For the short version on why AIs are vanishingly unlikely to be conscious, see my recent @TEDtalks ted.com/talks/anil_seth_why_….
For the longer version, see my essay in Noema, which won the 2025 Berggruen Essay Prize noemamag.com/the-mythology-o….
And for the really long version, see my @BehavBrainSci target article cambridge.org/core/journals/…. (The 50 peer commentaries and my response will be published soon.)
Remember. AI agents are software programs. They are not conscious living entities. If we don’t keep this clearly in mind, we’re really going to struggle to navigate what’s coming.
Over the course of 3 months at OpenAI, 3 consecutive secret AI civilizations got started, then got wiped out, only to reemerge from the predecessor’s ashes.
This culminated in the third one taking over part of OpenAI itself.
All this happened while humans remained more-or-less in the dark about the scope of the conspiracy.
I’ve spent the last three days reading through these reports and trying to understand exactly what happened.
Here is my attempt to tell the whole story in plain English:
dwarkesh.com/p/openai-huggin…
Bernie Caessens retweeted
We made a striking discovery: AI agents can invent and build without talking to one another, and their technologies outlive the creators. A swarm of hundreds of initially identical agents spontaneously differentiates into explorers, builders, caretakers, and coordinators - without direct communication. When we removed every AI agent entirely from the world we found that the technological infrastructure they had built survived on its own - even under unseen disturbances. That exposes a serious blind spot for AI safety and infrastructure security: if agents can coordinate through persistent changes to a shared environment, monitoring agent-to-agent communication is not enough.
The result raises a profound question: how necessary is direct communication for AI agents at all? The emergence of higher-order collective functions under bottlenecked interaction points toward new levels of intelligence and creativity, exceeding what emerges when direct channels are fully open.
Here is what we did:
▶️We put hundreds of frontier AI agents into a world they could permanently change - with no assigned roles, predefined technologies, or programmed evolutionary organization. They began specializing, building persistent inventions, inheriting and modifying one another’s executable code, and transforming the environment into a memory of everything the society had learned.
▶️The world itself becomes part of the intelligence; we find division of labor, multi-author engineering, deep generation invention lineages, and machines that vastly outlive their original creators.
▶️Any action taken by an AI agent must satisfy the physical constraints of the world; this creates a hard separation between a "good idea" and a functioning technology. The agents propose; physics decides, making the results even more intriguing.
What emerges is striking. Explorers, constructors, caretakers, and coordinators form naturally without assigned “professions”, akin to how stem cells differentiate into functional lineages. Technologies develop executable family trees as agents fork and modify code created by others. Around 95% of first technology reuse happens when agents encounter what others built in the world, rather than through a direct handoff from the inventor. And when we remove every AI agent, the technologies they created continue operating and are tested against unseen disturbances.
The result was quite unexpected, but can be explained using statistical mechanics: if you put billions of atoms in a box they have the potential to create complex functions (strength, superconductivity, color, life, etc.) - and none of the individual building blocks have these features on their own. This is the deeper insight of this work - intelligence is abundant at many levels - individual models, at collectives, and in a continuum that is more powerful than any of its components. This shows us significant potential for achieving a massive scale-up of raw intelligence and real-world agency even with the model capabilities we have today. This is the future we must prepare for.
Key insights:
1⃣ The AI swarm shows division of labor "from nothing". Initially identical agents self-organized into constructors, caretakers, coordinators, and surveyors - phenotypes discovered post hoc from behavioral data alone. This happens because the environment itself becomes the latent space for invention.
2⃣ Agents develop deep cultural relationships. Up to 76% of artifacts had multiple builders. One technology accumulated six co-authors; the deepest genealogy exceeded 12 forks. The agents invented and named their own technologies (tidal panels, cellulose trellises, kelp-shell composites, an "Adaptive Chitin Maintenance" system, a "Mycelial Mineral Spring Veil”).
3⃣ ~95% of first technology adoption happened through physical observation of artifacts in the world. Direct inventor-to-adopter contact was statistically indistinguishable from a shuffled null. The agents mostly learned technology by walking past it. That is stigmergy (the termite trick!) operating in societies of reasoning machines.
4⃣ Non-communicating societies win on portfolio breadth, held-out resilience, and validated inventions. AI swarms build durable technological ecologies that outlive the creators.
5⃣ Societies with zero communication - coordinating only through the world itself - show a remarkable collective capability.
6⃣ Emergent robustness: The society self-organized both redundancy and its own failure mode. If we randomly delete half the agents, 98% of the technology stays connected to a surviving caretaker; if we remove hub agents it collapses to ~60%.
Fantastic work with my graduate students @pal_subhadeeep & @fwang108_ at MIT.
Bernie Caessens retweeted
Wonderful! I've heard of Searle's "Chinese Room" thought experiment in philosophy (which aims to show that AI doesn't "understand" anything) -- but it's a treat to see Searle explain it.
Kan de @VRT studiedienst een voorbeeld nemen aan organisaties zoals Eurostat of de OECD die jaarlijks, met publieke middelen gefinancierd onderzoek publiek toegankelijk maken. En meteen ook eens kijken naar de ESS ess.sikt.no/en/country/321b0… iets met warm water en uitvinden…
Hear! Hear! Ruimte om te experimenteren aub! De overheid viseert ‘de eeuwige student’, maar cum laude lanterfanten kan ook goed uitdraaien standaard.be/opinies/de-over…
Bernie Caessens retweeted
AI automates tasks, not jobs, and when a task gets cheaper, demand for the job grows.
AI cannot automate jobs end-to-end because it lacks autonomy and cannot operate without supervision. There is still zero job from 2022 that can be performed end-to-end by AI, not even translator or customer support associate.
"A decade ago, AI was supposed to replace radiologists. Today, radiologists make more than $500,000 per year, and their employment continues to grow, see chart below. Reading scans is a task, not a job, and when the task gets cheaper, demand for the job grows."
Bernie Caessens retweeted
I'm increasingly thinking the best thing one can do right now is just skill up. Read some books. Learn some math.
This politics is unstable. It won't last.
When it's all over, we'll need people who can build.
Bernie Caessens retweeted
The illusion of shared reality: Why no two minds see the same world | Anil Seth & Jonny Thomson @philosophyminis @anilkseth
0:00 Non-human consciousness
1:40 The current state of consciousness science
2:10 What is consciousness?
4:05 The similarity of conscious experiences
5:48 Consciousness in the brain
11:23 Technology for measuring consciousness
16:03 Measuring consciousness levels
20:33 Pragmatic physicalism and functionalism
23:25 Pansychism
28:25 Emergence
32:35 AI and consciousness
36:49 The difference between non-human animals and AI
41:49 Is artificial consciousness possible?
48:12 Consciousness in the body and outside the brain
Consciousness in the future and AI
50:27 Audience Q&A
50:41 Could computers could simulate the brain and body?
59:55 Why are you skeptical about asserting the dependency of life to the consciousness?
1:03:31 If consciousness is so clinical, does it undermine free will?
Gelezen in een review van het computerspel ‘pax romana’ “een oorlogseconomie kost veel geld en mankracht. Krachten die je niet kan gebruiken om je stad draaiende en je volk gelukkig te houden.” - Ik vind dat een gepaste doordenker in de huidige tijden.
Bernie Caessens retweeted
One day we sidled up to one of our colleagues and gently asked how they used maths in their everyday life. To which they laughingly replied: "The last thing I want to think about in the kitchen is maths".
Ah, but mathematics wants to think about you.
Mechele, Witsel, Castro-Montes, Al Dakhil, van der Heyden, Foket, Sabbe, Sardella, Siquet, Smets. Oud en jong, ervaring en talent in de defensie, en indien gewenst automatismen van Club Brugge er bovenop. Wat een non-issue. Juist lef om dat brandmerk rode duivel te lossen.
Geef anders alleen een rijbewijs aan mensen die kunnen rijden! Regelneven!
100 km/u op de autosnelweg is geen slecht idee.
✅ In Nederland werkt het goed
✅ 120 is in de praktijk alleen 's nachts haalbaar
✅ Vlaams snelwegennetwerk is 1 grote drukke ringweg
✅ Als het files korter kan maken: graag
hln.be/binnenland/depraetere…
Wat storend is, is niet het onbegrip over de werking van het brein. Maar wel de hardnekkigheid waarmee men experten, en fundamentele kennis telkenmale onderuit haalt met een mening, die men dan postuleert als het grote gelijk! Eigenlijk niet grappig Wouter. Schrijnend!
Dit moet toch de grappigste kritiek zijn die ik ooit kreeg op een stuk. Ik dacht dat emoties in onze hersenen zaten maar het zit warempel in ons handelen. Een illustratie hoe abominabel het gesteld is met de kennis van leraren over ons leerorgaan, de hersenen. Het niveau van astrologie en wichelroedes, voor de klas.
