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My interview for a senior policy role at a major lab a few years ago told me that they did not understand what was about to happen. The backlash was obvious even then. You can’t tell people that the good outcome of your thing is the loss of millions of jobs and an outsourcing of creativity, and the bad outcome is human extinction.
The frontier labs are happy to warn us that they are building something so amazing and so smart that it could threaten humanity. Let’s set aside the obvious financial motivation for saying that and take them at their word.
If they want us to take them seriously, then they need to take their responsibility seriously too. Stop building with inadequate controls, stop using the failures of those controls to promote the intelligence of your model, stop calling for a regulatory moat, and tell us what you’re actually prepared to stop doing.
logicalintelligence.com/blog…
Patrick Hillmann retweeted
LLMs are not the only way to model intelligence.
Many strong voices believe the future of intelligence lies in other routes, like energy-based modeling.
We spoke with @evelovesolive, founder and CEO of Logical Intelligence, to understand how energy-based reasoning models (EBRMs) work and what kinds of problems are well suited for them.
In this deep dive, we'll explore:
- Why LLMs struggle with problems like Sudoku
- What is an energy-based model
- How energy-based reasoning works
- What EBRMs can and cannot do
- How EBRMs handle verification and safety
Read full deep dive here:
Patrick Hillmann retweeted
I raised awareness of this issue with three major blockchains as far back as a year ago. Without formal verification in place at scale to ensure their public code is hardened, worst case scenario is a matter of when not if. This tech exists today but major crypto companies are moving too slow
Today I call upon the blockchain industry to calmly begin planning for "bunker mode". My personal recommendation is to set in motion a controlled mass migration of assets to fresh addresses, i.e. addresses whose pubkeys remain hidden behind a hash.
Holders, starting with large and sophisticated ones, should consider moving the bulk of their funds to addresses that have never signed a transaction. And when they do sign one, they should also move remaining funds to a new address (possibly generated from the same seed phrase).
Don't rush. While I believe there is cause for action a rushed migration would do more harm than good. Don't panic either. Moving assets to protected addresses is a simple, preventative step which does not require new cryptography or new wallets.
IMO it is now reasonable to brace for the possibility that ECDSA breaks before qday, in the worst case in months not years. By "break" I mean fast private key recovery (e.g. in one week) on available hardware (e.g. a large GPU cluster).
Recent days have been humbling for human mathematical intuition. Long-held, unquestioned hypotheses have fallen. This includes the n log(n) bound for integer multiplication and the 3SUM conjecture. In hindsight, May's unexpected disproof of the Erdős unit distance conjecture was our warning shot.
Yesterday's OpenAI drop made it clear that mathematical superintelligence is upon us. They say there are weeks where decades happen. We are about to live through weeks where centuries of mathematical progress happen. Could our magic 64-byte ECDSA signatures be too good to be true? Was it just security through obscurity all this time?
Elliptic curves feel especially vulnerable to superintelligence. Curves carry rich structure, with room for fancy tricks like Schoof, Frobenius, pairings. (By contrast, hashes are designed to minimise algebraic structure.)
Separately, as Ewin Tang can attest, an efficient quantum algorithm sometimes foreshadows an efficient classical one. We should be open to the possibility of a classical counterpart to Shor that breaks elliptic curves and RSA at once.
Also noteworthy is the striking under-representation of cryptographic breakthroughs among the 722 mathematical results OpenAI published. I've witnessed first-hand the US government censoring academic quantum cryptanalysis results. Backroom interventionism is my base case.
I urge large, sophisticated actors to lead by example. Project11's "risq list" (bitcoin-risq-list.projecteleven[.]com) is a great tracker of exposed BTC pubkeys. Binance, Bitbank, Robinhood, Bitfinex, and Tether have an opportunity to harden their cold storage. Next month I'll address institutions in London in a live Q&A (forum.ethereuminstitutional[.]org/london-2026).
Again, please do not rush. Wallets holding under 50 BTC enjoy partial cover from "Satoshi's shield", i.e. his 20K exposed addresses that hold 50 BTC each. Load-bearing signers like oracles and L2 security councils should consider rotating ECDSA pubkeys with every signed message and/or multi-signing with a hash-based schemes like SPHINCS.
Exiting bunker mode safely will require post-AI cryptography. My inclination is to go all-in on hash-based cryptography and avoid structured mathematical assumptions entirely, whether from curves, lattices, or isogenies. A single battle-tested hash (e.g. from the SHA or BLAKE families) yields plausible post-AI security.
The Ethereum roadmap on strawmap[.]org fully embraces hash-based cryptography with end-to-end formal verification as a response to the quantum threat. Those timelines must now be revisited and accelerated in light of mathematical superintelligence. I'll be pushing for maximum defensive acceleration.
The White House's AI accord contains some good ideas, but as I told Politico, “all of those things any company should already have in place."
I don’t think anything has changed.
politico.com/newsletters/dig…
"AI did not replace the mathematician. Different tools played specific roles alongside him: exploration, proof construction, formalization, and verification, while the essential mathematical insight remained human."
Since 1995, the known frontier of “good groups” in 4-manifold topology had remained essentially where Freedman and Teichner left it. Today that frontier moves farther.
Slava Krushkal, working with Michael Freedman’s Discovery Team at Logical Intelligence, has proved that certain Sturmian groups are good, expanding the class of fundamental groups for which the machinery of topological 4D surgery theory is known to apply. logicalintelligence.com/blog…
Patrick Hillmann retweeted
The relevant question is not, “how intelligent is this model?”
We should be asking “what can this system do, what prevents it from doing something else, and what happens when those protections fail?”
That should be the starting point for any proposed deployment in a critical setting. - @PRHillmann
The “Coke vs Pepsi” race to superintelligence, consequences be damned, is frustrating to me as a builder.
My concern about LLMs is not that every improvement brings us another step toward an inevitable machine apocalypse. It is that we risk continuing to confuse increasingly impressive capabilities to mimic intelligence with real machine intelligence and giving these models increasingly consequential responsibilities.
These are general purpose models that are being smushed to fit every role for every customer. Systems are built around the model to keep them on task and staying within the constraints of a particular problem. But it will never fundamentally understand that it can’t violate a constraint. Constraint is not in its nature.
The relevant question, therefore, is not, “how intelligent is this model?” We should be asking “what can this system do, what prevents it from doing something else, and what happens when those protections fail?” That should be the starting point for any proposed deployment in a critical setting. logicalintelligence.com/blog…
The “Coke vs Pepsi” race to superintelligence, consequences be damned, is frustrating to me as a builder.
My concern about LLMs is not that every improvement brings us another step toward an inevitable machine apocalypse. It is that we risk continuing to confuse increasingly impressive capabilities to mimic intelligence with real machine intelligence and giving these models increasingly consequential responsibilities.
These are general purpose models that are being smushed to fit every role for every customer. Systems are built around the model to keep them on task and staying within the constraints of a particular problem. But it will never fundamentally understand that it can’t violate a constraint. Constraint is not in its nature.
The relevant question, therefore, is not, “how intelligent is this model?” We should be asking “what can this system do, what prevents it from doing something else, and what happens when those protections fail?” That should be the starting point for any proposed deployment in a critical setting. logicalintelligence.com/blog…
As I told the BBC, the AI labs' trust issues have been a long time coming.
They approached communications like this would be a "Coke vs. Pepsi" competition among beloved brands. Not a sea change that at best would upend jobs and at worst (apparently) doom humanity.
OpenAI boss says world 'right to be afraid' but 'should trust' AI firms bbc.in/3VgtcYO
Patrick Hillmann retweeted
Replying to @raphaelmilliere
Sure, but when it turns out the leak was caused by the plumber who neglected to tighten a pipe fitting, or perhaps poked a hole in one of the pipes, you shouldn't question the entire plumbing industry. You should question the plumber's compétence and/or motivations.
Patrick Hillmann retweeted
Honestly it might be just time to rethink intellectual property policies. AI is a tool for humans and we trust this tool our creativity, and AI companies should be serving this only mission to preserve trust of their users. this whole story violates everything and breaks my heart
I deleted my previous post. I'm just going to post the entire statement page by page. It's a complicated situation.
Statement: cims.nyu.edu/~tristanb/state…
cims.nyu.edu/~tristanb/euler…
cims.nyu.edu/~tristanb/ipm.p…
cims.nyu.edu/~tristanb/bouss…
github.com/tristanbuckmaster…
Patrick Hillmann retweeted
See the letter with a final list of signatories here: microsoft.com/en-us/corporat…
Patrick Hillmann retweeted
Logical Intelligence is proud to sign this letter in support of open-weight AI models.
Open-weight models expand research, innovation, and defensive security. The future is safer when defenders have the same, or better, tools than attackers.
For my first post, I’m sharing a letter @NVIDIA signed on why open models matter.
AI will transform every industry, power every company, and be built by every country.
Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.
The world needs both frontier closed models and frontier open models.
images.nvidia.com/pdf/Open-W…
Patrick Hillmann retweeted
What is actually taking shape today is the growing likelihood that a diverse ecosystem of different types of AI models, each handling a specific role, will soon power the most important corners of the global economy.
Read more about the "AI Sandwich" logicalintelligence.com/blog…
Patrick Hillmann retweeted
Just submitted a paper on which I worked during my PhD with incredible team of physicists, neuroscientists and mathematicians (kuddos to @ninamiolane ) . I always wondered if this methodology (time correlated persistent homology) can be applied to AI models? I can see that some models could learn better or worse because of their topological order parameter. I also predict that similar could be for brain diseases: e.g. Alzheimer/Parkinson/Dementia/various levels of consciousness under anesthesia has specific topology . Maybe @JosephJacks_ can test some with legend @StuartHameroff
Link on pre print biorxiv.org/content/10.64898…
Patrick Hillmann retweeted
Replying to @deanwball @natolambert
I have not said anything like that.
I have said that governments around the world REQUIRE AI sovereignty, not that they will have "their own models as digital public infrastructure"
But open weight foundation models will INEVITABLY be the dominant form of AI.
Patrick Hillmann retweeted
Impromptu board meeting at Raise Summit’s amazing AI gala in Versailles! – at Versailles, France
Certain outspoken industry peers on this platform arrogantly mocked us and called us “unserious” for not trying to build our own LLM.
Luckily, markets have a funny way of rewarding conviction well before consensus catches up 🤷♂️
Patrick Hillmann retweeted
"Every LLM is a very confident guessing machine." @PRHillmann , CSO/COO at @logic_int
Logical Intelligence model vs. leading LLMs on Sudoku:
LLMs: 2% solved, $14,000
LI model: 98% solved, $4
Deterministic AI just made its case.
ShiftAI.fm🎙️




















