hex6c retweeted
I don't recommend anyone scramble to move their funds to new wallets today. But we should take the risks to cryptography from AI-accelerated math seriously, and minimize our exposure to not just quantum-vulnerable cryptography, but also potentially AI-vulnerable cryptography.
The core new area of risk from this viewpoint is, unfortunately, ML-DSA / FHE / lattices.
(and it's also another reason, along with quantum, why ECDSA might fall even faster than expected, hence the "fresh address" recommendation)
So far most people have been in the mode of thinking "elliptic curves broken, hashes safe, lattices safe". But there is a good chance that the concrete security of lattices will take serious hits from the next two years of AI math.
The basic threat model is: factoring is something that naively takes 2^(n/2) time, but over decades smart people have found and optimized number field sieves, and degraded that to 2^O(n^(1/3)), which is why RSA keys and signatures need to be ~400 bytes (and not 64 bytes). What if there are skeletons in the closet like that, both for elliptic curves and lattices, that we are simply not smart enough to discover - but bots soon will be?
This is a major part of the reason why for the past year ethereum's lean roadmap has been going in the "hash-only" direction: no lattices, no ML-DSA, no Falcon, no lattice-based commitments inside ZK proofs, etc. Signatures in lean ethereum are all hash-based, either WOTS or SPHINCS-.
For signatures and proofs, we already know how to go hash-only. The bigger challenge is for *public-key encryption* - and this goes far beyond blockchains. Secure communication, anonymizing protocols, lots of things need public-key encryption.
And unfortunately there are long-standing mathematical theorems showing why public-key encryption cannot be done with hashes alone. You have to have some kind of trapdoor object that has at least one form of usable "structure" - either group theory (incl. isogenies) or lattices or code-based or potentially in the future even more newfangled and spooky things (local mixing?). But for anything that has structure, you should assume that AI will make at least some progress in breaking that structure. Here, one reasonable inference is that if you want to make something plausibly long-term secure, multiply the key sizes by 10.
To me that's a very plausible world and something not at all extreme to predict. If AI will bring us 50 years of math in 2 years, then that 50 years of math may very plausibly include a "naive factoring -> GNFS" level of improvement to our ability to break lattices. In that world, lattices will still exist, but they will have to be significantly bigger to guarantee the same level of safety.
And at those new larger sizes, hash-based constructions will beat lattice-based constructions on concrete efficiency in every use case where hash-based constructions are possible at all.
Theoretically, of course it's possible that hashes are broken too (eg. P = NP would imply that). But I think P = NP is very unlikely. And intuitively, it's much more likely that a mathematical object has exactly no exploitable structure (like hashes are intended to), than that a mathematical object has exactly ~3 forms of exploitable structure (for elliptic curves: associativity, Schoof, pairings) and not some secret fourth form of structure we have not yet discovered that greatly degrades its security (for elliptic curves, ECDLP and pairing security). Similar for LWE, SVP, RLWE and the zoo of lattice problems.
For this reason, we do not yet see any reason to worry and start padding the byte size of hashes (if we start to worry more, we would pad the round count first before doing anything to the byte size).
Concrete TLDR, my own personal views:
* Hash-based > lattice-based, in those situations where hash-based is possible at all
* For anything lattice-based, be much more paranoid on param sizes. Remember that blockchains are only a small portion of the cryptography story; this point goes far beyond blockchains and applies to eg. access to websites, secure messaging, Tor / VPNs ...
* For privacy protocols, strongly favor NOT putting encrypted notes onchain. Instead, send them offchain through some third-party mechanism.
* If it's not difficult for you, keeping your funds in addresses which have not yet been used to make a transaction is a good idea. If it's easy for you, do it. **But be careful about migrations; I personally have lost more money in botched migrations than I have lost in all hacks combined**.
* For multisig wallets, doing confirmations offchain is better than onchain, because this way the signatures of signer wallets do not get exposed to the public, so if ECDSA falls to AI much faster than expected, at least the multisig "gracefully degrades" to a 1-of-1 where the 1 is whoever was gathering the signatures - a much better place to be than "anyone can take the money"
firefly.social/post/x/210783…
hex6c retweeted
END OF AN ERA. A NEW CHAPTER AWAITS.
As you’ve probably heard, I’ve said goodbye to CryptoPunk #8348 for $5.9M.
This wasn’t an easy decision. I spent months flip-flopping on whether to sell, but after more than six years, I felt it was time. This Punk became my identity, so there was a lot more to think about than just the price.
I wanted to write this earlier, but the transaction literally happened in a beer tent at Oktoberfest... So I needed some time to collect my thoughts.
The 2021 NFT mania was insane. It gave me the opportunity to explore digital identity in ways I never expected when I bought 8348 in 2020 for $18,000. I DJ’d across Europe, North America and the Middle East, worked with luxury brands including Louis Vuitton, Swarovski (with mmERCH) and Dolce & Gabbana, and helped curate art events in Miami, Ibiza and London. I also released original music, vinyl records, merchandise, and much more.
Looking back, I accomplished a lot with this Punk.
But the landscape has changed considerably since then, and my interests and priorities have evolved too. Over the last 12–18 months, I’ve been winding down parts of the Seedphrase business and refocusing on what’s next. That’s meant going back to my roots in trading, which was my focus before 2020, taking on new challenges in gaming with Wolf Game, and exploring new possibilities with AI.
On the creative side, I want to see what I can do under my own name. DJing without a helmet, playing more of my own taste in music, and being more involved in the art scene as Danny. I’ve spent six years building an identity around 8348, and I’m ready to give myself a bit more freedom to explore outside of that.
I’m proud of what we built with this Punk. Selling it doesn’t change that, or my interest in the space. There’s still plenty I want to do here.
I won’t reveal the new owner’s identity. They’re welcome to come forward in their own time. One of the first things I asked was that they be a good custodian of such a legendary CryptoPunk, and they’ve assured me they will.
8348 has been a huge part of my life since 2020. It’s strange to move on from something so many people know me by, but I’m excited to put that same energy into what comes next.
You’ll be seeing more of me. Just without the helmet (and with fewer traits).
🤖 Made with AI
hex6c retweeted
"Art is other people. Art is a social reality." @0x113d
hex6c retweeted
The pioneering crypto artist @hex6c coded a variant of Conway's Game of Life called Game of Pixel.
hex6c.medium.com/game-of-pix…
Broken Beauty (2018)
In the Game of Christ (2018)
Replying to @KateVassGalerie
2/ John Conway’s Game of Life is a mathematical model in which every cell on a grid is either alive or dead. At each step, its next state is determined by the living cells around it.
Depending on the starting arrangement, these simple rules can produce structures that remain stable, oscillate or move across the grid.
No cell directs the whole. Complex behavior emerges from local interactions.
hex6c retweeted
The sometimes organic quality in my work does not come from trying to imitate nature visually, but from allowing rules to interact until their behaviour becomes too complex to read as mechanical
hex6c retweeted
Oxford researchers argue that LLMs can never invent anything.
It is mathematically impossible.
They published a paper called “Theory Is All You Need" and it argues against the claim that computational models can generate genuine novelty or new knowledge.
They analyzed the limits of generative ai, and the results are a brutal reality check for the idea that ai will replace human decision making under uncertainty.
Here is why AI is stuck and human cognition wins:
backward-looking vs forward-looking.. llms are probability machines that look backward at existing data. human cognition is forward-looking and capable of generating genuine novelty. human cognition operates theoretically "top-down" rather than "bottom-up" from data.
the "data-belief asymmetry".. the researchers use the invention of "heavier-than-air flight" to illustrate this concept. an ai relies on data-based prediction, which is largely imitative. humans, however, use theory-based causal logic that allows them to hold beliefs that go beyond existing data.
the intervention gap.. humans don't just process information; we use theory to practically "intervene" in the world. we engage in directed experimentation to generate entirely new data. ai-based models are theory-free and place primacy on existing data and prediction.
tldr?
AI uses a probability-based approach to knowledge and ia largely imitative. It can process data and make predictions, but human cognition relies on theory-based causal reasoning.
The decades-old analogy comparing human minds and computers to mere "input-output" devices is fundamentally flawed.
hex6c retweeted
MIT published a brutally honest report on what AI is doing to students.
A committee of professors and students spent five months studying how AI changed learning on campus, and the findings read like a warning to every university on the planet.
Study groups are disappearing. Office hours are emptying out. Problem sets and take-home exams no longer prove anything, because AI can produce credible solutions to almost any written assignment in the undergraduate curriculum. Students who lean on chatbots lose mastery and confidence, and some slip into what the report calls cognitive surrender, reaching for AI at the first hint of struggle.
The numbers are rough. 46 percent of surveyed MIT undergrads use LLMs daily. 90 percent worry about their own overreliance. Undergrads who feel AI makes them replaceable now outnumber those who feel it makes them capable.
The committee's answer surprised me. They refused to fight AI with surveillance. The report calls AI detectors unreliable, says lockdown browsers feel like spying, and warns that policing students builds a classroom atmosphere of mutual distrust.
Instead, MIT wants to rebuild education around the things AI can't replace. That means oral exams, semester portfolios, in-person project work, and a required social component in every subject. The report even floats the idea of rethinking grades entirely, since without a GPA to optimize, much of the incentive to cheat with AI evaporates.
The committee warns professors against replacing undergrad research assistants with AI agents just because they're cheaper, because a university exists to grow people, not output.
The most famous tech school on earth admitted the machines broke its way of teaching. Its answer is more humans, not more software.
hex6c retweeted
I resigned from Anthropic today. I spent the last three years doing pretraining research at both OpenAI and Anthropic. Neither company is acting responsibly. They are racing straight to self-improving superintelligence and gambling with our lives. More thoughts below.
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics.
The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra.
The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
hex6c retweeted
Enjoying cryptoart at home
Three pioneering works from the "second wave":
💚 by @GordonBergerArt (May 16, 2018)
Maxxena by @obv_ious (May 31, 2018)
Genesis Block by @hex6c (October 12, 2018)
hex6c retweeted
L'aliquota per la tassazione delle criptoattività è al 12,5%.
Sembra strano,ma è così.
matteoflora.com/criptotax
coinlex.it/2024/10/31/possib…
hex6c retweeted
💎 seed_1449 💎
✨ Artwork by @hex6c
💰 Sold to anonymous for 0.25 ETH ($666.68)
superrare.com/0x41a322b28d0f…
$RARE #CryptoArt #NFT
hex6c retweeted
Back in 2021, I wrote a tribute article for @hex6c, which makes connections to some of this history, including his projects recovering and exploring historic computer and generative art algorithms ("Recode"):
takenstheorem.medium.com/aut…
hex6c retweeted
The first academic treatment of cryptoart was actually back in 2019 by @hex6c @MLOdotArt & collaborators; you can read it for free, all kinds of detail about origins & themes & market dynamics, right here (next post).
hex6c retweeted
Cypherpunk - a.t.t.e.s.e.3.3
(sound ON)
...
soon on Gallery Library Space curated by @hex6c & @BraidottiChiara on @SuperRare
...
take a look
superrare.com/spaces/glspace…


































