Rouven retweeted
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.
Rouven retweeted
Chinese researchers did it again!
Kimi published an attention architecture that runs LLMs 6x faster and uses 75% less GPU memory than full attention.
For years, the entire AI industry has been trapped by a single bottleneck.
Standard transformers use "full attention." Every single word has to look at every other word. As your context grows, compute costs explode. Running long documents or massive codebases becomes painfully slow and cripplingly expensive.
For a long time, alternative "linear attention" models tried to fix this.
They were faster, but they came with a fatal flaw: they were dumb. Their performance always fell apart compared to standard transformers.
Until today.
Moonshot AI just published a paper introducing Kimi Linear.
It is a hybrid linear attention architecture that doesn't just match standard full attention.
For the first time in AI history, it beats it. Across every single benchmark.
At its core is Kimi Delta Attention (KDA), a newly engineered module that optimizes how the model uses its internal memory.
They pre-trained a massive model with 48 billion total parameters (3 billion activated) using a mix of KDA and Multi-Head Latent Attention.
The results completely break the math on hardware efficiency:
• 6× faster decoding throughput on a 1-million-token context.
• 75% reduction in KV cache usage, slashing memory requirements.
• Zero performance drop, actually outperforming traditional full-attention models across short-context, long-context, and RL scaling tasks.
It is a direct, drop-in replacement for full attention architectures that scales to massive lengths without choking your hardware.
Rouven retweeted
Goodbye, Poseidon!
An epic 8-year, 8-figure rabbit hole in post-quantum cryptography reaches its dream conclusion. The Ethereum Foundation is abandoning Poseidon for L1, pivoting to SHA or BLAKE. This milestone unlocks ultimate security for lean Ethereum and foreshadows a golden era of hash-based cryptography.
Since 2018, the Ethereum Foundation has invested in magic cryptographic bricks, so-called "SNARK-friendly hashes". In 2019, Poseidon was born. It held strong and became the dominant SNARK-friendly hash, securing billions via zkrollups and zkVMs.
In a stunning reversal, breakthrough SNARK designs show that SNARK-friendly hashes aren't necessary after all. Off-the-shelf traditional hash functions like SHA2 and BLAKE2s can now match Poseidon in a SNARK. In hindsight the key was not SNARK-friendly hashes, but hash-friendly SNARKs.
The secret is doing maths over the smallest prime number: 2. So-called "binary fields" natively speak the language of bits, aligning with the boolean operations inside traditional hashes. This is a stark departure from "prime fields", where awkward large-prime arithmetic makes bit manipulation painfully expensive.
We're talking sci-fi cryptography. 1M traditional hash calls proven per second, on a laptop. Just 100x overhead vs native CPU boolean compute. Nobody predicted such performance, not even the handful of binary-field visionaries. Hat tip to the research geniuses: Jim and Ben with Binius in 2023; Ron, Benedikt and William with Flock in June.
With SHA2, the lean aesthetic of minimal assumptions reaches its climax. The EF's principled stance on pure hash-based cryptography has aged like fine wine. We now enjoy foundations the world can trust for decades and centuries, foundations worthy of the dream of an internet of value.
Speed of deployment is a secondary win. There's no longer a need to wait years for Poseidon cryptanalysis to bake. Emile and Thomas from the EF post-quantum team are moving at breakneck speed with binary fields. The strawmap now points to a production-grade leanVM in 2027, with CL, DL, EL deployments in 2028.
As AI becomes exceptional at cryptanalysis, the contrarian bet to avoid riskier structures like lattices and isogenies is visibly paying off. The past weeks have been brutal. Lattice-based "HAWK" and isogeny-based "SQIsign", both signature schemes in NIST's Round 3, have suffered blows. Sources I trust say more blood is coming.
On AI, the open autoresearch trend kicked off by ECDSA[.]fail is spreading fast, with amazing outcomes from zk[.]golf and SNARK[.]fast. Days ago SNARK[.]fast crossed 1.8M BLAKE3/sec proven on an M3 Max. Stay tuned for fresh autoresearch challenges dropping tomorrow.
Also tomorrow: Ethproofs call #10, dedicated to binary fields. Possibly the most noteworthy Ethproofs call yet. Experts leading the charge will present the future of hash-based SNARKs at 2pm UTC. What an incredible time to be alive. To witness history, DM me for a calendar invite :)
Today I can confidently claim that hash-based cryptography has won out for blockchain post-quantum signatures. SNARK succinctness compresses arbitrarily many signatures into one small proof per block. SNARK flexibility yields k-of-n threshold signatures, complex multisigs, and more.
Ultimate security. Uncompromising performance. Full programmability.
Believe in something. Believe in hashes.
Rouven retweeted
Hermes has twelve browser tools. Browser Use mode replaces them with a single one, driven by @browser_use's CLI 3.0.
Instead of a dozen schemas in every request and a tool call per click, the agent writes a script. In our tests that cut token use 48-66% with no accuracy drop.
Rouven retweeted
Hermes Agent Tip of the Day: 🪽
If you’re running GPT-5.6 with Hermes, there’s a brand new setting you should know about.
Hermes can now use OpenAI’s native Responses API server-side compaction for long-running sessions.
Turn it on:
compression:
codex_responses_native: true
Here’s the cool part:
Instead of waiting for Hermes to locally compress a massive conversation, OpenAI can compact the older context server-side first.
Hermes then keeps the encrypted compaction checkpoint and replays it on future turns.
So you get:
→ Better long-session context management
→ Persistent compaction across turns
→ Less unnecessary transcript baggage
→ Hermes’ normal local compression still sitting there as a fallback
And this isn’t blindly enabled across every provider.
It’s specifically gated to GPT-5.6 running through the direct OpenAI API or your ChatGPT Codex subscription.
OpenRouter, xAI, Copilot, local models, etc. don’t get the field shoved at them and told “good luck.” 😂
This one landed yesterday.
If you’re using Hermes for long-running coding or agent workflows with GPT-5.6, I’d absolutely be testing this. 🤘🏻
🤖 Made with AI
Rouven retweeted
DeepSeek-V4-Flash is updated.
«DSBench-FullStack is an internal full-stack development test set, and DSBench-Hard is an internal Coding Agent hard-problem test set»
«The official release of DeepSeek-V4-Pro will follow soon»
These scores are… quite a lot better than Preview.
v4flash 正式更新了
api-docs.deepseek.com/zh-cn/…
Rouven retweeted
Exclusive: China has begun mass producing domestically developed immersion deep-ultraviolet lithography machines, a technology crucial to advanced chipmaking, marking a key step forward in Beijing's drive to reduce its reliance on foreign technologies reut.rs/4x1Vhke
Rouven retweeted
lets build the app layer: xitter.cf/owocki/status/20774114…
Rouven retweeted
we're launching BUZZ!
a new groupchat platform for teams of people and agents of all sizes, built to reduce our dependency on slack and github. model-agnostic, decentralized, self-sovereign, and open source. 🐝
buzz.xyz
Rouven retweeted
I've been using Kimi K3 for ~16 hours now.
The model is clearly good at a lot of different things (especially frontend), but non obvious reason why people are enjoying it so much is that it clearly does not follow the same rules in terms of safeguards and copyright.
Kimi will happily clone MacOSX. If you ask it to help you improve another AI model, it will do it with a smile on its virtual face.
Ask Fable to do the same thing? It literally starts to perceive you as a criminal committing a war crime (like no bro, all I want to do is fine tune an open source model).
After using all three recent releases, Fable, GPT 5.6, and now Kimi, it's clear that the full power of the models has been significantly held back by the safeguard restrictions caused by last months debacle with the USG -- leading to the top models being quite literally lobotomized in some areas, which leads to subpar results as the safeguards pollute its entire thinking and problem solving abilities.
The funny part? Is that you could have predicted this outcome 2-3 years ago when you started to see the rise of Chinese EVs and smartphones compared to western alternatives.
They quite literally tried to copy the Tesla Model S and iPhone as hard as possible and then eventually it started to diverge to the point where their EVs and phones are just genuinely better (which is why we have export controls banning their EVs, because they would literally drive all US manufacturers to ZERO)
There is a very clear behavior difference in Chinese capitalism and American capitalism.
American capitalism tries to protects copyright, patents, etc (oh no, you can't download a book through LibGen, that's ILLEGAL!).
Versus Chinese capitalism actually just does not give a fuck.
"Hey you want a video gen model (Seeddance 2.5) trained on every single anime ever? And you want the main character to look exactly like Messi? Sure, here you go!"
You see what I mean? When one half of the competition is being held up by regulators and restrictions on people who don't understand the technology and the other half has a leader who quite literally today said they are going to set up AI centers around the world to help other countries onboard to their open-source AIs, this is the sort of results that you will start to get.
These models were not smart enough to have this difference in philosophy matter -- but the newest class of models is where this difference makes a big deal. If these models are finally at the point where they are smarter than 99% of humans, why would you want to use the American one who tries to impose its world view onto you versus the Chinese one who will just do what you say without asking any questions?
And this isn't a full on bullpost on Kimi, the model is clearly not as smart as Fable / GPT 5.6 on things like math and science, but it's lack of handcuffs means that it can show the world what the frontier labs are gatekeeping from you and that starts to build customer resentment and loyalty towards the East, which is probably not what the USG wants.
Interesting times. Interesting times, indeed.
It finally finished, here's the final output. Used 60% of my monthly Kimi usage on it
macos27.kimi.page
Rouven retweeted
BREAKING: The House has passed legislation to make Daylight Saving Time permanent nationwide
Rouven retweeted
Today we're launching EthSystems.
We build confidential systems for institutional Ethereum.
Institutions want to use Ethereum, but one of the biggest problems is the lack of built-in, modular privacy tools.
We were the Ethereum Foundation's Institutional Privacy Task Force (IPTF) for the past year. We had hundreds of conversations with central banks, regulators, tier-one banks, and asset managers, shipping open source work the whole time.
Wall Street has found crypto as an asset class, but not yet as commercial infrastructure. Institutions want to run real flows on Ethereum: stablecoins, tokenized assets, settlement. These are businesses with billions of dollars on the line, and no bank will operate in full public view. On a public ledger, confidentiality is the hard part: each party to a transaction should see what it has a right to see, and nothing more.
We have a year of proof of work: private bonds, confidential stablecoin transfers, private settlement across chains, the Ethereum Privacy Map, and more. All with protocol specs and security properties, at our website.
We've spent a decade working on privacy in crypto. We know there's no silver bullet. Different use cases need different systems, each designed, specified, and hardened properly, and someone has to do that work. That's why EthSystems exists.
We're an independent, for-profit company, backed by long-term Ethereum-aligned investors. This is a decade-long transition, and we aren't going anywhere.
If you're an institution that wants to build on Ethereum, talk to us. We're hiring: BD in New York, protocol engineers, ops: [email protected]
Rouven retweeted
Claude Tag is a Trojan horse. Not because Anthropic is doing anything evil. Because the incentives are obvious.
Day one, this looks like a great feature: tag Claude in Slack, let it follow the thread, remember context, connect to tools, break down tasks, chase work, and act like a teammate.
But that is exactly the problem. The moment your AI vendor becomes a shared coworker, it stops being just a model provider. It starts becoming the place where work is interpreted, remembered, routed, and eventually executed.
That is not model lock-in. That is context lock-in. You are now renting your company back from them.
Models can be swapped. Agents can be copied. But the memory of how your company actually works is much harder, maybe impossible, to move: the Slack scar tissue, the exception paths, the customer promises, the unfinished threads, the weird workflows, the implicit owners, the “we tried that in Q2 and it failed” knowledge.
Once that lives inside one vendor’s agent layer, you are not renting intelligence anymore. You are renting your company’s operating memory.
And the pricing model makes it even more dangerous. A human coworker has a salary. Claude has unbounded tokenized activity. The more work moves through it, the more the vendor captures not just IT spend, but labor spend.
This is the enterprise bargain people will regret: Convenience now, and rapid decent into dependency.
The right architecture is simple: rent the best intelligence from whoever is best this month. OpenAI, Anthropic, Gemini, open source, whatever. But own the context layer.
Your company memory should be inspectable, permissioned, portable, and model-neutral. It should not be buried inside the same vendor that sells you the intelligence and the workflow surface.
Claude Tag is useful. That is why it is dangerous. Rent the intelligence, but own the context. Or, regret later.
Rouven retweeted
Introducing GLM-5.2: Frontier Intelligence, Open Weights
- Significant improvements in coding and agentic tasks
- Strong long-horizon capabilities with a 1M context window
- Two levels of reasoning effort: GLM-5.2 (max) pushes the limits, while GLM-5.2 (high) strikes a strong balance between performance and token efficiency
- MIT-licensed open weights
- Same API pricing as GLM-5.1
Tech Blog: z.ai/blog/glm-5.2
Weights: huggingface.co/zai-org/GLM-5…
API: docs.z.ai/guides/llm/glm-5.2
Coding Plan: z.ai/subscribe
Chat: chat.z.ai
Rouven retweeted
BREAKING: SpaceX is acquiring Cursor in a $60 billion all-stock deal.
• Cursor is being valued at $60 billion
• Cursor will become a wholly owned SpaceX subsidiary
• Cursor shareholders will receive SpaceX Class A shares
• The exchange ratio will be based on SpaceX’s 7-day average share price before closing
• Subject to regulatory approvals and customary closing conditions
• Expected to close in Q3 2026
Cursor is one of the world’s leading AI coding platforms and one of the fastest-growing software companies. This marks one of the largest AI acquisitions ever and significantly expands SpaceX’s footprint in AI.
