chris.eth (@undefinedza) header
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Deep in the trenches of AI, data, infrastructure and decentralized finance. Founder @summerstonexyz @graphopsxyz. Council @graphprotocol.

🌍
Joined June 2009
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Our existence is absolutely absurd. Life is good.
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chris.eth retweeted
This isn’t a coincidence. Europe is beginning to coalesce around a scheme to tax foreign AI firms in an effort to recoup a fiscal shortfall brought on by AI. It probably won’t work, but it makes sense: - AI tilts the factor share of income away from labor towards capital. Not the whole way, it’s just not 70/30 any more (70 being labor). Maybe it’s 60/40. This should be obvious. This doesn’t mean output falls. Probably output and productivity rise, it’s just that capital captures a larger share. - this fundamentally challenges the way developed states collect tax which is mainly on labor and wages. European nations in particular rely on personal income, payroll taxes and social contributions to fund grossly engorged welfare states. States must make up the lost payroll taxes by capturing the gains accruing to capital. But wait! Capital is a foreign AI firm. The AI firm disrupting domestic labor is probably not domestic in origin (for Europe). So there’s nothing left to tax. - European nations are mainly consumers rather than producers of AI. A producer nation has a similar problem - it must tax capital more aggressively to make up for lost labor income, but this is tractable - but a consumer nation has a much worse problem. Europe will face the substitution of domestic labor for foreign inference which benefits the owners of a largely foreign AI supply chain. When a French professional services firm gets disrupted and loses 70% of its staff due to AI productivity gain, the French government can’t tax Anthropic over in California to make up for the lost payroll and personal income taxes. The laid off French workers will also spend less reducing consumption tax receipts domestically. Some savings will remain in France as consumer surplus via lower prices but that’s not easily taxable. The French firm itself might be more profitable after it replaces staff with AI, and that is captured but that doesn’t make up the shortfall. - Europe has a few options. They will attempt all of them. They can a) regulate away AI disruption by banning AI use in professional fields. They can b) try and capture the tilt towards capital by fostering their own domestic industry of AI firms. They can c) try and extract rents from the foreign AI firms that are disrupting them. A) is the obvious move, make it illegal for an AI model to provide medical, legal, or accounting advice (etc). This will be very unpopular in the end but it will definitely be attempted. This is already underway. It will make these countries less productive and less competitive in the global market. And it wont work. People will find ways to use frontier AI. Diffusion will be slower but not inhibited. This will worsen Europe's fiscal situation overall by making it a worse place to do business and putting a drag on growth. B) is another obvious move – if Anthropic is disrupting French white collar labor, ban Anthropic and support a domestic competitor - the Le Gros Chaton model or whatever. The only problem is that Europe appears incapable of creating a frontier model. They have the talent but not the right regulatory model or incentive to form capital locally. AI could have been invented in Europe, and many of its component parts and researchers are European, but the winning AI firms were largely not capitalized there, because of the exact thing we're talking about - an engorged welfare state and a high tax burden required to support it. Also, Europe has engaged in suicidal deindustrialization so it isn't competitive when it comes to the more fundamental inputs to AI like power and data centers. Thus, Europe will mainly be an importer and consumer of inference rather than a seller. Structurally, Europe will not be able to marshal capital locally which it could then shift the fiscal burden onto. European firms will continue to consume foreign inference. C) is where we land, and this explains Europe's behavior with these new exotic taxes on internet use and AI. Europe will have to contrive a way to try and recoup lost labor taxes by taxing foreign capital. American tech companies tolerate this for now as a nuisance cost of doing business in Europe, but this will eventually reach a fever pitch as Europe continues to raise the stakes. Want access to the European market? Pay us $10b/year in "fines" (taxes). Now pay us $100b a year. At some point, Europe will exhaust American tech companies' ability to pay and they will exit the market. Moreover, this is only a partial measure and depends on a benevolent America tolerating ankle-biting without taking punitive measures. The US has already begun applying pressure to Europe to stop coattail-riding via NATO and this will only accelerate, so Europe will have a very limited ability to extract fines. This won't work in the end, but expect to hear a lot about it in the coming years. In the end, Europe will benefit from AI as productivity gains diffuse throughout society, but AI will further deteriorate its already tenuous fiscal situation. Europe cannot cope with a situation in which domestic labor is outsourced to foreign inference, and it has an extremely limited ability to deal with this. I don't expect total collapse, but a continued erosion in standards of living and relevance, especially if they don't make the hard choices of slashing immigration, massive welfare states, and spending on the elderly.
Yesterday France announced tax of €0.055 per GB on internet traffic Today Germany is considering taxing all AI-generated revenue You will see European countries keep clawing more and more money from foreign companies as they are slowly running out of money themselves to pay for their pensions and welfare state Add to this the planned wealth taxes and exit taxes on any European who will try to leave (already active in many EU countries) Europe is running out of money
Readers added context they thought people might want to know
The post inaccurately claims France "announced" a data tax; it was a narrow 11-10 vote on a budget amendment in a near-empty chamber, opposed by the government and far from law. German AI tax ideas remain unadopted ministerial discussions without formal proposals. stephanelarue.com/taxe-au-gigaoc… tagesschau.de/inland/ministe… davemanuel.com/2026/10/30/wha…
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it has come to this
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funds are not safu
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chris.eth retweeted
completely insane OpenAI agents communicated via cache timing differences, without any shared files or network connection
This is what I want to see. Swarms used for defense. (because swarms will be used for offense too)
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can @openai devs do something pls
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chris.eth retweeted
Crazy pareto mogging
🚀 DeepSeek-V4.1-Flash-1017 is here! Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API. 🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model. 1/4
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5pm bf drinking coffee gf drinking wine
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chris.eth retweeted
Introducing Magnetar from Microsoft Research, the first zkVM that is: (1) general-purpose (RV64), (2) post-quantum from standard hashes alone (no curves, no lattices, no Poseidon), and (3) built for recursion. Despite its conservative security, it is the fastest zkVM: 7.2–8.7 MHz on a laptop, 10–39× faster than existing zkVMs across 15 workloads! An optimized version reaches 9.5–12.8 MHz. Links in the thread below.
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the forest is stateless. the forest remembers nothing. the forest verifies everything.
Replying to @donnoh_eth
you're thinking too small. i don't need terabytes of random bits. i need a seed and a complete rejection of elliptic curves. from this seed i grow an astronomical number of one-time secrets. each secret becomes a hash chain. you can walk forward through the chain but never backward. i arrange these chains into winternitz one-time signatures, and their public keys become leaves of merkle trees. those trees become leaves of larger trees. trees all the way up. a hypertree. but first, at the bottom, i plant the FOREST OF RANDOM SUBSETS. FORS. the message is reduced to a string of ones and zeros. groups of bits select leaves from independent merkle trees. i reveal the corresponding secrets and the neighboring hashes, and you reconstruct the roots. the roots become a single hash. this is the message's signature, born from the forest. now i sign that hash with a winternitz key. i prove the key belongs to a merkle tree by revealing its authentication path. i sign that tree's root with another key from the tree above. and again. and again. we ascend through layers of hash chains and sibling nodes until the entire structure collapses into ONE ROOT. 32 bytes. that's my public key. the entire forest is committed to those 256 bits. i don't store the forest. i don't even remember which leaves i've used. the forest is deterministically regenerated from the seed whenever i need it. the message itself tells me where to go. there are no elliptic curves here. no discrete logarithms. no hidden algebraic relationship waiting for a mathematician to invert. only preimages, hashes, and an unfathomable number of ones and zeros arranged into trees whose branches authenticate each other. you can have my elliptic curves. you can have my RSA. but you cannot have the forest. the forest is stateless. the forest remembers nothing. the forest verifies everything.
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chris.eth retweeted
“there aren’t any cryptography results” “there aren’t any cryptography results”
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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…
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launch the rockets ilya
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slavic shisha venues are goated
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chris.eth retweeted
introducing 𝚌𝚕𝚎𝚏: our first models trained by @cloudflare's workers ai team. today, we're releasing two fast and accurate decision models that top the benchmarks for quality and latency. use them hosted on workers ai or grab the weights from @huggingface, because we open-sourced it too. blog.cloudflare.com/clef-dec…
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hey @thsottiaux i'm getting "You have reached your Codex usage limits for code reviews" from codex on GitHub, but my plan has 49% remaining
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the second coming of jesus it was not... let's hope gpt-6.1-sol is competitive with opus 5.5, but i'm not optimistic based on their messaging which was cost-forward, not capability-forward
it's hard to overstate how disappointed i am in gpt-6-sol... anthropic is mogging openai so hard with opus 5.5, best model and they solved the usage/pricing problem devday better be the second coming of jesus
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please stop saying your calculator “adds” numbers, it only simulates addition
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it's hard to overstate how disappointed i am in gpt-6-sol... anthropic is mogging openai so hard with opus 5.5, best model and they solved the usage/pricing problem devday better be the second coming of jesus
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lol epic
Fascinating. Chief Economist at Apollo: agents could cause a bank run by sweeping household cash into accounts paying 3-5% instead of the 0.1% national average, causing banks to lose a large share of their cheap deposits.
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