AI Engineer living in the San Francisco Bay Area

Santa Clara, CA
Joined January 2013
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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Replying to @not_so_gratian
The most disturbing part is that he runs local models and thinks they have a soul. I understand if he was talking about Mythos or something, but Qwen3-4B? come on!!!!!
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Replying to @Hesamation
they say many times they will leave everyone unemployed and might end civilization, and is all good. They think they might hurt Claude feelings and they publicly apologize. This is Kent Brockman level of stupidity
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Replying to @notkevinzhang
still have room for one more?
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Replying to @Polymarket
I guess Claude convinced them of that.
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At this point I think is safe to say that LLMs are very elaborate NPCs
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Yo no estoy tratando de lavarle la cara a nada. Yo solo estoy diciendo que el Chavismo es consecuencia de décadas de abandono a los sectores populares. Chavez y Maduro solo culminaron un proceso de decadencia social que parecia inevitable.
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Las cifras de CEPAL, que son bastante confiables, indican que en 1998 cerca de la mitad de la población vivía bajo la linea de pobreza, y 20% en pobreza extrema. Mas de un millón de personas vivían en los cerros caraqueños. Esto en tiempos donde el promedio latinoamericano era 40%. Entonces, no solo se vivía en pobreza, si no que teniamos mas población pobre que muchos países latinoamericanos.
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De acuerdo. Sin duda alguna los Venezolanos sabían arreglárselas muy bien. Pero eso que describes, aunque muy cierto, no es lo que dice el video. Yo me pregunto si es verdad que los millones de personas que viven en los cerros, tenían fiestas de navidad en hoteles 5 estrellas. Por otro lado, me parece irónico que se nombren planes como FECAFASV, Cesta Tickets, Salud Gratuita, Ipasme, etc. Ya que son políticas que hoy en día serían consideradas casi de ultra-izquierda. Y más irónico aún, que hace 20 años, Chávez llevaba 7 años en el poder y CAP había salido del poder hace 12 años. Entonces, cual es el mensaje del video, que con Chávez se vivía mejor?
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Replying to @whitezuelans
Para un porcentaje pequeño de la población quizás, pero para la gran mayoría que vivia en pobreza la realidad era diferente.
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Replying to @FishAudio
Fish
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Today we’ve raised $52M Seed and we are announcing the public launch of S2.1 Pro. >It can clone a voice from 5 seconds of audio >2x faster than Cartesia & 1/6th the cost of Eleven Labs >most expressive model with word level control over emotion, intonation, pacing etc We support frontier AI companies including HeyGen, LiveKit, Retell, Sanas, and OpenArt all run our model in production. If you're a business and we can't cut your voice AI costs by 50%, we'll give you 1 year of Fish Audio for free. Book a demo: s.fish.audio/tmapke To celebrate our first birthday, we'll give you 1 month of S2.1 Pro for free. Like, retweet, and comment “Fish” to get it.
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Replying to @OrinKerr
or just feed it to the prompt 😂
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Replying to @deanwball
So, basically the government show lie to the public about the risk of open source models. There's strong evidence against this in Strategic Trade Policy (Brander-Spencer) and Game Theory (in repeated games short-term NE is not the same long term NE). Not to mention that this is classic rent-seeking, i.e., a ditorsion of capitalism. Most of the economic schools from Smith, to Buchanan, to Hayek to Friedman denounced this behavior. I mean, since you are so worried about AI communism. The issue here is that is not suggesting that the US government should help American AI industry, but that they need should protect OpenAI and Anthropic.
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Our modern crises are intertwined: a warming planet, a rising human footprint, and societies strained by inequality and political polarization. And yet, Marten Scheffer approaches these problems with a fundamentally hopeful outlook in his new book, Tipping out of Trouble: How Societies Transformed and How We Can Do So Again. The book argues that societies, like other complex systems, can shift suddenly from one stable state to another, and asks how ours might move toward one where humans and other species can thrive in the centuries to come, writes SFI External Professor Tim Kohler in this book review. santafe.edu/news-center/news…
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What will it take to bring AI into the physical world? @drewhenry joins @Emerj AI Research CEO Daniel Faggella to discuss the compute foundations needed for Physical AI, from energy-efficient, heterogeneous compute to the importance of digital twins for real-world deployment. 🎧 Listen: okt.to/vj8ue1
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"We have almost a control tower view of the entire industry. We see everything. We talk to everyone."   On @TBPN, Arm CEO Rene Haas shared how our position at the center of the world's compute ecosystem gives us a unique perspective on the technology and trends shaping the next era of AI and computing.   Watch the full interview, starting at 01:05:36: okt.to/MnhWOY
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Replying to @atmoio
Mo you are may favorite digital stripper
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how many TPS do you think you are getting with claude?
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