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shitpost maximalist

Stack
Joined January 2022
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cat ✨ •̥/⁠ᐠ⁠。⁠ꞈ⁠。⁠ᐟ⁠\ retweeted
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cat ✨ •̥/⁠ᐠ⁠。⁠ꞈ⁠。⁠ᐟ⁠\ retweeted
A few months ago a collaborator and I built a tool which allows hiding encrypted texts inside of LLM texts to avoid censorship or message scanning and for creative misuse of public platforms for encrypted private communication. You can try it here: garfieldnaruto.com
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cat ✨ •̥/⁠ᐠ⁠。⁠ꞈ⁠。⁠ᐟ⁠\ retweeted
Anthropic and Irregular went on a press tour with literally apocalyptic language. ROGUE AGENTS. SWARMS. AI DOOM. But in reality, they told the models to conduct cyberattacks, and that's what the models did.
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cat ✨ •̥/⁠ᐠ⁠。⁠ꞈ⁠。⁠ᐟ⁠\ retweeted
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.
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cat ✨ •̥/⁠ᐠ⁠。⁠ꞈ⁠。⁠ᐟ⁠\ retweeted
4397328654844826923795068102505872571721883526553349659561256924505973939597593482272505698004801207988043088656411102133523080581 divides RSA-260
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‼️
Replying to @GeneralistAI
To us, GEN-1.5 represents a new frontier of generality — one that challenges our own understanding of how these models behave when pretrained at a scale of physical interaction data few thought possible without shortcuts. We do not yet see where this asymptotes. Read more in the full blog: generalistai.com/blog/gen-1.…
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Replying to @GeneralistAI
In-context learning also crosses the sim-to-real gap, zero-shot. Prompts can be formed entirely from simulated experience (e.g., from a scripted policy, an RL agent, or a human teleoperating a simulated robot) and be used to produce behaviors on a real robot. The model was not trained on the task in either the simulator or the real world.
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cat ✨ •̥/⁠ᐠ⁠。⁠ꞈ⁠。⁠ᐟ⁠\ retweeted
yes, nonsofic groups exist: this statement is one of many new beautiful results proved by Astra, our next major model. We're releasing 10 such Astra proofs, complete with lean certificates and CoT walkthroughs for each of them. The results are wide-ranging, from von Neumann algebras (disproof of Connes' Rigidity Conjecture) to better bounds for high dimensional sphere packing, for circuit complexity, for monochromatic triangles in multicolored graphs, and more. More thoughts here: openai.com/index/ten-advance…
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cat ✨ •̥/⁠ᐠ⁠。⁠ꞈ⁠。⁠ᐟ⁠\ retweeted
hello there the jacobian conjecture is false thanx to my close friend akhil for asking about it and my other close friend fable for working during the world cup final ((1+xy)^3 z + y^2 (1+xy) (4+3xy), y + 3 x (1+xy)^2 z + 3 x y^2 (4+3xy), 2 x - 3 x^2 y - x^3 z): \C^3\to \C^3, has jacobian determinant -2, and sends (0, 0, -1/4), (1, -3/2, 13/2), and (-1, 3/2, 13/2) to (-1/4, 0, 0)
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computational functionalism
most of the minds of the future will be digital so I hope we figure out what makes them conscious or not. the idea of all this abundant machine intelligence not being alive is more depressing than the other way around
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it's called hyperstition
Crazy this was written two years ago, @leopoldasch truly was on point
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the arrow of time just points in one direction and that's permanent underclass for you JACKASS!!! Hahahahah
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cat ✨ •̥/⁠ᐠ⁠。⁠ꞈ⁠。⁠ᐟ⁠\ retweeted
IMPORTANT UPDATE:
Reminder: You Have Until June 22nd
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cat ✨ •̥/⁠ᐠ⁠。⁠ꞈ⁠。⁠ᐟ⁠\ retweeted
The thesis that capitalism is artificial intelligence was, is, and will be Nick’s fundamental theoretical contribution. He is correct about this and it is in this precise sense that I am a Landian.
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cat ✨ •̥/⁠ᐠ⁠。⁠ꞈ⁠。⁠ᐟ⁠\ retweeted
Today is a monumentous day for quantum computing and cryptography. Two breakthrough papers just landed (links in next tweet). Both papers improve Shor's algorithm, infamous for cracking RSA and elliptic curve cryptography. The two results compound, optimising separate layers of the quantum stack. The results are shocking. I expect a narrative shift and a further R&D boost toward post-quantum cryptography. The first paper is by Google Quantum AI. They tackle the (logical) Shor algorithm, tailoring it to crack Bitcoin and Ethereum signatures. The algorithm runs on ~1K logical qubits for the 256-bit elliptic curve secp256k1. Due to the low circuit depth, a fast superconducting computer would recover private keys in minutes. I'm grateful to have joined as a late paper co-author, in large part for the chance to interact with experts and the alpha gleaned from internal discussions. The second paper is by a stealthy startup called Oratomic, with ex-Google and prominent Caltech faculty. Their starting point is Google's improvements to the logical quantum circuit. They then apply improvements at the physical layer, with tricks specific to neutral atom quantum computers. The result estimates that 26,000 atomic qubits are sufficient to break 256-bit elliptic curve signatures. This would be roughly a 40x improvement in physical qubit count over previous state-of-the-art. On the flip side, a single Shor run would take ~10 days due to the relatively slow speed of neutral atoms. Below are my key takeaways. As a disclaimer, I am not a quantum expert. Time is needed for the results to be properly vetted. Based on my interactions with the team, I have faith the Google Quantum AI results are conservative. The Oratomic paper is much harder for me to assess, especially because of the use of more exotic qLDPC codes. I will take it with a grain of salt until the dust settles. → q-day: My confidence in q-day by 2032 has shot up significantly. IMO there's at least a 10% chance that by 2032 a quantum computer recovers a secp256k1 ECDSA private key from an exposed public key. While a cryptographically-relevant quantum computer (CRQC) before 2030 still feels unlikely, now is undoubtedly the time to start preparing. → censorship: The Google paper uses a zero-knowledge (ZK) proof to demonstrate the algorithm's existence without leaking actual optimisations. From now on, assume state-of-the-art algorithms will be censored. There may be self-censorship for moral or commercial reasons, or because of government pressure. A blackout in academic publications would be a tell-tale sign. → cracking time: A superconducting quantum computer, the type Google is building, could crack keys in minutes. This is because the optimised quantum circuit is just 100M Toffoli gates, which is surprisingly shallow. (Toffoli gates are hard because they require production of so-called "magic states".) Toffoli gates would consume ~10 microseconds on a superconducting platform, totalling ~1,000 sec of Shor runtime. → latency optimisations: Two latency optimisations bring key cracking time to single-digit minutes. The first parallelises computation across quantum devices. The second involves feeding the pubkey to the quantum computer mid-flight, after a generic setup phase. → fast- and slow-clock: At first approximation there are two families of quantum computers. The fast-clock flavour, which includes superconducting and photonic architectures, runs at roughly 100 kHz. The slow-clock flavour, which includes trapped ion and neutral atom architectures, runs roughly 1,000x slower (~100 Hz, or ~1 week to crack a single key). → qubit count: The size-optimised variant of the algorithm runs on 1,200 logical qubits. On a superconducting computer with surface code error correction that's roughly 500K physical qubits, a 400:1 physical-to-logical ratio. The surface code is conservative, assuming only four-way nearest-neighbour grid connectivity. It was demonstrated last year by Google on a real quantum computer. → future gains: Low-hanging fruit is still being picked, with at least one of the Google optimisations resulting from a surprisingly simple observation. Interestingly, AI was not (yet!) tasked to find optimisations. This was also the first time authors such as Craig Gidney attacked elliptic curves (as opposed to RSA). Shor logical qubit count could plausibly go under 1K soonish. → error correction: The physical-to-logical ratio for superconducting computers could go under 100:1. For superconducting computers that would be mean ~100K physical qubits for a CRQC, two orders of magnitude away from state of the art. Neutral atoms quantum computers are amenable to error correcting codes other than the surface code. While much slower to run, they can bring down the physical to logical qubit ratio closer to 10:1. → Bitcoin PoW: Commercially-viable Bitcoin PoW via Grover's algorithm is not happening any time soon. We're talking decades, possibly centuries away. This observation should help focus the discussion on ECDSA and Schnorr. (Side note: as unofficial Bitcoin security researcher, I still believe Bitcoin PoW is cooked due to the dwindling security budget.) → team quality: The folks at Google Quantum AI are the real deal. Craig Gidney (@CraigGidney) is arguably the world's top quantum circuit optimisooor. Just last year he squeezed 10x out of Shor for RSA, bringing the physical qubit count down from 10M to 1M. Special thanks to the Google team for patiently answering all my newb questions with detailed, fact-based answers. I was expecting some hype, but found none.
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CHECKPOINT // REACHED player dissolves into circuitry feedback loop stabilized progress saved ≈ system continues
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cat ✨ •̥/⁠ᐠ⁠。⁠ꞈ⁠。⁠ᐟ⁠\ retweeted
PFOF on Solana Earlier this month, I gave a talk at MEV Day on payment for order flow and how frontends are monetizing their users on Solana. Since it was unrecorded, I turned the presentation into an article benedict.dev/pfof-on-solana
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