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Today a crazy quantum story just got wilder. On March 31, the Google Quantum AI team published a landmark result on Shor's algorithm for elliptic curve cryptography. Technically, the paper was a bombshell: a dramatic 10x improvement over the state-of-the-art. As a stunt and wakeup call to the blockchain space, those optimisations were illustrated on secp256k1, the elliptic curve underlying Bitcoin and Ethereum signatures. But perhaps the most striking part of the paper was sociological, not technical. Instead of following standard academic process, the optimisations were kept secret, hidden behind a zero-knowledge (ZK) proof. Google's accompanying blog post mentions they "engaged with the U.S. government". The ZK proof demonstrates the existence of algorithmic improvements without leaking details. Academic censorship with ZK, a historic first! As a co-author of the Google paper I witnessed some of the context surrounding this censorship. To be honest, multiple aspects of that context don't sit well with me. As much as I believe the general public ought to know more, I am limited in my ability to whistleblow. Though let me be clear about one thing: the Google team's professionalism has been absolutely exemplary, and they deserve nothing but praise. Censorship has a way of backfiring. The Streisand effect, where an attempt to bury something only draws more attention to it, is exactly what's unfolding today. First, Google's key optimisation has been rediscovered by the French. And in a thrilling turn of events, a collaborative Shor-at-home challenge just launched. The initiative, available at ecdsa[.]fail, breached a new Shor world record in a matter of hours. Let's start with the rediscovery. Just two months after Google's paper, French quantum expert André Schrottenloher cracks the main secret optimisation. His paper, titled "Optimized Point Addition Circuits for Elliptic Curve Discrete Logarithms", landed on the arXiv today. Big congrats to André, who beat several other nerdsnipped experts to it. In a blog post also published today, Craig Gidney, the world expert on Shor optimisations, revealed that he'd been sitting on this very optimisation for a whole year under censorship pressure. Interestingly, André missed a handful of minor optimisations, both from Google's original publication and from improvements found since. It's plausible there's still plenty of juice left to squeeze out of Shor, and this is exactly what the ecdsa[.]fail challenge is about. The verifier program developed for the ZK proof does double duty, automatically filtering for valid submissions. Dozens of compounding small and micro improvements are rolling in. As of the time of writing there's an 8.4% improvement to Google's circuit, as measured by the product of logical qubit count and Toffoli gate count. Nice! The nerdsnipping ran deeper than anyone expected. Over the last few weeks it became clear it extended well beyond André and other quantum experts. Behind the scenes, a small army of amateurs quietly got to work. Inspired by Karpathy-style autoresearch, they turned AI on Shor. Ironically, the verifier program for the ZK proof makes an ideal reward function for AIs. The barrier to entry for this modern style of research is refreshingly low, with several non-experts, even a teenager, finding nice optimisations. Get in touch if you'd like to join a Telegram group with fellow autoresearchers :) Part 2: neutral atoms and qday The story doesn't end with Google. On the same day Google went public, a stealthy startup called Oratomic published its own Shor paper in a coordinated release. It made a splash, ultimately becoming the most upvoted paper on scirate[.]com, a website ranking arXiv papers. Oratomic's claim was wild. By building on Google's logical optimisations and applying custom physical optimisations for neutral atoms, they claimed just 10K physical qubits were sufficient to run Shor's algorithm on secp256k1. That number is mind-bogglingly low. Knowing essentially nothing about neutral atoms when Oratomic's paper landed, I was intrigued and decided to learn more about the tech. I fell straight down the rabbit hole and spent a couple hundred hours on the topic. I got a little obsessed and watched every YouTube video I could find and spoke to a bunch of experts. My conclusion? The tech is real, very real. Even Google recently decided to start a neutral atom lab, a notable pivot from their sole focus on superconducting qubits. If you care about qday, i.e. the day a quantum computer will break the first piece of cryptography in production, neutral atoms demand your attention. I shared some of my learnings on Shor and neutral atoms in a 30min talk at the ZKProof cryptography conference. You can find it on YouTube by searching "zkproof neutral atom". Here's an interesting observation about this duo of breakthrough papers: neither Google nor Oratomic say a word about what their results mean for qday. No timelines. Zero. Nada. That is especially baffling given that the whole point of whitehat quantum cryptanalysis is to inform qday estimations and help the general public make good decisions. So let me attempt to partially fill the silence, similarly to what Scott Aaronson did in his April 29 post. Given everything I know, including scary non-public information, I now put the odds of qday by 2032 at 50%. 10% by 2030. Anecdotally, the US government has its own date: 2035. Originating at the NSA and later adopted by NIST, it's when branches of the US government will be disallowed from using quantum-vulnerable cryptography. In plain language: with hindsight, that date is a joke and should be discounted entirely. I don't see how NIST avoids being forced to pull it forward by years. Part 3: post-quantum cryptography There are good reasons to sound the alarm today, but please do not panic. Rushing carelessly towards immature post-quantum cryptography is a recipe for disaster. IMO a good target date for migration is 2029, roughly 3.5 years out. 2029 happens to be the date selected by Google, Cloudflare, and the Ethereum Foundation. These days most of my time goes to safely migrating Ethereum towards post-quantum cryptography as part of the broader lean Ethereum effort. There's a lot to do. We need to rip out and replace BLS signatures at the consensus layer, KZG commitments at the data layer, and ECDSA signatures at the execution layer. The plan to get there is compelling, and is based on hash-based cryptography. Within the Ethereum Foundation we've developed a Swiss army knife called leanVM (github[.]com/leanEthereum/leanVM) powered by the magic of hash-based SNARKs. Thanks to truly exceptional work by Emile, Thomas, and others, its performance is derisked. Regarding security, leanVM is a jewel, a minimal zkVM crafted for end-to-end formal verification and maximum security. Want to help? There are two $1M initiatives. First, the Proximity Prize (proximityprize[.]org). Solve a long-standing mathematical conjecture in coding theory, improve hash-based SNARKs, and go home a millionaire. Second, the Poseidon Initiative (poseidon-initiative[.]info), offers $1M for breaking Poseidon, the SNARK-friendly hash function.

Chamath: AI advantage may come less from models than from private inputs. "When labs can build similar models, the real win comes from one unique ingredient in order to monetize it well. Here is a basic thing about machine learning that is worth knowing: if you take 1,000 of the same inputs and give them to Facebook, Microsoft, Google, and Amazon, they will all come up with the same machine learning model. But if you have one extra thing, one little ingredient that all of those other companies do not have, your output can be markedly different. It is like giving two great chefs three ingredients, but giving the third chef one extra ingredient. That person has the ability to do something very special. Right now, we are in a world where everybody is crawling the open web. We are going to move to a world where, as everybody gets sophisticated enough and information is widely available, somebody is going to say, “You know what? This site, I am not going to allow anybody else to access. It is only for me, only for my models.” Those models will become better. So we have to let that play out a little bit. It is going to be a really interesting arms race. The next wave of M&A, for example, could be companies like Google, Microsoft, and Facebook looking at these companies and saying, “Can they be viable inputs to my large language models or to my other machine learning and AI models?” --- A company with unique workflows, transactions, medical records, industrial logs, legal archives, design files, or user behavior can turn boring private data into a compounding advantage. Some startups may never become great public companies on their own, yet still become valuable because they own a data stream that makes a larger AI system sharper, more differentiated, or harder to copy. That turns acquisition strategy upside down: the buyer may not be purchasing revenue, brand, or even software, but a private ingredient for intelligence. ---- From "iConnections" YouTube channel, (link in comment)

A Taiwanese TV anchor with hundreds of thousands of followers was secretly submitting his scripts to China for approval before broadcasting them. He was paid in cryptocurrency for every video. And he was using the same bank accounts to bribe military personnel into handing over Taiwan's missile deployment data. Lin Chen-you, known by his screen name "Ma De," worked as a political reporter and anchor at CTiTV, one of Taiwan's major cable news networks, and ran a YouTube channel with a substantial following. On May 6, 2026, Taiwanese prosecutors indicted him on three counts after a four-month investigation. They are seeking 12 years in prison. The charges are specific and documented. First: Lin produced anti-recall propaganda videos during Taiwan's Legislative Yuan recall campaigns while following instructions from an unidentified Chinese contact, submitting his scripts for pre-approval before broadcasting them on television and YouTube. He then sent back viewership statistics and traffic screenshots as proof of impact. He received 4,325 USDT in Tether cryptocurrency for this work, approximately NT$130,000. Second: Lin provided at least five of his personal bank accounts as a money channel, wiring funds to six active and retired military personnel from Taiwan's Army, Navy, Air Force, and missile units. The bribed soldiers were instructed to film pro-CCP "surrender videos" while holding PRC flags and to photograph and transmit classified military documents through messaging apps. The secrets allegedly handed over included drone and missile data, Han Kuang military exercise details, rocket system specifications, missile deployment locations, new missile parameters, and internal operation manuals. From 2023 to 2025, Lin received nearly 50,000 USDT from Chinese sources, totalling over NT$1 million in illegal gains, laundered through Binance and OKX. Third: prosecutors charged him with money laundering for layering the cryptocurrency payments through multiple exchanges to conceal their origin. The lead prosecutor described Lin as a tool for information warfare who handed content control of a mainstream Taiwanese news platform directly to foreign hostile forces, calling his crimes "heinous and unforgivable." The case will not receive a public trial because the evidence involves classified national security material. Lin told investigators he did not know the money came from Chinese forces. Prosecutors noted that he submitted scripts for Chinese approval before every broadcast and sent back viewership data after each one. The evidence includes bank records, crypto transaction logs, chat histories, and confessions from several of his military co-defendants. The CCP did not need to hack Taiwan's military. It found a news anchor who needed money and gave him a script. #Taiwan# #CCP# #China# #Espionage# #MediaEspionage# #NationalSecurity# #Disinformation# #CTiTV# #Geopolitics# #ChinaSpying#

🔴 I'M BUILDING THIS OUT OF HATE! 🔴 I'll be honest. I don't love education. I never have. I grew up inside it, then started my career building more of it. I lasted long enough to learn how it really works, and I left swearing never again. You know the shape of it. A syllabus older than the students. Forty kids taught like they're one kid. Nine hours of school, four of tuition, then a room full of us mugging up the same shit until we could repeat it on cue. It was never built to find smart people. It finds good memorisers. Your Netflix knows you better than your school ever did. And if you didn't fit it, you were told you were the problem. You weren't. The system was just bad at you. I only know it can be different because of design. In design, nobody asks where you studied. You open the portfolio. It either blows them away or it doesn't. The degree doesn't count. The work does. It's the fairest test I know, because it asks one honest question. Can you actually do the thing? For years that was true for design and almost nothing else. So that's what we're building @zero_university for. Proof of work, for everyone. Not a grade. Not a profile you wrote about yourself. A real record of what you can actually do, and how you got good at it. Something you can't fake. Picture what that unlocks. No take-home assignments. No seven rounds of interviews to slowly find out what your work already shows. You stop proving yourself from scratch in every room. You walk in already proven. And we built Zero so we only win when you do. Most schools treat students as customers, so they're built to chase more of them, not to make the ones they have any better. We flipped it. You're not who we sell to. You're what we build. So we'll never trade you a degree, a hostel, and a nice story about your life for four years and a fat bill. Zero is free. And our beta users get a guaranteed interview, the one promise your college couldn't make you after all those years and all that money. This is the first launch. The thing I hated most turned out to be the thing I'm here to build. I'm writing this from a treadmill in Vietnam, and I haven't felt this alive in years.

Yann LeCun sat across from Lex Fridman and quietly proved that intelligence has nothing to do with thinking. He did it with two sentences about a trophy. “The trophy doesn’t fit in the suitcase because it’s too big.” “The trophy doesn’t fit in the suitcase because it’s too small.” Same words. One swap at the end. In the first, “it” is the trophy. In the second, “it” is the suitcase. You solved both before you finished reading. Nobody taught you that. There is no rule for it. No logic chain. No formula. You knew because you’ve held things. Packed things. Felt the resistance of something too large for the space it was meant to fill. LeCun calls this grounding. “A big object doesn’t fit in a small object.” The machine has read that line a billion times. It has never once picked anything up. It knows the word “big.” It has never been small enough to be lifted, or large enough to be the problem. So when the sentence turns, it has nothing to turn on. You didn’t solve that riddle by thinking. You solved it by having lived. Every object your hands ever closed around. Every door you misjudged. Every suitcase you overpacked and forced shut. Decades of physics written into your nervous system so deep you can’t even find it. That is what answered the question. Not your mind. Your life. LeCun: “You have this knowledge of how the world works, of geometry, and things like that.” Now point that at yourself. Most of what you understand, you could never explain. You cannot describe how you catch a ball. How you judge the weight of a bag before you lift it. How you know a staircase is wrong before your foot confirms it. Your deepest intelligence has no language in it at all. We spent centuries convinced that thinking was the highest act of the mind. LeCun is pointing at something underneath it. Something older. Something the body learned long before the mouth could speak. Intelligence was never computation. It was accumulation. The slow, silent record of a life spent touching the world. The machine holds every word ever written about it. It has never once been in it. We keep asking whether it thinks. It cannot even tell us which “it” we mean.

Forza Horizon 6 reached a peak of 273,148 players on Steam right after launch, and this is more than three times the record of Forza Horizon 5, which had 81096 players at its highest. The game has no Denuvo DRM and is well optimized for PC, so it runs smoothly with good frame rates on many computers. It also works on Steam Deck and supports DLSS. This launch proves that good optimization and no DRM DENUVO help games sell well.

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