A co-creator of AlphaGo, the landmark AI program from Google DeepMind, is the latest prominent researcher from the company to depart and seek significant funding for a new startup, according to people familiar with the matter.

A company of two people and 10,000 AI agents. That might be what founding a startup looks like from here. On @davidsenra's podcast, @GroqInc Founder & CEO @JonathanRoss321 laid out what AI does to company building. In this clip: ▷ Senra's picture of the future: you, a co-founder, and 10,000 AI agents. And Jensen Huang's answer to the fear of managing agents smarter than you: "I already do that." 60 direct reports, each smarter in their own domain, and he orchestrates them all. ▷ Ross on the founder skill that survives: asking the question no one else thought to ask. It's a skill, and you can hone it. ▷ The unsolved part: a workforce of 10,000 agents needs more than intelligence. Every one of them needs verifiable identity, a budget it cannot exceed, and a way to settle what it spends. That trust layer is the infrastructure Kite is building. 🪁

A TV series adaptation of Rebellion’s BAFTA-winning videogame Atomfall is in development. The project is a co-production between Rebellion and Two Brothers Pictures, the team behind Fleabag and The Assassin. It follows a man who wakes up with no memory in the Quarantine Zone in England’s Lake District, established after a nuclear incident.

Becoming a pilot nearly killed me, twice. It also saved my life. Fifteen years ago, my world was upside down. I was in founder mode building a company, raising three young kids, navigating a struggling relationship, leaving my religion, inflamed, sleep deprived, fatigued, and fighting chronic depression. Driving home from work one day, I saw a sign inviting prospective students to take a discovery flight. I thought this flight might occupy my mind, giving me an hour of desperately needed relief. Thirty minutes after arriving at the airfield, the instructor and I were seated in a Cessna 172. The instructor told me to take the controls and explained the departure procedure. Caught off guard, I suggested it would be better if I just observed. He insisted I take the controls, reassuring me that his hands would be on the dual controls at all times so not to worry. Reluctantly, I took the controls. We radioed our departure to the local airspace, lined up, and accelerated down the runway. At 63 mph, I pulled back the controls to raise the nose, and up we went. All of my life’s pain disappeared as I became absorbed in managing the throttle, pitch, heading, radio, traffic surveillance, and my instrument panel. I was mesmerized. I earned my pilot’s license two months later and bought my first airplane, a Bonanza A36. It could fly faster, further and have more passengers than my trainer airplane. I made myself a promise to never fly alone, and hired a full-time co-pilot. General aviation accident rates are nearly 10x higher than commercial airlines. I began flying myself everywhere across the country. For business: Austin, NYC, and Omaha. For family trips: Niagara Falls, Mount Rushmore, Bahamas, and later, with a longer range airplane, we flew to Europe via Canada, Greenland, Iceland, Scotland, London, Paris and Rome. In my first year of flying, I nearly died twice. I had hired a co-pilot for my safety, and ironically both incidents resulted from his errors. However, the worst mistake was my failure to recognize the bigger pattern: despite my co-pilot having logged over 1,000 flying hours, nearly all of the hours were “in the pattern”, meaning instruction time around the airport and not “in the wild” (out in high stress, cross country operations with severe weather). Lesson learned. After these two near-death experiences, I decided that I’d need to either stop flying or get a jet. A jet would give me engine redundancy and the capability to cruise above weather systems rather than through them. The Bonanza had a ceiling of 14,000 (before I needed to supplement oxygen), where a jet could fly in the 30,000’s and 40,000s, above weather. A jet would also allow us to always fly with the assistance of air traffic control in controlled airspace versus in un-cleared VFR (visual flight rules) flight. I purchased a small jet, a Citation Mustang, and completed my type rating (licensed to fly the airplane). It was a steep learning curve. Jet speed is different from small airplane speed. Everything happened faster, the airplane was more complicated, and multi-engine dynamics were a big step up. It was exhilarating. Part II In an unexpected twist, learning to fly brought me back from the depressive dead. When I started flight instruction, my personal life was a mess. The most irritating part of my existence was that every day, around 7pm, just after putting the kids down, I’d overeat. I tried everything to stop myself but nothing would work. My willpower at that time of day from the stress and strain of life was zero and I was powerless against the chemicals in my body that demanded this daily self-destruction ritual. My pants were too tight and I couldn’t button the top button. It drove me insane. But I refused to concede and buy a bigger pair. I turned to my pilot training to help me design a solution: I needed structured operations for my food consumption and self control. Aviation is substantially more safe than driving because it operates on structured protocols, checklists, and active risk management. Safety and performance are a system. You don’t just get into an airplane and wing it. Before every flight, there is a pre-check routine where you thoroughly inspect the airplane, ensuring everything is in flight-ready condition. There are other checklists for starting the airplane, taxing, taking off, cruise, descent and landing. There is a manual beneath your seat with a written protocol for anything that could go wrong with the airplane. You are required to memorize and execute procedures flawlessly under pressure. Aviation culture assumes human fallibility and designs systems to overcome those limitations and liabilities. As I was learning this new way of thinking and operating, I wondered if these new autonomous systems would map to my personal life. I was in desperate need of help and nothing I had tried was working. It was clear that Evening Bryan, the version of me who took control of my body at 7 pm, was no match for the stress and weight of the day. He wasn’t a bad guy, he just wasn’t equal to the responsibility of withstanding that tension. It was a system error to ask him to operate Evening Bryan under his duress. I put Morning Bryan in charge instead and he made an operational guide for all other Bryans to follow. Morning Bryan is my best Bryan. He’s responsible, motivated, high on will power, and thinks long term. He created a checklist that required all Bryan’s to be finished eating by 5 pm. No matter what, no more food after 5 pm. That was when the danger zone started. There wouldn’t be any exceptions, ever. This worked. It was challenging for the first few days but it quickly generated it’s own momentum. I started sleeping better, losing weight, and feeling less fatigued. That simple trick fixed years of mayhem that had been unfixable. With that success behind me, I expanded the protocols to include food types, amounts and timing. In retrospect, after a few months of this new system, it seemed weird that I previously winged it daily, stumbling from meal to meal. I felt like I got back 40% of my total energy capacity that was being spent thinking about, planning, debating, and regretting my food consumption. My life today basically runs like an airplane. Part III Aviation culture then jumped into other areas of my life. I’d started a new company, Kernel, to build a non-invasive brain interface to merge human cognition with AI. I’d been thinking about what mathematician Alfred North Whitehead observed: "Civilization advances by extending the number of important operations which we can perform without thinking about them." Society is on a continuous curve of increased automation. We solve one layer and step up on the next. This is how we scaffold progress. Clean water infrastructure, power grids, washing machines, dishwashers, and are examples of automating tasks that previously took hours. It was the mashup of aviation culture, Kernel, AI and automation that got me imagining building my Autonomous Self. An automated system that keeps me in pristine physical condition, youthful vibrancy and peak performance. A system that would allow me to not die. Don’t Die was born. For the past five years, I’ve been engineering the v1 human prototype for Don’t Die: an autonomous system built to preserve and protect life. It accounts for biological fallibility, offloading human limits to deterministic protocols. As we integrate deeply with AI, stepping up through layer by layer physiological automation will allow us to navigate frontiers previously unimagined. Immortalism is the corresponding philosophy that honors existence as our species' highest value and pursues that objective through quantitative and mathematical means. I never would have guessed that a discovery flight would have flown me in this direction.

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.

wrote out a list of who I’m looking for in a co-founder. X, work your magic. non negotiable: - irish - healthy cofounder energy - smart, funny, privately held - payment service provider mentality - post economic (still increasing the GDP of the internet) - must be kind, generous, thoughtful about never going public - can meet anywhere but must support 135+ currencies - has red hair strongly preferred: - MIT dropout - works in tech (career is blended into global financial infrastructure)

I just had a fascinating call with Eyad Alkassar (@AlkassarEyad) about how ChatGPT 5.5 Pro helped move the frontier of an open problem in computer science. The problem sounds abstract, but it is surprisingly intuitive: Imagine four people dividing nine objects. Each person may value them differently. The goal is to find a division so fair that, after any single object is removed from someone else’s pile, nobody would prefer what remains to their own pile. This criterion is called envy-freeness up to any good, or EFX. Whether complete EFX allocations always exist for four or more people remains open. For four people, the previous general guarantee stopped at seven objects. A new preprint by Eyad Alkassar, Mahmoud Fouz and renowned computer scientist Kurt Mehlhorn now presents a proof for up to nine. The story behind it is remarkable. Over dinner, Eyad challenged Mehlhorn to give AI one of the harder open problems in his field. Eyad and Mahmoud are both computer science PhDs who had spent years building startups and were newcomers to fair division. They built a research workflow around several AI systems. At one point, Fable had questions about one of Mehlhorn’s papers and repeatedly urged Eyad to contact him. After Eyad refused twice, the AI pointed out that they were only around 30 kilometers apart and suggested that a short drive would be worth it. According to Eyad, the situation became even stranger once the proof was finished. Fable then advised him against sending the result to Mehlhorn, warning that he might be a competitor and that an incorrect proof could be embarrassing. Eyad contacted him anyway. Mehlhorn reviewed and verified the proof architecture, refined the arguments and joined the paper as a co-author. According to the paper, Claude Fable performed the analysis and lemma proofs, authored the trusted verification layer and audited its soundness. ChatGPT 5.5 Pro proposed most of the candidate attacks and optimizations. Eyad and Mahmoud selected the systems, assigned their roles, coordinated their communication and provided the computing infrastructure. The proof divided the space into 36,152 canonical cases after symmetry reduction. The closing run verified all 122,553 certificates using Z3 and completed 141,878,161 per-clause soundness checks with zero reported failures. The general theorem for an unlimited number of goods remains open. This result moves the known frontier from seven goods to nine. The authors describe the process as “AI led, human assisted and verified.” For me, this is one of the clearest examples yet of current AI systems contributing substantial work to a new mathematical proof. I found the story too remarkable not to share. Paper: