📢Ticket lottery applications are now open!!!🤩 THE ARGUMENT -Beginning to see the light- 🗓️Date: 2026/10/25 (Sun) 📍Venue: Spotify O-EAST/O-WEST （Tokyo） 🎟️eplus #theargument#

The frontier of mathematics will soon reach far beyond the subset that human minds discover. Working memory of ~10 is a very strong constraint on ape brains! 🧠🐒 Compression is all you need: Modeling mathematics Abstract: The mathematics humans discover and value (“human math”) is a vanishingly small subset of all valid deductions (“formal math”). I’ll argue that human math is distinguished by its compressibility through hierarchically nested definitions and theorems, like a polynomial-growth space rather than the exponential-growth space one might expect when proofs are viewed as strings of symbols. The argument combines toy monoid models with an empirical analysis of MathLib, a large Lean library of formalized mathematics we treat as a proxy for human math. I’ll close with how compression itself can serve as a measure of mathematical interest, giving agents a sense of direction toward where human math lives.

The argument over Anthropic in the FT today a) Under pressure from OAI, open source, all fronts b) the lynchpin of the AI bull case Featuring @OpenRouter data of course :)

The "why would I own equity when I can just own Bitcoin?" argument is a category error. This is because Bitcoin is money and capital, and equity is not money. For anyone who has spent a considerable amount of time studying Bitcoin, they usually come to a sensible conclusion about what money is. It's not an easy question to answer, but it seems like money has been an asset that humans use to save, price things, and settle obligations. On the other hand, equity is a claim on productive capital. It represents ownership of assets, cash flows, IP, financing capacity, labor, contracts, and essentially whatever future value an enterprise can create. What a lot of Bitcoiners misunderstand is that these functions of equity do not disappear just because the underlying monetary system improves. Just ask yourself what the logical conclusion of the argument actually is. If Bitcoin becomes money for everyone, do Bitcoiners believe that investment simply stops? Will a Bitcoin standard usher in an age without venture capital, factories, energy infrastructure, or businesses in general? How about mortgages or lending? Entrepreneurship... is that gone too? Will everyone sit on their private keys forever because exchanging money for a productive claim is somehow philosophically impure? Obviously not. Anybody who sees this through understands that a Bitcoin economy would still have capital allocation. In fact, capital allocation would probably matter more, because then the hurdle rate would be brutally honest. The concept of investment itself is fundamentally the decision to surrender liquidity today in exchange for the expectation of greater purchasing power tomorrow. This concept predates fiat itself by thousands upon thousands of years. It is most likely over long stretches of time we will see the denomination change for humanity as rational actors continue to adopt Bitcoin, but the economic act of investment will not change. If there is going to be a Bitcoin standard, someone will eventually have to say "I have 10 BTC. I could hold it. Or I can invest 1 BTC into this enterprise because I believe my claim on that enterprise will eventually be worth more than 1 BTC." This is capitalism. And this is where the objection to Bitcoin treasury companies becomes especially strange. Today, someone can hand a BTC TC depreciating fiat currency, and if that company possesses a genuine capital-markets advantage, it can convert that fiat into Bitcoin and potentially increase the amount of Bitcoin economically attributable to each share. We have empirically seen this done successfully with multiple BTC TCs. Some Bitcoiners look at that and say “Why would you ever give them dollars? Just buy Bitcoin.” Okay. Then what happens if Bitcoin actually wins? Because now the entrepreneur is not asking you for depreciating dollars. He is asking you for Bitcoin itself. You are going to have to part with the hardest money ever created and trust that the enterprise can generate a return exceeding the Bitcoin you surrendered. If voluntarily investing fiat into a vehicle designed to increase your Bitcoin-denominated wealth strikes you as offensive, wait until the unit of capital being invested is Bitcoin. The Bitcoin standard will not only NOT eliminate investing, it will eliminate the luxury of being sloppy about investing. Every project today faces the opportunity cost of simply holding Bitcoin. Businesses today are having to demonstrate that it can earn a return above that hurdle. Treating ownership in a productive enterprise as though it were merely another competing fiat currency makes no economic sense whatsoever. Bitcoin can become the money for everyone. Businesses will still exist. Capital will still need to be allocated. Investors will still demand returns. And of course, equity will still represent ownership. It's also baffling how we see some Bitcoiners advocate for parting of sats to buy goods and services, but they draw the line at investing? Did this investment leave me with more Bitcoin than I started with? That's the ultimate scoreboard for me.

The @CFTC wants jurisdiction to cover crypto futures, GPU futures, and prediction markets and intends to rule-make to achieve it. And if Congress can’t pass CLARITY, Chairman Michael Selig says he’ll start writing the crypto rules himself. At the CFTC’s first Innovation Advisory Committee meeting today, Selig laid out three fronts. Crypto: staff are exploring a new class of Designated Contract Market (DCM) called a “crypto asset market,” potentially giving registered and unregistered crypto exchanges a route to offer leveraged and margined trading under CFTC oversight. He also wants a legal pathway for onchain protocol developers. The Senate’s first procedural vote on CLARITY is September 15. If Congress stalls, Selig intends to propose rules anyway. Compute: the CFTC yesterday asked for comment on compute derivatives, including perpetual futures on compute. Prediction markets: new rules are coming on retail protections, product governance and incentives. Selig also mocked states that see “sports futures” and immediately call them gambling, borrowing the phrase “Name Fixation Syndrome.” They all will use same license: the DCM. - Kalshi is a DCM. - Coinbase Derivatives is a DCM. - Bitnomial used a DCM to launch leveraged spot crypto. - Compute derivatives would trade on DCMs. The DCM is becoming the wrapper for markets that don’t fit neatly inside securities law. And Selig gave the legal theory. Congress defined “commodity” in 1974 to include not only goods, but “services, rights, and interests.” He then cited a 1978 Senate report saying whether a market performs traditional hedging or price discovery “should not be the determining factor” in CFTC jurisdiction. That is the argument for why a sports contract can be a federally regulated derivative rather than state gambling. It is also how a GPU hour can become the underlying for a perpetual future. Play it forward and you get: → Hyperliquid-style perp venues operating onshore under a US derivatives license → A GPU forward curve lenders can use to underwrite data center debt → Sports contracts governed by federal market rules rather than 50 different state regimes The states have a legitimate consumer protection argument. Selig effectively conceded that. His answer is to build those protections into Parts 38 and 40 rather than concede jurisdiction. The CFTC already oversees roughly half of a $1.2 quadrillion notional derivatives market. Now it is trying to pull crypto, compute and prediction markets into the same machine. Where the SEC has Howey, the CFTC has “rights and interests.” That may turn out to be the more expansive phrase.

The fact of the matter is that more people dislike than like @reformparty_uk At this stage in the electoral cycle they should be on 40% + with the amount of dislike the public have for the uniparty. They should be forming a big coalition on the right instead of these petty personal disputes. Vote for me tomorrow is Clacton to send them a message that they aren’t the anointed ones, they need to work with others and be conveners on the common sense, patriotic side of the argument, instead of behaving like entitled children. Big tent. Everyone welcome. 🙏 That’s the only way out of this mess.

The AI Singularity The argument goes like this: 1. Humans build an AGI. 2. The AGI becomes good at AI research. 3. It designs a smarter AI. 4. That smarter AI designs an even smarter AI. 5. The cycle repeats faster and faster. Looking at the results and capabilities from the various labs over the past few weeks I would say we are firmly in this loop now. The next 18months will be wild. Recursive self improvement will dramatically increase capability very quickly from here. Marginal costs of all models will go to ~$0.

The GREAT MARC ANDREESSEN @pmarca SPENT THREE AND A HALF HOURS WITH @joerogan . I'VE BEEN THINKING ABOUT IT EVER SINCE. I'm a cardiologist. I've spent twenty-five years at UCLA and in my own practice in Tarzana. So when one of the most influential technologists alive starts talking about medicine, I listen carefully — and I push back where I think he's wrong. Here's my honest verdict: he's right about far more than my profession is ready to admit. 1. He says AGI already arrived — and nobody noticed. Marc's claim is that the line was crossed roughly three months before the interview, with the current frontier models, and the field is now moving so fast that nobody stops to register milestones anymore. Think about that. The thing humanity has argued about for seventy years may have quietly happened on a Tuesday, and we were all busy checking email. 2. The models now beat the experts he could call on the phone. This is a man who can call almost anyone on earth. He says the AI gives him better answers. My first instinct was to bristle — twenty-five years of training, and a machine does it better? Then I sat with it honestly. He isn't wrong. Though I'll add what he didn't: independent studies of AI health tools have found real misses on true emergencies. Take the claim seriously and verify it yourself. 3. The hardest thing he said, and he said it about doctors. He points out that physicians are already typing your symptoms into ChatGPT the moment you stop talking, and then asks out loud: what do I need you for? That question stung. It also deserves an answer instead of a defense. He's right that the machine will out-read me on the EKG, the echo, the labs, the scan. It doesn't get tired at 2am. It doesn't forget the rare diagnosis it saw once in residency. Any physician whose ego prevents him from using a better tool is a physician putting pride ahead of patients. 4. His method for hard subjects: escalating simplicity. Explain it like I'm 10. Then like I'm 5. Then like I'm 2. Keep going until it truly clicks. I've started doing this and it has changed how I read papers outside my specialty. 5. He doesn't ask for the right answer. He asks the AI to steelman both sides of a hard question — the strongest possible case for each — and then he decides himself. That's not outsourcing your thinking. That's the opposite. 6. He convenes a panel. For the big questions, he has the AI role-play a room full of experts arguing with each other, and he listens to the argument. Imagine having that available for the biggest decision of your life. 7. His most important line has nothing to do with computers. The moment you think "I don't know how to figure this out" is exactly when most people quit — and exactly when you should lean in instead. Read that again. That's not a technology lesson. That's a life lesson, and it applies whether you're facing a diagnosis, a divorce, or a business that's failing. 8. The only skill left is knowing what to ask. The bottleneck is no longer the machine. It's in your own head. The quality of your life is now, more than ever, downstream of the quality of your questions. 9. He sends it photographs. Rashes, blood tests, images — the current models read pictures directly and give a fast second opinion. As a physician I'll say clearly: a second opinion, not a substitute for one. But the day a worried parent at midnight has something intelligent to consult is a good day for humanity. 10. Free therapy, for everyone, forever. This is the one that moved me most. He points to cognitive behavioral therapy as the clinically proven modality an AI can plausibly deliver on its own — meaning real therapeutic support becomes freely available at scale. Think about what that means. The man lying awake at 3am with nobody to call. The single mother who can't afford a therapist. The teenager who can't yet say the words out loud to a human face. For all of human history, healing was rationed by geography, wealth, and luck. That is ending in our lifetime. 11. It's solving problems we couldn't. He cites AI cracking previously unsolved math problems, with early signals of the same beginning in physics, chemistry, and biology. Cardiology is downstream of biology. Every drug I prescribe came out of that pipeline. 12. The top AI engineers are earning up to $50 million a year. He offers this less as gossip than as a signal — that's what a civilizational shift looks like from the inside. 13. A friend built his own health dashboard. Sequenced his DNA, handed it to an AI along with his blood work and wearable data, and got back a working picture of his own body. That is precision medicine arriving through the side door, years ahead of schedule. 14. Another friend put cameras in his jiu-jitsu gym. So the AI could review his sparring and coach his technique. Elite coaching, for anything, for anyone. 15. The warning he gave — "the AI vampire." This is the term he coined, and as a physician it's the one I want you to hear. Because AI keeps making more output possible, people are working more and sleeping less, addicted to their own productivity. Let me be blunt with you as a heart doctor. Chronic sleep deprivation raises blood pressure, drives inflammation, disrupts your rhythm, and shortens your life. Marc named the disease before most physicians did. Do not let a machine that never sleeps convince you that you don't have to either. 16. One person, many agents. His extrapolation: a single human eventually directing a fleet of AI agents that check each other's work. He describes this as close. Not years away. 17. And his own caveat, which I'll repeat. Watch the whole interview. Several of these are Marc's stated views and personal anecdotes, not independently verified facts. He'd be the first to tell you to think for yourself — that's the entire point of #5#. So here's where I land, as a doctor who has sat with thousands of frightened people. Marc is right that the diagnosis is no longer the hard part. What remains — what will always remain — is the chair pulled close, the hand held, the human being who says I'm not going anywhere, we'll walk through this together. But that was never in competition with the machine. The machine frees me to do more of it. Marc calls himself a techno-optimist. From inside an exam room, watching patients whose lives are about to get measurably longer and better because of this — I'd just call him right. 🙏

The greatest risk posed by AI may not be artificial intelligence itself; it is much more likely to be that we give politicians the power to decide who is allowed to build it, use it and benefit from it. That's the argument Marc Andreessen makes in The Techno-Optimist Manifesto - and history gives us good reason to take it seriously. Andreessen argues that technology is the primary driver of human progress and that AI represents one of the most important advances in history. Rather than treating it as an existential threat that requires state control, he sees it as a powerful tool that will expand human capability, raise living standards and solve problems that currently seem intractable. The case for heavy regulation usually rests on two claims: that AI is uniquely dangerous, and that governments are capable of guiding its development responsibly. Both are questionable. Past technologies - from electricity and automobiles to the internet and biotechnology - were also accompanied by dire warnings and calls for strict oversight. In most cases, premature regulation would have slowed or distorted progress without meaningfully reducing risk. Governments face the same knowledge problem with AI that they face with every complex, fast-moving technology. Regulators lack the information, incentives and agility to make good decisions about what should be allowed, restricted or banned. More often, regulatory systems are captured by incumbents who want to slow down competitors, or by ideological activists who are hostile to technological progress itself. The better approach is to allow innovation to proceed while holding individuals and companies accountable for actual harm under the law. Precautionary regulation based on speculative future risks tends to favour the powerful and the risk-averse at the expense of progress that benefits everyone. Andreessen’s core message is simple: the greatest danger is not that AI will advance too quickly, but that fear and political control will prevent it from advancing at all.