Every camp just got its proof Last night OpenAI announced that one of its AI models has refuted a hypothesis in computer science that hundreds of research papers rely on. A day earlier, Microsoft offered 60,000 people a voluntary exit, and Anthropic wrote in its IPO filing that AI could pose “catastrophic or existential risks to humanity.” If you follow AI, you’ve probably noticed that people react to the same news in completely different ways. As I see it, there are five camps right now: 🫧 The bubble-callers. Investors and economists who think the money pouring into AI is far ahead of real profits and that it will all burst like the dot-coms in 2000. ☢️ The doomers. Researchers and people in AI safety who think we’re building something smarter than us without knowing how to control it. 💼 The ones worried about their jobs. Millions of workers who see AI already doing parts of their job, while no one tells them what comes next. 🛠️ The builders. People using AI to do things that were impossible yesterday. For them, every new model is a new superpower. ⚖️ The middle. People who are scared and excited at the same time, because they see both sides. I’m in the middle. And it turns out I’m not alone: according to Pew, 37% of Americans are equally worried and excited. Another 52% are more worried than excited, and only 9% are more excited than worried. The interesting part is that in just the last 48 hours, every camp got proof that it’s right. 🫧 The bubble-callers In China, the AI bubble has already burst. The STAR50 index of Chinese AI and chip companies fell about 40% in under four months, wiping out roughly $480 billion in market value. Robot maker Unitree is trading at about half its price from its August debut, when demand for its shares was about 8,000 times the supply. (Reuters) Torsten Slok, chief economist at Apollo: AI has delivered “zero financial payoff to corporate America outside of tech.” Goldman Sachs expects AI’s boost to the US economy to peak at the end of this year or early next year. The counterargument: Anthropic reported $16.3 billion in revenue for the first half of the year alone, against $4.6 billion for all of last year. It also reported an $80.7 billion loss, but that’s mostly an accounting loss, not cash actually spent. 💼 The ones worried about their jobs Microsoft is offering voluntary buyouts to about 60,000 employees, roughly 27% of the company, at vice president level and below in the US, Canada, India, and the UK. Microsoft itself doesn’t name AI as the reason. That’s the media’s framing, but it’s hard not to see it. Goldman Sachs: across US non-manufacturing sectors, the more firms use AI in their regular work, the slower employment grows in that sector. The effect is now showing up outside of tech. Bill Gates on The Verge: he expects a roughly 20-year transition with “winners and losers and a lot of disruption” before we reach abundance. He suggests reserving some jobs for humans as a policy choice: childcare, cooking, art, and sports. (You may have seen viral posts about “20 years of hell.” They heavily exaggerate what he said.) 71% of Americans expect AI to mean fewer jobs over the next 20 years. ☢️ The doomers and security Anthropic filed to list on Nasdaq under the ticker ANT. The filing says its technology could pose “catastrophic or existential risks to humanity” and that insurers may not have the capacity to cover a catastrophic AI incident. The most popular reaction on X: “Imagine asking people to invest billions in a product you’re warning could wipe out humanity.” A follow-up to “Black October”: hackers breached the cloud service of Japan’s GMO, which forex traders rent to keep their trading platforms running around the clock. The attackers took clients’ logins and placed trades from their accounts. Five brokers confirmed unauthorized trades, and up to 26,739 servers may have been exposed. GMO’s CEO Masatoshi Kumagai called it a national crisis and says ARTEX was used, the same Chinese AI tool behind the Korean bank breaches. That’s his claim; it hasn’t been independently confirmed yet. He also admitted his team had flagged the vulnerability but it wasn’t fixed in time. The irony: GMO’s own cybersecurity unit was the one that exposed ARTEX in attacks on Japanese companies a week earlier. 🛠️ The builders This is where the big news is. OpenAI announced three discoveries made by its models: 📐 Mathematics. They proved the local smoothing conjecture in every dimension, which also settles the famous Kakeya conjecture. Until now, Kakeya had only been proved in three dimensions, and that was just last year. 💻 Computer science. The Exponential Time Hypothesis (ETH) is false. Without getting technical: hundreds of research papers rest on the assumption that some problems can’t be solved faster than a certain limit. The model claims they can. This doesn’t mean computers suddenly become super fast, since the practical speedup is modest. In theory, though, it’s an earthquake. ⚛️ Physics. They proved that quantum chromodynamics (the theory of what happens inside protons and neutrons) rigorously exists mathematically. It’s also part of one of the seven Millennium Prize Problems, each worth $1 million, which OpenAI says it won’t claim. The important part: none of this has been checked by outside experts yet. ETH will be reviewed by the very people who proposed it 25 years ago, with no NDAs and no pay. The proof has been machine-checked, but the physics work hasn’t been published yet. And three weeks ago, when OpenAI released 722 math manuscripts at once, it withdrew three of them the very next day. So on X the enthusiasts are celebrating while the experts wait. The most-liked reply under the announcement: “I hope none of these are hallucinations.” More from the builders: About 30 physicists from Harvard, Google DeepMind, and other institutions gave AI 50 unpublished research problems in theoretical physics, each roughly a day’s work for an expert. GPT-6 Astra solved 49 of them for under $3 per problem, and Claude Opus 5.5 solved 46. The authors’ caveat: these are routine research problems, not breakthroughs. Mathematician Steven Strogatz in The Atlantic, “The Year AI Ate Math”: his colleagues are torn between awe and grief for the profession they know. OpenAI released GPT-6.1 Terra. They say it matches their strongest model on a test of how well agents use software at work, at a tenth of the price. More than 25,000 nonprofits now use Claude, most of them small local teams. 🧠 The idea that lifted a weight off my shoulders If you read just one thing from this post, make it this. Venkatesh Rao’s essay “Cognitive Mercantilism” lifted a weight I’d been carrying for months. Before capitalism, elites believed four things: wealth is finite and you only gain it by taking it from someone else; ordinary people can’t be trusted; only supply matters, not demand; and 80% of people will work the fields forever, because what else are they good for? Rao argues that today’s fear of AI repeats the same logic, just with intelligence: it’s scarce, it must be guarded from “the masses,” and if machines take over thinking work, we’ll be left with billions of useless minds. But the agricultural revolution didn’t create millions of useless mouths. It freed people from the fields. Rao can’t keep a houseplant alive, yet he eats a wider variety of food than any king did 300 years ago. His inability to produce food doesn’t matter. What matters is that he can consume it. The same could happen with intelligence. The question isn’t how much intelligence you can produce, but how much you can use. And demand for intelligence, like the demand for tea, sugar, and cotton once was, may have no ceiling. Cheap intelligence changes what we can even want. My favorite detail: Claude Code and a standard Netflix subscription cost about the same, around $20 a month. Rao suggests people will start choosing between them, just as people once cut back on food to buy a TV. For balance: not everyone agrees. Some think it’s naive about existential risk, and others think competing with another kind of intelligence will be harsher than anything capitalism brought. But for me it’s the best antidote to panic I’ve read. What to do Jascha Sohl-Dickstein, a researcher at Anthropic, gave advice on how to use the years before AGI. The talk is from June, but it just went viral: Bring AI into your work early, and pick problems that will get easier with better models, not obsolete. Don’t assume the traditional “safe” paths are automatically safe. Delegate execution to AI, but keep your judgment, and always check its work. And most important: “Writing is thinking. If you outsource writing, you are actually outsourcing your thinking as well.” (That’s why this post, for all the AI-assisted research behind it, was written and thought through by me.) Bonus science Physicists in Okinawa moved a diamond using nothing but the force of electron spins inside it, driven by green laser light. The setup weighs about 128 milligrams, which is huge by quantum standards. It moved only about 100 nanometers, but it’s an object big enough for gravity to matter. A step toward the question of where the quantum world ends and ours begins. Finally Every camp could take this week’s news and say “I told you so.” The bubble-callers have China. The doomers have Anthropic’s filing. The worried have Microsoft. The builders have the math. That’s why I’m staying in the middle. Not because I can’t choose, but because I think the middle is the most honest place to be right now. I’m scared because the speed is unprecedented and no one knows what the other side looks like. I’m excited because, for the first time in history, intelligence could become as cheap as food. Live your life, spend time with the people you love, and try something new with AI this week. ☮️ § ❤ SOURCES IN THE FIRST COMMENT