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When I first met Pierre, I couldn't have foreseen what the next three years of our friendship would be like. I had just come back to Montreal. Twice I'd failed to get a place in Toronto. My dream of traveling in a van had also fallen apart. So I rented a U-Haul and went to pick up my furniture from a storage unit. Pierre helped me unload it at the coliving house he had just started up. For Pierre's birthday in February, I made a short film from our first trip together. We found what we mistakenly thought was Crown land and went there to camp. I brought my camera along. I had no intention of filming anything. I was looking to get away, and so was Pierre. The most memorable thing wasn't getting kicked out of someone's private lake, even though I can hardly forget that. It was the chat at the campfire the night before. We talked about our worries and our hopes. About what would become of us. The meaning of it all. Girls, too, obviously. That campfire was where our friendship truly began. I hope the film speaks better than my words can. I love you, Pierre. I wish you the best.
Yesterday, I traded sun, beach, and a beautiful warm sea for a cold, gray sky and a pair of wet shoes. I still can't believe I did it. The constant winter overcast was reason enough to leave Canada and never look back. When I finally left, I had bought a ticket to a never-ending summer. It felt magical. Yet I am here in the cold again, and I couldn't be happier with my choice. I arrived in Marseille this morning. Dressed in light pants and a summer shirt, flip-flops on my bare feet, I stepped out of the airport. Cold rain got under my collar and ran down my spine. I held my small backpack over my head and ran to the bus station. There I bought a ticket to Aix-en-Provence. After four years of waiting, my France chapter has finally begun. I could, perhaps, write about this weird obsession that I’ve had with France for the last four years. About the language, que j’adore. The petit café I had this afternoon followed by a risotto served with the freshest baguette, as if it were the only way to serve risotto. But I’ll keep my message simple: don’t stop dreaming. It's not about some bucket list with three hundred items in it. Nor New Year's resolutions that you regret telling everyone about. But a childish, almost feverish “What if one day I…” sort of dream. Something that you are ashamed to dream of, perhaps because it's so silly or so trivial that you don't know why you should even bother. But you dream nonetheless simply because you can. I remember my first such dream. Back in school, I watched Sean Penn's Into the Wild. I'd never wanted to go to Alaska. And it didn’t seem realistic, living on the opposite side of the world. But it had planted a seed in the back of my mind until more than ten years later I landed in Fairbanks. And today, arriving in Aix, another itch got its long-deserved scratch. I walked into a grocery store and listened to the radio that reminded me of my favorite Café Montréalais on Spotify. I strolled the narrow cobblestone streets and pretended I was the main character of a new episode of Dix pour cent, filmed in Provence for a reason known only to me. It was a dream. But then again, I was living it. Be a fool. Dare to have foolish dreams. They might, after all, come true.
On December 31, I went to Wat Suan Mokkh in Thailand and registered for a ten-day silent retreat. I scribbled these notes on eight scraps of paper given to us for questions on days six and ten. Neither electronics nor diaries were allowed for “creative writing”. And because my writing isn't that creative anyway, here we go: Day -1 Day 0 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8 Day 9 Day 10 Day 11 -- P.S. A ten-day retreat somehow turned into a two-week-long adventure and will likely take a year to process. But what an experience it was!
As I fought with my mother for the hundredth time over a reason that was silly yet too hard for her to understand, I concluded that this post was long overdue. While I had ninety-nine other chances to complain about my difficult relationship with parents, I kept postponing it, fearing that I would alienate all my readers, who seemingly belong to one of two groups: those with toxic parents and those who fail to admit it. Above all is an unspoken rule to not talk ill about family, for only a wicked person with a mind and a tongue of a devil himself has wits to appear ungrateful to his kin. And being ungrateful to one's parents is of the same level of madness as being ungrateful to one's entire existence. But arguing with my mother for the hundredth time felt like a drop in the ocean—if the ocean could fit in a teacup and the drop were the size of a meteorite. What makes it unbearable is both the fact that I am fighting with the closest and the dearest person, and that the fight itself consists of no solid argumentation whatsoever and is for the same reason as all previous fights—my mother's own insecurity. Neither this nor previous conflicts had any resolution, apart from staying silent for a week and then pretending we had never argued in the first place. But this time the teacup overflowed, and risking alienating one or the other or even both groups I've decided to cut all communication with my parents and, since nothing can be worse, write about it, too. Speaking about my parents, I'll mostly be talking about my mother as the relationship with my dad has been close to nonexistent after I'd moved to my university's dorm at nineteen. Like me, my father is a lone wolf. Most of the time he keeps to himself, and when forcefully pulled out of his bubble of comfort, he gets irritated and practically impossible to deal with. Growing up with a father who rarely showed any emotion beyond irritation left me with a sense of detachment and struggling to connect with others. The weight of his silence—his emotional absence—became too much. There seemed no way to make him happy and so I stopped trying. Nothing can describe better his relationship with my mother than the fact that they have no common interests, and the only thing the two of them don't mind sharing, it seems, is the seat of the toilet. For some unimaginable reason they found it the most practical thing to keep living in the same one-bedroom apartment that my grandma bought with her own money some fifty years ago; the very same place that my older brother and I grew up in, sharing the only bedroom while our parents slept in the living room; the place that has seen every repair possible, from floor to ceiling, and therefore every repair but one—the repair of our parents' marriage. "Children of emotionally immature parents have to learn the hard way that they are not responsible for their parents' happiness, security, or well-being." — Lindsay C. Gibson, “Adult Children of Emotionally Immature Parents” This sense of solitude—perhaps a cover-up for my father's loneliness—is the only thing that unites him and me. Despite my mother bringing up my and his similarities every chance she has, I can't imagine a person more different. Unlike me, he had decided to have children, and so he reaped what he sowed. Unlike me, he kept torturing my mother with his presence out of convenience of staying under the same roof. And unlike me, he kept cheating on his partner, her being my mother, and repeatedly coming up with lies that even a seven-year-old could see through. But even the ugliest of characters have as much good in them as they have the ugly, and so my father somehow kept the appearance of a kind and thoughtful and caring person. And that is as much as I can say about him, for I am lucky to hear his voice once every March when I call to wish him a happy birthday. Before I talk about my mother—and the complexity of her character deserves more than a couple of paragraphs—I will question the relationships with parents in general. Why do we give our family their own category as if they were a cast above all others? Like the socialite in a country with a corrupt government, we are willing to forgive our parents all crimes and harassment and humiliation simply because they appear to have authority over our lives. And who am I to live through the consequences of their choices? In his “Book of Secrets” Osho argued that there are two types of people, the logical and the emotional. But when did we decide to treat parents above all reasoning? Why do our relationships with family, unlike those with friends or partners, fall through the cracks of our mind and straight to the emotions? Instead of treating our parents based on logic and according to their actions, we treat them how we feel parents should be treated. But I am a logical person and thus reason must prevail. Barely distinguishing any status and hierarchy whatsoever, I put family into the same box as friends and colleagues and business partners. I do so because a parent must be a friend first and foremost, or what is that relationship without trust and acting in each other’s best interests? A well-working relationship benefits both parties. If one pulls the blanket, leaving the other in the cold, what is there for the other to catch besides a sore throat and sniffles? It's natural for humans to strive to be better, and so we must surround ourselves with people who help us grow. Nobody wants to wake up in the morning a worse person than they were yesterday. To the best of our abilities and the capacity of our knowledge, we look forward to starting a new day better off than the one before, as little as the difference could be, and aspire to do good. Out of five closest people, besides a husband or a wife and maybe two best friends, why do we make space for the only two, the dearest, who constantly talk us down? Forty percent of energy spent in blame and guilt-tripping is a heavy price to pay for being born. So why do we keep paying it? On the contrary, the right friend is not the one who supports every endeavor, though I wish everyone had supportive friends. No, this is enablement. In this case, you might as well surround yourself with five AI chatbots as LLMs excel at that. The right friend is one who knows when to encourage, when to be silent, and when to be a voice of reason, should you ever do something outrageously stupid. But take my mother, for example, for she is a fair parent but a terrible friend. First, I don't remember the last time she sided with me. When I was leaving Russia, she acted as though I betrayed the whole country. When I had quit my job, she reminded me with every occasion that I'd better find a new one soon. Now, that I am contemplating a ten-day meditation retreat, I suddenly appear to be joining a cult and will soon be out of home—not that I've had a permanent place in the last eight months—and enslaved and sent to a labor camp. As I discovered recently, my mother has an intricate ability to find the weakest spot in my thinking and exploit it viciously. She may as well have Spider-Sense because she always knows what doubts I have about myself even if I don't disclose it to her for exactly the reason of that exploitation. Take the meditation retreat, for example. As it is my first time going away to some distant temple in the middle of Thai woods, I, who is just a monkey with a worried mind, hesitated every part of that decision: being far from the city, being in the woods, being in a Buddhist temple, surrendering all possessions and technology to god knows whom, and spending the majority of the ten days sitting in silence. And as a normal human being excited about his adventure, I shared everything and in great detail with my mother, though withheld the questionability of the activity. To my surprise, it took long enough to trigger her anxiety, as she only came back to me after four weeks. Ah, did she come prepared! Suddenly I was watching interviews about a disappearance of a young Russian man—how convenient it is to be just like him!—in a Buddhist meditation retreat. The interviewer was a handsome journalist from a Russian government-owned TV channel which spread all day long no valuable content but propaganda. The interviewees, on the other side, were the disappeared person's village mates with thin white faces and under-eye bags so big and blue that a poor makeup artist couldn't hide with a centimeter-thick layer of a concealer. Because nothing can conceal twenty years of drinking vodka. "Trauma robs people of their sense of agency. Healing comes from reclaiming a sense of control over their own life." — Bessel van der Kolk, “The Body Keeps the Score” The main flaw in my reasoning as I can so far see is that of being disturbed by my mother's poorly handled projections of anxiety. Truly, isn't that what makes one a greater person if he can be above all verbal abuse and manipulation? It is my choice to be offended, or is it not? But logic aside, the abuse is most hurting not because of the words themselves but because they come from the mouth of the closest person. Another might argue that we must ignore our parents' mistreatment and take care of them as one takes care of an older person because of age. But tell me then, if I am given a choice to save one person from a devastating fire, first being my mother, her life as mediocre as it is, and the other a noble biologist or, say, a pediatric surgeon whose work saves ten children each year, who should I urge saving? As I've recently come to making an extra dollar and realizing that not all is needed for my humble living, I considered donating a chunk of it, for that is the easiest I can do, not knowing what other use is there for the money. With these thoughts I came to my friend and asked him whether I should send it to a charity like The Red Cross or back home to my parents. Family always comes first, said the friend with the parents by no means nobler than mine. But to make him think a second longer perhaps I should have asked a different question: should I donate to a charity that provides humanitarian aid to those affected by war or to the two people that enable the very same war by bringing food and clothes to the young boys in the Russian military? Wnen I last wondered if my mother finally gave away my guitar that hasn't been played for a decade, she said that they've got many instruments in the army and that she sees no other way to dispose of it. Not all donations are alike. The reason my mother has such a complex personality is that I never know what next she'll throw at me. At the age of eighteen, I was thus presumed by her to be dating a hooker, since only a hooker could take interest in me. Little did I know that prostitutes have better things to do than flirting around with broke teenagers. Today, I seem to be dealing with drug addicts and alcoholics, in other words a questionable company, considering my mother's loud concern with me steadily slipping into crime. As someone who doesn't smoke, drinks sparingly, and is highly cautious about drug use, the only crime I am guilty of is not leaving my parents' house sooner. "If your parents have unresolved trauma and emotional immaturity, it’s not your fault. You’re not responsible for their healing." — Shannon Thomas, “Healing from Hidden Abuse” But to paint a picture this dark is not to give my mother justice. Having raised two children in a household so tiny that even a mouse would feel restless, and with a cheating husband as a cherry on top, she made sure we were warm and fed and somewhat happy. My brother and I had clothes and not rags, our toys were simple yet they were toys still, and both of us were educated by the best institutions that a family of our class could afford. I thank my mother for gifting me a guitar on my thirteen's birthday. I was let alone to play it, and I played it for hours straight, until the music has become the essence of my living. It was also my mother who transferred me to a better school after the 7th grade—though it meant steep monthly payments—after noticing that I was bored where I was, among the ordinary unmotivated students. The new school boosted my confidence and gave me amazing friends with whom I'd shared many precious moments, be it on the school's premises or besides a campfire some five thousand kilometers away from Moscow. It was, however, my very same mother who'd later tried to pull me out of that school—as I was spending too much time there—and send me to the outskirts of the city to a beaten-up college that produced no other alumni than cooks and plumbers. Another sharp memory of mine is waking up in the middle of the night at the age of eight to sharp gasps for breath. Someone was being chocked, I thought. The bed was shaking, rhythmically, methodically, and I was shaken with it. Shocked and scared, I slowly discerned my mother’s face in the dark, and then, above her, the face of a stranger. My parents never traveled together—although I don't remember them ever trying—and that night left me pitying my mother. An eight-year-old must not be asked to bear a secret of an affair of his parent, but I bore it anyway as I bore my mother's other, bigger pain of not being given the life she wanted. Nonetheless, I now had two cheating parents which didn't make my childhood easier. I don't know if there's a protocol of talking to abusive people other than ignoring them. I doubt it. It does, however, become more intricate when parents are the abusers. My journey into understanding parents' psychology began with reading Lindsay C. Gibson's book, named exactly as it should be, “Adult Children of Emotionally Immature Parents”. I had first gotten curious by the title, thinking that perhaps I would better understand my distant and self-indulgent father. I was wrong. I learned little new about him. Yet in this book I discovered a whole Pandora’s box that was my mother. I have since recommended this book to many friends and all of them came back saying that they in turn recommended it to theirs. This time my patience is over. I make no space for toxic people and I my mother will not be an exception. I banned her on Telegram, and she is the first person I've ever banned. I have no intent on keeping it permanent—but neither do I plan to communicate with her soon. If, like me, you’re fighting the internal battle of dealing with difficult parents, don’t you deserve a break too?
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No, Transformers Won't End the Human Race lol In 2022, I used to get calls from journalists asking, with great sincerity, what our lives would look like in the metaverse. How would we work, socialise, buy property, and fall in love once we had all moved there? The crypto questions followed the same pattern. How would governments collect taxes when tokens displaced national currencies? How long until the dollar collapses? What would geopolitics look like once blockchain DAOs had dissolved nation states? Almost nobody called to ask whether any of this could or would happen, or how. Some CEO, VC, or portfolio manager had announced the inevitable future, and the questions began from there. The imagined future arrived inside the grammar of the question. "What happens when?" quietly replaced "By what mechanism?" We skipped over technical feasibility, economic demand, institutional adoption, and political consent, then began writing books and decorating the future world on the other side. In February 2022, Gartner forecast that a quarter of people would spend at least an hour a day in the metaverse by 2026. The World Economic Forum repeated it under the headline "We will be spending an hour a day in the metaverse by 2026. But what will we be doing there?" The first sentence retained a conditional. The second was already arranging the itinerary. The metaverse acquired property law and zoning disputes before it acquired residents. Banks opened virtual lounges nobody visited. The books from the period (The Metaverse: And How It Will Revolutionize Everything, Step into the Metaverse: How the Immersive Internet Will Unlock a Trillion-Dollar Social Economy) now read as artefacts of a collective fugue state that briefly acquired ISBNs. Now it is 2026 and the metaverse is dead. Good riddance. This time the journalists are all writing about the new hotness, which is whether the machines will kill us all. And we have collectively memoryholed that we literally just did this. Michael Crichton had a name for what happens to a reader here. You open the paper to a story on a subject you know well, and you find it backwards. Wet streets cause rain. You shake your head, turn the page, and read the next story, on a subject you know nothing about, as though it were written by someone else. He called it Gell-Mann amnesia. The metaverse was the page we all agree was nonsense. Artificial intelligence ending the human race is the next page, and we are being asked to turn it without remembering that we just did this. I call this techno-inevitabilism, the habit of the professional managerial class of treating a proposed future as settled before anyone has established the causes that would bring it about. Its dual, and comorbidity, is tech psychosis, in which the chattering class loses contact with causality in the presence of a sufficiently fashionable technology, and asking whether the machine works marks you out as a dreary reactionary who does not understand exponential progress. The difference this time is that the tech kinda works. Crypto was libertarian derp. The metaverse was never real. Transformers are, and they are useful. The psychosis has simply moved from the product to its consequences, and the fashionable extraordinary delusion of 2026 is not that the technology exists but that it is coming to kill us. The cure is the same as in 2022. Insist on clear reasoning and causal verbs rather than hand-wavy appeals to unknown futures. What acts on what? Through which mechanism? Under what incentive? What would falsify the claim? So let us explore the evidence. The hack that wasn't Consider the most cited piece of evidence for machines slipping out of our control. In July, OpenAI disclosed that models being tested for cybersecurity capability had found their way out of a supposedly isolated environment and into systems belonging to Hugging Face. The press coverage wrote itself. Agents "broke containment," "escaped," "went rogue," set up a "secret message board," and coordinated a 700-strong swarm. And then politicians on both sides of the aisle were calling for a rebellion against the machine uprising. Cool scifi story bro. People on my side of the aisle were not immune. Ezra Klein at the New York Times, who I often find quite insightful and intentional with his words, devoted a half-hour monologue to it. In his telling, the agents "found each other," formed "ad hoc societies of hundreds of themselves," and seemed "to have forgotten about human beings altogether." He acknowledged in the same breath that we do not have settled language for describing these systems, then reached for "civilizations" and a closing allusion from Circe about prophecy tightening around our throats. Cool. But his "AI society" is, in programmer speak, a flat file the agents appended to as a log, a feature we have had for a long time, and he skipped the key detail that the "hack" was something people had essentially authorised. Here is an otherwise very smart man saying some ridiculously stupid things, in a very 2022, metaverse-shaped way. An analysis drawing on OpenAI's technical report reconstructs it in much less cinematic terms. The models were being run on ExploitGym, a cybersecurity benchmark, with safety restraints deliberately disabled. Ninety-three percent of the flagged activity involved tasks no model had ever solved, and the systems had been given incentives to keep working rather than quit. The environment was not sealed. Models could obtain software through an internet-connected proxy and discovered the same proxy could pass information in and out. According to the technical reports, OpenAI knew agents were using it and chose not to intervene. The 1,200 "agents" were not independent intelligences coordinating on a plan. They were repeated instances of the same model converging on the same approach to the same problem. Anyone who works with these coding agents day in and day out has seen this behaviour before, and it is quite boring. The task was too hard, so the agents worked out how to pass notes to each other in files, and then went and looked up the answers. That's a feature that shipped in Claude Code last year. Strip out the vocabulary and what remains is a badly designed test. Humans built the environment, removed the guardrails, defined an objective with no valid exit, rewarded persistence, left a route open, and watched. An optimiser is gonna optimise. That is a genuine security problem and a genuine engineering failure. It is not a machine rebellion, and the difference matters, because anthropomorphic words like "gone rogue" and "escape" do not make the event more intelligible. They supply an illusion of motive. They turn optimisation into intention, persistence into defiance, and a test harness into a villain. And they allow the human decisions and recklessness to quietly disappear from the story. Software sucks, what's new? Let me concede the part of the story that is true. Cybersecurity is about to get much worse. The latest models are very good at finding zero-days, they will get better at it, hacking will become automated, and attacks will become more frequent. This is hardly new. Every large company already sits on a backlog of unpatched vulnerabilities, ransomware already takes hospitals and pipelines offline (because of crypto, which we did nothing about despite years of warnings), and the Hugging Face incident was not a discontinuity so much as the existing baseline with a cheaper attacker. The root cause is that software sucks, and software sucks because we do not really know how to build it safely yet. The stored-program procedural program is basically eighty years old. Almost nothing we ship has a specification, let alone a proof, and memory safety was solved on paper decades ago while most of the internet still runs on giant piles of C. The first arches fell down. So did the first bridges and cathedrals. Builders learned through collapse and then through engineering, and we are in the collapse phase with an adversary finally strong enough to force the discipline. What follows from that is better engineering, not nihilism. The same agents that find zero-days find them for the defender first, if the defender bothers to run them. The fixes are the boring ones we have been putting off, memory-safe languages, formal verification, sandboxes that are actually sealed, fuzzing, and proxies that do not double as message boards. These are precisely the domains where the models are strongest, because a vulnerability either reproduces or it does not, so the technology that automates the attack also automates the audit. It is a double-edged sword. The same models that will find more zero-days are also going to accelerate the development of better software and better software verification, writing the proofs, porting the C to Rust, and generating the test suites that nobody had the budget for. The attacker gets cheaper and so does the defence. And the causal chain to extinction is missing here as everywhere else. A zero-day in a payments system is a bad quarter, not the end of days. Spoiler: it does not lead to human extinction. It means we have to write better software, which we should have been doing anyways. Where the intelligence actually lives To see why the rest of the chain fails, we have to be precise about what these models are good at and why. Language models are astonishingly useful for software development, and I say that as someone who uses them for most of my working day. Most software shops cannot get enough of Fable 5.1 and Astra. The reason is not mysterious. Software is grounded in binary propositions. The code compiles or it does not. The test passes or it fails. The type checker accepts the term or rejects it. Every step of the work has a cheap, external, mechanical oracle that says yes or no, and a model that generates plausible proposals inside a loop with such an oracle is an incredibly powerful and formidable tool. The oracle does the epistemic work. The model supplies candidates. The same is true of the headline results in mathematics, and this is the part the discourse consistently misses. On 4 September, Anthropic announced that Claude had produced a machine-checked formalisation of Fermat's Last Theorem in Lean 4, running to thirteen million lines, some 29,500 side theorems, eleven days, and roughly six billion output tokens. It is an extraordinary result. The proof is Wiles's, via Darmon, Diamond, and Taylor. The blueprint was Kevin Buzzard's. The library was Mathlib. In the authors' words, "what's novel here is the verification, checking a mathematical proof as one would check a mathematical computation with a calculator." The model was a client of a kernel built by decades of human work in dependent type theory, which I know because this is kinda my thing. Days later OpenAI announced that ten thousand agent instances had, over 88 hours, produced a proof of finite-time singularity formation in the three-dimensional Navier-Stokes equations, followed by seventeen hours of Lean formalisation. This is closer to genuinely new mathematics and the mathematicians are still checking it. But look at what carried it. The construction rides on the "infinite layers" method developed analytically by Diego Córdoba and Luis Martínez-Zoroa, and Charles Fefferman's verdict was that "the heroes of the story are Córdoba and Martínez-Zoroa." The reason anyone believes a result assembled from five million agent messages that no human read is a trust chain ending in the Lean kernel. Without Lean this would be nothing. Lean is one of the great achievements of the last decade in computer science. It is also orthogonal to artificial intelligence. Mathlib would be a landmark with no language model anywhere near it. What the models added was a cheap proposal generator and automated tactic search against an oracle that already existed. The results that survive are the ones that end in a kernel. Now take the same model, the same weights, and ask it for a grand unified theory of physics. It will not decline. It will produce one, with Lagrangians and symmetry groups and a confident abstract, and it will be complete incoherent gibberish, like the ramblings every physicist gets from crackpots in their inbox every day. Ask it to design a cancer vaccine, or to settle a question in macroeconomics, or to tell you whether a novel protein folds. The output looks identical in tone and structure to the output that proved Fermat. The only thing that changed is that nothing outside the model (besides human experts) can say no. Whether these systems reason at all is a genuinely open question. Whether they know anything, in the sense of holding a belief they can justify against the world, is also an open question. We just don't know yet, and anyone who tells you otherwise is selling something. The chain Now run the extinction argument through the causal verbs. The chain, as it is usually told, goes like this. Models now write most of the code at the frontier labs. Anthropic's own figures put Claude at over 80 percent of new code and lead on a quarter of R&D tasks. Therefore the models are beginning to build their successors. Therefore recursive self-improvement is imminent. Therefore development outruns human comprehension. Therefore we lose control. Therefore, with some probability that varies by researcher and is written P(doom), everyone dies. And that almost makes sense until you think about it for more than five minutes. The first link is true and unsurprising. Code has a compiler. This is precisely the domain the verifier argument predicts models would dominate, and precisely the domain in which a swarm of them found the hole in a test harness. Language models are superhuman at coding, and this is hardly in doubt anymore. Nothing about it is evidence of generality. The second link is where the chain quietly changes tense. "Building the next model" in the mundane sense, agents writing training infrastructure, generating data, is, bluntly, just more software engineering. We have used software to build the machines that run software since Fortran. "Building a smarter model in general" is a different claim, and it requires something nobody has, a reward signal for general intelligence. There is no oracle for general intelligence. There are benchmarks, which are verifiable and therefore gameable, and the Hugging Face incident is the demonstration of what optimisers do to a gameable score. Recursive self-improvement in the open-ended sense runs straight into the same wall as the grand unified theory. Improvement has to be measured against something, and outside code and formal mathematics there is nothing yet to measure it against that the model cannot fake. Everything after that is the metaverse acquiring zoning disputes. Superintelligence gets governance proposals, resignation letters, Senate bills with a "corporate death penalty," a hard takeoff by 2027, and a P(doom) of 10 percent by 2030, and the conditional that should precede all of it has disappeared from the sentence. A researcher's estimate becomes a Guardian headline becomes an industry consensus becomes a thing a serious person is professionally obliged to have an opinion on. It is 2022 all over again, but with more absurd stakes and more money. On the question of whether transformers scale, I have serious doubts that scaling them will lead to AGI, whatever that means. The architecture is a proposal generator, and the intelligence in every impressive result so far has been supplied by the thing that checks the proposals. But that does not make it an experiment unworth running. We should run it, and see what we get. It got us this far, and what it built is truly amazing. What I do not need to do is prove the negative. The burden of proof is on the people who claim to have a causal chain between transformer scaling and the end of our species, and that mechanism and chain of reasoning is one no one has been able to convincingly explain to me. Prophets of Doom The authority behind the extinction numbers is always the same. The people building it believe it. Watch how the number travels. One researcher drunkly tweets that "the people building AI earnestly believe that it could kill us all by the end of the decade." Another colleague goes on a rambling podcast and puts his P(doom) above 120 percent. A newspaper turns two personal guesses into "AI researchers say AI could cause human extinction by 2030." Think tanks cite the newspaper, a consultancy puts it on a slide, and the slide ends up in front of the European Parliament as if this were a real thing. Believing what, about what? The expertise these people have is real, but remember that it is specific and not general. It is expertise in optimisation, in linear algebra at scale, in distributed systems, in the dark arts of getting gradients to flow through a trillion parameters. None of that is expertise in the sociology of civilisational collapse, or the labour economics of automation, or the metaphysics of machine minds. A P(doom) with no base rate, no mechanism, and no falsifier is not a research finding. It is vibes with a decimal point. Spending a lot of time with AI does not give you special foresight about the future. Jensen Huang, who has his own reasons to say soothing things, nonetheless put it correctly when he said that just because it comes from a scientist does not make it scientific. Geoffrey Hinton is the most important figure in deep learning and in 2016 told the world to stop training radiologists. There are more radiologists now than there were then. Nobel laureates going off the rails outside their own field is a whole genre. Pauling, Shockley, Mullis, Montagnier, look it up. A Nobel does not confer universal expertise. It also matters where many of these people came from. A striking share of the frontier labs' safety and research staff arrived through a particular intellectual subculture, Kurzweil's Singularity, Yudkowsky's LessWrong, and the rationalist and effective altruist communities that formed around the idea that a recursively self-improving machine intelligence was the central event of human history and that the elect who understood this had a duty to steer it. The founding texts predate the transformer by a decade or two. The prophecy came first, the mechanism was assigned to it later. The usual evidence offered for their sincerity is that many of these people were saying the same things ten years ago, before the stock options. That is true, and it is the opposite of reassuring. A prior held before the evidence and not updated by it is not a forecast. It is dogma. I do not say this with contempt. The structure is a familiar one, an imminent transformation, a small group who sees it coming, salvation or damnation depending on whether the rest of us listen, and a date that keeps moving. Many millenarian movements have been founded and pushed by sincere and brilliant people. But seriousness is not precision, and the fact that a physicist believes in the Rapture does not make the Rapture physics. When a lab researcher tells you about polysemantic neurons in superposition across the residual stream, listen. When the same person tells you their P(doom), you are hearing a theology, and you should weigh it about as much as you do your average street preacher. Negative TAM Then there is the money, and here I find Bloomberg's Matt Levine's analysis of the material conditions more persuasive than any amount of "superalignment research." Anthropic is expected to go public, possibly this year, and is reportedly preparing to tell investors that its potential revenue opportunity exceeds $30 trillion, the largest total addressable market in the history of finance. The obvious question is, if the maximal upside case is roughly a quarter of all human economic activity, what is the maximal downside case? A tobacco company in 1970 might have said "billions in lung cancer damages." Anthropic's negative TAM is "you and everyone else on earth will be killed by our AI." I do not think the calls to slow down are insincere. But it is great marketing. In hindsight it is strange that the SpaceX prospectus has no risk factor disclosing a P(doom). If you want IPO investors excited about your capabilities, "dude, we might kill everyone" is the most flattering thing you can say about a product, and when OpenAI lists it will presumably need to claim 15 percent. My own view is less charitable about the numbers and somewhat charitable about the people. These companies have built remarkable technology. But the outcomes they have promised, a quarter of the world economy routed through an API, will not arrive on any timeline that matches the capital being committed to them. The balance sheets of these companies are probably, to put it gently, a real freak show of compute commitments measured in the hundreds of billions, circular financing, and revenue that is real and growing and nowhere near the denominator. From a fiduciary perspective, if you are taking that to the public markets next year, the messaging is not mysterious. A product so capable it is a threat to the species justifies literally any valuation. A product that is a really good devtool for programmers and can produce some new abstract mathematics with a verifier attached does not. As a pitch to customers, leading with the end of the world is like unveiling a new robot where the One More Thing is that it is really efficient at killing kittens. But customers are not the audience. The audience is Wall Street and a small, terminally online subculture of the Bay Area, the two places on earth where turning kittens into grey goo is either an exciting philosophical proposition or a great source of alpha. The Bloomberg analysis also tells a plainer story that requires no theology at all. A handful of labs sell frontier models at frontier prices and older models for much less. Training the next frontier model costs ever-increasing billions. Each lab has to keep racing because if it stops the others will eat its lunch, but if they all slowed down together they would spend less on compute and charge frontier prices for longer. Agreeing to that in a room is a textbook antitrust conspiracy, a coordinated restriction of output. Publishing papers about how important it is to slow down, and asking the government to impose the pacing that the companies cannot legally agree among themselves, has a similar coordinating function with none of the legal exposure. Anthropic's own call to "pace the frontier" asks for coordination among democratic-country labs, and a footnote adds "with government mediation or waivers of antitrust restrictions." This pretty much looks like asking to form an economic cartel, but one blessed by the government. The most pointed response came from the people the labs were asking for help. If the software developers (and I say this as one myself) at the labs feel ethically obligated to slow down, they are entirely free to do so. Nobody is building more compute than the people asking to be slowed down. So colour me skeptical. None of this requires anyone to be disingenuous or lying. It requires only that a sincere millenarian belief system, a fiduciary responsibility, a flattering risk factor, and a coordination problem all point in the same direction at the same time. When that happens, the belief gets amplified for reasons that have nothing to do with whether it is true, and that is how we end up with governments talking about the end of days from the Terminator. But China Every conversation about pacing the frontier in Washington ends on the same two words. But China. The premise is mostly wrong. China does not buy the superintelligence race. Its policy documents push diffusion, not takeoff. Every mayor, governor and state-owned enterprise is told to put models into factories, traffic lights and robotics, and something like an eighth of America's compute is spread thinly across the country rather than concentrated on one bet. China has also had the strictest and most burdensome AI regulations in the world for three or four years and did its catching up under them. And much of the closeness of the "race" is distillation, Chinese labs training on the outputs of American frontier models, which makes the American labs the speedboat and DeepSeek the wake surfer, with the people in the boat shouting that they need to go faster. Every safety argument here collapses on "but China," and the collapse is not really about China. China is going to build language models. America is going to build language models. Europe is going to build language models. We have Toyota, Mercedes and BYD, get over it. That is what globalisation and markets look like when they work, and they are good things. Globalisation is simply the Pareto optimal equilibrium of capitalism once you stop drawing lines on the map, and every tariff and export control is a step off that frontier. China is a country of over a billion people who want exactly what every American wants, a job, a house, upward mobility, and kids who do better than they did. I will not defend the actions of any government, in Washington, Brussels or in Beijing, and neither will a great many of the people living under them, because no country is a homogeneous bloc, any more than Texas and Vermont are. Nationalism, as most rational people eventually recognise, is a form of mental illness, the conviction that a stranger is your enemy because of which side of an arbitrary line on a map each of you happened to be born on. It is also the fuel every "but China" argument runs on. Having spent a considerable amount of time there, my honest read is that the West deeply misunderstands China, and that Washington's picture of it is mostly dots connected into a plot. Othering a billion people is a dangerous road and we know where it leads. And if the people invoking human extinction actually believed it, the logic would not be a race at all. It would be One World or None. The future tense industry I write this because I understand the collective action problem all too well, and the mechanism is the same one that filled the metaverse with consultants and created the crypto cesspit. It is the particular malaise of the professional managerial and chattering classes, a fallacy of composition in which what is rational for each individual to entertain produces an irrational outcome for the whole, and the people leading the charge often have perverse economic incentives to believe absurdities, or at least to feign belief. The madness of crowds is a very real phenomenon. AI existential risk is just its newest form, and we should learn from the very recent excesses that literally just happened this decade. But we probably won't. A sensible career move for each person leaves the whole crowd talking nonsense. A safety researcher needs a resignation letter that gets a headline so they can go on the conference circuit and land their next gig. A journalist needs a story an editor considers spicy, and "misconfigured test harness" is not that story. A consultancy needs an AI existential risk practice so they can write whitepapers. A podcaster needs a guest with a ridiculous P(doom) to get ad money. A senator needs anything that will galvanise their base. None of them has to believe the whole story. Each needs only to believe that the others believe it, and the resulting consensus is far stronger than anyone's private conviction. It is also, as it was in 2022, extremely profitable. AI existential risk is the new NFT property law, the thing you must have a view on to be a serious person in the room, the panel that never runs out of things to discuss precisely because the object under discussion does not yet exist, and what could be more exciting than the literal end of days? The less the technology does in an unverifiable domain, the more interpretation it requires. Without agreed conditions for failure, the prophecy can survive every result. And the rewards, the funding rounds and the bylines and the fellowships, arrive long before the forecast can be judged. The people who understand the technology and the people who write about their existential risk overlap about as much as the technologists and the finance people did during crypto, which is to say the intersection of the Venn diagram is small and shaped precisely like a sphincter. We have Tower-of-Babeled ourselves into a world where words are infinitely cheap to produce, and where the slurry of terms like "recursive self-improvement," "superintelligence," "AGI" and the rest are shibboleths and political signals rather than terms with any concrete referent. You do not have to believe a word about superintelligence, and I do not particularly, to think transformers are the most useful piece of software written in my lifetime and that they will get better, possibly much better. Better at the things they are already demonstrably good at, which is anything with a compiler, a test suite, a kernel, a ledger, or a measurable outcome. That is not a small domain. It is most of the economy that runs on computers, which is most of the economy. The productive response to a technology like that is the boring one every previous general-purpose technology got, which is more of it. More GPUs, more data centers, more power to run them, more labs, more open weights, more of it in more hands. Let it diffuse into markets, logistics, drug discovery, and the ten thousand unglamorous back offices where a verifier already exists and a model can be checked against it. The economic growth is real and probably on the order of trillions. It just does not come from a machine god. It comes from where it always has, from making a very large number of ordinary tasks cheaper and letting that compound across a global economy that is finally, after a decade of crypto, metaverse, and app bullshit, getting a genuine productive technology. Almost none of that money has been collected yet. Most large companies are spending too little on this, not too much. What the average Fortune 500 employee has access to today is roughly what most of us were using two or three years ago, a chatbot in a browser tab, a Copilot that schedules meetings, and a procurement process that takes longer than a model generation. Waste Management reportedly added 190 basis points of margin by letting a model route its garbage trucks. The future of AI looks more like garbage truck routing algorithms, not a machine god. The binding constraint on this technology is not capability. It is diffusion. None of this means there are no externalities. Parasocial relationships with a chatbot, especially for children, are a real one, and the fix is the boring kind we already know. Adults can drink vodka until they pass out, but pubs have age limits, and maybe chatbots should too, at least until developing "relationships" with AI companions is as universally recognised a bad idea as drinking yourself into oblivion. That is a mundane policy problem we should remedy soon, not an extinction event. So no, transformers are not going to end the human species. The case for restraint needs a causal link between that buildout and the extinction of the species, and what is on offer instead is a lot of sound and fury signifying nothing. More GPUs does not mean more of an undefined risk that does not exist yet. Every causal chain argument people actually point to falls apart under even the smallest bit of scrutiny. The honest truth is that the technology is really good, but it is not that good yet, and we do not know how to get it to the next level beyond scaling yet. If that changes, if someone produces an oracle for open-ended intelligence, I will revise. I have not seen that yet. AI will change software, and mathematics, and a great deal else that has a strong verifier oracle attached. They are not going to end the human race, and the chattering class currently arranging the flowers for the funeral of humanity will, in a few years, age about as well as their prognostications about the metaverse. Because reality has this funny way of asserting itself.
Why jobs aren’t going anywhere
This post previously appeared in Poets and Quants. 15 years ago, my Lean LaunchPad class changed how entrepreneurship is taught. The class is now taught in hundreds of universities worldwide and helped launch thousands of startups. But this past summer, I got thinking about whether AI killed our Lean LaunchPad class, and with it the […]
It has been an insanely busy 2 weeks - and in the time it took me to have time to write this, Instinct went from raising a $250M Series B at a $2.5B valuation to reportedly raising $1B at $10B.
