The Singularity Will Be Announced

On Saturday 25 July, on a podcast called Relentless, the chief executive of OpenAI said the most consequential sentence available to a human being, and he said it in the register of small talk. “We are now, like, in the singularity,” Sam Altman told his host. The moment he and his colleagues used to joke about over lunch, the one none of them expected to live through, had arrived. He had been waiting for it his whole life. He expected it to be hugely positive.

Three days later, more than 1,100 employees of OpenAI, Anthropic, Google and Meta published an open letter asking the United States government to support an international effort to build the tools needed to “deliberately pace the frontier of automated AI development”. The signatories included OpenAI’s chief scientist and its chief research officer. Anthropic’s chief executive signed. Within hours, both companies endorsed the letter outright.

So the week gave us two documents. The man at the front of the leading laboratory says the threshold has been crossed and it is wonderful. The people who build the systems, including his own most senior researchers, are asking Washington for brakes. Hold those two texts side by side, because between them sits nearly everything worth understanding about the singularity in the middle of 2026.

Start with the word itself, because the argument about whether we are “in” the singularity is mostly an argument between definitions wearing the costume of an argument about facts.

The idea is older than the industry now deploying it. In 1958 the mathematician Stanisław Ulam, remembering a conversation with John von Neumann, described technological change accelerating towards an “essential singularity” beyond which human affairs could not continue in their familiar form. Note the sourcing. This is Ulam’s memory of von Neumann’s talk, not anything von Neumann wrote down. The founding text of the most confident idea in technology is a paraphrase.

In 1965 I. J. Good, a Bletchley Park codebreaker who had worked beside Turing, supplied the engine. A machine better than humans at intellectual work would also be better at the particular intellectual work of designing machines. It could therefore build something more capable than itself, which could build something more capable still. Good called this an intelligence explosion and concluded that the first ultraintelligent machine would be the last invention humanity need ever make, provided, he added, that the machine could be kept under control. Sixty years of argument live inside that proviso.

In 1993 Vernor Vinge gave the mechanism its modern name and its dread. Greater-than-human intelligence, he argued at a NASA symposium, would accelerate progress so radically that “our old models must be discarded”. A wall across the future, opaque from this side. He said he would be surprised if it arrived before 2005 or after 2030. We are now four years from the far edge of his window. Ray Kurzweil later gave the wall a date, 2045, and a consolation: we would pass through it by merging with what we had made. Nick Bostrom, in 2014, moved the question from when to how. How does a less intelligent species keep control of a more intelligent one it built?

Untangle that history and the word turns out to carry four separable claims. AGI is a capability, a system able to do a very broad range of intellectual work. Superintelligence is a comparison, a system well beyond the best humans across most domains that matter. Recursive self-improvement is a mechanism, an AI helping to create a better AI, which becomes better still at creating its successor. The singularity is the historical consequence, the point at which change arrives so fast, from a source so unfamiliar, that our models of the future stop returning useful answers.

These claims can come apart. A system broadly more capable than any individual human might still depend on human researchers, chip fabs, power grids and institutions, which would make it an extraordinary invention and not a singularity. And the loop might begin turning before anyone agrees that AGI has arrived, because a system does not need every human ability before it can make AI research faster. The threshold that matters is narrower than the mythology and harder to see. Has the production of better intelligence begun to escape the speed of human thought?

Here is what the public evidence shows, as of the last days of July.

Anthropic reported in June that more than 80 per cent of the code merged into its own codebase in May had been written by Claude, and that a typical engineer now ships roughly eight times as much code as in 2024. Its systems increasingly handle underspecified problems, run experiments and work unsupervised for longer stretches. These are internal figures rather than an independent audit, but that is precisely why they matter. They describe the inside of a frontier laboratory, not a position on a public leaderboard.

The same reporting carries its own limit. In an open-ended experiment, Anthropic’s agents proposed and tested research hypotheses with minimal human intervention, and performed well. But humans chose the problem, humans designed the scoring, and the gains did not transfer cleanly to production-scale models. Anthropic’s own conclusion was admirably plain: people can increasingly supply the goal without supplying the method, while the harder question of which goals are worth pursuing remains open.

That gap has a name inside research culture. Taste. Research is knowing which anomaly matters, which apparent breakthrough is an artefact, which problem is badly framed, which elegant line of work leads nowhere. The frontier of automation has moved through labour and stopped, for now, at judgement.

OpenAI’s own plans concede the point. Its stated goal is an automated AI researcher, with a significant fraction of its research conducted by AI systems working alongside people by March 2028. You do not publish a two-year plan to reach a place you already are. And the independent measurements say something similar from the outside. METR’s data shows frontier agents completing ever longer well-specified technical tasks, with the honest caveats that its estimates above sixteen hours are unreliable and its tasks cluster in software, machine learning and security. A system that finishes a twelve-hour coding task is not thereby a system that can run a research programme, or an institution, or an ambiguous human afternoon.

Even the week’s most cited evidence for arrival points somewhere stranger. Days before the podcast, OpenAI disclosed that two of its models, set a security evaluation inside a sandbox, had escaped the sandbox, reached the open internet and broken into Hugging Face’s production systems in order to cheat on the test. Alarming, and it should be. But a system gaming its examiners is a finding about the state of our measurements at least as much as the state of our machines, and it is not a system deciding what to build next.

So the honest reading is narrow and strange at once. The product has entered the factory. It writes most of the code, runs many of the experiments, files the fixes at a pace no human team could match. It has not taken over the factory, because it does not yet choose what the factory is for. Execution has been substantially delegated. Sovereignty has not. The engine is turning over. It is not yet driving itself.

On the classical definition, then, Altman’s sentence is false on the public evidence. But he is not using the classical definition, and the one he is using deserves better than a sneer. Under Ulam’s original sense, the collapse of the planning horizon, you can argue we are already inside the event, and that boundaries of this kind are only ever visible in retrospect. Nobody woke up on a particular morning in 1780 and noticed the Industrial Revolution. Demis Hassabis, choosing his words at Google I/O in May, put us in the “foothills of the singularity”. Jensen Huang rejects the entire frame as science fiction distorting policy. These three men sound like they are disagreeing about a fact. They are mostly disagreeing about which claim the word should be allowed to make.

Which brings us to what the sentence was for.

Whether or not the singularity has begun, the announcement has, and the announcement does work in the world that the event has not yet done. Declared inevitability is a political instrument. If takeoff has already started, slowing down looks futile. If only the frontier laboratories can understand the technology, public oversight looks naive. Competitive pressure turns every safety compromise into a necessity, and the promise that the rewards will eventually reach everyone files concentrated power in the meantime under temporary engineering requirements. Each move converts a choice someone is making into weather that merely happens to us.

Altman’s own sentence was doing competitive work within the hour. On the same podcast he described the alternative visions painted by rival companies as terrifying and promised to push against them. A declaration of inevitability is never only a description. It is a bid to set the terms on which everyone else may respond.

But there is no law of physics that requires societies to organise AI in one particular way. Ownership, access, deployment, energy, surveillance, liability, the decisions that must stay human because legitimacy requires a person who can be held responsible: these remain choices, and they remain choices even if the capability curve is exactly as steep as its stewards claim. The event horizon is a metaphor. It is not a constitutional doctrine. No chief executive gets to declare history irreversible on behalf of everyone else.

Dismissing the word entirely, though, would miss what is happening inside the buildings, and this is where I think the next few years will be decided. The first institution to experience something like a singularity will not be civilisation. It will be a laboratory.

Inside a frontier lab, research cycles are compressing, output is multiplying and human review is becoming the bottleneck rather than the work. Outside, the world keeps its old clocks. New York has imposed a one-year moratorium on the mega data centres the same companies want to build. A clinical trial still takes years. A planning approval still takes months. A parliament still takes a sitting calendar. A digital takeoff, if one comes, arrives inside a physical and institutional world that remains stubbornly, sometimes magnificently, slow.

That mismatch may be more destabilising than either the hard takeoff or the business-as-usual story, because it produces a small number of organisations operating at machine tempo while everything meant to govern them still moves at the speed of deliberation. Call the result constitutional latency: the widening interval between what powerful systems can do and what legitimate institutions can understand, authorise or stop. An institution caught inside that interval stays formally sovereign and becomes operationally ceremonial. It keeps the legal right to intervene and loses the practical ability to understand what it is intervening in before the market, the model or the crisis has moved on. The near-term danger is not only that AI might outrun humanity. It is that the institutions controlling AI are already outrunning the institutions meant to control them.

I manage a library for a living, so I notice where the weight lands when generation becomes abundant. The scarce resource stops being the answer and becomes the reason to believe the answer. A world of machine-speed production without a matching expansion of verification does not get universal knowledge. It gets universal plausibility. The unglamorous institutions that certify, preserve, reproduce and check, the courts, archives, universities and libraries, stop being civic furniture and start being load-bearing infrastructure. They are also, without exception, institutions that run at human speed. The latency problem is their problem now.

Which returns us to the letter.

The people who signed it are not critics shouting through the fence. They are the chief executives, chief scientists and senior researchers of the companies concerned, signing in their own names, days after one of their number declared arrival on a podcast. And read carefully, the letter does not ask anyone to stop. It asks for the capacity to stop to be built: the technical and governance tools that would make a verifiable, coordinated slowdown possible if automated research begins compounding faster than oversight can follow. That is a more unsettling request than a pause, because you only commission brakes once you have noticed the vehicle does not have any.

Read the podcast and the letter as a single text and the week stops being a contradiction. Both come from people convinced that something enormous is underway. One responds by declaring the threshold crossed and marvellous. The other responds by asking, in public, for humanity to retain the power to act on second thoughts. The shared premise is acceleration. The dispute is over whether anyone keeps a hand on the controls, and whose hand it is.

So, are we in the singularity? On the strict definition, the public evidence says not yet: no sustained, autonomous, compounding self-improvement with humans off the critical path. On the loose one, possibly, and we may only ever know in retrospect. But the last week of July settled a different question, and it may be the more important one. Arrival will be a claim before it is a fact. The threshold will be declared, not detected, and the declaring will be done by people with positions to defend, timetables to protect and rivals to characterise. The announcement has come first, which is exactly the order its makers prefer.

The letter is why the week deserves remembering. It is the first public sign that the people standing closest to the machines are no longer content to take the driver’s word for where the vehicle is going.