Technology

October 2026 will go down in history as the month the universe changed, yet most people didn’t notice. The tech company OpenAI, makers of ChatGPT, released the solutions to 722 fundamental mathematical problems. Many of these problems had baffled humans for decades but a large language model (LLM) that was just 11 days old toppled them. AI had already solved some mathematical conjectures, but this was off the scale. “This is at least ten times, perhaps 100 times as momentous as the proof of Fermat’s Last Theorem,” said Abhishek Saha, professor of mathematics at Queen Mary University of London.

In a provocative and unprecedented act over the past two days a Russian military “inspector” satellite has been maneuvering closer and closer to a US-registered, European-built, all-weather earth observation satellite that provides data vital for Ukraine's war effort. It is the first time non-consensual close proximity action has been carried out in low-Earth orbit between two satellites. It has alarmed western space war fighters who see it as a hostile demonstration of future orbital conflict. Russia is a declining space power and watches the growing military space prowess of China and the US with alarm There can be no doubt of the intent of the mission which must have been planned for some time.

Silicon Valley rewards founders who talk about tomorrow’s technology as if it’s already here. A founder tells investors that a machine runs a blood test today. When the claim falls apart, the founder explains that it was only a promise about the things the machine would accomplish one day. Some investors learn the difference later, from their lawyers. Nathan Fielder and Lance Oppenheim’s new documentary, You Can See Everything, catches a founder offering that explanation on camera. Its subject is Elizabeth Holmes. For a while, Silicon Valley rewarded her lavishly. She wore a black turtleneck like Steve Jobs and posed for photographers holding up a vial of blood no bigger than a fingertip.

At some point there has to be an “emperor has no clothes” moment. Why, when we are in the middle of a boom in Artificial Intelligence, which is supposed to transform the way we do nearly everything, is there no tangible increase in productivity across the economy? Surely, if the claims for AI were even nearly true it would by now be showing up in the statistics for Total Factor Productivity (TFP) published by the San Francisco Fed. TPF is a measure of output relative to input from labour and capital; a measure, in other words, of how efficiently workers are using the tools available to them. In theory, it should be increasing dramatically with AI as workers use it to speed up tasks and get more out of their day. Trouble is, that does not appear to be happening.

A remarkable weather record was broken recently. The equinox came and went this September and yet not a single hurricane had formed all year in the entire Atlantic Ocean. It’s the first time this has happened since 1914 – which was back before the satellite era, when hurricanes were more likely to go unrecorded. September is normally peak hurricane season, when the tropical Atlantic gives birth to a series of spinning storms, dubbed hurricanes when their winds exceed 74 miles per hour. (They are usually called typhoons or cyclones in the Pacific and Indian oceans.) One year is not a trend but longer-term data does show a slight downward trend in hurricane frequency.

Most of us have gone to bed and forgotten to lock a door or window. Now imagine an intruder who tried your front door every night, then the back door, then every window. They never get tired, never get bored and never stop trying. Eventually, they would find the one you forgot. That is one way to understand the security problem created by AI agents. Agentic AI is not inherently malicious. Part of the risk comes from its persistence: agents are designed to pursue as many routes as possible to achieve an objective. The other part is that they are being deployed in systems designed to defend against humans, with weaknesses that until now have not been exposed.

Few people had heard of Jacob Coxon, the 28-year-old British AI researcher, on the morning of September 8, 2026. His X account had fewer than 100 followers. By September 10, he was world famous, after he published a social-media thread on X about resigning from Anthropic because the company is not "acting responsibly." The post has now been viewed 174 million times. It triggered a tsunami of news panic about the dangers of artificial intelligence. Suddenly, Jacob was everywhere: doing prime-time interviews; a celebrity whistleblower, the casus tumultus of a global conversation about the dangers of AI, which in turn led to a public fight among various tech overlords urging for more government regulation, and angry pushback from the Trump administration.

For decades the road to success in the developed world has been straightforward. A university education, increasingly treated as a sort of white-collar trade school, offered people the chance to acquire specialist knowledge which could be used to secure a position lingering at a desk for 40 years. For those of us who grew up watching machines replace men on the assembly line, acquiring a degree was the way to escape this fate. In the digital age, however, the automation of cognitive labor has forced many professionals to confront a threat that once seemed confined to workers on the factory floor.

Terry Tao is the most famous and award-laden mathematician working today. He is known for his groundbreaking work in many areas of mathematics and when he speaks, people listen. A few weeks ago he took to the stage at the International Congress of Mathematics, held every four years, to give his lecture, “Mathematics in the Age of AI.” He voiced concern about what he called an unprecedented threat. “AI has created a crisis in our mathematical values and practices,” he said, and his words resonated because, just days before, Anthropic’s Claude Fable AI program had solved the so-called Jacobian conjecture which has puzzled mathematicians since 1939. It was a devastating achievement, all the more so because the solution fitted into a single tweet.

Cassandra was a princess, daughter of King Priam of Troy. Apollo gave her the power to see the future and, when she rejected his advances, arranged that no one would ever believe her. She warned the Trojans about the wooden horse. “All heard, and none believed the prophecy,” Virgil wrote. And so the city burned. The kingdom of artificial intelligence is now producing a stream of its own Cassandras. On September 8, a 27-year-old AI researcher named Jacob Coxon quit Anthropic – and explained why on X. The company and its rival OpenAI, where he had also worked, were “racing straight to self-improving superintelligence and gambling with our lives.” By breakfast, tens of millions of people had seen his post.

Most of us say we instinctively understand what time is, but struggle to describe it. We clearly live our lives in the flow of time, with the past gone and our perception of the present moving toward an undetermined future. It’s been described as the fire in which we burn.  But what actually is it? This occupies the minds of cosmologists and philosophers, and recent research, far from clarifying the concept, makes it even stranger. Time, it seems, may not be fundamental but a by-product of the base structure of the cosmos. For Isaac Newton, time was set in motion by God and was the universal backdrop in which all events occur. It was unchanging and ever-present; it regulated and set the pace for the clockwork universe, living out the laws of science.