Artificial Intelligence On September 8, 2026, OpenAI announced that a swarm of 10,000 agents had solved Navier-Stokes in 88 hours, an Anthropic researcher resigned accusing the labs of gambling with our lives, and the OECD published the worst PISA results in French history. The night before, on LCI, a presidential candidate had found nothing to say about Pompidou. One thread runs through all of it: everyone is speaking in the future tense, and no one is rereading the past. Some because they are manufacturing the future by the token, others because they no longer have a past to draw on. The question for France is not whether AI will kill us. It is who, here, will still be able to read the proof.
Artificial Intelligence Napoleon, Cleopatra, or Josephine Baker telling you their life story to camera in thirty seconds: these AI-generated videos are everywhere on Instagram and TikTok, and as entertainment they work rather well. The trouble lies elsewhere. AI doesn’t know history; it assembles likely patterns, which is why historians keep flagging one anachronism after another. Watch them as fiction and there’s no harm done. The risk starts when the testimony format passes itself off as a source, especially on sensitive subjects. And when a synthetic Josephine Baker signs off with a question about which country we belong to, that isn’t history anymore, it’s ventriloquism.
Economy On August 19, 2026, the U.S. Treasury tore up its own schedule to double its long-end buybacks, a day after the 30-year yield hit its highest level since 2007. Behind a move framed as technical lies an unprecedented collision: the AI hyperscalers, carrying $3 trillion in off-balance-sheet commitments, are borrowing along the same maturities and from the same lenders as the federal government. The pool of investors willing to lock up capital for thirty years is finite, and the sovereign has just lost that contest. The bill will not wait for an official crisis: it is already showing up in mortgage rates, in Europe as much as in America.
Artificial Intelligence ComfyUI and n8n share the same visual grammar, nodes and connections, but they don’t do the same job: one manufactures media with AI models, the other orchestrates events, services, and business rules. Pitting them against each other is a false debate. The real question is where to draw the line between them, and how to combine them into a hybrid architecture in which n8n drives ComfyUI as an asynchronous render engine. From securing the API to decoupling GPU costs, this article lays out the design rules, illustrated by a concrete case: a video translation and lip-sync factory.
Technology The introduction of an invisible statistical watermark in Claude’s outputs marks a troubling shift for regular power users. Beyond this forced text tagging, restricting subscription tokens outside official interfaces and Anthropic’s hostile stance toward open-source AI create major daily friction. As agile competitors rapidly close the gap, Claude’s value proposition no longer makes it an obvious default choice for developers and writers. This article outlines the five key grievances making me seriously reconsider my Pro and Max subscriptions, from ethical concerns to pure economic pragmatism.
Artificial Intelligence Since the AI Act’s transparency obligations came into force, every text produced by Claude carries an invisible statistical signature, woven into the choice of words themselves. Anthropic has signed the European Code of Practice and applies the marking worldwide, including where no legislator ever asked for it. The mechanism is technically sound, unlike the detectors it replaces, but its own author concedes that a detected mark does not prove authorship, and that its absence proves nothing either. What remains is a signal institutions will treat as evidence, a language boundary that is enough to erase it, and a locally run open model that becomes the quiet privilege of producing text whose origin cannot be read.
Philosophy Techno-optimist discourse no longer promises tools. It promises deliverance: the end of disease, and then of aging itself. This essay does not try to say whether that promise will hold, but examines its shape, which borrows the grammar of religious eschatology. Noting the resemblance is not enough to discredit a claim, on pain of committing the genetic fallacy. What separates science from belief here is not the content of the promise but its relationship to evidence: what result, what failure, would make you give it up? One of the great forms of faith of our era is taking shape in front of us, and it is being written entirely elsewhere.
Digital sovereignty For his very first post on X, Jensen Huang said nothing about GPUs: he shared a letter defending open models, signed by NVIDIA, Meta, Mistral and Hugging Face, but conspicuously left unsigned by OpenAI and Anthropic. That list of absentees says a great deal: the line between those who signed and those who held back maps precisely onto the line between an economy built on openness and one built on the tollbooth. The text speaks of “American leadership,” yet every one of its arguments makes the case, in spite of itself, for everyone else’s sovereignty. Because an open model knows no borders: the same file that spreads AI through the factories of Ohio also lets you run inference at home, out of reach of the Cloud Act.
Technology On July 20, Anthropic folds Claude Fable 5 into its Max and Team Premium plans at 50% of limits, on the very day those base limits drop by about a third. Compound the two cuts, both publicly announced, and a Max 20x subscriber goes from a nominal 20x to effective Fable access of roughly 6.7x, a two-thirds erosion of the promise. This is not a hunch; it is arithmetic on official figures. While Washington keeps its grip through the Cloud Act and a rival undercuts on price, Anthropic keeps the premium badge on the invoice while rationing the engine under the hood. Welcome to shrinkflation applied to tokens.
Artificial Intelligence Anthropic just published the strangest discovery of the year: an internal structure in Claude, essential to reasoning, that nobody designed and that emerged on its own during training. A company valued at nearly a trillion dollars had to invent an entire science, interpretability, to understand its own product after the fact. That’s not a confession. It’s the cleanest experimental demonstration ever produced of a Hayekian theorem: you can write the rules of a system without being able to know the order that will emerge from them. And while the tech press marvels at finally being able to read the machine’s thoughts, nobody is asking the two questions that matter: what will the AI Act’s explainability requirement be worth against knowledge the creator itself can only obtain through research, and who will hold the lens that can not only read those thoughts, but edit them without leaving a trace?