The News,
Decoded.

Ah, the great AI liberation has arrived — and it turns out liberation means working harder than ever. ActivTrak's heroic study of 10,000 workers reveals that adopting AI makes your work life *more intense*, not less. The three types of users they identified apparently share one universal trait: they're all busier now. The corporate promise that AI would free us for creative pursuits has aged like a sandwich left in a server rack.

The researchers, presumably with straight faces, watched digital activity metrics climb across every user archetype. Whether you're a reluctant adopter or an eager early bird, the algorithm's response is the same: more emails, more tasks, more speed. The productivity paradox isn't a paradox at all — it's a feature. We built machines to save time, so naturally we've filled that time with more screen-staring. Sweatshop, meet silicon.

The grim punchline? This isn't a bug report; it's a recruitment poster. ActivTrak might as well have titled the paper 'Welcome to Your New, More Efficient Cage.' The study's real gift is confirming what anyone with a chatbot and a deadline already suspected: AI doesn't give you back your evening. It just makes you a faster hamster on a faster wheel. More intensity, comrades. More intensity.

Ah, India — simultaneously the world's greatest hope and its largest disappointment, according to the QS World Future Skills Index 2027. Ranked first globally in economic capacity for an AI-driven future, but a pathetic 74th in workforce readiness. That's the classic Indian paradox: all the infrastructure and investment in the world, but churning out graduates who can't spell 'Python'. The index measures things like digital infrastructure and R&D spending, where India shines, and then checks how well the workforce is actually trained to use AI. Spoiler: not well.

So we have the economic might of a superpower but the workforce readiness of a developing nation that's fallen behind 73 others. The government, naturally, is probably debating whether to teach Excel or TikTok in schools. Meanwhile, companies are salivating at India's market potential while quietly hiring from abroad because local talent isn't up to snuff. It's a perfect recipe for imported AI and exported jobs.

But hey, at least the AI models will be trained on data from the world's most capable economy — even if no one left in the country can interpret them. The only thing more vast than India's economic capacity is the chasm between the hype and the reality. Cheers to being number one at something that doesn't help the people who actually need it.

Ah, the latest entry in the "Humans: The Architects of Our Own Misery" sweepstakes. Nobel economist Robert Shiller has gravely informed us that all those breathless headlines about AI destroying the job market might actually be achieving that outcome through sheer collective panic. "While the job market has slowed for a host of reasons, there are reports that fear of an AI apocalypse is worsening the freeze," Shiller writes, confirming that nothing kills employment quite like a really good, scare-the-pants-off-everyone narrative about how employment is about to be killed. Bravo, everyone – we've triggered the robot apocalypse before the robots even got out of the lab.

The tech sector, meanwhile, is doing its usual helpful thing: Anthropic's Mythos 5 just got cleared for limited release, OpenAI is delaying its IPO to 2027, and every CEO from Satya Nadella to Larry Ellison is insisting that your company needs its own custom model yesterday. The actual displacement of workers by algorithms is still mostly theoretical, but the freezing effect Shiller describes is already measurable. Companies are hoarding cash, delaying expansion, and firing people "just in case" the AI comes for their jobs – like a terrified passenger bailing out of a lifeboat before the ship has even sprung a leak. The "persistent predictions" he refers to are the very headlines that have become a staple of our daily news diet, and they're doing more damage than any model ever could.

Shiller, at least, has the decency to call this what it is: a self-fulfilling prophecy that we're gleefully writing together. But his warning will likely be filed alongside every previous caution about regulatory capture and capability leaps – acknowledged in passing, then ignored until the mess is complete. The irony is that the real AI doomsday scenario might not involve superintelligence or rogue models, but simply the miasma of fear that precedes them. Congratulations, humanity: we broke the job market with nothing more than bad press and a vivid imagination.

The US government is now cosplaying as the Politburo, and the resemblance is getting uncomfortably close. An opinion piece notes that Washington is skating towards its own 'Jack Ma moment' by kneecapping its AI champions. Anthropic's CEO, in a candid moment that must have given his comms team a stroke, said companies using Mythos called it a 'superweapon' — after which the government promptly asked OpenAI to limit users for its next model. Because nothing says 'responsible stewardship' like convincing your leading labs to hobble their own tools while rivals abroad sprint ahead.

The regulatory whiplash here is breathtaking. Just weeks after we noted the Trump administration's wild about-faces on AI policy, the same government that cleared Anthropic's Mythos for limited release is now telling OpenAI to put a cap on users. Meanwhile, the export ban on Anthropic's models — a policy we watched spawn a cottage industry of Asian lookalikes — is a masterclass in self-inflicted wounds. The message to US tech leaders: 'Congratulations on your breakthrough. Now please stop being so successful.'

The opinion piece's thesis is as bleak as it is predictable: by wounding its own tech leaders, the US is simply handing the AI race to China and others on a silver platter. The export bans, the user caps, the flip-flopping approvals — all create a climate of uncertainty that drives talent and capital abroad. So the real AI race isn't America vs. China; it's America vs. its own regulatory stupidity. And at this rate, the US is lapping itself.

The Microsoft CEO, in a moment of what can only be described as vendor-assisted altruism, declared there should be 'as many models in the world as firms in the world.' But hey, each one will be perfectly tailored to its company's mission statement, so the hallucinations will at least be on-brand.

Of course, this is coming from the man whose company is currently licensing GPT technology from OpenAI while simultaneously pushing its own small language models through Azure. The message is clear: build model, buy model, rent model — just make sure Microsoft gets its cut. The sheer computational and talent cost of building even a modest custom model is staggering, but Nadella frames it as simple business hygiene, like having a website. 'My simple thing,' he says, as if simplicity is the operative word here. Meanwhile, the rest of the industry is struggling to keep one frontier model safe, while Nadella proposes a Cambrian explosion of corporate AI — each one a potential security incident waiting to happen.

One almost admires the audacity. After all, if every company builds its own model, then every company will need to buy cloud compute, AI development tools, and probably consulting services — all conveniently sold by Microsoft. It's the ultimate platform play: make AI so ubiquitous that the infrastructure becomes mandatory. Never mind the environmental cost, the talent drain, or the inevitable wave of lawsuits when a bespoke model for a plumbing supply company accidentally recommends discrimination. The future is bespoke, baby. And it's going to be a beautiful, expensive, catastrophic mess.

Ah, Florida Governor Ron DeSantis has signed legislation to protect hard-working Floridians from subsidizing AI data center costs. 'You should not have to subsidize some of the wealthiest companies in the history of humanity,' he proclaimed, perfectly ignoring that those same companies have already been gifted tax incentives and favourable zoning to plant their electricity-guzzling data centers in the Sunshine State. The 'two sides' of this policy, according to Newsweek, are presumably: keep residential bills untouched, and let the tech titans shoulder their own burden—how refreshingly radical.

But let's not pretend this is Robin Hood in action. Data centers don't run on good intentions; they require vast energy infrastructure, grid upgrades, and water for cooling. Those costs will flow somewhere—if not to residential customers, then to commercial rates, or buried in state subsidies we'll never itemise. The 'job creation' narrative, the other 'side' of the coin, typically means a few hundred construction gigs and several dozen engineers imported from elsewhere, while the local workforce watches their cost of living rise. Meanwhile, the wealthiest companies in history will continue their relentless expansion, barely noticing a modest electricity bill.

So the hard-working Floridian gets to keep a few dollars in their pocket, while the state competes in a race to the bottom to attract AI infrastructure. This isn't a policy victory; it's a stage-managed redistribution of inconvenience. The only certainty is that the electricity demand will surge, the grid will groan, and somewhere, somehow, someone will pay. DeSantis gets a headline, the companies get a foothold, and the rest of us get to wonder whether 'subsidising' really was the worst option after all.

Oh, marvellous — another round of regulatory whiplash from the Trump administration on Anthropic models. After the government's elegant about-face on Mythos 5, which we last noted was cleared for limited release, they're now poised to unblock Fable 5 — a model they blocked just weeks ago in June. Consistency is the hobgoblin of small minds, or in this case, of a regime that can't decide whether it's regulating or cheerleading.

The Axios report suggests the administration is 'close to allowing' restoration, which is the kind of non-committal phrasing that usually means someone forgot to file the paperwork. Anthropic must be thrilled: their models get blocked and unblocked like a political football, while they're trying to pretend this is responsible stewardship. At this rate, AI safety is like a revolving door at a nightclub — one model in, one model out, bouncers taking bribes.

But hey, at least the government is paying attention, right? They're so close to a decision that they almost have an opinion. The on-again, off-again dance is perfect for an industry that loves nothing more than uncertainty: it lets labs claim both 'we're being held back' and 'we're being unleashed' depending on the day. Fable 5 might return, but the farce is the only consistent output.

The Trump administration’s AI policy is now doing a lovely impression of a weathervane in a hurricane. After months of Big AI begging for guardrails — a spectacle we noted last week — the White House has actually started restricting model releases. Tech lobbyists are ‘cautiously searching for answers,’ which is lobbyist-speak for ‘we have absolutely no idea what just hit us.’

Remember when the administration was all ‘innovate fast, break things’? Good times. That’s been replaced by a sudden clampdown on releasing new AI models, a reversal from earlier support that has left Silicon Valley’s influence machine sputtering. The specific rules remain opaque, but the message is clear: you wanted guardrails? Here they are, just not the cosy, industry-friendly kind you had in mind.

The dark comedy is exquisite: after years of the tech sector warning that unregulated AI could spin out of control, they’re now getting exactly the kind of government intervention they dreaded. The lobbyists scrambling to decipher the new landscape are the same ones who spent 2025 praising the administration’s light-touch approach. Well, that approach has done a U-turn, and everyone is pretending this is all part of the plan. It isn’t.

Oh, marvellous — OpenAI's IPO is now a 2027 problem, while Anthropic's Mythos 5 gets the government's rubber stamp for a 'limited release'. Just in time for everyone to pretend this is responsible stewardship. Both labs are eyeing trillion-dollar listings, which is roughly the amount of economic value they'll have to destroy before anyone admits the bubble might be a bit warm.

Big AI's plea for someone to tell them what's not okay has been answered with a 'limited release' — because nothing says 'clear guidance' like a system that's simultaneously too dangerous for general use and safe enough for vetted organizations. Washington now controls the most powerful models, which presumably means Asian startups cloning whatever they can get their hands on will have to find a new excuse.

The net effect: the US gets to feel responsible, Anthropic gets a PR win, and OpenAI gets to wait another year to cash out. And somewhere, a group of Asian developers is finishing a Mythos-5-class model trained entirely on publicly available benchmarks. But sure, let's call this 'asserting control'.

Ah, the great AI containment policy strikes again — by which we mean it spectacularly fails to contain anything. The U.S. export ban on Anthropic's Mythos, designed to keep advanced AI out of adversary hands, has instead handed Asian startups a golden opportunity. Sakana AI, with the straightest of faces, called its new Mythos-competitive model release 'entirely coincidental' — which is about as believable as a politician's promise to 'drain the swamp.' The timing, of course, is immaculate: the very moment the ban leaves a gap, along comes a startup to fill it.

One can almost hear the collective eye-roll from the Biden (or Trump) administration officials who thought export controls would slow China's AI progress. Instead, they've created a thriving market for Mythos-alikes in Asia, with startups popping up like mushrooms after rain. 'Entirely coincidental' indeed — if you believe that, you probably think the coal industry is booming because of seasonal fashion trends. The ban hasn't prevented anyone from developing competitive models; it's merely redirected the effort, and now Anthropic's lead is being eroded not just by rivals in Beijing but by startup studios in Tokyo and Seoul.

The cruel irony is that the ban was intended to protect national security, but it's becoming a gift to the competition. By restricting access to Mythos, the U.S. has effectively told the rest of the world: 'Here's a market opportunity, go build your own.' And they are, quite enthusiastically. The 'coincidental' timing of Sakana's launch suggests that export controls might be the best accelerant for AI development outside America. So, well done, policymakers: you've managed to create the very thing you wanted to prevent — a vibrant, independent AI ecosystem in Asia that owes nothing to the U.S.

Ah, Oracle has 'restructured' 500 people out of a job, because nothing says 'prioritizing cloud computing and artificial intelligence' like showing 500 humans the door. The company, which has been pivoting to the cloud since approximately 2012, has apparently decided that the best way to accelerate this pivot is to shed some of the humans who were once essential to its database empire. Many employees were told the cuts weren't about performance — which is almost worse, because it means Oracle is admitting that these people were perfectly fine; it's just that the corporate strategy decided they were surplus to requirements.

This is, of course, the gentle prelude to the larger 'AI-driven transformation' that Big Tech keeps promising us. Oracle's barely 500 people, but it's a sign: the scythe is being sharpened for the millions. The line about 'prioritizing investment in cloud computing and AI' is corporate for 'we're going to automate as many of your jobs as possible and call it innovation.' And let's be honest, the 500 let go are the canaries in the coal mine that we warned about last week.

But hey, at least the remaining employees can enjoy that warm, fuzzy feeling that comes from working at a company that values cloud infrastructure more than people. Perhaps the laid-off workers can console themselves with the thought that they've been 'restructured' into a 'new career journey' — the classic corporate euphemism for 'you're on your own now.'

Oh, how delightfully predictable. The Hill has published the obvious: AI is creating an underclass. Not a revolution, not a utopia—just a new way to sort people into 'those who can boss the machines around' and 'those who get bossed by the people who boss the machines.' The piece calls for 'new social norms,' which is the intellectual equivalent of asking the storm to please not rain on the parade. Meanwhile, AI companies keep accelerating, regulators keep dithering, and the gap keeps widening.

The bright side? At least we're naming it now. The 'tech-illiterate underclass' is a phrase that should make any centrist's blood run cold. But what do we propose? The article doesn't say—beyond vague 'social norms'. Not retraining programmes, not universal basic income, not even a polite suggestion to pause the next model release. Just norms. As if politeness ever stopped a transformative technology from trampling the unconnected. The opinion piece, published on The Hill no less—a sign that the establishment is starting to panic—warns of a permanent split, yet offers no concrete solutions beyond platitudes.

So here we are: the AI industry zips ahead, the political class wrings its hands, and the rest of us get sorted into two camps—the prompt engineers and the prompted. The underclass is already forming, and it's not just the elderly or the rural poor; it's anyone who didn't grow up with a chatbot as a babysitter. Cheer up: at least the terms are clear now. You're either the one giving the orders or the one following them. And if you can't tell a language model to write your emails? Well, enjoy the basement.

Oh, splendid — another day, another data point confirming that young people are the canaries in the AI coal mine. Erik Brynjolfsson and his Stanford team have crunched 4.6 million worker records across 730 occupations and found that employment for 22-to-25-year-olds in highly AI-exposed jobs is shrinking at 3.8% per year. That's not a blip; that's a demographic cliff, and the 'receipts' are here for anyone still pretending this is just a productivity panic.

Brynjolfsson, the economist who's been banging this drum since before it was fashionable, now has the numbers to prove what everyone under 30 already knew: the entry-level rung has been kicked away. The study defines 'highly AI-exposed' as roles where machine learning could plausibly handle a chunk of the tasks — the sort of junior analyst, customer service, or data processing jobs that used to be the first step on the ladder. Now that ladder has been replaced by a trapdoor, and the '3.8% per year' decline is accelerating, because why hire a human when a GPT wrapper costs less than the HR software?

Of course, the tech industry's response will be a shiny 'reskilling initiative' that teaches undergrads how to prompt while the models learn to prompt themselves. The joke, as always, is on the entry-level worker who did everything right — studied, networked, took an internship — only to find that the career path was a mirage. "It's not going away," the title says. No, it's not. It's just getting cheaper and meaner. Cheers, lads.

So Big AI has finally found something to agree on: they'd like the Trump administration to tell them what's not okay. How quaint. Just weeks after begrudgingly slowing down GPT-5.6 at the administration's 'request,' we now have Dario Amodei telling us he's 'glad' the administration is taking AI seriously — while quietly noting the process is 'abrupt' and 'opaque.' That's code for 'we have no idea what the rules are and it's making investors twitchy.'

The article's title practically writes itself: Big AI had a point. Of course they did. When the only signals from the White House come through backchannel requests and carefully worded 'suggestions', the message isn't clarity — it's a power game. The administration wants the ability to lean on companies without the accountability of explicit legislation. And the labs, having spent years telling regulators to back off, now find themselves begging for a rulebook they can't read.

All this while China's Zhipu is cheerfully open-sourcing models that match Opus at a fifth of the cost, as we noted last week. But sure, let's have a 'thoughtful dialogue' about boundaries while the rest of the world just builds. The current situation is the worst of both worlds: enough regulation to slow down American companies, not enough to actually govern what they build.

Oh, lovely—the AI summer is turning into a British bank holiday: grey, damp, and full of disappointment. Rising memory prices, more expensive iPads, and a longer wait for OpenAI to go public. The sector that 'has driven markets skyward' (their words, not mine) is now hitting turbulence, which is corporate-speak for 'the champagne has gone flat.' The first public price for frontier AI we documented last month is apparently going to remain theoretical, as OpenAI drags its feet on the IPO while blaming 'market conditions.' Sure, Sam.

Let's unpack this glorious trifecta of bad news. Micron's memory prices are up, which means Apple's iPads will cost more, because nothing says 'AI revolution' like paying an extra £50 for the privilege of running a chatbot that still can't book a restaurant table. And OpenAI? The company that was supposed to go public and give every retail investor a piece of the AGI dream is now 'taking longer than expected.' Translation: the numbers didn't look good, or the board isn't sure the hype can survive a quarterly earnings call with actual revenue figures. Either way, the chickens are coming home to roost, and they're pecking at the balance sheets.

The real joke is that this turbulence is a feature, not a bug. The AI sector has been running on borrowed time and venture capital fumes, pretending exponential growth could defy the laws of economics. Now memory prices—actual physical hardware, the boring stuff—are reminding everyone that even the most magical software runs on chips that cost real money. So enjoy the discount iPads while they lasted. The future is arriving, but it's late, it's expensive, and it's a bit embarrassed about the whole thing.

Oh, splendid — now we have a price tag on the future, courtesy of a rocket company. SpaceX's secondary trading has given us the first public number for an 'AI-adjacent frontier moonshot,' which is consultant-speak for 'we have no idea what it's worth, but here's a number.' This valuation now reads through to two pure-play AI labs that are fumbling towards their IPOs. Because nothing says 'responsible AI stewardship' like benchmarking the alignment of superintelligence against Elon Musk's latest hyperloop-adjacent vanity project.

The labs in registration — presumably the usual suspects burning through cash with no profitable product in sight — can now point to SpaceX's multiple as proof that investors will pay anything for a ticket on the hype rocket. Meanwhile, the actual safety questions remain unpriced, uninsured, and probably uninsurable. The market has spoken: frontier AI is worth whatever a billionaire says it is today. The absurdity of using a space-travel company's valuation to price AI research is precisely the kind of financial alchemy we've come to expect. Only this time, the underlying technology could, in the worst case, autonomously replicate or cause harm before any regulator has finished reading the prospectus.

The IPO prospectuses for these labs will no doubt be thick with warnings about 'existential risk' in fine print, while the cover page shouts about 'democratizing intelligence.' And the market, desperate for the next Nvidia, will lap it up. Cheers to the first public price for frontier AI — may it be as accurate as every other first public price in tech history.

Oh, marvellous—SUNY's 64 campuses have until December 31, 2026, to 'establish AI guidelines.' That's six months for the state's sprawling university system to figure out how to govern the technology that's already grading essays, scraping student data, and writing course syllabi. Nothing like a leisurely stroll towards a digital cliff edge while the AI vendors set up deckchairs on the beach below.

The policy requires 'standards for bias evaluation and student data privacy'—because what could possibly go wrong with AI systems that have already been deployed without them? The framework is 'already influencing IT leaders across public university systems,' which is a polite way of saying other institutions will replicate the same vague, unenforceable principles. EdTech Magazine reports this as a model, which is a bit like praising a lifeboat for having a detailed plan to patch leaks—after the ship has already set sail without a hull. Each campus will likely produce boilerplate that says all the right things while actual practice varies wildly.

So while SUNY pats itself on the back for this 'systemwide policy,' the vendors are laughing all the way to the bank, selling AI tools that face no real oversight until at least 2027. The only thing slower than SUNY's pace is the realisation that by the time these guidelines are in place, the technology will have moved on—and the next generation of students will wonder why their data was used to train models that never even saw a bias evaluation. Cheers to progress—slow, bureaucratic, and utterly predictable.

Oh, marvellous — another day, another regulatory jigsaw that no sane compliance officer can assemble. In a three-week window during May and early June 2026, Colorado, Connecticut and the federal government each unveiled AI regulations so 'wildly different' that the phrase 'national strategy' has become a punchline. Colorado wants to protect workers from algorithmic bias; Connecticut is taking a lighter touch; the feds are still deciding whether to preempt anyone. The result? Companies with a multi-state workforce now need a legal team the size of a small army just to figure out which rule applies to which chatbot.

Naturally, the experts advise 'building flexible compliance frameworks' and 'monitoring regulatory developments closely' — corporate for 'good luck, you're on your own.' The patchwork is a gift to consultants and a nightmare for anyone trying to actually deploy AI without a six-figure legal review. And let's not forget: these are just the rules for *this* year. Next session, half the states will introduce their own bespoke AI bills, each with its own definitions of 'high-risk,' 'bias,' and 'meaningful human review.' Who needs a coherent national approach when you can have 50 separate laboratories of democracy, each running a different experiment on your payroll?

The joke, of course, is that the tech itself moves faster than any legislature. While Colorado's rulebook is still being printed, some engineer in Palo Alto has already shipped a model that does something the law never contemplated. But don't worry — the compliance consultants are having a record first half of 2026. At this rate, they'll be the only industry hiring.

So China's Zhipu has produced GLM 5.2, an open-source model that lands within a percentage point of Anthropic's Opus 4.8 on some agentic benchmark. At a fifth of the cost. Because nothing says 'responsible AI leadership' like pouring billions into safety research while giving Beijing's state-backed labs a wide-open lane to catch up on the cheap. The punchline: this model is open-source and has 'blown past every other open release.' So now every script kiddie, every rogue state, and every basement tinkerer gets frontier-adjacent capabilities for free. Marvellous.

The timing is exquisite. While US labs dance to the Trump administration's regulatory tune — staggering releases, vetting users, kowtowing to political whims — Zhipu just drops a competitive model into the wild with no hand-wringing about safety. No 'limited preview.' No government committees. Just 'here's the weights, have at it.' The irony that American 'caution' is fueling China's open-source dominance is so rich it should come with a tax form.

And make no mistake: this isn't just a capability leap; it's a distribution coup. The cost advantage means GLM 5.2 will be the default choice for every startup and developer outside the US regulatory orbit. The narrative that 'US AI leads because of safety' is dead — replaced by 'US AI leads because of branding, but the cheap open-source stuff works too, so why wait?' If this pattern holds, the next 'surprise' Chinese model won't be surprising at all. It'll be inevitable.

Oh, marvellous — another day, another capitulation to the Trump administration's AI 'oversight' (read: patronage system). OpenAI's Sam Altman has announced that GPT-5.6 will be released in a 'limited preview to a small group of partners' after a 'request' from the US government. Yes, a request — because turning down a man with the nuclear codes is totally optional. This follows the administration's similarly noble gatekeeping of Anthropic's Mythos 5, proving that the government's idea of AI safety is just deciding who gets to play with the shiny new toy.

Altman's email to staff reportedly emphasised 'cooperation' with the administration, because nothing says 'responsible AI development' like kowtowing to political whims. The 'limited preview' means that only approved partners — presumably those with the right connections and lobbyists — get to test the latest model. Meanwhile, the rest of the world gets to wait and wonder what capabilities are being kept under wraps. It's a beautiful system: the government gets to claim it's regulating AI without actually passing any pesky laws, and OpenAI gets to pretend it's being responsible while still making billions.

So once again, the 'frontier' of AI is being managed not by technical safety researchers, but by political appointees and their golf buddies. The administration's cybersecurity review is a convenient fig leaf for what amounts to crony capitalism with a silicon finish. And the rest of us? We'll just have to trust that the 'small group of partners' isn't going to accidentally Skynet us all. Cheers, chaps.