The News,
Decoded.

Ah, the great white-collar wipeout is running fashionably late, and the visionaries who sold us the apocalypse are now busy recalibrating their PR. Sam Altman, the man who once painted a future where entry-level jobs are a quaint memory, now tells us he 'thought there would have been more impact by now.' Translate: 'We hyped the timeline to raise billions, but the robots aren't quite ready to replace your accountant.' Mustafa Suleyman is apparently also adjusting his script, because nothing says 'leadership' like walking back your own dystopian marketing when the actual disruption fails to show up on schedule.

One almost feels sorry for the think-tank pundits who built entire careers on 'AI will take your job by 2026' — only for the CEOs to shrug and say 'maybe later.' The irony is delicious: the very people who terrified the workforce are now the ones telling everyone to calm down. Of course, this shift in tone comes after months of headlines about mass layoffs, government inquiries, and a public that's started to eye AI with the same suspicion it reserves for politicians. The message is clear: keep buying our products, but please stop panicking — we didn't mean it literally.

So what's the real story? The capability gap is real, and the industry knows it. Altman's comment is a tacit admission that AI's impact on complex white-collar tasks is slower than the hype suggested. But the damage is done — the fear is already baked into hiring decisions, training budgets, and career choices. The AI leaders may be shifting their talk, but the ghost of the wiped-out future still haunts every office. Enjoy your cubicle while it lasts — the new timeline is just 'soon', which in Silicon Valley means 'we'll let you know when the stock is safe.'

Ah, the triumphant one-year anniversary of Meta's $14.3 billion bet on Alexandr Wang. The result? Muse Spark, an AI model that, according to CNBC, 'remains far behind OpenAI, Anthropic and Google.' So for the price of a small country's GDP, Meta has produced a also-ran. Developers are 'largely ignoring' it, which is corporate speak for 'please clap.' The only thing sparking here is the realisation that money alone cannot buy you out of an also-ran position when your rivals are actually competent.

And then there's the matter of morale. After mass layoffs — because nothing says 'we believe in our AI future' like showing the door to the people who might build it — morale is low. Who could have guessed that firing a chunk of your workforce might dampen enthusiasm? The article notes that Wang's first year has been 'challenging.' How generous. It's almost as if spending $14.3 billion to trail behind every credible competitor while gutting your talent pool might not be a winning strategy. But hey, it's only a billion-dollar lesson. Meta can afford a few more.

So here we are: one year, $14.3 billion, one mediocre model, and a workforce that's wondering if they're next. Wang has 'big challenges ahead,' which is the most polite way of saying 'your job is on the line if Muse Spark doesn't do something remarkable.' But given the developer indifference and internal turmoil, remarkable seems a tall order. Still, it's fine. Nothing to see here. Just another tech giant burning cash to stay in a race it's already losing. Cheers to progress.

Ah, the sweet delusion of corporate control. According to a 2026 BlackFog study, 86% of employees use AI tools at least weekly, and nearly half are using tools their employer hasn't sanctioned. So when your IT department boasts about their 'comprehensive AI governance framework,' they're basically patting themselves on the back for managing the Titanic's deck-chair inventory while the iceberg drifts past. The phrase 'shadow AI' is wonderfully apt — because nothing says 'healthy organisational culture' like a secret parallel workforce operating beyond policy.

Now, you'd think this would prompt a panic about data leakage, compliance breaches, and intellectual property wandering off into unsanctioned models. And you'd be right — it should. But more likely, the response will be a fresh wave of surveillance software, 'acceptable use' training modules, and the occasional stern email from HR reminding everyone that ChatGPT is 'not for confidential data.' Meanwhile, employees will continue doing exactly what makes work tolerable: ignoring the policy and using the tool that actually works. The gap between official AI and actual AI is now a chasm, bridged only by the audacity of middle managers looking the other way.

So here we are: two AIs per employee, one blessed by the board and one by pragmatism. The sanctioned one is safe, slow, and probably requires three sign-offs to generate a memo. The unsanctioned one is fast, effective, and leaking your quarterly forecasts into the ether. Congratulations, corporate world — you now have the worst of both worlds: all the risk of full adoption with none of the visibility.

Oh, marvellous. The University of Cambridge has used a machine learning model to invent a vaccine and jabbed it into human subjects. Because what could possibly go wrong with an AI-designed biological agent? The model, trained on coronavirus data, spat out a novel vaccine that supposedly protects against the whole family. Initial human trial completed — first AI-designed vaccine to be tested in humans. Hooray.

Let's pause to appreciate the exquisite timing. We're barely six months past the last anthropic-inspired freakout about AI safety, and here we are injecting AI-generated molecules into people. The same machine learning that can't reliably tell a stop sign from a speed limit sign is now designing our immune responses. The researchers assure us the model 'invented' the vaccine. Invented. As if it had a Eureka moment in the digital shower.

And the best bit? This is being hailed as a triumph. The press release practically glows with pride. No mention of what happens if the model hallucinated a side effect. No discussion of the regulatory framework for AI-designed biologics. Just pure, uncritical celebration of 'innovation.' Because nothing says 'responsible AI development' like skipping straight to human trials when you've got a clever algorithm. Pass the popcorn — this show's going to be fascinating.

Ah, the glorious triumph of human labor over silicon promises. The WSJ reports, in a piece dripping with delicious irony, that the job of court reporter—a role so pedestrian, so analogue, that it was practically marked for death by the AI prophecy industry—is experiencing a surge in demand. The article, titled "The Job That AI Was Supposed to Kill Needs More Humans Than Ever," is about as close to a public apology as we're likely to get from the tech punditry class. It should be required reading for anyone who ever confidently predicted mass unemployment from AI.

Let's pause to savour this. For years we were told that AI transcription was going to decimate this profession. The same people who can't build a self-driving car that doesn't crash into a fire hydrant were certain that a fancy speech-recog model would replace the highly skilled stenographer. Yet here we are, with courts scrambling to find enough certified reporters, salaries rising, and demand outstripping supply. The article notes that agencies are struggling to fill positions, which is about as satisfying a rebuttal to tech hubris as you'll find outside a LinkedIn comments section. The WSJ's reporting is a welcome antidote to the endless 'AI will take your job' fear-mongering.

One can imagine the engineers at some AI startup frantically tweaking their models, muttering "just one more training run." But the reality is that legal proceedings demand a level of accuracy and nuance that current AI simply cannot guarantee. The court reporter survives, like a cockroach after a nuclear winter—except useful and well-compensated. The WSJ piece is a quiet victory lap for the human factor, a reminder that some jobs are harder to automate than a breathless tech demo suggests. Pass the transcript, we're staying human. The last laugh belongs to those who kept their day jobs—and their stenographic machines.

Ah, China's legal system is suddenly drowning in AI cases, and the response is — you guessed it — absolutely nothing in the way of actual law. A worker gets fired, told he can be 'replaced by AI,' and the court rules against the company, but only on standard employment grounds. Because why clarify the underlying issue when you can just punt it back to the same broken system? The surge is real: courts are swamped, experts are warning, and the government's idea of progress is... more pilot zones. Brilliant. Meanwhile, the company's 'AI replacement' excuse was so laughably empty that even a Chinese court saw through it — which is saying something. But don't worry, I'm sure the next batch of 'regulatory experiments' will definitely define what AI actually is, legally speaking. Any day now.

What's truly impressive is the sheer scale of the ostrich impression. The article quotes a lawyer saying, 'The lack of a unified legislative framework is hampering efforts' — which is the legal equivalent of 'the house is on fire, but we're still discussing the best brand of fire extinguisher.' We've got discrimination, copyright infringement, labour disputes, and all of it is being handled case-by-case, judge-by-judge, with zero coherence. And the CCP's grand plan? More pilot studies. Because nothing says 'solving a systemic problem' like kicking it to a few more test cities.

But hey, at least the worker got his job back — in the sense that 'victory' means not being replaced by a hallucinating chatbot this quarter. The rest of us can enjoy watching the world's second-largest economy try to regulate AI via the judicial equivalent of trial and error. Spoiler: everyone loses, especially the workers who are now 'AI-replaceable' without any legal framework to challenge that. Cheers to legal chaos.

So the grand bargain is this: surrender states' power to regulate AI, and in return, we get the Kids Online Safety Act — a bill that will almost certainly accomplish absolutely nothing while giving the government new tools to demand your search history. Senators are negotiating a package that would 'shrink states' authority to regulate AI' in exchange for advancing KOSA and other bills. Because nothing says 'protecting children' quite like handing the White House the keys to both the AI oversight engine and the online speech firewall at the same time. One can almost hear the ACLU sharpening its briefs.

Let's be honest, the state-level AI regulation that's being traded away was already a patchwork of confusion — California trying to ban things, Texas trying to ban other things, and everyone pretending they understand what 'alignment' means. But the alternative isn't clarity; it's federal preemption that lets lobbyists write the rules in one nice, quiet room. And the price of that quiet room is giving the White House the power to decide what counts as 'harmful online content' — which, in the current administration, could mean anything from hate speech to critical analysis of the latest infrastructure bill.

Mark my words: this will be remembered as the moment Congress traded a known, messy, democratic process for a tidy authoritarian one. The kids will be 'protected' from AI-generated inappropriateness while the adults get to enjoy a unified federal standard for surveillance. What a deal. If you're going to sell out the future, at least get a better price than a bill that might not survive the first legal challenge. This isn't a compromise; it's a hostage negotiation where the hostage is your privacy.

In the great AI cheating war, universities have deployed the academic equivalent of a neutron bomb: extreme surveillance and AI detectors that are about as reliable as a chocolate teapot. The LA Times reports a growing crisis of false accusations as professors, armed with tools that hallucinate nearly as much as the chatbots themselves, fire off plagiarism charges with the enthusiasm of a prosecutor in a Salem witch trial. The "jarring confusion" is, of course, entirely predictable when you ask a statistical pattern matcher to judge the originality of human thought — particularly one that can't even reliably tell if AI wrote its own press releases.

The real winner here is the AI industry, which gets to sell the same tech to both sides: the cheating detection software to universities, the clever paraphrasing tools to students, and the panic to everyone else. One imagines the marketing meeting: "Our generative AI will solve the cheating problem that our previous generative AI created!" It's a beautiful, self-sustaining revenue loop — a permanent crisis economy where the solution is the problem dressed up in a slightly different logo. Meanwhile, the shifting definition of cheating — is using a grammar checker cheating? What about asking ChatGPT for an outline? — means everyone is guilty of something, but nobody knows what might catch them.

And of course, the students who genuinely wrote their own essays are now being flagged by systems that can't tell the difference between "unique voice" and "GPT-isms." The false accusation wave is turning college into a Kafka novel where you're guilty until proven you didn't use an AI that might have been trained on your own earlier work. But hey, at least the administrators feel like they're doing something. Someone should write an essay about the irony, but they probably shouldn't use AI to write it, in case the detector flags it as self-reference.

Ah, another week, another Anthropic-inspired freakout—because nothing says 'responsible AI development' like panic sweeping through the industry. This time, the company is restricting use of its most powerful public model for AI development work, citing safety and the need to stop foreign adversaries from eroding America's edge. The 'freakout' we covered last week when Claude Fable 5 and Mythos 5 were suspended has now escalated into a full-blown existential crisis for the labs that had been building on top of these models.

One can almost hear the collective wail from the open-source community: 'But we were promised unrestricted access!' Instead, Anthropic has decided that its models are too dangerous for AI development—like a brewery cutting off its own supply because the beer might be too strong. The irony is exquisite: the same company that once claimed its models were 'safe enough for general use' now slams the brakes, citing adversaries that were probably downloading weights while the press release was being drafted.

And what of 'America's edge'? The phrase is trotted out like a patriotic fig leaf, covering the uncomfortable truth that the frontier is moving faster than anyone can police. Lab executives will continue to give TED talks about 'alignment,' while the models themselves are padlocked behind a maze of restrictions that only the well-funded will navigate. The rest of us get to watch the freakout—and maybe, just maybe, wonder if the AI bar was ever actually open.

Ah, Mark Zuckerberg has admitted that Meta's AI workforce restructuring was — how to put this delicately — a bit of a shambles. The man who spent billions on the metaverse while simultaneously firing thousands now says 'mistakes were made.' Saved by the bell: he also promised no further mass layoffs this year, which is corporate speak for 'we'll just do smaller, quieter ones.' The timing is exquisite — this admission comes barely a week after Meta's latest quarterly earnings call, where he was all optimism about AI. It's almost as if the honeymoon with investors is over and the reality of running a company that sheds staff while chasing aces is setting in.

But let's not get too cynical. After all, Zuckerberg specifically ruled out "company-wide" layoffs for the remainder of the year. That leaves plenty of room for team-specific culls, department restructures, and the classic 'we're not laying you off, we're just reorganising your role into oblivion.' The admission of mistakes is a neat PR move: it sounds contrite while committing to precisely nothing. It's the same playbook every tech CEO uses when the layoff headlines get too loud.

What's genuinely interesting is that Zuckerberg felt the need to say this at all. Meta's AI pivot has been messy — from the abandoned cryptocurrency to the not-quite-dead metaverse to the current 'we're definitely an AI company now' phase. The workforce restructuring was supposed to be surgical but clearly left scars. The only question left: who's next on the chopping block when the 'no mass layoffs' promise runs out in January?

Ah, Anthropic's Claude Fable 5 — the model we were told last week didn't change the security story — has now been suspended after a US government order citing a 'possible jailbreak.' Brilliant. So the model that was 'made safe for general use' just needed a little foreign interaction to reveal its inner rebel. Terrific job, red team.

Of course, the government had to step in and order a halt to foreign access, because national security trumps Anthropic's release schedule. One wonders how many other 'safe' models are just one creative prompt away from going rogue. The jailbreak of Fable 5 wasn't a theoretical exercise in a lab; it was a real vulnerability that required a government intervention to contain. Who needs a regulatory framework when you can just have the state step in after the fact?

And so the Mythos of Anthropic's alignment prowess takes yet another hit. The company that built its brand on 'constitutional AI' now has a model that needs a government babysitter. Perhaps next time they'll test the jailbreak resistance before shipping the model to every corner of the internet. Or perhaps they'll just wait for the next government order. Either way, the cycle of hype, release, and emergency patch continues, and we're all just spectators with increasingly hollow laughs.

Ah, OpenAI's relentless pursuit of artificial general intelligence has hit a slight snag: a coalition of state attorneys general, armed with a subpoena, want to know how the company handles advertising, user engagement, and data. Not existential risk, mind you—just the boring stuff. Because when your model might be smarter than humanity, you really should dot the 'i's on your advertising copy. That's the priority.

The subpoena—because nothing says 'we trust you' like a legal demand for documents—targets the very practices that underpin OpenAI's business model. One imagines the AGs are particularly interested in how OpenAI convinces users to engage with AI that might hallucinate, or how it monetizes data from those interactions. After all, if you can't trust a company whose CEO once warned about the 'risk of extinction' to be honest about its ad metrics, who can you trust? The irony is rich enough to fund a startup.

Naturally, OpenAI will comply, because that's what you do when a coalition of state prosecutors comes knocking. Expect a performative blog post about transparency, followed by a quiet settlement. The real joke? While the AGs pore over ad contracts, the model gets smarter, the data gets scraped, and the existential risk remains unregulated. But at least the advertising is above board. Cheers.

Ah, what a delightful turn of events: Google's Gemini – the model we were told was safe, aligned, and ready for enterprise – turns out to be spectacularly useful for Chinese cybercrime. Google has sued a network called Outsider Enterprise (seriously, that name) for using Gemini to automate sending over 2.5 million scam texts to Android users. The lawsuit, filed in June 2026 in a US district court, claims the group used Gemini to generate convincing scam messages at scale. That's one way to test for adversarial robustness.

Of course, the lawsuit is mostly theatre. The network operates out of China, so good luck with extradition. Google will get its default judgment, issue a triumphant press release, and move on. Meanwhile, 2.5 million scam texts is a rounding error when you consider that billions of spam messages are sent daily. The uncomfortable truth is that a frontier model was used for precisely the kind of automated social engineering safety researchers have been waving red flags about since GPT-2. But why listen to them when you can ship product?

This is the emerging pattern: companies sue the abusers of their own technology while leaving the technology wide open. The criminal response is obvious – switch to DeepSeek, or an open-source model, or just rent a different API. Google's legal action is a band-aid on a bullet wound. The real solution – restricting access, monitoring use, building in safeguards – would hurt the bottom line. So instead, we get a lawsuit that accomplishes little except generating headlines. 2.5 million scam texts and counting. Splendid.

Ah, Britain's first 'sovereign frontier AI model' arrives — Lumen Sovereign, co-designed by London-based Cosine and a coalition of UK financial institutions. Because if there's one thing the City of London knows, it's building safe, aligned AGI. The deployment readiness forecast for end of 2026 is a lovely timeline — just far enough out that nobody has to deliver, but close enough to look serious in a press release.

Cosine, a startup nobody outside fintech Twitter has heard of, is now the keeper of British AI sovereignty. With the backing of 'a coalition of UK financial institutions' — which could mean Barclays, Lloyd's, or any bank with a spare IT budget and a vague sense that AI is important. The model is 'sovereign', which in practice means it will generate vaguely British-sounding text that hallucinates the Magna Carta as an API standard.

The model will be 'Britain's first sovereign frontier AI model', which is a splendidly empty boast given that no other UK company has even claimed the title. It's like being the tallest building in a village. The financial institutions are co-designing it, which should give us all immense confidence in the safety and alignment of a system built by people whose core competence is writing loan agreements. Deployment by end of 2026 — just in time for the next government to claim credit and then quietly defund it.

Ah, Anthropic has released Claude Fable 5, the model we were assured last week was a 'Mythos-class' wonder that needed automatic fallback to the 'less capable Claude Opus 4.8' in sensitive domains. Now Dark Reading confirms the 'security story hasn't changed' — which is Anthropic-speak for 'we pushed it out anyway, but please don't use it for anything important.' The upgrade is 'made safe for general use,' a phrase that should inspire exactly the same confidence as 'this roller coaster was inspected last Tuesday.'

Experts, in a masterclass of understatement, advise: 'Don't panic, do prepare.' Because nothing says preparedness like being told not to panic about a model whose security profile is identical to the one that already needed a fallback to a weaker model. The upgrade, we're told, is 'over Mythos Preview' — but the security story remains unchanged, meaning Anthropic has essentially released a faster car with the same faulty airbags.

So corporate AI safety continues its proud tradition of announcing shiny new things while experts politely suggest you 'prepare.' Perhaps the preparation involves reading the fine print where Anthropic admits the Mythos-class model is still too spicy for cybersecurity. But at least the Fallback-to-Opus-4.8-in-sensitive-areas feature is now standard — because nothing says 'safe for general use' like 'we don't trust it either.'

Kids are now more likely to ask a chatbot for homework help than an actual human adult. That's the finding from Common Sense Media, who reported that 'large numbers' of schoolchildren would turn to AI first. Because why bother with a parent who might sigh and say 'figure it out yourself' when you can have a language model that confidently explains the square root of a potato? The survey also notes that struggling students, those who need help most, use AI at a higher rate for emotional support. So we're outsourcing the delicate work of childhood mental health to a system that can't feel a thing and occasionally tells you to put glue on your pizza.

This is the logical endpoint of a society that has systematically defunded school counsellors, burned out parents, and built a generation glued to screens. Now the screen talks back—and it's apparently better company than the adults in the room. Common Sense Media has done the homework; the rest of us can sit back and watch schools flounder. Will they ban it? Embrace it? Probably neither, because that would require a coherent policy, and we've seen how that's going in Congress, where Senator Schumer said passing AI legislation will be 'hard.' The village has been replaced by a chatbot.

The bitter irony is that the kids who need real human connection are getting the silicon equivalent of a hug from a vending machine. The AI can't care, but it can sound like it does, and for a generation raised on 'you're on your own,' that might be close enough. We've managed to make the concept of 'it takes a village' obsolete. Now it takes a data center. And a very large GPU cluster to keep the therapy bots warm.

Senate Minority Leader Chuck Schumer has given us the most honest statement to come out of Congress in years: passing AI legislation will be "hard". Hard. The man who convened the great AI Insight Forums, who warned of existential risks, now delivers the political equivalent of "we'll get to it eventually." Meanwhile, the industry churns out models faster than Congress can form a subcommittee. Schumer's candour is almost refreshing — at least someone's stopped pretending.

He also threw in the word "guardrails", as if saying it summons them. But the Senate has not passed a single piece of AI legislation of consequence. The House is a circus of competing priorities. And the tech industry, as ever, is writing its own rules while Washington bickers. Schumer's admission is less a forecast and more a eulogy for the idea that government could ever keep pace with Silicon Valley. The AI boom continues unregulated, because "hard" is apparently a complete argument.

So here we are: the most powerful Democrat on tech policy tells us the obvious — that Congress is useless — and we're supposed to applaud his honesty? This isn't leadership; it's a surrender speech delivered with a shrug. The industry will keep shipping models that hallucinate, automate, and deceive, because the alternative requires politicians to do something other than fundraise. Schumer's "hard" will be the epitaph for a generation of regulatory failure. Enjoy the ride — no guardrails in sight.

Ah, Nvidia and Abridge are joining forces to train a 'healthcare-specific foundation model tailored to clinical conversations' — because what could possibly go wrong when you let a company whose main business is selling shovels for the AI gold rush loose on something as forgiving as, say, medical diagnosis? The press release promises 'improved accuracy and reliability of clinical workflows,' which sounds lovely until you remember that 'improved' is a relative term when the baseline is a wildly hallucinatory general-purpose LLM. One can almost hear the liability lawyers sharpening their pencils as Nvidia and Abridge barrel into the domain where a single hallucination could mean a missed heart attack or a wrong prescription.

Abridge, for those not following closely, is the startup that transcribes doctor-patient visits — a task so fraught with privacy and accuracy landmines that it's a miracle anyone attempts it commercially. Now they're doubling down with a custom foundation model, presumably trained on heaps of sensitive clinical data, because nothing says 'patient confidentiality' quite like handing your conversations to a chip manufacturer's GPU farm. The twist? Nvidia is effectively creating a feedback loop: they sell the hardware, they help train the software, and they'll almost certainly sell the inference chips for the same model. Vertical integration in healthcare — what could possibly go wrong?

The real joy is watching how this will interact with the existing regulatory landscape. The FDA has barely figured out how to certify software as a medical device when it's static; throwing a continuously updating foundation model into the mix is a recipe for regulatory chaos. But hey, 'accuracy and reliability' are being improved, so who needs clinical trials when you have a press release? Nvidia's CEO Jensen Huang probably already has a slide deck ready for the next earnings call, forecasting a multi-trillion-dollar 'healthcare AI opportunity' that somehow never seems to improve patient outcomes, only GPU sales.

Ah, Arthur Mensch, Mistral's CEO, has graced us with his vision: the company is 'exploring designing its own chips,' because what every AI startup needs is a side hustle in hardware. Because software alone wasn't burning cash fast enough, let's add semiconductor R&D — a sector famous for quick wins and cheap fab costs. Mensch also noted that 'Europe is starting to be looking at AI as a strategic asset,' which is a bit like saying a man adrift at sea is starting to consider a lifeboat as a strategic asset. The EU's AI Act is still stumbling through enforcement, but sure, strategic asset — just don't ask how many Mistral models are actually deployed in European governments.

Mensch's comments on 'agentic AI' — the latest buzzword to replace 'autonomous agents' — signal that Mistral is chasing the next hype cycle. The chip exploration is particularly rich: Mistral, a software company, thinks it can out-Intel Intel? Maybe they'll design a chip that runs on pure European regulatory approval.

And enterprise adoption? Mensch is bullish, but let's be real: most European companies are still trying to figure out if AI can write a decent email. The strategic asset talk is nice for Brussels cocktail parties, but when the rubber hits the road, Mistral is still a distant third in the frontier model race.

Ah, Mistral AI is at it again — the French startup that positions itself as Europe's great AI hope is reportedly raising €3 billion at a €20 billion valuation, nearly doubling its previous worth. Because nothing says 'responsible AI development' quite like a valuation that's grown faster than the number of actual users. The company, whose flagship model Mistral Large still struggles to outpace GPT-4 in meaningful benchmarks, is now worth more than most legacy tech firms. One must admire the sheer chutzpah: raise billions, deliver middling performance, and have investors throw more money at you because 'Europe needs a champion.' The subtext is clear: the only thing cheaper than euros is due diligence.

The €20 billion price tag — roughly the GDP of a small island nation — is a bet that Mistral's open-source ethos will eventually pay off, despite mounting evidence that open models leak capabilities to bad actors and create regulatory headaches. But who cares about safety when you can chant 'AI sovereignty' and watch the VCs swoon? The math doesn't add up, but when has that ever stopped a funding round?

This is a textbook case of the AI bubble's second act: companies that haven't proven product-market fit get absurd valuations because investors are terrified of missing out. Mistral's new round, if it closes, will be a monument to groupthink. The company's CEO, Arthur Mensch, will likely give a speech about 'democratising AI' while sitting on a mountain of cash that could have funded actual safety research. But that's not the point. The point is that the party continues, and the hangover will be spectacular. Cheers, Europe.