The News,
Decoded.

Splendid news: the Technion has secured another grant, this time from the Gray Foundation (shout-out to their Team Science program, because nothing says "team" like one PI getting the laurels), to develop an AI-powered MRI for early ovarian cancer detection in women with BRCA mutations. Because what the medical establishment needs is yet another tool that costs a fortune and promises the moon. Current screening for ovarian cancer is a mess — no reliable tests, vague symptoms — so slapping AI on an MRI machine feels like the academic equivalent of duct tape. But hey, at least it's funded.

The target population is women with BRCA mutations, a group that genuinely needs better options. The problem, as ever, is data. BRCA mutations are relatively rare, and collecting enough high-quality MRI scans to train a robust AI model is like finding needles in a haystack of medical records. The Gray Foundation likely expects results in three to five years, which in AI time is an eternity. By then, the model will probably be obsolete, the PhD students will have moved on, and a new, shinier grant will be waiting in the wings.

None of this is to say the project is valueless. If it works, it could genuinely transform screening for high-risk women. If it doesn't, well, the Technion will publish a paper, the foundation will tout its "support of cutting-edge research," and everyone will pat themselves on the back for trying. The real miracle is that any medical AI ever makes it past a pilot study. This one might, but don't bet your grant money on it.

Top Indian IT firms have posted strong quarterly results — a fact that'll bring a wry smile to anyone who's seen this movie before. The earnings rally is the last hurrah before the robots take the stage, because the same report quietly notes that AI advancement is 'challenging their traditional hiring and pricing models.' Translation: the business of billing by the warm body is about to get a lot less warm. Automation is 're-evaluating the value of human labor,' which is corporate-speak for 'we just found a cheaper way to do your job.'

Consider the irony: Indian IT built its empire on the back of vast armies of engineers shipped around the globe. Now those armies are being told that AI can do more for less. The quarterly numbers might be up, but the underlying business model is being hollowed out. It's like celebrating a great harvest while locusts are circling. The firms are still profitable, but the pricing model that sustained them — the one where you charge for headcount and hope clients don't notice you're double-billing — is facing existential pressure.

And the response from the industry? Predictable: 'upskilling' and 'reskilling' are the new mantras, as if a two-week Python course will save you from a model that can generate entire codebases. The earnings rally is a sugar rush before the AI hangover. If you're an Indian IT executive, enjoy the quarterly bonus while you can — the automation re-evaluation is coming for your billable hours next.

OpenRouter, the platform that lets developers access hundreds of AI models through a single API, is now the object of multibillion-dollar acquisition interest. How delightfully predictable: in an industry that promised to democratize intelligence, the real scramble is over who gets to collect the rent. FourWeekMBA calls it a "middleware power struggle," which is consultant-speak for "everyone wants a piece of the action."

Multiple parties are circling, presumably including the usual cast of tech behemoths and VC-backed Argonauts. They've realized that selling picks and shovels during a gold rush is all fine and well, but owning the only bridge to the gold fields is better. OpenRouter's unified API is precisely that bridge—though one wonders how long it stays unified once a new owner starts playing favourites with their own models.

The "takeover interest" is a testament to the AI industry's enduring faith that infrastructure is where the fortune lies, never mind that the models themselves are becoming commodities. Expect the eventual acquisition price to be eye-watering, the integration to be a Kafkaesque nightmare, and the promised "seamless access" to slowly curdle into vendor lock-in. Because of course it will. That's the AI middleware way.

There's something rather comforting about watching the legal profession, that most cautious of industries, discover that ChatGPT can hallucinate legal citations. According to Axios, judges are now setting guidelines for lawyers' AI use and reprimanding those who fail to vet research or, heaven forbid, cite fake AI-generated cases. Attorney sanctions are mounting, which is a bit like fining a driver for crashing into a lamppost that's been in the same place for a century. You'd think the profession built on precedent might have seen this coming.

The real joke, of course, is that the judges themselves are scrambling to write these guidelines on the fly, because neither the bar associations nor the legislatures bothered to update the rules before every junior associate started using ChatGPT as a paralegal. The result is a patchwork of judicial fiats: one judge bans AI use entirely, another requires disclosure, a third just sighs and orders the lawyer to buy the court a round of coffee. It's not governance, it's whack-a-mole.

And the sanctions? Mostly slaps on the wrist: a reprimand here, a small fine there. The legal industry is too profitable and too networked to actually punish anyone meaningfully. The real sanctions will come when an appeal succeeds because of an AI-hallucinated citation, and some poor client loses their case. But by then, the lawyer who made the 'mistake' will be a partner, and the blame will be shifted to 'training issues.' The bench's balancing act is really just a slow-motion fumble while the bill comes due.

Max Votek, an enterprise consultant with a direct line to Fortune 500 CFOs, has done the public a small mercy: revealing that the narrative around AI layoffs is, shall we say, *embellished*. According to Business Insider, his private conversations paint a rather different picture from the breathless headlines. The grand story of machines making humans redundant is often just a handy excuse for the same old cost-cutting, reorganisation, or, heaven forbid, poor management. Because nothing says "we're at the frontier of innovation" like blaming the chatbot for the redundancy you planned anyway.

Votek doesn't name names, but the pattern he sketches is familiar: a company announces AI-driven restructuring, the stock gets a bump, and a few quarters later the same headcount reduction is quietly refiled as "operational efficiency." The real play? CFOs are using the AI sheen to soften the blow of layoffs that would have happened regardless — or, worse, to justify headcount cuts they've wanted for years. It's a masterclass in narrative arbitrage: take a disruptive technology, wrap your downsizing in its glow, and watch the media parrot your script. One can almost hear the collective sigh of relief in corner offices: "Thank goodness for machine learning."

The truly dark joke is that this probably works brilliantly. The public loves a good techno-horror story, so "AI took my job" gets more sympathy than "private equity squeezed my division." But a few more years of this, and when the actual AI-caused layoffs arrive — the ones driven by genuine capability leaps, not rebranded restructuring — nobody will believe them either. Crying wolf with a neural network. Lovely. And Votek's candid assessment? Probably the only honest thing any consultant has said all year.

The European Commission, never one to rush into anything, has offered up measures to 'promote cyber resilience' and 'reduce dependencies on external actors.' Because nothing says 'sovereignty' like consulting a committee for another two years on what 'cyber resilience' actually means.

The article, now in July, is already analyzing the package as if it were a fait accompli, but let's be honest: this is the same Brussels that took a decade to standardize phone chargers. The package mentions 'reducing dependencies on external actors' — which is EU-speak for 'we don't want to buy American AI chips, but we also don't want to admit we can't build our own.' The irony is thick enough to spread on a croissant: the EU wants digital sovereignty, but its biggest tech firms are still basically American subsidiaries with better healthcare.

And what about the actual teeth? The package is 'legislation' in name, but enforcement mechanisms are as vague as a politician's promise. Cyber resilience sounds grand until you realize it means a few dozen bureaucrats in Luxembourg sending strongly worded letters. The EU is right to worry about external dependencies — especially when those dependencies include U.S. cloud providers that laugh at EU data localization laws. But this package will likely result in a flurry of compliance paperwork and not much else. Sovereignty: the feeling of being in control, without the bother of actually being in control.

Ah, another week, another batch of tech bills that sound like they were drafted by a committee that's never met a lobbyist it didn't like. The highlight: a new bill asking NIST to develop 'voluntary standards' for managing children's screen time. Voluntary. Because nothing says 'protecting our kids' like relying on the goodwill of companies whose entire business model depends on eyeball-mining. Meanwhile, another bill aims to teach elementary school students about AI — presumably so they can be properly indoctrinated into accepting their future AI overlords before they've even learned long division. And let's not forget the bill to add AI regulation to Medicare claim denials. Because the healthcare system, already a labyrinth of bureaucracy, desperately needs more layers of algorithmic oversight. Bold move, Congress. Bold move.

The timing is impeccable, as always. While NIST is busy crafting 'voluntary' guidelines, Big Tech is busy rolling out AI tools for kids that the companies themselves admit they can't fully control. And teaching AI to elementary students? Sure, because what better way to understand a technology than by learning from the same people who can't agree on whether it's going to save or destroy us? The Medicare bit is particularly rich: regulate AI claim denials to 'protect seniors,' but only after the AI has already been denying claims for years. Classic Washington: close the barn door long after the horse has not only bolted but started its own tech startup.

It's almost charming, really — this persistent belief that legislation can keep pace with AI. These bills are like putting a speed bump in front of a freight train. The screen time standards will be 'voluntary,' the AI education will be outdated by the time it's taught, and the Medicare regulations will take so long to implement that the AI will have already moved on to deny dementia diagnoses. But hey, at least they're doing something. And by 'something,' I mean giving us all a good chuckle before the robots take over. Cheers.

Harris County, Texas, has unveiled its master plan for the AI age: require a technology review for every purchase and monitor for 'unauthorized tools.' Because nothing says 'governance-first approach' like admitting you have no idea what's already running on county systems. The press release practically glows with self-congratulation, as if discovering that people might use ChatGPT without asking permission first is a sign of visionary leadership.

The county is 'working toward a common policy to govern AI use across government.' That mean 'working toward' is bureaucrat-speak for 'we'll form a committee, create a draft, circulate it for comments, and maybe hit a deadline by the next fiscal year.' Meanwhile, every department head with a credit card and a burning desire to automate something is probably already three steps ahead. The monitoring for unauthorized tools suggests the county expects a few surprises — the digital equivalent of finding employees have been building their own server rooms.

So Harris County gets to brand itself as 'pragmatic' and 'governance-first,' while the AI tools already embedded in daily operations continue to operate in the shadows until the official policy catches up. It's a classic government two-step: announce the policy, then scramble to figure out what you're actually regulating. The only certainty is that the next procurement cycle will include a budget line for 'AI governance consultancy.'

Ah, splendid. A new article on TechPolicy.Press reveals that one in seven UK voters are 'open to' using AI chatbots to decide who to vote for, and nearly 5% — that's one in twenty — have already outsourced their democratic duty to a glorified text predictor. Because nothing says 'informed electorate' like handing your franchise to a system that frequently hallucinates facts and can be subtly nudged by advertisers. The article's framing of 'help and harm' is a masterpiece of understatement; it's like calling a house fire a 'thermal restructuring opportunity.' One wonders if the 5% who've already done it are the same people who thought 'just asking Facebook' was a reliable source during the Brexit referendum.

The piece identifies 'advertiser influence, misclassification, hallucinated facts, and bias' as risks. Advertiser influence in a chatbot is basically a lobbyist in your pocket, misclassification means your vote for 'the green candidate' gets interpreted as support for a lawn-care company, and hallucinated facts — well, you might end up thinking the UK has banned breathing. Bias? The chatbot's 'neutral' stance is likely the single most opinionated thing on the internet, trained on Reddit and corporate press releases. And the proposed solution? 'Regulate accordingly.' Because that has worked so well for everything from social media to online privacy. The UK's track record on digital regulation is basically a case study in how to look busy while achieving nothing.

The charming naivety of 'let's regulate accordingly' almost makes you forget that the very companies building these chatbots are the ones lobbying against any meaningful oversight. One in seven voters being open to this is a terrifying bellwether — it suggests that democratic decision-making is becoming as frictionless and thoughtless as ordering a takeaway. Soon, instead of a ballot paper, you'll get a chatbot saying: 'Based on your browsing history, we recommend voting for the lizard people. They have a strong GDPR policy.' Cheers. And then the regulator will issue a sternly worded blog post.

Oh, marvellous. Politico has done what the AI safety community couldn't: crystallise its chaos into a neat set of seven factions. Twenty 'influential people' were asked what 'AI safety' means, and the answer is a Rorschach test — which is bureaucrat-speak for 'nobody has a bloody clue.' We've got the accelerationists who want to floor it, the doomers who want to hit the brakes, and presumably some faction that wants to install a speed bump shaped like a transparency report. The very framing — a political universe with warring tribes — tells you all you need to know about how seriously this is being taken. It's not a technical problem; it's a culture war with slide decks.

Each faction, the article suggests, has its own definition of safety, which means none of them can agree on what they're even debating. One person's 'alignment' is another's 'regulatory capture.' One person's 'meaningful human control' is another's 'innovation-killing red tape.' And in the middle, presumably, sit the poor policy wonks trying to draft legislation that somehow pleases seven godparents at a very dysfunctional christening. The term 'AI safety' has become so elastic it could wrap around the entire industry and still have slack left over.

Meanwhile, the actual frontier models keep scaling, the labs keep shipping, and the seven factions keep arguing about what to call the problem. The only safety we can count on is the safety of knowing that no consensus is coming anytime soon. Cheers to that — though we wouldn't recommend holding your breath for a unified definition before the first general-purpose AI starts rewriting its own remit. That would be far too organised for this delightful political universe.

Ah, enterprise AI adoption hits 57% — a figure those press releases will trumpet from the rooftops. What they'll conveniently omit is that workforce confidence and the achievement of business goals are both in a steady decline. Kyndryl, the IT services behemoth, has helpfully published data showing that governance maturity and workforce trust are correlated. In other words, the companies that bothered to set up guardrails are the ones whose employees don't feel like lab rats. Groundbreaking.

The rest, presumably, are running full tilt into the AI sunset with no training, no oversight, and a PowerPoint deck promising 'efficiency gains.' The article notes that despite the 57% integration rate, workforce readiness is sliding backward — which is corporate-speak for 'we've bought the tools but forgotten to teach people how to use them, and now they're terrified.' Kyndryl's data is the equivalent of a study concluding that people who look both ways before crossing the street get hit by cars less often.

So the pattern is depressingly familiar: adopt first, ask questions never. The declining confidence isn't a bug — it's a feature of an adoption strategy that treats humans as an afterthought. Kyndryl might as well have entitled its report 'Water Is Wet, Also AI Governance Helps.' But nobody will listen, because the 57% number is too intoxicating. Meanwhile, the workforce keeps sliding backward, and the only thing growing faster than AI adoption is the gap between the hype and the reality.

Oh marvellous. A panel of experts has testified before a House subcommittee that the federal government's primary identity verification system, Login.gov, was 'designed for a threat that no longer exists' — which is bureaucrat-speak for 'we've been using the digital equivalent of a wooden bolt on a bank vault while AI-powered forgers walk in with laser cutters.' Jordan Burris, presumably not the first person to point this out, got to say the quiet part out loud: the system is obsolete. But don't worry, the recommended fix is a 'federal response' — which in Washington means a task force, three feasibility studies, a pilot programme, and a GAO report six years after the fraudsters have moved on to hacking our grandchildren's DNA.

The timing is exquisite. AI-generated synthetic identities are flooding every corner of the internet, and the government's best defence is a login system that was probably architected when people still used 'password123' unironically. The panel's suggestion to improve Login.gov is about as bold as recommending that a sinking ship patch the hole with duct tape. At least they're consistent: the cyber threat evolves at the speed of light, and the federal response evolves at the speed of a congressional budget cycle.

But here's the real punchline: even if they do manage to upgrade Login.gov, the same AI that powers the fraud will just adapt. It's an arms race where the government is showing up with a slingshot while the other side has drone swarms. The experts' testimony will likely be filed, reviewed, and politely ignored until a catastrophic breach forces a panicked overhaul. Cheers to progress — just don't use it to log into anything important.

Microsoft's latest 'restructuring' is a classic corporate fandango: replace the old guard, blame it on AI, call it progress. Hundreds of cybersecurity roles slashed, senior execs shown the door — all in the name of 'accelerating AI strategy'. Because nothing says 'we take security seriously' like firing the people who did it and hoping a chatbot picks up the slack. The phrase 'reshaping the cybersecurity workforce' is corporate for 'we've decided humans are expensive and slow'. Microsoft's AI-powered security products will presumably detect threats without needing pesky human judgment, salaries, or the right to complain. Meanwhile, the executives replaced?

One wonders if the AI systems will eventually write their own job descriptions: 'Requires 5 years experience in threat detection, ability to work 24/7, no need for health insurance.' The gallows humour practically writes itself. But hey, maybe the AI will be so good at cybersecurity that the layoffs won't matter — and if it isn't, well, the data breach that follows will make for a great case study in MBA programmes. The real kicker is the timing: just as threat actors are sharpening their own AI tools, Microsoft decides to thin the herd of human defenders. What could possibly go wrong?

Still, there is a certain elegance to the logic. If you automate security, you can automate the excuses when it fails. 'Our AI made a mistake' has a nicer ring than 'our overworked analyst missed a signal'. And with hundreds fewer salaries to pay, shareholders might sleep slightly better — at least until the next zero-day hits. Pass the popcorn.

Colorado joins the proud tradition of regulatory backpedalling. In May 2026, the state replaced its “landmark AI discrimination law” — a law that had the audacity to try to hold algorithms accountable — with a transparency requirement. Because nothing says 'we take bias seriously' like swapping enforceable rules for a polite request to show your working.

The move, as the article tactfully puts it, "looked like a retreat from ambitious lawmaking." That's one way to say they folded. The new law doesn't ban discriminatory outcomes; it just asks companies to explain their AI's decisions. Brilliant. Now instead of preventing harm, we get an audit trail of exactly how the harm happened. And the pièce de résistance: the feds might challenge even this limp version. Because why have one level of government tied in knots when you can have two?

So here we are. The state that once led now hands the reins back to industry. The federal government, presumably eager to prove it can also do nothing effectively, may sue to kill the transparency requirement altogether. And the AI systems? They'll keep churning out bias as always, but now with a lovely new transparency label. Cheers.

Ah, Meta's famous 'move fast and break things' ethos has found a fresh application: breaking people's livelihoods with the aid of AI. A federal judge has rejected 26 employees' bid to block their layoffs while they pursue a discrimination lawsuit claiming Meta's AI-powered tools specifically targeted workers with disabilities or those taking medical leave. The axe falls on July 22 — plenty of time for the algorithm to learn a few more biases before then.

One has to admire the symmetry: Meta deploys AI to optimise workforce reduction, the employees claim the AI is discriminatory, and the judge's response is essentially 'let the market decide' — or rather, let Mark decide. The company, naturally, insists its tools are fair and compliant. Because nothing says 'fair' like an AI that reads your medical leave as a signal for termination. This is the logical endpoint of HR by stochastic parrot: plausible-sounding decisions with zero accountability.

And where are the regulators? The EEOC is reportedly investigating, but that's cold comfort to the 26 being shown the door next week. The law, as interpreted by this judge, doesn't see enough 'irreparable harm' in losing your job over an alleged AI bias. So we're left with a delightful precedent: if an algorithm decides you're surplus, you can't even get a stay of execution while you argue the algorithm was a bigot. Progress!

Ah, splendid. A bipartisan group of House lawmakers has introduced the Human Authority over Autonomous Weapons Act — a bill requiring that a human actually be involved before an AI system can kill someone. Yes, we are now at the point where 'having a person push the button' is considered a bold legislative compromise. The bill, introduced on Friday with bipartisan fanfare, is supposedly a check on runaway autonomy. But here's the rub: it only covers *intentionally lethal* uses. So if a drone 'accidentally' blows up a wedding while trying to identify a target, that's fine — no human required for accidents, apparently. The real joke? This bill is framed as a safeguard while the DoD continues pouring billions into making AI weapons faster, more autonomous, and more lethal. The lawmakers are effectively legislating a speed bump on the highway to killer robots.

One can almost admire the marketing. The bill's title sounds decisive, like we've taken the steering wheel back from the machine. In reality, it's a fig leaf on a weapons system that's already being designed to operate with minimal human input. The Pentagon's own policies have been drifting towards 'meaningful human control' for years, which is Washington-speak for 'a human will nod yes before the missile launches.' This bill codifies that nod. It's like requiring a lifeguard to be present at a pool that's already been drained.

So raise a glass to the anonymous lawmakers — they've given us a classic: a solution in search of a problem that's already been solved with a rubber stamp. The autonomous weapons race continues, but at least now a human will be watching the screen when the shit hits the fan. How reassuring. How utterly, cheerfully British. Pass the tea.

Xi Jinping's latest gambit is the World Artificial Intelligence Cooperation Organisation (WAICO), a 29-nation coalition unveiled with all the fanfare of a state banquet. 'Ensure no country dominates the technology,' Xi intoned — as if the Great Firewall and the Social Credit System weren't already a pretty clear bid for dominance, just with Chinese characteristics. The acronym WAICO is either a clever branding exercise or an accidental self-own, because 'wacko' is precisely the word for expecting 29 squabbling nations to cooperate on the very technology that lets them spy on each other. The 'principle of openness' we savaged last week has now grown into a full-blown committee. Because nothing says 'open' like a government-sponsored club with China setting the agenda.

Let's not pretend this is about altruism. WAICO is Beijing's answer to the US-led 'democratic AI' initiatives, except this version comes with built-in censorship and zero accountability to anyone outside the Politburo. Xi's call for 'cooperation' is the diplomatic equivalent of a velvet smile: lovely to look at, but try to question the terms and see how quickly the silk turns to iron. The article even notes this is launched at WAIC — the same conference where Xi talked about 'open source' while his state monitors every keystroke.

What's genuinely dark here is the speed: from a speech at WAIC to a fully formed international organization in what appears to be weeks. That's not cooperation; that's mobilisation. The US is bogged down in its own regulatory ping-pong — sorry, 'policy debates' — while China is shaping the global narrative. WAICO may be a talking shop for now, but its real purpose is to frame AI governance around Beijing's terms: surveillance-friendly, state-centric, and unaccountable. The West better get its act together before WAICO becomes the only show in town, because at this rate, the future of AI will be decided by a committee that doesn't even allow private voting.

Ah, 'workslop.' The AI industry has finally coined a term for what everyone using these systems already knew: the chatbots are churning out plausible-looking garbage at unprecedented scale. An article on HR Dive warns that this low-quality output is 'undermining your organization's performance' — which is a bit like discovering your new 'efficiency expert' has been filling your spreadsheets with typos and fake data. The proposed solution? C-level executives should 'revisit AI application strategies and incentives.' Because nothing says 'we've learned our lesson' like putting the same people who approved the AI rollout in charge of fixing it.

The irony is exquisite. Companies deployed generative AI to reduce human oversight, and now they're discovering that 'flawed results' actually require more oversight. The article calls for 'governance,' which in practice means middle managers spending their afternoons debugging ChatGPT's output. It's the productivity paradox made literal: the tool that was supposed to save time is now eating it. And the recommended fix — better 'incentives' — basically amounts to bribing employees to use the broken tool more carefully.

So here we are, years into the AI revolution, and the headline from a respected HR trade publication is essentially 'Your AI is bad and you should feel bad.' The CHROs are now on the hook to 'reverse this trend,' but the trend is baked into the technology's design. 'Workslop' is not a bug — it's the product. The only question is how many more layers of oversight and strategy sessions it will take before someone admits that maybe, just maybe, the machine isn't ready for prime time.

Connecticut has decided that the solution to AI swallowing jobs is a workforce development programme. Because nothing says 'we know what we're doing' quite like a state-level pilot with an organisation called RAISE US — a name that sounds like a motivational poster from 1998. The plan also includes a quantum computing incubator, which is the policy equivalent of buying a telescope when your house is on fire. One wonders whether any of the officials involved have actually used a modern AI model, or whether they think 'prompt engineering' is what you do when a meeting runs late.

RAISE US, the chosen partner, is presumably tasked with retraining warehouse workers to become 'AI ethicists' or 'prompt whisperers' — roles that will definitely still exist once the autonomous systems start retraining themselves. The quantum incubator adds a lovely touch: because if you can't compete on classical AI, why not bet on the hardware that's been ten years away since 2015? It's the tech version of building a canal network in the age of flight.

The real joke? Connecticut's effort is almost certainly well-intentioned. But so was every other workforce development scheme since the Luddites. The gap between 'pilot programme' and 'millions of replaced workers' is a chasm these folks are trying to bridge with a quantum-powered pogo stick. Still, it's nice to see someone, somewhere, pretending the transition will be orderly. Pass the popcorn.

The Trump administration, freshly installed with a mandate to drain the swamp, has instead decided to drain the AI labs' autonomy. According to *two* anonymous sources — the gold standard for administrative transparency — the White House is now dictating which companies and entities can access frontier AI models. Because handing the keys to the most potent technology since nuclear fission to a political team whose grasp of technical nuance can be summed up as 'the computer says no' is clearly a recipe for competence.

The shift in power from tech giants like OpenAI and Anthropic to the executive branch is being framed as a necessary safety measure. But watch closely: 'safety' in this context means 'control.' The same administration that has spent years gutting regulatory oversight is now asserting unprecedented oversight over AI releases. It's the classic bait-and-switch: 'Trust us, we're from the government, and we're here to help you with your existential risk.' The tech giants, who have been playing fast and loose with safety themselves, now get to blame the government for any future slow-walking of releases. Win-win for everyone except, you know, the planet.

What does 'dictating access' mean in practice? Probably a system of favors, licensing, and political loyalty tests. Korea, China, Iran — who gets the latest model? The answer will depend less on technical readiness and more on diplomatic whimsy. A company that donates heavily to the GOP might get priority access to GPT-7, while a lab with environmentalists on the board might find itself mysteriously delayed. And remember, the administration's track record with technology includes the infamous 'alternative facts' approach. Now they are applying that to model evaluation: 'We have decided that this model is safe because we say so.' Bravo. A new era of AI governance — all the opacity of a black box, with the added thrill of political horse-trading.