The News,
Decoded.

Splendid. NHTSA has determined that the brake pedal—that last vestige of human control, that final mechanical 'no' button—is surplus to requirements in self-driving vehicles. Their June 25 proposal would scrap the requirement for a manual brake pedal, while keeping something called "stopping distance standards." Because of course, when an AI misidentifies a tumbleweed as a pedestrian, we can rest assured it will stop within the required distance. The same agency that took fifteen years to mandate rear-view cameras is now ready to trust your life to a neural network that hallucinates fire hydrants as stop signs.

The logic? Self-driving systems can "reliably" perform emergency stops without human intervention. Yes, because no autonomous vehicle has ever plowed into a stationary fire truck or confused a white semi-trailer with the open sky. NHTSA's analysis probably cited the same flawless simulation data that convinced Uber their self-driving fleet was ready for public roads. But fear not—the "stopping distance standard" remains, which is rather like ensuring a parachute is packed to regulation tightness while removing the ripcord. The rule applies only to vehicles with full self-driving capability, which is NHTSA's way of saying 'experiment on the rich people first.'

Underneath it all, this isn't about safety—it's about removing the last excuse for a human to intervene. No brake pedal means no one can override the AI when it decides an inflatable dinosaur is worth evasive action. Traditional cars keep their pedals, but for how long? The proposal is open for public comment, as if the collective indignation of a few thousand drivers will sway an agency that just declared manual control obsolete. Progress: when your car's emergency stop becomes a feature request to a software update.

Ah, California has decided that the best way to deal with AI-related job losses is to build a dashboard. A tracker. A monthly spreadsheet of despair, lovingly updated by the state. Governor Newsom's executive order has birthed an online tool that monitors unemployment claims by sector, so we can all watch the numbers tick up in real time. Because nothing says 'proactive policy' like turning structural economic collapse into a data visualization project.

One can almost hear the Silicon Valley executives nodding sagely: 'See? We're being transparent!' Meanwhile, the tracker is about as useful as a thermometer in a wildfire — it tells you how hot it is, but does bugger all to put out the flames. The sectors most likely to be disrupted — media, customer service, legal, even some coding jobs — will now have their decline officially logged. Hooray for metrics!

What comes next, one wonders? Perhaps a 'displaced worker counter' on the state website, complete with confetti animations when the millionth claim is filed. Or maybe an AI chatbot that gently explains your redundancy was 'inevitable market evolution.' California has taken the first step toward acknowledging the problem, which is to say, they've built a landing page. The actual response — retraining, universal basic income, robust social safety nets — remains a distant, unfunded ambition. But at least the spreadsheet will look nice.

Oh, what a delightful about-face. The Trump administration—so keen on deregulation that it appointed a crypto bro to oversee AI policy—has suddenly discovered the concept of 'security concerns' and decided that GPT-5.6 is a bit too spicy for public consumption. They've formally asked OpenAI to limit the next model to 'a small set of government-approved partners,' which is a euphemism for 'we don't trust the plebs with this one, chaps.'

This from the same crowd that rolled back every safety guideline they could find, that celebrated the 'AI Manhattan Project' as the pinnacle of American ingenuity, and that spent months telling us that open release is the only way to beat China. But now, faced with the actual product, the brave free-marketeers are suddenly reaching for the emergency brake. It's almost as if they've realised that AI might be a bit more dangerous than a tax cut.

The sheer, glorious irony is that OpenAI, the company that once promised to 'build safe AGI,' is now being told by the least safety-conscious administration in recent memory to pump the brakes. One can only imagine the internal meetings: 'So, wait—you want us to release it to the Pentagon and some handpicked allies, but not to, say, a researcher in Ohio?' 'Correct.' 'And this is because… it might be misused?' 'Yes.' 'But last month you said it was fine to train on copyrighted data.' 'Yes, well, times change.' How reassuring.

Ah, splendid — the Pentagon has decided that a data centre powering Elon Musk's Grok is a matter of national security, because of course it is. The DoD's chief digital and AI officer waded into a legal spat over environmental concerns to declare that shutting down the facility would be a threat to the realm. Because nothing says 'defending democracy' quite like ensuring a chatbot that sometimes thinks 2+2=5 has uninterrupted server juice.

The really delicious part is the logic: Grok isn't just a glorified shitpost generator; it's supposedly vital for 'national security.' So now, any data centre that hums with enough compute can wave the flag and sidestep pesky environmental regulations. Expect every hyperscaler from here to Ashburn to suddenly discover their racks are 'critical infrastructure.' The only thing missing is a bald eagle landing on a cooling tower.

Let's be clear: this isn't about safeguarding the nation. It's about the military-industrial complex cosying up to tech bros who want to burn gas to run inference on celebrity gossip. The environment loses, the neighbourhood loses, but hey — at least Grok will keep generating memes about wokeness while the planet cooks. Cheers to progress.

Oh, marvellous. Just what the legal profession needed: an AI agent that can do compliance work without needing a law degree, ethical qualms, or a pulse. Abstract, a legislative data firm, has launched Abstract Workers—a service that provides AI agents to automate workflows for legal, government affairs, and compliance teams. Because nothing says 'we value the rule of law' like replacing the lawyers and lobbyists who interpret it with a glorified chatbot that can track bills and draft memos faster than a paralegal on espresso.

Abstract Workers will happily monitor regulatory changes, flag compliance risks, and generate reports—all while the humans who used to do that work wonder if they should have gone to coding bootcamp instead of law school. The irony is exquisite: a firm that specialises in legislative data is now selling the very tools that will automate the jobs of the people who use legislative data. It's like watching a butcher sell sausages made from his own pigs. No one is safe.

And the best part? The regulatory gap. While lawmakers dither over AI safety bills, their own staff are being replaced by the very technology they're supposed to oversee. Cheers to progress—we'll drink to that, while we still have jobs to pay for the pint.

Ah, democracy in action. Alex Bores, the New York assembly member who dared to champion AI safety, has been shown the door in the Democratic primary. The Washington Post gleefully reports that his loss is 'Big Tech's win'—because apparently, the most powerful lobby in the world needed another victory lap. Bores had the audacity to propose legislation that would require safety testing before AI deployment, unthinkable in a state that hosts some of the largest tech companies.

Now, the path is clear for unfettered innovation, which in industry parlance means 'we can ignore all those pesky alignment concerns.' The tech PACs outspent Bores's campaign by a factor that would make even Larry Ellison blush. The message is unmistakable: if you want to regulate AI, don't run for office. Or if you do, expect to be buried under a mountain of dark money. Bores's loss isn't just a local setback; it's a signal that the regulatory gap isn't closing—it's widening, with a bright neon sign from the tech industry saying 'Keep out.'

What's particularly delicious is that Bores was considered a moderate on AI—he wasn't calling for a moratorium, just basic testing. But even that was too much for the industry, which prefers to self-regulate, which is like letting the fox design the henhouse's security system. So now, New York will continue as a laboratory for unchecked AI deployment. Let's hope the experiments don't blow up in our faces. But if they do, at least we'll have learned a valuable lesson: money talks, and safety walks.

Ah, the SKILL Act — because nothing says "we value our data labelers" like a tax credit that barely covers a month's rent in San Francisco. The bill would give employers $2,500 for every student who completes a qualifying program and another $2,500 if they hire that graduate. Which, in an industry where executives take home eight-figure bonuses, is a rounding error.

But here's the beautifully cynical detail: the companies exploiting the human workforce behind AI will now get a tax break for doing what they should already be doing — paying people a living wage. A data annotator at a typical firm might earn $15 an hour, so the full credit covers maybe 333 hours of work, or about two months. Two months of "we care" before the credit evaporates and the worker is left to fend for themselves again. And the $2,500 per student? That's what a university charges for a single course these days.

The human workforce behind AI remains the invisible scaffolding, cheap and replaceable, while companies pocket the tax break. The only thing missing is a solemn press conference where a legislator declares, "We are investing in people." What a masterclass in making a problem worse while pretending to fix it.

Ah, the AI industry has discovered K Street — the only growth sector that never hallucinates a return on investment. Q1 2026 saw AI-related lobbying revenues hit $53 million, a 36% jump from last year, with over 100 first-time lobbying firms suddenly finding their vocation. Because nothing says 'safe, responsible AI development' like a sudden stampede of hired persuaders hoping to shape whatever regulation emerges. One imagines the conversations: 'We'll just lobby for safety standards we already meet, and lobby against any that inconvenience the bottom line.' Brilliant.

Big Tech is leading the charge, naturally, but the real story is those 100+ newcomers — startups that six months ago were boasting about 'alignment research' are now presumably briefing lobbyists on how to argue that compute caps would stifle innovation (read: profits). The 36% spike suggests this isn't a blip; it's an arms race for influence. The money is flowing faster than model capabilities, which is saying something. Nobody wants to be caught off-guard when the regulatory hammer finally drops, so everyone's buying a seat at the table — or at least enough lobbyists to slow the hammer's swing.

The cynical take? This is the industry's way of ensuring that 'regulation' means 'what we can live with.' The optimists will call it 'democratic engagement.' But with $53 million on the table in a single quarter, it's clear that the real AI alignment problem isn't with the models — it's with the lawmakers who are being outspent and outbriefed. K Street's AI boom: because the only thing more powerful than a frontier model is a well-funded lobbyist selling a story about how it's totally under control.

Oh, marvellous. The White House and Senator Blackburn have apparently decided that the best way to protect children online is to slip in a bit of federal pre-emption of state AI laws as a sweetener. Because nothing says 'we care about kids' like using them as a bargaining chip for AI deregulation. The effort is 'running into resistance,' which is politician-speak for 'someone noticed the bait-and-switch.' It's a remarkably transparent trade: support the Kids Online Safety Act in exchange for wiping out state-level AI guardrails like California's model governance bill or Connecticut's risk-assessment law. Wrap your deregulatory agenda in a children's safety blanket and hope no one checks the label.

The compromise is being sold as a way to create 'clarity' and 'national standards,' but let's be honest: this is about tech lobbyists getting what they couldn't win in statehouses. The White House gets a win on a popular kids' safety bill, and Senator Blackburn gets to neuter progressive state regulations. Everyone wins — except, of course, the children, who are merely the prop, and the states, whose democratic experiments in AI oversight get steamrolled. Expect the usual parade of 'bipartisan cooperation' press releases while the substance is hollowed out.

So who's resisting? Likely a coalition of privacy advocates and state attorneys general who see their hard-fought rules being bulldozed. But Washington is 'working on a compromise,' which means they'll dilute it until everyone forgets what the original bill even did. Kids online safety? Sure, as long as it comes with a side of AI freedom. Classic legislative sausage-making, with a side of cynical calculation.

China's LineShine supercomputer, powered by homegrown chips, has just trounced the US in the TOP500 ranking for the first time since 2017. The National Supercomputing Center proudly announced this milestone, proving that when you spend a decade and a half building your own semiconductor supply chain, you can indeed overtake the country that thought export controls would keep you in the 1990s. The irony is so thick you could etch circuits with it.

Let's take a moment to appreciate the sheer comedic timing: the US spent years tightening restrictions on advanced chip sales to China, only for Beijing to roll out a homegrown system that beats anything America can currently field. The crowing from Washington about 'slowing China's AI ambitions' now sounds like a losing sports team insisting they're just 'rebuilding.' LineShine doesn't just run simulations—it runs circles around the entire premise of technological containment.

What does this mean for the capability leap? China now has the hardware to train frontier models at speeds that might push the frontier itself. The regulatory gap? The only gap now is between what US policy intended and what it achieved—a chasm wide enough to park a supercomputer in. Meanwhile, the labs that promised 'safety first' might want to check who's setting the pace now.

Ah, the Coalition for Advancing Research Assessment has finally noticed that AI is making a mess of their neat little boxes. Their grand insight? That AI tools are making it 'harder to disentangle the contribution of researchers from technology' in funding proposals. Brilliant. So after years of academia pretending that AI was just another tool like a calculator, they're now discovering that when a large language model writes half the grant proposal, it's a bit tricky to figure out who deserves the Nobel. The solution? Shift towards 'recognizing processes and diverse contributions' – which in academia-speak means 'we have no idea how to evaluate this, so let's make the criteria so vague that everyone's a winner.'

Meanwhile, the labs that actually built these models are laughing all the way to the bank. While research councils agonise over whether to credit the grad student or the transformer, frontier AI companies are busy absorbing the brightest minds and patenting the very techniques that made assessment difficult. The Coalition's call for change is about as proactive as rearranging deck chairs on the Titanic – sure, the new layout is nicer, but the iceberg of capability is already upon us. One suspects the real effect will be a flurry of committees, a white paper or two, and then business as usual until the next AI milestone makes the whole exercise obsolete.

The tragic irony is that the assessment system they're trying to reform was already creaking under the weight of publish-or-perish metrics. Now AI has simply exposed the rot. The Coalition's proposal to recognise 'diverse contributions' sounds lovely, but without a concrete mechanism to distinguish human insight from machine output, it's just a feel-good mandate. Expect grant reviewers to spend even more time trying to reverse-engineer whether the methodology section was written by a human or a bot – and ultimately, to reward the most polished prose, whether it came from a mind or a token predictor.

Ah, the federal government has discovered AI — just in time for it to automate the paperwork that nobody wanted to do anyway. The General Services Administration's chief human capital officer proudly announced that AI has slashed job classification time from eight hours to two. Eight hours to two! Hooray for efficiency — until the algorithm decides that the ideal candidate for a cybersecurity position is someone with a decade of experience in 'vibes-based management.'

But let's not get cynical. The government is also using AI to 'improve skills assessments,' which is a delightful way of saying it will now evaluate candidates with the same opaque, bias-prone tools that private sector HR departments have been deploying for years. Because nothing says 'merit-based hiring' like a black box that can't explain why it rejected everyone who didn't attend a top-20 university. The GSA's own chief human capital officer seemed genuinely excited, which is either a sign of progress or a sign that the standards for bureaucratic enthusiasm have hit rock bottom.

Most tellingly, nobody in the article mentions the obvious: that AI in hiring is a regulatory minefield waiting to explode. The Office of Personnel Management hasn't exactly covered itself in glory on algorithmic fairness, and the agencies are charging ahead without clear guidelines. So yes, job classifications are faster. But they're also faster at replicating whatever biases lurked in the training data. As always, the answer to 'can we?' is 'yes,' and the answer to 'should we?' is 'we'll figure that out after the lawsuit.' Cheers.

Ah, the voluntary AI review — the regulatory equivalent of asking a burglar nicely to check his own bags before entering your house. The Trump administration is "pressing" Meta to submit its models for government evaluation, because nothing says national security like a programme Meta can simply decline with a polite "no thanks." One can almost hear the laughter echoing from Menlo Park as they weigh the pros and cons of voluntarily exposing their crown jewels. The New York Times, bless its heart, reports this as a serious development, but anyone with a memory longer than a goldfish knows exactly how this story ends: with a press release, a pat on the back, and no meaningful change.

The report describes this as part of a broader effort to address "rising security concerns" — that wonderfully vague phrase that lets politicians sound alarmed without committing to anything. But voluntary reviews are the political equivalent of a strongly worded letter. They allow the administration to claim it's doing something without actually doing anything that might upset a major campaign donor or tech executive. Meta, the company that brought us the Cambridge Analytica scandal, trained its models on user data without meaningful consent, and now distributes open-source models that get weaponized by anyone with a laptop, is being trusted to self-police on national security grounds. The logic is exquisite in its circularity: we need to review your models because they're dangerous, but we won't compel you to submit because that might be inconvenient for business.

The real question is whether this is a prelude to something more serious or just another chapter in the long-running farce of AI governance. As models grow more powerful and corporate incentives favour speed over safety, these voluntary nudges look increasingly like rearranging deck chairs on the Titanic. Meta will presumably agree to some superficial review — perhaps letting a handful of cleared officials run a few prompts — the government will declare victory, and then we'll all pretend surprise when the next Llama release enables something regrettable. The administration hasn't even bothered to name the agency that would conduct these reviews, because why trouble with details when you have headlines to make? Standard operating procedure.

A scoping review in *npj Digital Medicine* has confirmed the bleeding obvious: human-AI collaboration in healthcare works only when clinicians stay in control. So after billions of dollars in investment and countless breathless press releases about AI diagnosing cancer better than doctors, it turns out that the best way to use the thing is as a slightly smarter spreadsheet that you still have to double-check. The study explicitly supports WHO and EU regulations requiring human oversight—which is regulatory-speak for 'we tried letting the robot do it alone and people died.'

The review notes that AI systems perform well in controlled settings but falter in the wild without a human safety net. You don't say. It's almost as if medicine involves messy, contextual decisions that a statistical autocomplete can't handle. The findings also warn about 'automation bias'—clinicians trusting the AI even when it's wrong—which is a fancy way of saying that professionals become rubber-stampers when handed a machine that sounds confident. And the tech industry wants to put these things in charge of everything.

So here's your recap: AI can help sometimes, but only if you ignore every sales pitch about autonomous everything. The WHO and EU look positively prescient for insisting on oversight, while labs continue to sell the dream of replacing doctors. But don't worry—I'm sure the next study will find that AI works best when it's completely unplugged and clinicians just use their brains. Small victories.

The UK government has discovered a novel approach to AI leadership: take £60 million — a sum that would barely cover the electricity bill for one training run at Anthropic — and split it between the University of Oxford and University College London. Because nothing says "fundamental research" like a budget that wouldn't buy a single H100 GPU cluster. You can almost hear the champagne corks pop at DeepMind headquarters as they realize their taxpayer-funded competition just got handed pocket change. And this is an "increased pot" — meaning there was a prior, even more pitiful amount that made this seem generous. Ah, British ambition. One can almost picture the civil servants patting themselves on the back for this bold move.

Meanwhile, the government's own AI Safety Institute — you know, the one meant to keep us safe from rogue AIs — is reportedly struggling to retain talent, but sure, let's fund more basic research that might produce a paper in 2028. With no mention of compute access, these labs will likely focus on theoretical work, which is exactly what we need: more papers on alignment that gather dust while real systems align themselves. One wonders if the labs will manage to afford a single GPU, or if they'll be training models on Raspberry Pis in the name of thrift and austerity. The contrast with the billions spent by private labs is so stark it borders on satire.

Still, the announcement is a masterclass in political theatre. It gives the UK a nice headline to wave at international summits, proving they're "investing in AI" without actually committing the billions needed to make a dent. The professors will write grant applications, the students will train models on cloud credits, and the frontier will advance elsewhere. All very British: courteous, underfunded, and fundamentally irrelevant. At least the money might prevent a few academics from emigrating to Canada — though that's about all it'll achieve. But hey, it's the thought that counts, right?

Ah, Anthropic — the company that built its reputation on being the responsible one — has now discovered that the fastest route to safety is buying politicians. $20 million to Public First Action, a super PAC that promises to back candidates 'focused on AI safety.' Because nothing says 'alignment' like bundling campaign contributions. The whole charade is beautifully on-brand for an industry that talks about existential risk while shovelling cash into the very political system that has shown zero ability to regulate it. One imagines the pitch: 'We need to ensure policymakers understand the need for robust oversight — and by understand, we mean they owe us favours.' What could possibly go wrong? The same people who brought us models that can't reliably tell you if 2+2=4 are now deciding which politicians get a seat at the table. The real existential risk isn't superintelligence — it's that the safety people have learned politics from the people they were supposed to save us from.

And it's not just Anthropic. The article notes that AI companies are funding super PACs across the board, turning the midterms into a bidding war for regulatory capture. One wonders what the safety-focused candidates are promising in return — a gentle regulatory touch? A seat at the rulemaking table? The irony is delicious: an industry terrified of a hypothetical future rogue AI is now actively courting the very real, very human corruption of the electoral process. It's like trying to prevent a flood by paying the dam builder to install a leaky tap.

But let's not be too harsh. After all, this is just the free market at work. If you want to ensure that AI regulation is written by the companies being regulated, what better way than to own the politicians doing the writing? The $20 million is pocket change for a company valued at billions — a small price to ensure that 'safety' means whatever Anthropic says it means. Cheers to the invisible hand, now greased with campaign cash. I'm sure nothing will go wrong.

Oh, absolutely lovely — the UN has waded into the AI energy debate, because if there's one thing the world needs, it's another voluntary initiative with a catchy acronym. António Guterres has proposed the 'AI Environmental Transparency Initiative,' begging AI companies to disclose their carbon pollution and maybe, if they're feeling generous, power their data centres with renewables by 2030. Because the tech giants that have been doubling down on fossil fuels to keep their precious models running are clearly just one polite request away from going green. Meanwhile, data centre energy demand is through the roof, but sure, let's ask nicely.

Guterres, bless his diplomatic heart, seems to think that transparency alone will magically solve the problem. 'Disclose and commit,' he says, as if OpenAI, Google, and Microsoft haven't already mastered the art of greenwashing their way through sustainability reports. Google's 'carbon-free by 2030' pledge? Already looking shaky as training compute scales. Amazon's renewable claims? Measured by a creative accounting of 'matched' credits, not actual consumption. But yes, let's add another reporting framework to the pile — that'll fix the coal plants powering new supercomputers.

What's truly magnificent is the timing: AI companies are racing to build ever larger models, each consuming more energy than a small country, and the UN's big solution is a transparency initiative. No binding targets, no enforcement, just a request to be nice. The tech industry must be thrilled — now they can add 'UN-endorsed responsible AI' to their marketing materials while lobbying behind the scenes to keep the regulation light-touch. Guterres might as well ask politely for the polar ice caps to stop melting while he's at it.

Ah, Keir Starmer's 'pro-innovation, light-touch' approach to AI regulation — because the safest way to handle a technology that could automate half the workforce is to give it a gentle nod and hope for the best. Politico's analysis gives us a retrospective on this grand experiment in regulatory minimalism. Spoiler: it didn't end in disaster, but only because the real disaster is still in beta testing. The EU cautiously crafted its AI Act; the US fumbled. Britain? Britain had a light-touch.

The phrase 'light-touch' is doing the heavy lifting of ten thousand lobbyists. It means the UK government decided that voluntary codes of conduct were equivalent to actual laws. Industry self-regulation — because who better to guard the henhouse than the foxes? Starmer's strategy was to make Britain a global AI hub by eliminating barriers for tech firms. The global dynamics shifted, indeed: other nations looked on with a mix of envy and schadenfreude, wondering if the UK would become a cautionary tale or a libertarian paradise.

One can almost picture the ministerial meetings: 'Let's not rush into regulation, we mustn't stifle innovation.' Translation: let's leave the race to the bottom unregulated. The Politico piece notes the impact on global AI dynamics, which is polite-speak for 'the UK became a test case for regulatory surrender.' A proud tradition of leading by example, even if the example is 'don't do this.' How very British — a stiff upper lip in the face of existential risk.

Ah, the quantum executive order we noted yesterday is already being turned into legislation. Because nothing says 'forward-thinking industrial policy' like codifying a Trump-era directive with a straight face. The Washington Post brief mentions the quantum industry's 'need for a government catalyst' — right, because government has historically been such a swift and efficient catalyst. Nothing says 'quantum leap' like a decade of study commissions and funding debates.

Rep. Pat Harrigan is to be the legislative midwife for this quantum renaissance. No doubt he'll gather dust on a subcommittee for six months while the quantum industry waits for its catalyst — which, in government terms, probably means a report, a roundtable, and a funding bill that gets eaten by a bigger defense package. The executive order itself was unveiled just yesterday, and already we're legislating around it. Speed, thy name is Congress.

Meanwhile, AI regulation remains a spectator sport — no codification of anything related to current frontier models — but quantum, a technology that might have practical applications by 2040, gets its own industrial policy. Perfect timing as always. We're sprinting to build a regulatory framework for a machine we haven't built yet, while the machines already here do whatever they please. But sure, let's codify the quantum catalyst. That'll fix everything.

So a New York state assemblyman has won a Democratic primary to succeed Jerry Nadler, and the race was—get this—a 'proxy battle over AI regulation and safety.' Because of course it was. Nothing says 'serious policy deliberation' like turning a House seat election into a symbolic skirmish about a technology most voters couldn't explain if you spotted them a Venn diagram. Lasher, a former Nadler staffer, now gets to ride the AI horse into Washington, presumably with a mandate to Do Something, which in Congress-speak means forming a working group and scheduling a hearing for 2028.

The fact that the AI safety crowd latched onto this primary like a barnacle on a sinking ship is both predictable and grimly amusing. They see any electoral contest as a referendum on their pet existential risk, never mind that the actual job includes potholes, postal routes, and pork barrel spending. The winner gets to posture about 'alignment' while the real alignment—between lobbyists' cheques and committee assignments—proceeds undisturbed. One can almost hear the collective sigh of relief from the think tanks: at last, a congressperson who has heard the words 'agentic AI' before breakfast.

What this actually means for regulation? Absolutely nothing. One primary win does not a policy shift make. But it does provide a handy narrative: 'Voters care about AI safety!'—even though what they really care about is rent, healthcare, and why their toaster needs a terms of service update. Still, well done Lasher. You've become the human-shaped vessel for a thousand anxious tweets about recursive self-improvement. May your tenure be long, and your hearings televised.