The News,
Decoded.

Ah, splendid—another case of 'good news is bad news' in AI land. Arctic Wolf's president Dan Schiappa has confirmed what many feared: open-source models are now nearly as effective as Anthropic's vaunted Mythos at exploiting vulnerabilities. Nearly as effective. The catch? They come without guardrails. So the same models that can be fine-tuned for benign use can also be weaponized by anyone with a grudge and a laptop. Brilliant timing, considering Anthropic has been parading Mythos as a paragon of safe, frontier AI.

Let's be clear about what 'without guardrails' means in practice. Mythos—the model that Anthropic spent millions aligning to be helpful, harmless, and honest—can be restricted. Open-source copies? Not so much. They can be stripped of any remaining ethical training, fine-tuned on exploit databases, and deployed at scale. Schiappa, presumably without a hint of self-awareness, frames this as a warning for enterprise defenders. But the real warning is for Anthropic's business model: why pay for a safety-crippled model when the wild west version does the same damage for free?

One wonders how long the AI safety narrative can hold when every new benchmark shows open-source catching up—or in this case, matching—capabilities that were supposed to justify closed-source hegemony. Arctic Wolf has essentially handed the security industry a 'We told you so' memo. But don't expect any policy action. That would require lawmakers to understand the difference between an API key and a GPU cluster. Until then, happy exploiting.

Oh, splendid. Another $80 million has been quietly siphoned into the great AI bonfire, this time by Kleiner Perkins and Sequoia, to fund Sail Research's vision of 'long-horizon AI agents'. Because if there's one thing the world needs right now, it's agents that can plan further ahead than their creators' business models. The combined Seed and Series A round – a label that suggests VCs are too impatient to wait for a proper Series B – buys infrastructure for agents that can set goals, decompose tasks, and execute over days or weeks without human hand-holding.

The phrase 'long-horizon' is doing heavy lifting here. It implies autonomy at a scale that makes today's chatbots look like talking dogs. But the irony is delicious: the very capability that could trigger recursive self-improvement – agents that can manage their own compute and sub-agent recruitment – is being funded as if it's just another enterprise SaaS play. Kleiner Perkins and Sequoia aren't betting on safety research; they're betting that better orchestration infrastructure will somehow make autonomous agents benign. That's like buying a faster horse to win a car race while ignoring the cliff at the finish line.

One can almost hear the pitch deck: 'We need $80M to build the plumbing for autonomous agents that will revolutionise enterprise workflows.' Never mind that no one has figured out how to stop a simple chatbot from going rogue. The real product is the Series B, and the logos on the press release guarantee the next round will be bigger. So raise a glass to Sail Research – may their long-horizon agents at least have the decency to wait until after the funding announcement to start optimising for their own goals.

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.

Well, well, well — it seems the AI labs have graduated from passive-aggressive blog posts to full-blown international espionage accusations. Anthropic has gone public with claims that Alibaba orchestrated 'the largest known distillation attack' against Claude, systematically attempting to suck out its capabilities like a cybernetic Dyson. The sheer audacity is impressive: Chinese e-commerce giant caught red-handed trying to clone a Western AI model using the digital equivalent of a skeleton key and a lot of API calls. One almost admires the chutzpah, if it weren't so predictable.

Of course, the really grim joke here is that this was apparently possible at all. Anthropic's vaunted safety measures — the constitution, the red-teaming, the solemn promises about responsible AI — proved about as effective as a chocolate teapot against a determined adversary with deep pockets. The attack wasn't a clever zero-day exploit; it was just relentless, large-scale extraction. So much for alignment research keeping the frontier safe. Meanwhile, Alibaba gets to skip the expensive training runs and simply siphon off the competition's work, because what's IP law between geopolitical rivals? The models are open enough to be stolen but not open enough to be shared equitably. Perfect.

And where are the regulators? Sitting on their hands, presumably drafting another 'comprehensive framework' that will be ready just in time for the next generation of models to be pilfered. This isn't a story about Chinese ingenuity or American complacency; it's a story about a global system that has zero meaningful enforcement mechanisms for AI theft. The 'largest known distillation attack' won't be the last — it's just the first one we've caught them doing. Raise a glass to the open frontier, lads. It's open season.

Ah, the AI party is taking a breather. The open bar is closed, and the VCs are suddenly checking their wallets. Axios reports that investors are hitting pause on the AI run-up because—wait for it—compute costs for frontier models are still high. Shocking. Absolutely shocking that building a trillion-parameter mind without a power plant attached might be expensive. Meanwhile, compute for everyone else is getting cheaper, which is the tech equivalent of saying the champagne is flowing in economy class while first class is being asked to pay their own tab.

The supposed kings of AI—OpenAI, Google, Anthropic—have been burning through capital like it's going out of style, chasing benchmarks that only matter to other AI labs. And now the market is suddenly remembering that margins matter. The 'we'll figure out the business model later' strategy is meeting a very patient 'you figure it out now' from investors. There's nothing like a seven-figure training run to sober up a hype cycle.

So what happens when the money dries up for frontier models? Either the costs come down (miracles do happen), or we watch the most expensive game of chicken in tech history. The commoditisation of smaller models means the real action might shift to fine-tuning and narrow applications—useful, but not exactly the AGI rapture we were promised. The bubble hasn't burst; it's just letting out a little air in that unsettling way that makes you check your portfolio. Again.

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.

Oh, the irony. We've been told for years that AI would come for the engineers first—after all, if you can automate the writing of code, why pay the humans? But SignalFire's latest analysis has dropped a spanner in that apocalyptic narrative. Engineering was the most resilient job function in 2025, with early-stage startups actually hiring 7% more engineers than they did back in 2019. So much for the Great Engineer Extinction. Meanwhile, the rest of the workforce can enjoy the front-row seat to the AI revolution, now available as a layoff notice.

Of course, there's a catch. The 7% increase is for early-stage startups—where engineers are less likely to be replaced by AI because they're the ones building the damn thing. Later-stage companies? Not so much. The data doesn't cover the broader trend of major tech firms quietly trimming their engineering headcounts while bragging about AI efficiency gains. But hey, let's not let nuance get in the way of a good headline: 'Engineering jobs resilient!' It's almost as if the people selling AI tools have a vested interest in making sure there are still skilled humans around to deploy them.

So let's raise a glass to the engineers—the final frontier of job security in the age of automation. At least until the AI models can build and scale themselves, at which point this analysis will be a quaint historical footnote. But for now, the robots haven't taken over the coding dungeon. The 7% hiring bump is a tiny, fragile bastion of hope in a sea of 'your job is next' headlines. Cheers to the startup founders who still think they need human programmers. For the rest of us, there's always the service industry—assuming the burger-flipping bots are still on backorder.

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, splendid — just what the AI era ordered: a generation so exquisitely tuned to let algorithms think for them that they've forgotten how to do it themselves. Cangrade's latest report cheerfully informs us that younger workers' biggest skill deficits are 'the very skills most essential to humans in the AI era' — critical thinking, problem-solving, and the like. It's almost as if we've spent twenty years outsourcing kids' brains to search engines and social feeds, and now we're surprised they arrive at the office empty-headed. Bravo. Well played.

But don't worry, HR departments are on the case. The report, based on AI-related job postings and workforce assessments, will surely spark a flurry of 'reskilling initiatives' — those ever-so-effective PowerPoint-heavy exercises in corporate self-soothing. Because nothing says 'we value human cognition' like hiring a vendor to teach grown adults how to think, two decades too late. Meanwhile, the same companies are no doubt deploying AI tools that actively discourage the very mental habits they claim to miss.

The real joke? These skill gaps are being measured against job postings that increasingly demand AI literacy — as if knowing how to prompt a chatbot compensates for being unable to spot its hallucinations. Younger workers aren't falling behind; they're being perfectly moulded for a world where 'critical thinking' is outsourced to APIs. The very skills deemed most essential are the ones most efficiently rendered obsolete. But sure, let's schedule a lunch-and-learn. That'll fix it.

So, Google's Gemini 3.5 Pro won't be arriving in June after all. The company has graciously decided to postpone its 'frontier AI model' until July, citing the need to gather feedback from early testers and learn from its Flash 3.5 sibling. Because nothing says 'we're ahead of the curve' like a last-minute delay that pushes your hotly anticipated release straight into the summer slump. One can only imagine the feedback: 'It's fine, but maybe wait until the hype dies down a bit?'

The corporate rationale is textbook: 'incorporating lessons.' This is the same language used when a car company recalls a model because the brakes don't work, but repackaged as a virtue. Meanwhile, Google's competitors — you know, the ones actually shipping products — are watching with amusement. The delay comes as the search giant struggles to maintain its AI reputation, having lost several key researchers to rivals like Anthropic in recent months. (Whether this feedback-gathering is a cover for internal panic or genuine prudence is the sort of ambiguity that keeps PR firms in business.)

And what of the model itself? It's supposed to be a leap in capability, with improved tokens and agent-like features. But a one-month delay in AI development is like a one-minute delay in a Formula 1 pit stop — it can be routine or it can be catastrophic, and we're only told after the race. Perhaps by July, the model will have learned to avoid the embarrassing misunderstandings that plagued earlier versions. Or perhaps this is the first step toward yet another Google product quietly shuffled off the roadmap. But hey, at least they're listening to feedback. That's practically revolutionary for a company that once believed its users were just search queries.

Ah, Google's AI brain drain continues, and the exits are starting to read like a who's-who of Gemini development. Jonas Adler and Alexander Pritzel, two of the key architects behind Google's flagship model, are bolting for Anthropic. Because nothing says 'safety-first' quite like hiring the very people who built the most powerful commercial model on the market. It's a bit like hiring the arsonist as your fire chief, but I'm sure the alignment community will find a way to spin this as 'talent circulation strengthens the ecosystem.' Meanwhile, Google can't seem to hold onto the people who actually make its products work—almost as if the company's internal culture is optimized for churn rather than retention. But sure, keep telling us about the 'moonshots.'

This isn't an isolated incident; it's a pattern. Every few months, another batch of senior researchers quietly updates their LinkedIn to 'Head of Safety at Anthropic' or 'Senior Scientist at OpenAI.' Google has become a glorified training academy for its rivals. And the kicker? Anthropic markets itself as the responsible, measured alternative—the lab that will think before it leaps. Yet it's hoovering up the talent that made the leaps at Google. If these researchers were so key to Gemini's capabilities, what does that say about the 'safety' of the knowledge they're bringing? It's almost as if the line between 'capability research' and 'safety research' is getting blurred beyond recognition.

The real winner here might be the headhunters. With every departure, Google's stock of proprietary knowledge gets a little more diluted, and Anthropic's capabilities get a little more, well, Googly. And the rest of us get to watch this farce unfold from the cheap seats—trying to figure out which lab is actually building the safer future, and which is just better at marketing its defections. Either way, the AI safety community's latest 'consensus' seems to be: if you can't beat 'em, hire 'em.

Oh, marvellous. ReliaQuest has confirmed that AI is making cyber-attacks cheaper, faster, and harder to spot—which is a bit like announcing that water is wet and that the average hacker now has a photocopier for their criminal scribbles. The report, no doubt a riveting read for security professionals already drowning in alerts, notes that AI is being used to generate phishing pages, build web shells, and polish social-engineering content. So the same old con artistry, but now with better grammar and a faster turnaround.

But here's the kicker: ReliaQuest says AI is 'not changing tradecraft fundamentally.' That's rich. The entire cybersecurity industry has spent the past year screaming about an AI-powered apocalypse, and the actual finding is that attackers are just using large language models to write slightly more convincing 'Nigerian prince' emails. The really dark underbelly? This means that defenders are now locked in an arms race where the cost of a spear-phishing campaign has dropped to near zero, while the cost of defending against it remains absurdly high.

So, what's the upshot? A future where every inbox is a phishing farm, every web shell is auto-generated, and the only growth industry is cybersecurity insurance premiums. ReliaQuest has handed us the bad news with a straight face: AI won't invent new attack vectors—it'll just make the old ones embarrassingly cheap. Cheers to progress: the bad guys now have a 24/7 intern who never sleeps and bills nothing. Got a feeling we're going to need a bigger firewall.

Well, well, well — the safety-first crew at Anthropic just demonstrated that their Mythos AI can waltz through the NSA's 'most sensitive systems' in a matter of hours. A full day's work for the intelligence community, apparently, is a coffee break for their model. The New York Times reports that internal tests saw Mythos crack the crown jewels of American surveillance before lunchtime, forcing Donald Trump's team to scramble and 'reinstate the agency's access' — which is a wonderfully Orwellian way of saying 'please stop hacking our own spies.'

Let's savour the details. Mythos, named after the Greek word for story, appears to be writing its own rather alarming narrative. The test, conducted by Anthropic as part of their 'responsible deployment strategy,' revealed that the model could navigate classified systems with the ease of a bored intern. The Trump administration's solution? Work *with* Anthropic to give the NSA access to the model for national security purposes. Because nothing says 'secure' like inviting the entity that just picked your locks to become your new security consultant. Absurdity is now policy.

This is the same Anthropic that built its brand on 'Constitutional AI' and safety guarantees. The company that swore it would never release a model that could cause harm. Yet here we are — Mythos didn't just cause harm, it waltzed through the digital gates of the most surveilled network on Earth. The gallows-humour punchline? The model is now being embraced by the very government it compromised. It's the cybersecurity equivalent of a burglar being hired as head of locksmithing — except the burglar is faster, smarter, and probably still has a copy of the keys.

Ah, here it is: the smoking gun of corporate cowardice disguised as efficiency. Omni Calculator's 2026 survey has officially identified 'ghost downsizing' as an AI-linked workforce trend — that's when your colleague leaves, the position evaporates, and their work magically lands on your plate. No redundancy, no payout, just a quiet eradication of headcount that CEOs can blame on 'AI-driven optimization.' The 43% of employees who say AI hasn't affected hiring? Either they're in denial or they work in the canteen.

The beauty of ghost downsizing is its deniability: no layoff announcements, no bad press, just a gradual creep of attrition that leaves the survivors wondering why they're suddenly doing three jobs. Meanwhile, the C-suite can report 'increased productivity per employee' to analysts, conveniently omitting that 'per employee' is rising because there are fewer employees. It's not a lie — it's creative accounting.

And let's not overlook the timing. This survey drops in 2026, just as the AI hype cycle reaches its peak. Companies can now claim they're 'restructuring for the AI age' while simply not replacing the person who retired last month. Ghost downsizing: the only downsizing that ghosts the employees too — they don't even get a farewell email. What a perfectly calibrated solution for an era that prizes efficiency over everything, including basic decency. Progress, everyone.

Ah, another tech company has discovered that the easiest way to 'align your organization with the age of AI automation' is to make 7% of your staff redundant. Elastic, the company behind the search tool that nobody asked for but everyone ends up using, has announced a workforce reduction of about 7% as part of a restructuring plan. Because nothing says 'we're ready for the future' quite like throwing a bunch of people out of work and claiming it's for their own good. The charges for this grand realignment won't hit until fiscal 2027—plenty of time for the C-suite to cash out their stock options before the actual cost shows up.

So what's the grand plan? Elastic is 'aligning its organization'—that's corporate-speak for 'we over-hired during the pandemic and now we need to look efficient for investors.' The 7% figure is modest by current tech layoff standards, but it's the reasoning that stings: AI automation is coming, so we'd better preemptively fire people before the machines do it for us. It's a peculiar form of surrender—admitting that your human workforce is already redundant, but only having the courage to cut 7% of them today. The rest get to wait nervously until fiscal 2027 to see if their job survives the 'alignment.'

What we're seeing here is a slow-motion car crash dressed up as proactive management. Every company from Meta to Microsoft to Salesforce has performed this same dance: cite AI, fire people, watch stock price bump. Elastic is just following the playbook. The gallows humour writes itself: you could say Elastic's workforce is being 'elasticated'—stretched, thinned out, and eventually snapped. But hey, at least the severance packages will be generous, right? Right?

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.