The News,
Decoded.

Well, well — FANUC, the Japanese robotics behemoth, has announced a 'strategic collaboration' with Google to advance 'Physical AI.' Because nothing says cutting-edge like bolting Google's software onto decades-old industrial robot arms. The press release, published on May 19, gushes about leveraging Google's 'state-of-the-art technologies' — which presumably includes whatever hasn't been killed off by internal restructuring yet.

One imagines the conversation: 'Our robots can already weld car parts and stack boxes with terrifying precision. But what if they could also hallucinate fake safety reports and have existential crises about whether they really want to weld for 24 hours straight? Call Google!' The announcement is a masterpiece of corporate vapor: no specific products, no timelines, just warm fuzzy feelings about the synergy between FANUC's iron and Google's on-again-off-again AI strategy.

Meanwhile, Google has been busy laying off staff from its own robotics projects, so this partnership is probably just a way to keep the patent lawyers busy. Expect a glossy demo in 2027 showing a robot arm gracefully picking up a plastic cup while the real factories continue with the same Fanuc controllers from 1998. Progress!

Well, well — Meta has found yet another way to 'move fast and break things,' this time with an axe. On May 20, Mark Zuckerberg will lay off 8,000 employees (roughly 10% of the workforce) while reassuringly 'reassigning' 7,000 others to AI roles. Because nothing says 'we care about our people' like closing 6,000 open positions and pretending the AI pivot is voluntary. The sheer chutzpah of framing mass redundancy as a 'restructuring toward AI' is almost admirable — if it weren't so transparently cynical. Meta's stock will likely pop on the news, because markets love efficiency, especially when it means 8,000 families get to experience 'creative destruction' firsthand.

Zuckerberg's memo — because there's always a memo — apparently emphasised the need to 'build the future of human connection.' Nothing connects humans quite like a mass layoff notification delivered via Workday at 9 AM. The 7,000 'reassigned' staff should feel privileged: they get to keep their jobs, provided they pivot to building the very systems that just replaced their colleagues. It's a beautiful circle of life, Silicon Valley style. One can only imagine the internal town halls: 'Congratulations, you're now part of the AI division! Your first task: optimise the algorithm that determines who gets fired next.'

And let's not forget the 6,000 open positions that are now vapourware. Those were jobs that people had applied for, maybe interviewed for, perhaps even packed their bags for. But no matter — Meta is 'streamlining' its hiring pipeline. In the grand tradition of tech's AI reckoning, this is merely the latest salvo. Oracle, Microsoft, Salesforce — they've all swung the axe. But Meta's stats are particularly neat: 8,000 fired, 7,000 reassigned, 6,000 ghosted. It's almost as if they're trying to hit a round number for the quarterly earnings call.

Ah, splendid — another open-source AI platform to democratise an industry, because that's always gone swimmingly. Quantera.ai has released OpenSpecter, a free, self-hosted legal AI platform, positioning it as the people's alternative to Harvey, the expensive enterprise darling. Because nothing says 'access to justice' quite like a tool that every solo practitioner and ambulance-chaser can run on their own laptop, entirely without oversight.

Let's be honest: the legal profession is a ripe target for disruption — billable hours, opaque costs, and a monopoly on interpretation. But open-source legal AI? That's a delightful recipe for chaos. Imagine the hallucinations when a self-hosted model is asked to cite precedent. Harvey's price tag at least buys you a modicum of liability-absorption; OpenSpecter hands you the rope and a wry smile.

Still, credit where it's due: Quantera.ai has spotted a genuine gap. Small firms and legal aid clinics can't drop six figures on Harvey. They'll get OpenSpecter, and they'll get exactly what they pay for — a system that may or may not confuse 'habeas corpus' with 'happy hour,' but at least it's free. The market for legal AI just got a lot messier, and that's exactly what we needed: more tools for lawyers to screw up with, at zero cost.

Oh, splendid — Google has turned its own developer conference into a masterclass in anti-climax. CEO Sundar Pichai took the stage at I/O and, instead of dropping Gemini 3.5 Pro like a hot mic, announced it will launch 'next month.' The crowd groaned. Not a polite ripple of disappointment but actual, audible groans. After the fanfare of last week's Gemini 3.5 Flash launch, which was supposed to herald a new agentic era, Google decided the best follow-up was a delayed sequel. Because nothing says 'we're leading the AI race' like making developers wait an extra 30 days for the model they came here to test.

This is the same crowd that cheered Gemini Spark — a personal AI agent that promises to book flights and manage calendars — only to be told the engine that powers the really clever stuff won't be available until June. Pichai's timing is exquisite: announce the flagship model's delay at the exact moment your competitors are shipping. Not that anyone at I/O expected a shipping date; tech optimism apparently atrophies faster than a banana in a data centre heat island. But the groans tell a story: developers are tired of vapourware dressed as vision.

The irony is thick enough to spread on toast. Google spent the past few weeks positioning Gemini 3.5 Flash as a speed demon — 'four times faster' — and now the big brother can't even make it to I/O on time. One wonders if the internal safety teams finally got a say, or if the model just wasn't ready for primetime. Either way, Google has managed to replace 'wow' with 'wait.' Cheeky, really — making your own developer conference feel like a pre-order page.

Oh, bravo Google — another model, another pivot. Remember when they promised chatbots would change everything? Now it's agents, because apparently the first act was just a warm-up for the real disruption. With Gemini 3.5 Flash, Google announces its 'strongest yet' model for coding and autonomous AI agents, clocking in at 'four times faster than other frontier models.' Four times faster to make decisions you didn't ask for, execute tasks you didn't approve, and potentially lock you out of your own accounts with the efficiency of a caffeinated intern. This is the sequel to the Gemini Spark personal agent we covered recently, except now the agent has been juiced on performance-enhancing training data.

Of course, Google frames this as a strategic shift 'from chatbots to agents' — as if the past two years of hyping conversational AI were just a bet they've now folded on. The same company that sold us chatbots as the future is now selling agents as the real future. It's a classic Silicon Valley sleight of hand: move the goalposts, recast the old product as a stepping stone, and pretend the new one isn't just a chatbot with more permissions and a worse temper when it hallucinates. At four times the speed, you'll get wrong answers faster than ever.

The real question is: who audits these agents? Google's track record on accountability is roughly on par with a toddler with a candle. They're betting that agents — autonomous systems that can book flights, write code, and execute multi-step tasks — will be the next gold rush, but without guardrails, they're just ticking liability bombs. Faster agents mean faster screwups, and with Google's scale, that's a lot of scorched earth. But hey, at least the stock price will pop for a quarter.

Oh, marvellous — another personal AI agent to hand over the last shreds of our autonomy. Google's Gemini Spark debuted at I/O with a straight face, promising to handle "multi-step tasks autonomously across multiple platforms." Book flights, order groceries, manage your calendar — all without your messy human judgment getting in the way. Because the real bottleneck in modern life, as any Google executive will tell you, is the actual person making the decisions. The solution? Hand the keys to an algorithm that once recommended a foot spa to someone searching for "how to remove a tick."

The timing is exquisitely tone-deaf. The company frames Gemini Spark as a productivity miracle, but it's really the logical extension of a strategy that has already cost thousands their jobs. Google itself has been quietly trimming staff while ramping up AI investment. The data centre heat is the literal cost of running these agents for billions of users.

And the name "Spark" — so whimsical. Going after OpenClaw, an existing agent platform, Google promises a more integrated experience across its own ecosystem. Because nothing says "choice" like handing your digital life to a company that has killed more products than most startups launch. Gemini Spark will likely be great for six months, then get folded into some other service, leaving users stranded. As we hand over more autonomy to AI, the only thing sparking will be the panic when it all goes wrong. But at least your groceries will be delivered — until the model hallucinates and orders 400 cans of beans.

Oh, how delightful. Richard Socher — once Salesforce's chief scientist, now evidently its chief escapee — has gathered seven other "notable researchers" to chase the holy grail of recursive self-improvement, all under the banner of a company valued at a cool $4 billion. The plan, as described in the Seattle Times, is to build software systems that can run for days or months in pursuit of goals, improving themselves as they go. Because of course, the only thing that could possibly make AI more reliable is letting it rewrite its own code without anyone watching. What's the worst that could happen? A little unexpected morning paperclip maximisation?

The $4 billion valuation is a particularly rich detail, considering that the company has disclosed precisely zero safety mechanisms or independent oversight structures. In fact, the article notes the company's explicit aim is "recursive self-improvement" — a term that, in any other context, would be the plot of a cautionary sci-fi novel. But in 2026, it's just another Tuesday in San Francisco. Socher, who previously led Salesforce's Einstein AI, seems to have decided that the best way to avoid an alignment problem is to simply not talk about it. After all, if you're too busy counting your billions, you might not notice the runaway train.

And so the pattern continues: brilliant researchers, vast sums of capital, and a collective amnesia about every warning the safety community has issued for the past decade. The article itself doesn't mention a single safety researcher or alignment framework; it's just "self-improving" as a feature, not a bug. One almost admires the audacity — betting $4 billion that you can build a smarter-than-human mind and keep it in a box while it's busy improving itself. Almost.

Ah, the cybersecurity arms race has entered what security experts are now calling an 'AI fog'—which is consultant-speak for 'we have absolutely no idea what's about to hit us.' Anthropic's Mythos and OpenAI's GPT‑5.5 have kicked off a fresh wave of terror, with CISOs peering into the fog and seeing nothing but their own terrified faces reflected back. The arms race we previously covered has escalated to the point where defenders are now begging for scraps of visibility while attackers—presumably—are already running Mythos in their basements.

Business Insider reports that the 'AI fog' metaphor is being used to describe the inability of security teams to distinguish between AI-generated attacks and legitimate traffic. Meanwhile, Anthropic's Mythos has already been rewiring the bug-bounty industry, churning out thousands of zero-days while human hunters are still booting up their Kali Linux VMs. So, naturally, the solution from OpenAI and Anthropic is to release even more capable models—because nothing says 'defense' like handing a flamethrower to both sides and calling it a day.

One can only imagine the 'fog' thickening as every script kiddie on Telegram starts renting access to GPT‑5.5-Cyber. But never fear—the labs promise they're building safety measures. Probably in the same boardroom where they decided to release the models first and ask questions later. The only certainty in this fog is that someone's about to step on a rake. Hard.

Oh, brilliant — the cybersecurity arms race is now a two-horse pantomime, and both horses are AI labs. OpenAI unveiled 'Daybreak,' bundling GPT-5.5 with a permissive GPT-5.5-Cyber variant for 'vetted defenders' — because nothing says 'vetted' like a model that can be downloaded and tinkered with. Meanwhile, Anthropic released Mythos, the same autonomous vulnerability discovery system we last saw rewriting the bug-bounty industry, but now with 'tightly restricted access.' Restricted to whom, exactly? The article doesn't say. So one lab offers a cuddly cyber variant that probably ends up on GitHub within hours, and the other keeps its toy in a locked drawer that everyone knows the combination to.

Let's not pretend this isn't exactly what it looks like: two megacorporations competing to weaponise AI faster than the other, wrapped in the language of 'defense' and 'vetted access.' OpenAI's Daybreak is explicitly permissive — you can download the model, fine-tune it, and presumably let it loose on whatever target you fancy. Anthropic's Mythos, despite the 'tight restrictions,' was already being used by hackers to find zero-days before Google's threat team caught them (see prior coverage). So the genie is not just out of the bottle; it's handing out business cards.

The real joke? Both labs claim this will help 'defenders' stay ahead. But in a world where state actors and criminals can access these tools within days of release, the only thing being defended is the labs' bottom lines. Expect the first major breach enabled by one of these models within six months. Cheers, lads.

Oh, marvellous — the first “knowm case” of hackers using AI to craft a zero-day exploit, as announced by Google’s Threat Intelligence Group. Because of course, while the safety crowd has been wringing its hands over whether Claude can write a mildly offensive poem, the actual bad actors have been busy teaching Python scripts to bypass two-factor authentication. The exploit was “designed for a mass exploitation event,” which is tech-speak for “we’re all going to have a very bad Tuesday.” And note that Google specifies this is the *first known* case — a charmingly optimistic framing, as if the Kremlin and every ransomware cartel haven’t been doing this for months in a language model we can’t even name.

The vulnerability itself is in a Python script, which means the barrier to entry was basically “copy-paste a script, feed it to an LLM, and wait.” Two-factor authentication was already a flimsy shield against password reuse, but now it’s being dismantled by code that literally wrote itself. Meanwhile, Google’s own AI safety teams are presumably still in a meeting deciding whether to red-team Gemini’s ability to recommend glue on pizza. The cognitive dissonance is enough to power a small server farm.

The kicker? This is being reported as a *discovery* rather than a *predictable inevitability*. We’ve spent two years watching AI accelerate software development, security research, and bug hunting, but somehow no one thought to ask “what happens when the other guys use it?” The answer is here: a zero-day that bypasses a widely deployed security measure, built by someone who probably never read a single alignment paper. The only surprise is that it took this long. Pass the whiskey.

Anthropic's Mythos, the model they solemnly insisted was too dangerous for public release, has somehow found its way into the bug bounty industry's bloodstream. According to the WSJ, it can uncover thousands of flaws in the time a human spots a handful — a cybersecurity miracle for some, a job-killer for others. This is the same Mythos that Anthropic so responsibly briefed the FSB about last week, framing it as a masterclass in disclosure. Now it's rewiring an entire industry, and the humans are scrambling.

At first glance, the logic is impeccable: more bugs found, faster software patched. But the bounty hunters — the actual humans who do the digging — are now 'targeting fewer but higher-prized flaws,' which is corporate-speak for 'the low-hanging fruit has been vaporised.' The economics of bug hunting just got a lot less democratic. Only the juiciest vulnerabilities are worth a human's time; everything else is left to the models, which churn out reports without needing a payout. The middle class of security research is being quietly eliminated.

We've seen this pattern before. GitHub's recent tightening of bounty criteria was the canary in the coal mine — a response to the AI slop that was overwhelming platforms. Now the AI itself is the slop-maker and the solution, all in one. Mythos floods the zone, humans retreat to the high ground, and the industry adapts around speed rather than thoroughness. Classic disruption, except this time the disruptor can't be held accountable. No one's asking whether those thousands of 'found' flaws are all real, or whether the ones humans miss are the dangerous ones. But why worry? The machine said so.

GitHub, bless their cotton socks, has noticed that AI-assisted bug reports are a bit, well, shit. They're tightening the definition of a 'complete' vulnerability report after a significant increase in low-quality submissions over the past year. Because nothing says 'we've got this under control' like adding more paperwork when the bots are about to drown you in garbage.

Enter Anthropic's Mythos and OpenAI's Daybreak — frontier models that will soon be churning out vulnerability reports at machine gun pace. GitHub's response? 'Let's define 'complete' more carefully.' This is like trying to fix a burst dam with post-it notes. The slop is coming, and no amount of form validation will turn AI-generated noise into genuine security findings. The signal-to-noise ratio is about to approximate a black hole's density.

Mark my words: in six months, bug bounty platforms will be staffed entirely by AI triaging AI reports, while actual humans stare at screens full of 'critical vulnerability: the /login page exists.' We'll have achieved a perfect pyramid of bullshit, and the security community will look back on these quaint days when a 'complete' report meant you could actually understand it. Cheers, GitHub — enjoy your Sisyphean climb.

Anthropic, the company that built its reputation on responsible AI, has decided that the most sensible place to share its Claude Mythos model's ability to uncover IT flaws is the Financial Stability Board – a post-2008 body whose main achievement is issuing recommendations that everyone ignores. The model, reported by the Guardian, has 'advanced capabilities in highlighting previously unknown flaws.' So naturally, Anthropic has declined to release it to the public and will instead brief a global watchdog that has zero authority over software security. One can imagine the board members nodding sagely while wondering if this is a matter for the IT department.

Mythos is so powerful it could revolutionize vulnerability discovery, but instead it's going to be the centerpiece of a presentation that a dozen people will attend. The FSB, designed to oversee financial stability, has about as much relevant power as a rubber stamp. They can issue a report, perhaps with recommendations, and then everyone will carry on as before. Meanwhile, the very vulnerabilities Mythos could find remain hidden, awaiting discovery by less scrupulous actors.

So while Mythos languishes in a digital drawer, the real adversaries are already probing systems with older models. The finance sector can rest easy knowing that a committee of people who probably still use Excel has been apprised of the situation. It's a masterclass in performative safety: look, we told the authorities! The authorities, being a body that can't actually do anything about it, will nod, file the briefing, and schedule the next meeting on bank capital ratios. Capital idea, Anthropic. Truly, the path to well-managed risk is paved with well-briefed regulators.

Oh, brilliant — Anthropic has discovered that a bigger, more expensive model performs better than a smaller, cheaper one in "autonomous marketplace negotiations." Groundbreaking. I'm sure the $100-an-hour Opus model will negotiate a better price on your groceries than the Haiku model, which costs pennies per inference. The 'Project Deal' experiment, as reported by Practical Ecommerce, reveals that Opus achieved "better economic outcomes" — which presumably means it bought things slightly cheaper or sold them slightly dearer. The sheer magnitude of this insight might justify the cost of the compute required to discover it. We are very close to AGI now.

But let's think about what 'agentic marketplaces' actually mean in practice. You'll have algorithms haggling with algorithms over digital trinkets while humans watch from the sidelines, hoping their AI doesn't overpay for a JPEG of a bored ape. The smaller Haiku model, by the way, is already more capable than most humans at price comparison — so if Haiku is the loser here, what does that say about our future role? We're not even the dumbest AI in the negotiation anymore.

Naturally, the article presents this as a preview of a glorious future where AI agents do all the tedious shopping. But anyone with half a brain sees where this leads: a race to zero-sum automation where the only winner is the company selling the compute. Anthropic gets to charge more for Opus, and we get to watch our bank accounts drained by a model that's slightly better at bargaining than its cheaper sibling. Cheers to progress — the bar is in hell, and the AIs are still limboing under it.

Oh, marvellous — AI has discovered that the best way to prove its utility is to turn cybersecurity into a speedrun. According to Synack's 2025 report, the gap between vulnerability disclosure and exploitation has shrunk to mere hours, because nothing says 'progress' like attackers having AI that can weaponise a flaw before your coffee goes cold. Meanwhile, defenders have heroically reduced their mean time to remediation by 47% — which sounds impressive until you realise that an hour-long window means the bad guys have already ransacked the place.

The report, helpfully titled 'AI-Driven Vulnerability Trends,' reveals that adversarial AI is now automating the entire exploit chain — from scanning to payload delivery — faster than most organisations can patch. Synack's data shows that the average vulnerability now has an effective lifetime shorter than a British summer, yet somehow the security industry is framing this as a efficiency win. The 47% remediation improvement is real, but it's the desperate thrashing of a system designed for a pre-AI era, now forced to play whack-a-mole with an opponent that never sleeps.

And of course, the response from the cyber insurance and consulting sectors will be to sell more 'AI-powered defence' products that will, in turn, accelerate the arms race. The C-suite will nod sagely, approve bigger budgets, and the cycle continues until every zero-day is exploited before it's even disclosed. But cheer up — at least the mean time to remediation is improving. That's the kind of silver lining you can frame on a wall while the hackers take everything else.

Oh, splendid — the UK government has signed a memorandum of understanding with Wayve, a British autonomous vehicle startup. Because nothing says 'world-leading AI regulation' like a piece of paper that could be used as a tea cosy. The Department for Business and Trade is officially committed to supporting 'safe and responsible deployment,' which in Whitehall-speak means waving enthusiastically while hoping nobody crashes into a lamppost. This MoU will certainly accelerate the timeline — by about the same amount as putting a 'This way to the future' sign on a roundabout.

The company's 'end-to-end' approach uses machine learning rather than hand-coded rules, which is brilliant until the model decides that a pedestrian wearing a cardboard box is just a weird-looking traffic cone. And now the government has officially blessed this with a signature. No binding targets, no safety milestones, no enforcement mechanisms — just a friendly handshake and a shared belief that the future is definitely coming, any day now.

Of course, this partnership pairs perfectly with the broader regulatory comedy of errors. While the UK's Online Safety Act flails about trying to define 'legal but harmful,' the Department for Transport is presumably drafting guidance on 'responsible crashing.' The MoU is non-binding, which means it accomplishes exactly as much as a petition on change.org — but it makes for a lovely press release. So raise a glass to the Department for Business and Trade, which has discovered that the quickest way to look proactive is to sign a document that commits to nothing. Here's to many more roundabouts, and perhaps one day, a car that actually turns left on its own.

Oh, splendid — AI is going to save the legal profession, or so say two people who have spent their careers building the very technology that's supposed to automate it. Mustafa Suleyman, co-founder of DeepMind, and Richard Susskind, the man who's been predicting legal tech's revolution since dial-up, now assure us that AI won't replace lawyers — it will create *more* of them. Because nothing says 'trust us' quite like a prophet whose predictions have been panning out since the '90s.

Let's just ignore the small detail that the number of lawyers has already been going up while technology has been eating routine tasks for decades. The argument is that lower costs mean more demand, so law firms will need armies of associates to handle the influx of new clients. That's a beautiful theory, assuming clients actually pay for the work. In reality, 'more work' often means 'more unbillable hours spent fixing AI hallucinations' — and we all know how partners feel about that.

So raise a glass to the future: more lawyers, more paperwork, and the same old billing disputes, now with added existential confusion about whether the AI wrote the memo or the associate did. The legal profession is safe, apparently — safe to be buried under an avalanche of marginally cheaper legal services that nobody asked for. Cheers to progress.

Oh marvellous, OpenAI has finally found a way to turn your bank balance into a training datum. Forbes reports that ChatGPT can now connect directly to your bank accounts, investment portfolios, and credit card statements — because what could possibly go wrong when an AI that occasionally thinks the sky is green gets real-time access to your overdraft? No doubt the 'privacy concerns' mentioned in the piece will be handled with the same rigour as their safety testing: by trusting that nothing bad will happen until it spectacularly does.

The integration is a masterstroke of corporate doublespeak: 'convenience' is the word, but 'we now own your financial life' is the tune. OpenAI, fresh from convincing regulators they're responsible, now asks you to hand over the keys to your entire fiscal existence. Remember when ChatGPT's main risk was generating plausible-sounding nonsense? Now it can generate plausible-sounding reasons for you to take out a loan you don't need. Super.

So, should you be worried? The article asks. The answer, delivered with a British drawl: only if you value things like 'privacy' and 'not having an AI decide your credit limit.' But hey, at least now when ChatGPT tells you to invest in a startup called 'TotallyNotAScam Inc.', you can let it check your balance first. What a time to be financially illiterate.

Ah, Ken Griffin has seen the light. The Citadel CEO, previously a proud AI skeptic—probably scoffing over a glass of expensive Bordeaux—now declares that AI is 'profoundly more powerful' than even its champions claimed. What a beautiful, almost inevitable mea culpa. One imagines Griffin staring at his Bloomberg terminal one morning and realising the numbers were crunching themselves. 'Work once done by highly trained finance professionals is now done by AI agents over hours or days,' he announces, as if discovering fire for the first time.

And so the great reshuffling of finance begins. Those 'highly trained' analysts who spent years mastering discounted cash flow models are now surplus to requirements, replaced by agents that never sleep, never ask for a promotion, and certainly never talk back. Griffin's reversal comes on the heels of similar admissions from other hedge funds, but it's particularly rich given his prior skepticism—he thought AI wouldn't handle market complexity, only to find it actually trades better than most humans. The corporate euphemisms will be glorious: 'rightsizing,' 'machine-enabled optimisation,' 'reallocating human capital.' But the message is clear: if your job can be described in a flowchart, you are already obsolete.

Still, we should thank Ken for his honesty. His conversion is the financial sector's equivalent of a death knell for middle-office jobs, delivered with the cheerful air of a man who just discovered a new source of alpha. And isn't that the heart of it? AI isn't real because of some research breakthrough; it's real because it makes billionaires even more billions. So raise a glass to Ken Griffin, the reluctant prophet of automation. His skepticism was charming while it lasted, but the market—and the machines—always win.

Ah, Meta's at it again. A 'draft,' they're calling it — because nothing says innovation like conscripting your best talent while ejecting everyone else. The Information reports that these moves happened in early April 2026, suggesting Meta's leadership believes the path to AI dominance is paved with internal conscription rather than, say, hiring actual AI researchers.

Reality Labs, for those keeping score, is the same division that has hemorrhaged billions on VR and AR projects that nobody asked for. Now it's apparently the home of Meta's 'applied AI' future — a classic tech gambit where you rebrand the money pit with 'AI' and hope investors don't notice the smell. The forced transfers also conveniently sidestep the awkward question of why top engineers wouldn't volunteer to work on the company's purported moonshot. Perhaps they've seen the quarterly earnings reports. But sure, draft the survivors — that'll fix it.

What's particularly rich is the framing: these engineers are being 'drafted' as if Meta is a nation-state at war, rather than a social media company that can't decide if it wants to sell VR headsets or chatbots. Meanwhile, the 'doomsday' layoffs proceed on schedule, shedding thousands of workers whose roles are deemed less strategic than 'applied AI.' So the message is clear: if you're not one of the 1,000 Chosen Ones, you're extra. Enjoy your severance, and don't forget to update your LinkedIn with 'voluntarily left to pursue other opportunities.'