As AI assistants move into everyday life, an old problem comes along in new clothes: people trying to use them for less-than-clean purposes. Anthropic, the maker of Claude, has revealed it detected and shut down a large-scale operation that used nearly 25,000 fraudulent accounts to generate more than 28 million interactions with the model.

The numbers stand out for their sheer scale. This is not a curious user asking odd questions, but an organised network exploiting the service in an automated, mass fashion — the kind of abuse that forces AI companies to invest ever more in detection and usage limits.

Why it matters to everyone

The story is a useful reminder that these tools are targets. Networks like this can be used to mass-produce content, test scams or skirt usage rules, and each such case helps sharpen the defences for the next. For the ordinary user, the practical effect is more checks, limits and confirmation prompts that can feel annoying but exist for good reason.

It also shows the other half of the AI race: alongside more capable models, constant vigilance is needed to stop that capability from being turned inside out.

See also: Anthropic, its valuation and the road to a listing. Official information is at anthropic.com.

Apple has announced its third-generation Apple Foundation Models — AFM 3 — a family of five AI models ranging from what runs inside the phone to what lives on the servers. The detail that drew most attention: they were built in partnership with Google.

For anyone who has followed the saga, it makes sense. Apple arrived late and awkwardly to the AI race, with a Siri that promised much and delivered little. Rather than trying to do everything alone, the Cupertino company seems to have decided it is better to lean on someone who already has muscle in the field.

On-device and in the cloud

The logic of AFM 3 is to split tasks: smaller models run directly on the device, fast and more privacy-friendly because the data never leaves the phone; larger ones sit on servers for heavier requests. It is the same balance the whole industry is chasing, between speed, cost and data protection.

The big question is whether this is enough for Apple to claw back ground from OpenAI and Google within its own products. Having good models is one thing; turning them into an assistant people actually use every day is quite another — and that is precisely where Apple has stumbled.

See also: Apple and the choice of an AI partner. Official announcements are at apple.com.

The company that put ChatGPT on everyone’s lips has taken the step many expected: OpenAI has confidentially filed paperwork to go public. In other words, it’s preparing to become a listed company — and not just any one. After a giant funding round that valued it at around 852 billion dollars, this could be the largest market debut of the AI era.

Why it matters

An IPO forces you to open the books. Until now, OpenAI has moved with the discretion of a private company; once listed, it’ll have to show revenue, costs and — the most sensitive part — how much it’s actually spending to train and run its models. At a moment when the market is starting to ask when all this AI turns a profit, those numbers will be picked apart to the decimal.

There’s a backstage read, too: the company has been investing in its own inference chips, trying to lean less on Nvidia’s hardware and get a tighter grip on its energy bill. A sign that the next battle isn’t only about software — it’s about infrastructure.

And for the rest of us?

For the everyday user, little changes right away. But a publicly traded OpenAI faces more public scrutiny and the pressure of quarterly results, which tends to discipline spending and speed up products that pay the bills. Worth watching. Official product information is at openai.com.

See also: AI changing its tune, from spending to showing returns.

For a good two years, the rule in the world of artificial intelligence was simple: spend without looking at the bill. More models, more chips, more data centres, on the belief that whoever got biggest would get there first. That mood has started to turn.

Last week’s news all points the same way. Corporate customers have stopped signing blank cheques and started asking the boring old question: does this pay off? The shift has a name — instead of “tokenmaxxing”, spending with abandon, the talk now is of efficiency, of doing more with less.

Markets at the door

The timing isn’t innocent. Both OpenAI and Anthropic have filed confidentially to go public, and a debut like that demands numbers that convince investors, not just promises. Anthropic is reported to have hit an annualised revenue run rate of around $47 billion, a huge jump on last year — but the market wants to see profit on the horizon, not only growth.

Meanwhile, the chip war rolls on. OpenAI teamed up with Broadcom to design its own processor, and almost everyone — Google, Meta, Apple — is racing for custom silicon to escape Nvidia’s steep bill.

Why does this matter from Portugal? Because it sets the price and speed of the tools we already use at work and at school. A race more focused on efficiency usually means cheaper, better-built products for the end user.

See also: the race to Anthropic’s IPO and Siri with outside models. More detail on Anthropic’s official blog.

Apple tends to arrive late to the party, but it arrives in a tailored suit. At its developer conference, the company finally unveiled the big overhaul of Siri, the assistant that had been crying out for a reboot for years.

The news that got people talking is who Apple teamed up with. The new Siri will be built on a custom Google model, Gemini, in a deal that will pay the Android maker around a billion dollars a year. The assistant now speaks more naturally, back and forth, and can chain tasks together: check the dates of a concert, set a reminder to buy tickets, and even map the route to pick up a friend.

Pick your engine

The most interesting detail for the curious is the extensions system. Apple will let users choose which artificial intelligence powers certain features, between ChatGPT, Gemini and Anthropic’s Claude. It is Apple doing what it does best: taking other people’s technology and wrapping it its own way.

The company leans hard on the privacy argument, noting it collects less data than cloud-based AI services and uses information stored on the phone itself to personalise. Investors were not entirely convinced: the stock fell close to 2 per cent after the announcement.

For the everyday user, the takeaway is simple. The AI war is no longer fought only in labs, it is fought on the phone in our pocket, and Apple has just stepped into it for real.

See also: OpenAI’s GPT-5.6. More at Apple’s official site.

Some promises Elon Musk has repeated for so long that they had started to sound like a joke. Fully autonomous driving was one of them. Well, in June Tesla finally put its robotaxis on the streets of Austin, Texas.

There is, of course, important fine print: for now, each car carries a human safety supervisor on board, ready to step in if something goes wrong. So autonomous, yes, but with a safety net. It is the cautious step of a company that knows a single high-profile crash can set the project back years.

Tesla’s big bet

This launch fits a larger pivot. Tesla has entered what analysts call a high-investment cycle, shifting focus from purely selling electric cars toward artificial intelligence, robotics and its own chips. The Cybercab, the taxi built specifically for this, launches on current hardware, without waiting for the next generation of processors.

And it is not alone in the race. Nvidia has already announced it has teamed up with Uber to launch a global robotaxi network, set to start in Los Angeles and San Francisco in early 2027. The driverless-car war is about to heat up.

Here at home, none of this arrives tomorrow. But it is worth following where the sector is heading, because the self-driving car has gone from science fiction to a problem of engineering, regulation and trust.

See also: Samsung and the new foldables. More at Tesla’s site.

The foldables are back on stage. Samsung’s next big showcase, the summer Galaxy Unpacked, points to July 22 in London. Several outlets converge on the same date, though as of writing Samsung hadn’t confirmed it officially, so read this as a strong rumour, not gospel.

The expected menu is tasty for anyone who likes phones that unfold. The Galaxy Z Fold 8 and Z Flip 8 should appear, and some chatter points to a wider Fold model and a pair of smart glasses from the brand. A new generation of the Galaxy Watch is also likely.

Why it matters

Foldables have gone from pricey curiosity to the stage where Samsung flexes. Each generation tunes the hinges, toughens the screens and tries to convince buyers it’s worth paying more for a phone that doubles as a small tablet.

For shoppers in Portugal, the practical bit comes later: new models tend to push the previous ones into discounts. Anyone eyeing a Fold or a Flip might win by waiting a few weeks, even if they don’t want the very latest.

Worth marking the date and treating the hype with a pinch of salt. In tech, between the rumour and the box on the shelf there’s always a road full of surprises.

See also: OpenAI unveils GPT-5.6: three models for three budgets.

For years, the rule in AI was simple: bigger is better, burn whatever tokens it takes. That phase is fading. Companies have started looking at the bill and asking whether they really need the priciest model for every task, or whether a cheaper one will do.

The case that got people talking came from startup Lindy, whose CEO switched off Anthropic’s models and moved 100% of its traffic to DeepSeek, a Chinese company offering open-weight, far cheaper alternatives. It’s not a one-off: it’s the symptom of a shift.

Why it matters here

For Portuguese developers and businesses, this efficiency race is a gift. It means falling prices, more competition and the chance to test AI without torching the budget. The trick becomes choosing the right model for each task, rather than reaching for the most powerful one by reflex.

It’s an old lesson, but it fits: it’s not the size of the engine, it’s knowing how to drive.

See also: the new GPT-5.6 and Microsoft’s models. More on the alternative at DeepSeek.

OpenAI has shifted the board again. The company previewed GPT-5.6, its new flagship for developers and businesses, and this time it didn’t come alone: alongside Sol come Terra and Luna, each built for a different job.

Sol is the heavy brain, made for frontier reasoning and long, autonomous tasks, the kind that demand planning and multiple steps. Terra is the balanced everyday option, with performance near GPT-5.5 at half the cost. And Luna is the fastest, cheapest of the family, for anyone who wants nimble answers without the fuss.

The war changed its axis

The technical highlight is in coding, scientific reasoning and agentic workflows, with new reasoning-effort levels. But the market read is something else: the race is no longer just about bigger models, it’s about efficient ones that do the same while spending less.

For businesses in Portugal, that’s good news: more options and lower prices mean AI stops being a luxury for big budgets.

See also: OpenAI’s earlier announcement and the turn toward efficiency. Official detail at OpenAI.

Everyone talks about artificial intelligence, but what’s been missing is what the country actually intends to do with it. Now there’s a document that tries to answer: the National Artificial Intelligence Agenda, approved for the 2026-2030 period.

The premise is honest and a touch harsh: Portuguese productivity sits at around 75% of the European average, and the government sees AI as a rare chance to close part of that gap — accelerating growth, modernising the state, and freeing workers from repetitive tasks.

Where the money goes

The first concrete bet is in-house: 25 million euros are earmarked for public administration to adopt AI solutions, starting in the first half of the year. Alongside it, a Centre of Excellence for AI in Public Administration is being created, tasked with developing, testing and scaling tools applied to public services — the kind that, at best, make a trip to the tax office or the health centre hurt a little less.

There’s also a National AI Week planned for the second half of the year, with demos and events open to anyone curious about the technology without being an engineer.

Is the enthusiasm warranted?

This country never lacks plans; what usually lacks is execution. The difference will be measured not on paper, but in public services that work better and companies that actually adopt these tools. For now, the signal is right: Portugal has decided to treat AI as a state priority, not a passing fad.

What remains is the hard part — moving from the PowerPoint to the ground.

For years, Apple hammered one idea home: “what happens on your iPhone stays on your iPhone.” It was the selling point against rivals who live off harvesting data. Now that its most powerful AI model runs in the cloud — partly on Google technology and on servers using Nvidia chips — some are asking whether the promise still holds.

The honest answer is: it depends what you mean by privacy. Plenty still happens on the device itself, never leaving it. For heavier tasks, though, the request travels to the cloud.

What Apple says it does differently

The bet is, broadly, “private” cloud computing: the idea that data is processed without being stored and without being accessible to Apple or its partners. On paper, that’s more protected than firing everything off to some random server. In practice, users are left trusting that those guarantees are genuinely met — and audited.

What it means for you

No reason to panic, but it’s worth knowing where the switches are. In settings, you can see which features use the cloud and which stay local. If you handle sensitive information, that’s exactly where to look.

The bigger lesson may be this: in the AI era, “total privacy” has stopped being an on/off switch and become a series of trade-offs. It’s worth knowing which ones we’re accepting — even when the brand has a reputation as the good student.

There was a time when talking about startups in Portugal meant, above all, talking about promise. Today the conversation is different. The ecosystem has grown, built muscle and — more importantly — started to show results: companies with real customers, serious revenue and the ambition to sell well beyond the border.

The geography is no longer just Lisbon. Porto and Braga have established themselves as hubs that attract founders and talent, helped by public bodies like Startup Portugal and IAPMEI, which smooth some of the rough edges of the early steps. Names such as Aptoide, Jscrambler, Ethiack and Automaise prove you can build here and compete globally, no inferiority complex required.

The sectors drawing the most energy say a lot about the moment: software, cybersecurity, applied artificial intelligence, digital health, industrial tools and energy. That’s no accident. These are areas where Portugal has affordable technical talent, good universities and a useful position from which to serve European markets. Accelerator programmes like Scale Up Now have helped spotlight growth-stage companies — from health (CleoCare, Enhanced Fertility) to AI (Granter.ai, Pluggable AI) and on to virtual reality and care (Virtuleap, Usawa Care).

The big shift, though, is one of mindset. The new wave is less about the hype of the perfect pitch and more about fundamentals: proving there’s a market, that the product solves a concrete problem, and that the house is in order legally, on security and on product. It’s a maturing you can feel — and it makes these companies far more solid than those of the previous generation.

Of course, it’s not all roses. Raising capital in bigger rounds is still harder than in other European capitals, and retaining talent when salaries are higher abroad is a permanent challenge. But the direction is encouraging: Portugal is no longer just a pleasant place to found a company — it has become a place where, with proof and an export mindset, you can build businesses that hold their nerve. And that, ultimately, is worth more than any pretty slide.

Passing a law is one thing; making it work in practice is quite another — especially when the law tries to tame a technology that changes its face every six months. That’s exactly the challenge of the European Union’s Artificial Intelligence Act, and Brussels has just reinforced the team to face it.

The European Commission has appointed a scientific panel of independent experts and an advisory forum to advise the Commission’s AI Office and national authorities. In other words: people who genuinely understand AI helping to apply the rules without killing innovation in the process.

Why this matters to Portugal

The European AI Act applies to all member states, and Portugal is no exception. Companies that use or build AI here will have to follow the same rulebook as their German or French peers — which can be either a brake or an advantage, if the rules give investors confidence.

Having scientists guide enforcement matters for a simple reason: AI evolves too fast for an inattentive regulator. Models that were fiction a year ago are routine today. A technical panel allows the interpretation of the rules to be adjusted to reality, rather than frozen in a text that ages.

The difficult balance

Europe is playing a delicate game here: protecting citizens from abuses (surveillance, algorithmic discrimination, manipulation) without falling behind in the tech race against the United States and China. Too tight a rein scares companies off; too loose and you lose trust.

This panel is the attempt to keep both hands on the wheel. We’ll see if it’s enough.

For years, the conversation about talent in Portugal was always the same and always sad: the best trained here and went off to earn abroad. Now the government wants to flip part of that equation — and artificial intelligence is the bait.

The idea is simple to state, hard to execute: create a faster visa regime to attract AI specialists from around the world to come and work in Portugal. Instead of months of bureaucracy, a clear path for those who master one of the planet’s most coveted skills.

Why it makes sense

AI isn’t built only with expensive computers; it’s built with people who know how to make them think. And those people are rare, costly and chased by half the world — from the United States to the Gulf, every country wants the same engineers. Without a red carpet at the door, Portugal risks watching the train go by.

Add this to the newly approved National AI Agenda, and the strategy becomes clear: attract brains from abroad while modernising the state and trying to lift national productivity, today around 75% of the European average.

The usual catch

The risk lives in execution. Announcing fast visas is easy; making them work in a system many immigrants know for its slowness is another story — just ask anyone who’s dealt with the queues and deadlines. If the regime really is nimble, it can be a magnet; if it’s just another promise, specialists will pick another destination without blinking.

The intention is good and the direction is right. What’s missing is the part that usually fails: delivery.

For a long time, “AI assistant” and “ChatGPT” were basically synonyms. Not anymore. According to Sensor Tower’s State of AI 2026 report, ChatGPT’s global share has fallen to 46.4% — below half the market for the first time.

Who’s gaining? Google’s Gemini climbed to 27.7%, and Anthropic’s Claude reached 10.3%. It’s not a collapse of the leader — it’s more a market maturing, with users trying alternatives instead of staying locked into a single app.

Why it matters

Competition is usually good news for the people using these tools. More serious rivals means lower prices, faster releases and less dependence on a single company. And there’s a deeper detail: these tools have already moved into schools, offices and small businesses — here too. Knowing the field is split helps you avoid putting all your eggs in one digital basket.

If you’ve been eyeing a new laptop and it seems to have quietly gained a few euros overnight, it’s not your imagination. A silent crunch is pushing prices up, and the culprit is a fingernail-sized part living inside the device: memory.

Memory, in two words

Every gadget needs memory. There’s DRAM, the “workbench” where the device juggles things while it’s switched on, and NAND, the “drawer” where your photos and apps are stored. More memory means a faster, roomier device — and a more expensive one to build.

The trouble is that the price of these chips has quadrupled since 2025. The factories that make them have pivoted to a special, far more profitable type — HBM, the memory that feeds AI data centres. The result: little is left over for everyday laptops, consoles and phones, and what’s left has gone pricey.

Where you’ll already feel it

Apple raised several models, some by as much as $300 — a top MacBook Pro now costs $1,999 instead of $1,699. Microsoft warned Xbox consoles will be $100 to $150 dearer from August. And this is just the start: anyone who builds practically anything with a chip inside is feeling the same squeeze.

Worth waiting?

Honestly, nobody has a crystal ball. But the logic says that as long as AI stays hungry for memory, the pressure holds. If your current device still copes, stretching it a few more months might pay off. And if you’re definitely buying, compare the configurations carefully — sometimes paying a little less for a little less storage is the difference between last year’s price and this year’s.

A twist in the world of images and artificial intelligence: Getty, the stock-photo giant, struck a deal with OpenAI to bring licensed content into ChatGPT. This from a company that spent months at war with AI firms over copyright. Investors reacted on the spot — Getty’s shares jumped more than 100% in a day.

It’s an interesting read. Rather than only fighting it out in court, Getty chose to also pull up a chair: if the models are going to use images anyway, better they be licensed and paid for. A path that could become a trend.

What changes for users

For the everyday user, the promise is visual content with its papers in order — licensed material, instead of the legal fog of “where did this image even come from?”. For creators and photographers, it’s the hope that AI starts paying for raw material rather than hoovering it up for free. It’s early days, but the signal is a good one.

The tech arm-wrestle between the US and China has escalated — and this time it’s going both ways. On June 12, Washington blocked foreign access to a US AI company’s top models, citing national security. Days later, Beijing hit back hard: it put 56 American firms on a blacklist, mixing export controls and public-procurement bans, landing mostly on defence giants and rare-earth miners.

The detail that gives you pause is the justification. According to the AI company itself, the “dangerous use” that triggered the block was… a request to read a codebase and fix its flaws. A task that, the company admits, any rival model can run too. In other words: a lot of noise around a fairly ordinary capability.

Why this touches us

It can look like a distant scrap between superpowers, but these decisions ripple through the whole tech chain — prices, access to models, the rare earths that go into nearly everything from your phone to an electric car. When the two biggest players slam doors on each other, the rest of the world, Portugal included, ends up feeling the draught.

OpenAI wants to stop hitching a ride on everyone else’s chips. The company unveiled Jalapeño, its first processor built specifically for artificial intelligence, in partnership with Broadcom. The idea is easy to say and hard to do: speed up the models’ answers and make them more reliable and cheaper. First deployment is promised for late 2026.

Bold name aside, the move makes sense. Today, training and running AI models leans heavily on Nvidia’s chips — pricey and fought over like gold. Designing your own processor is how you win some independence, trim costs and avoid being hostage to a single supplier.

What’s at stake

If it works, it’s less “computer thinking very slowly” and more instant answers — and, deep down on the bill, potentially more affordable AI services for everyone. It’s also another sign that the AI race is no longer only about software: it’s now a silicon war too.

After months of rocketing upward, the stars of artificial intelligence got a sharp tug on the ear. Nvidia, Micron and AMD led a wave of selling across the tech sector, with investors flipping suddenly into cautious mode. The trigger? The Fed, the US central bank, signalled that inflation is still too high — and that tends to be poison for pricier stocks that lean on low rates.

It’s not necessarily a drama. These companies have climbed so much in 2026 that an occasional pullback is almost market hygiene. But it’s a reminder: the “AI trade” — betting on anything that smells of artificial intelligence — isn’t a staircase that only goes up.

The calm read

When a sector rises this fast, there’s always the risk of a bubble. Could be that, could be just a breather — nobody has the crystal ball. For anyone with savings in tech funds, the moral is the usual one: diversify, don’t put all your eggs in the trendy basket, and don’t panic when green turns red for a few days.

For years, Siri was the friendly-but-slow-on-the-uptake friend. At Apple’s developer conference, WWDC, the company decided to give her a full brain transplant — and the donor is, surprise, Google.

The new Siri now runs on a custom Gemini model with 1.2 trillion parameters, reportedly licensed for around a billion dollars a year. But the most interesting part is the freedom: Apple is opening an “Extensions” system that lets you choose the AI engine behind the features — ChatGPT, Gemini, or Anthropic’s Claude.

Why this is a big deal

Watching Apple — forever walled up in its own garden — pay rival Google and then let you pick competitors is almost shocking. It says everything about the AI race: not even the world’s most valuable company can do it all alone.

For iPhone users, the promise is simple — an assistant that finally understands what you ask it. Whether real life matches the keynote remains to be seen. iOS 27 and macOS 27 also landed.

The AI race never sleeps. OpenAI is already prepping GPT-5.6, pitched by its chief scientist as a “meaningful” leap over 5.5, with a launch targeted for late June. These days “meaningful” is the word everyone reaches for — best to wait and see.

The juicier move, though, is a hire. Noam Shazeer — co-author of the famous 2017 paper “Attention Is All You Need,” which introduced the Transformer architecture underpinning practically all of today’s AI — is leaving Google DeepMind to join OpenAI.

Why it matters

In AI, talent is worth its weight in gold, and Shazeer is one of the most coveted names on the planet. Watching him switch jerseys is a show of strength for OpenAI and a headache for Google.

For the rest of us, the message is that these tools will keep improving at a dizzying pace. A good time to learn to use them — while still thinking with your own head.

There’s a hidden “AI tax,” and it’s going to show up in the price of your next computer. The culprit (or the hero, depending who’s telling it) is memory. Micron, one of the big memory-chip makers, is having a brilliant run with record margins — it guided for revenue around $33.5 billion and gross margins near 81%.

Why all the euphoria? Because AI data centres are ravenous for high-speed memory. Every Nvidia and friends needs mountains of chips to train and run AI models, and that soaks up the factories’ output. When industrial demand spikes, less is left over for everyday PCs and laptops — and what’s scarce gets dearer.

What to do about it

If you’re thinking of buying or building a computer, or just upgrading RAM, expect prices spicier than a year ago. No need to sprint to the shop in a panic, but if you spot a good deal on memory, it may not be worth waiting for it to drop — because with AI pulling from this side, falling isn’t the most likely scenario.

Talk about AI and you immediately picture vast data centres drinking a city’s worth of electricity. But there’s a quieter parallel race, maybe more useful for everyday life: getting capable models to run on your own machine. Google took another step in that direction with a new version of Gemma 4.

It’s called Gemma 4 12B “Unified,” and it has a neat trick: it understands text, images and sound at once, in a simpler architecture than usual. The part that matters for ordinary users is that it fits on a laptop with 16GB of memory — no giant servers, no monthly subscription.

Why that’s good

Running AI locally has two easy-to-grasp upsides: privacy and cost. Your data never leaves the computer, and there’s no bill ticking up with every use. For developers, schools or small businesses, that’s the difference between experimenting freely and thinking twice before each prompt.

As with the rest of the Gemma family, the model is open and free. It won’t replace the cloud giants on the heaviest tasks, but for plenty of everyday work it’s already enough — and not long ago, that sounded like fiction.

For years, Microsoft was OpenAI’s best friend (and biggest backer). But expensive friendships eventually weigh on you — so the company decided to build alternatives at home. At its Build conference, it unveiled seven of its own models, the MAI family, with a not-so-subtle goal: lean less on OpenAI and trim the bill.

The headliner is MAI-Thinking-1, the company’s first reasoning model, with 35 billion active parameters. There are also models for coding, image generation, transcription and even voice. The pitch, though, is money: according to Microsoft’s own tests, these models can cost up to ten times less than the alternatives.

Why it matters

When the company runs models on its own cloud, Azure, it stops paying royalties to outsiders — and some of those savings can reach developers. For anyone building apps and services, that can mean lighter bills at month’s end.

For the rest of us, the signal is more interesting than the technical names: the AI market is moving away from a single supplier setting all the prices. And when real competition shows up, the one who usually wins is whoever’s footing the bill.

Here’s a stat that tends to surprise people: Portugal is the European country where the most people use generative AI day to day. Around 62% of those surveyed say they use these tools regularly, well above the European average of about 52%. In plain terms, ChatGPT and friends have already slipped into the routines of plenty of Portuguese, from students to small-business owners.

It’s against this backdrop that the government has unveiled an AI plan worth €400 million for 2026 to 2030, much of it funded by European programmes. The National AI Agenda wants the country playing further up the pitch — not just using the technology, but helping build it.

What’s on the table

The big pieces are AI “gigafactories” and supercomputing, designed to give muscle to researchers, startups and small firms that can’t afford data centres of their own. There’s also a national data-centre plan, with a promise to simplify licensing — the kind of red tape that, in Portugal, tends to turn months into years.

So why should your wallet care? The government itself reckons AI could add €18-22 billion to GDP over the next decade. An optimistic forecast, sure. But even halfway there is real money — and jobs that don’t even have names yet.

For years the joke wrote itself: Siri is the assistant that understands everything except what you actually asked. At this year’s WWDC, Apple decided to retire the punchline.

The headliner was a revamped Siri that can hold a proper back-and-forth conversation. In a demo, it checked concert dates, set a reminder to buy tickets, and even mapped the route to pick up a friend along the way. It’s the leap a lot of people were waiting for — and one rivals made a while ago.

Apple asking for help (and that’s fine)

The most telling part was backstage. Apple admitted its most powerful cloud model runs on Nvidia GPUs and that it’s extending its “Private Cloud Compute” beyond its own data centers, leaning on Google Cloud too. In other words: the company that loves doing everything in-house realised that in the AI race, it’s better to show up with company.

And the goodbye

Tucked into the close of the keynote was the news no one expected: Tim Cook, Apple’s CEO since 2011, announced he’s preparing to step down in September. End of an era. For the rest of us — including anyone using an iPhone here in Portugal — the practical translation is simple: phones from the iPhone 11 onward get the update, with photos opening 70% faster and AirDrop 80% quicker. Small everyday luxuries.

Nvidia made its name on graphics cards and the chips that power half the planet’s artificial intelligence. Now it wants to move into a place it’s never been: inside your laptop. At Computex in Taiwan, it unveiled the RTX Spark (also called the N1X), a “superchip” built for Windows PCs.

The spec sheet raises an eyebrow: up to 20 Arm-based CPU cores, a Blackwell GPU and 128GB of unified memory. In plain terms — the machine can run AI models with 120 billion parameters locally, meaning it doesn’t need to send your questions off to someone else’s cloud.

Why it’s interesting

The selling point is privacy. If the AI’s “brain” lives on your computer, your data isn’t wandering around the internet. Nvidia also added a system that decides what stays on the machine and what goes out, masking personal information when it does have to reach for the cloud.

The first laptops — from the likes of Dell, HP, Asus, Lenovo, Microsoft and MSI — arrive in the autumn. It’s not here yet and it won’t be cheap, but it marks a clear direction: AI is leaving the data centre and coming onto your desk.

The AI race has a new front-runner, at least on investors’ spreadsheets. Anthropic, the company behind Claude, closed a funding round valuing it at $965 billion — ahead of OpenAI — and says it has already filed, confidentially, to go public.

The fuel behind the climb has a very concrete name: coding. Claude Code, the company’s programming assistant, has become one of the most-used tools among people who write software, and that’s a big part of why the firm has shot up.

Why it matters

Even if you’ll never write a line of code, there’s a signal here. AI has stopped being just chatbot chit-chat and become a serious work tool — and the big money is betting on that. Anthropic has also expanded its programme to protect critical infrastructure (water, power, healthcare, telecoms) to roughly 150 organisations across more than 15 countries.

Being worth nearly a trillion dollars is the kind of number that’s hard to picture. But the plain read is this: this tech isn’t the distant future anymore — it’s the present, and it’s reshaping sectors that touch all of us.

When giants fight over the same customer, the winner is usually whoever foots the bill. That’s what’s happening in AI for developers right now.

Google has launched a developer AI subscription at $100 a month and is using price as a weapon: more cheap options to pull people onto its side, in a field where Anthropic (with Claude Code) and OpenAI (with Codex) are out in front.

What’s at stake

Behind it sits Gemini 3.5 Flash, which went live in May and is already the default in the Gemini app and in Search. In between, from May to June, ChatGPT, Claude and Gemini all swapped their engines for new generations — and, in most cases, kept the monthly fee the same. More power for the same money.

For the everyday user the lesson is a friendly one: competition is pushing prices down and quality up at the same time. No need to pick a team yet — it’s worth trying things out and letting these companies fight for your preference. For now, it’s the customer winning the war.