Eshu Marneedi

Juli Clover, reporting for MacRumors:

Apple is working on camera-equipped AirPods that appear to be nearly ready to launch, based on a video MacRumors found in the macOS Tahoe 26.7 release candidate.

In a short demo, a man holds a book up so the camera in the AirPods can see the title. “With Visual Intelligence, your world becomes savable. See something you like? Just ask me to save it for later,” says the voiceover text.

I have been on the record as saying I have no interest in this product. I love my AirPods Pro 3 and have them in my ears almost all the time; I find the rumors about this product also carrying the AirPods Pro name concerning. It will be unacceptable to me if I have to purchase these AirPods just to get the best sound quality and active noise cancellation performance. My hopeful guess is that the standard AirPods Pro 3 will remain for sale at $250, whereas these new ones will be marketed as “AirPods Pro 3 with Visual Intelligence” for, say, $350. (I’m hoping the two products are otherwise identical.) There are two main reasons why I don’t want camera-equipped AirPods: practicality and privacy.

First, practicality. From the leaked video — which is remarkable by itself; this is one of the most embarrassing Apple leaks in a while — the AirPods’ stems are noticeably thicker. I wear mine to sleep every night, and even AirPods Pro 3 protrude too far outward to be completely comfortable. AirPods should always be light and as minimal as possible. I also just don’t find a practical reason for putting cameras in AirPods to begin with. Perhaps this is just me, but I have never picked up a book and wanted to save it. I have never held some nuts in my hand and asked myself how much protein is in them. I don’t go up to random people’s dogs and ask Visual Intelligence what breed they are. I’m yet to hear a single compelling use case for Visual Intelligence.

Second, privacy. Society is undergoing a mass revolution against surveillance. Flock license plate cameras, Meta Ray-Ban sunglasses, and artificial intelligence data scraping are hugely unpopular throughout the United States. I single out the United States because Americans are not averse to relinquishing their privacy for useful software — there has been no major push for data privacy regulation within the United States on a federal level, and Americans largely accept targeted advertising. But AI-enabled surveillance is widely unpopular politically and socially because Americans don’t see its utility, a position I largely agree with. There’s not much compelling about AI-enabled cameras everywhere. Camera-equipped AirPods will be symbolic of a Big Tech-powered surveillance state.

As a commentator, I’m intrigued to see how Apple spins this. But as a citizen and user of Apple products, I’m just not excited for yet another gadget with AI cameras.

Anthropic:

Future Claude models will generate text that contains a watermark. This is a way of determining the likelihood that Claude was involved in writing the text, and we, along with several other major AI providers, are implementing this change to comply with the EU AI Act.

In this article, we share answers to some of the questions we’ve received about how our chosen watermarking method works, whether it affects Claude’s outputs, and why we’re making this change. To summarize:

• We use a method of watermarking that does not have any practical impact on the quality or content of Claude’s outputs;

• The difference between watermarked and un-watermarked text will not be distinguishable to readers;

• Nothing is added to the text and there are no hidden characters;

• Watermarking doesn’t require extra tokens, and will not be more expensive;

• Watermarking carries no identifying information and can’t be traced to a specific person, organization, or chat;

• Watermarking won’t be specific to Claude. As of August 2, the EU requires AI providers serving its market to mark AI-generated content. Other major model developers have signed the same Code of Practice and will be implementing their own watermarks.

Large language models like Claude work by generating one word at a time. Each time the model decides on the next word, it chooses among a list of potential candidates, ultimately selecting the most sensible or likely based on the preceding text. Take the sentence “The weather today was cold and…”. The next word is very unlikely to be “sugary.” But it is quite likely to be “overcast” or “grey.” Under most circumstances, it doesn’t matter much to the reader which of these latter two words the model ultimately chooses—the meaning of the sentence is largely the same either way. In cases like this, the choice is settled by a random number.

Watermarking uses low-stakes choices like these—which occur many times over a piece of generated text—to leave a pattern in Claude’s responses. That pattern is undetectable to the reader, but is detectable to anyone who has a key that encodes it. When watermarking is used, choices are still made at random, but the source of the randomness is different. Instead of using an arbitrary random number generator to pick the next word, watermarking uses the key and a few words that come before to settle what word the model should pick. That is, the words that Claude picks are still random, but now, one can check the sequence of words and see if it’s consistent with the choices Claude would make if it was using the key. If it is, one can assign a probability that the text was generated by Claude.

Because the watermark is created through subtle differences in word choice, it won’t apply to code, which requires exact syntax to function properly.

I think it’s important for there to be a foolproof way to identify artificial intelligence-generated outputs, whether they be images, text, or audio. Social media platforms should also prominently mark AI-generated images and text as synthetic, especially if the content is political or official. I stipulate that identifying AI-generated content should be foolproof because false positives can have detrimental consequences. Pangram, the leading AI text detector which doesn’t — at least for now — rely on watermarking, is widely regarded as the most accurate but still can occasionally flag human-created text as AI-generated. Universities across the globe punish their students for passing off AI-generated work as their own; the consequences of these systems are enormous.

SynthID, a framework developed by Google DeepMind, embeds an invisible watermark within AI-generated images and videos. It remains intact even after manipulation or screenshots, and is completely random, meaning it cannot be faked or removed. SynthID is used by Google’s Nano Banana image generator and ChatGPT’s image generation feature, two of the most popular tools. Social media websites like Instagram, Facebook, X, and YouTube scan uploaded content for SynthID watermarks and display a badge next to synthetic imagery. SynthID is foolproof and one of the best systems for detecting AI-generated imagery online, but it just can’t be replicated via text.

This new watermarking framework outlined Friday is Anthropic’s first try at developing a text watermarking technology. The problem is that it objectively isn’t foolproof — again, SynthID cannot be replicated with text. I’m less concerned that the outputs will be lower in quality than those without the watermark, but I am worried about false positives. Text that has been edited by Claude shouldn’t have a watermark at all, whereas Claude-generated text edited by a human absolutely should. Here’s what Anthropic says:

Light editing probably won’t remove the watermark completely; a complete rewrite where every word is replaced will. In the latter case, of course, it’s arguable whether the text can any longer be described as AI-generated…

The watermark only applies to words Claude chooses. When Claude proofreads text written by a person, what it gives back has generally only been lightly edited; because nearly all the words are the person’s, there’s very little (if anything) for the watermark to attach to. Depending on the length of the text and how heavily Claude has edited it, those changes might not be enough to make Claude’s involvement detectable. The more Claude writes, the more decisions it has to make, and the more space there is for a watermark.

These paragraphs don’t project much certainty. “Probably won’t,” “generally only,” “might not be enough.” I don’t blame Anthropic for this — watermarking text is nearly impossible! Claude relies solely on word choice to watermark its outputs, and word choices can be changed trivially. But I’d argue that releasing a first-party watermarking tool that isn’t 100 percent accurate is a dangerous precedent. People will use this tool to check for AI-generated text, but because it’s a first-party framework, arguing against its judgment will be an uphill battle. This is not Pangram; it’s not a guess.

Again, I do think all AI-generated text in the future ought to be watermarked, but with the important caveat that the watermark is foolproof. This watermark doesn’t guarantee that, and I think it ought to be scrapped.

Marcus Mendes, reporting for 9to5Mac:

Which brings us to The Information’s report, and its account of several cases where “Apple employees who left for other companies over the past decade told The Information they, too, continued to have access to confidential documents after leaving the company, even though they made no effort to do so.”

From the report:

Former Apple employees say an unusual company policy that encourages them to blend professional and workplace technologies is why they unexpectedly ended up with access to confidential files after their departures.

When new employees join Apple, the company often issues them an iPhone and Mac and pays for an iCloud account with a large amount of online storage capacity. Crucially, during the onboarding process, Apple encourages new hires to use their preexisting personal Apple IDs with this iCloud account, through which their co-workers can share internal Apple documents and other files with them.

The reason behind this, The Information notes, is the fact that iPhone users “can only log into a single primary Apple ID that unlocks all iCloud capabilities at a time.” So to avoid carrying two different sets of devices, one for personal and another for work (which is not uncommon by any means), “most Apple employees opt to use their personal Apple IDs to access their iCloud accounts.”

The report explains that, since the late 2010s, Apple employees have had access to a company-managed folder within iCloud that is automatically removed when they leave.

However, many internal documents are reportedly not automatically saved there, allowing files shared outside the folder to remain mixed with employees’ personal data and accessible after their departure.

This iCloud news definitely makes the case look less like a slam dunk at first glance, but it’s still obviously winnable¹. Cases like these hinge on the idea that the plaintiff must take reasonable action to ensure its intellectual property stays confidential. This combined work and personal iCloud account structure will clearly be at the center of OpenAI’s argument, along with supposed evidence that it was actually Apple employees who messaged Chang Liu, the employee sued alongside OpenAI, for help with Apple internal projects after his departure. (OpenAI also claims, with seemingly no attached receipts, that Liu was trying to “do the right thing,” with no further elaboration.) The idea that Apple doesn’t care about guarding its intellectual property is laughable — I don’t think it’ll work in court.

The messages between Liu and an Apple employee don’t refute Apple’s argument that OpenAI instructed and encouraged its Apple hires to bring prototypes and other confidential information into interviews. OpenAI’s Monday-evening response to the lawsuit only says, “Tang has always been clear with the team that we do not want, and must not use, any confidential information… Tang served Apple for more than 24 years and was widely known as one of the most innovative leaders at the company,” referring to Tang Tan, now OpenAI’s chief hardware officer. OpenAI also doesn’t address the assertion that it asked an overseas supplier for information about Apple’s confidential manufacturing processes. The blog post only truly refutes — with evidence — one claim relevant to the lawsuit: that Apple’s lawyers tried but failed to contact OpenAI’s. I’m not sure whether that will even matter in court.

I still think the case is winnable for Apple because even if the documents weren’t secured — either in iCloud or, as Apple says, third-party cloud storage — Apple could (correctly) assert that it wasn’t suing because the employees simply had access to documents post-employment, but that they actively used these documents to get a job at OpenAI. And, to involve the company itself, that using those accidentally obtained documents was encouraged by OpenAI’s chief recruiters and officers. It will argue that Apple employees knew they should report such incidents rather than take advantage of them for future employment. The motives of OpenAI’s executives and employees are central to the lawsuit and, if it goes to court, will have to be investigated during discovery. (It’s very much possible this settles out of court.)

An update was made on August 5, 2026, at 5:19 a.m.: I’ve added further clarification on the iCloud storage claim.

Dominic Preston, reporting for The Verge earlier in July:

A year after overhauling its Z Fold phone with a radically thinner design, Samsung has changed things up again, this time altering the shape entirely. The Z Fold 8 is wider than any of Samsung’s previous foldables, and shorter too, a size and shape somewhere between Samsung’s traditional Flip and Fold models.

In photos, I wasn’t impressed by the squat shape. In person, to my surprise, it feels great, and almost immediately intuitive. If you want to get a feel for it yourself, grab your passport — the Z Fold 8 is about the same height and less than half an inch more narrow.

This isn’t Samsung’s only new foldable this year, and in fact, its lineup just got more confusing. The Z Fold 8 may be the official follow-up to last year’s impressive Z Fold 7, but in truth the Z Fold 8 Ultra is the straightforward sequel. That phone has the same squarish inner screen as previous Z Fold phones and a similar triple rear camera. The name feels like a sly trick to get around this year’s inevitable price hikes: Samsung slapped “Ultra” on the box of its highest-end model to help cover for pricing the phone at $2,099.99, up $100 from the Z Fold 7.

I don’t have much interest in Samsung phones but nevertheless have been linking to Samsung Unpacked news for years now. What’s more intriguing to me is this new form factor, which is widely speculated to be the same as that of the folding iPhone due in about six weeks. The first generation of folding smartphones, beginning with the Galaxy Fold in 2019, had long, narrow front screens and square inner screens. This aspect ratio made both screens less than ideal to use: the front screen was too narrow, and the inner screen wasn’t wide enough to be used as a tablet. This new “squat” form factor sacrifices vertical length for width, making the inner screen much more useful while sacrificing day-to-day use of the front screen.

I think this is the way to go, and I remember saying so when the Pixel Fold was first announced in 2023. The entire point of a folding phone is the inner display, which should be large enough to eliminate the need for a tablet. But this great aspect ratio debate of the 2020s has proven something more important: folding phones are inherently full of compromises. The front screen — which most people will use most of the time — must be sacrificed to make the inner screen useful. This is still better than the old design, where both screens weren’t ideal to use, but it’s still a compromise. For the best experience, people will open up the phone like a book. This style of folding phones ought to be called “tablets with front screens as an afterthought.”

This brings me to the foldable iPhone. I’m positive the software will be world-class. App developers will be there Day 1 to ensure their apps work well on both displays; Apple will make the front display useful and practical. But this device is rumored to cost upward of $2,000, while forgoing the professional-grade cameras of the iPhones Pro, the pocketable yet useful display size of the standard iPhones, and the battery life of the iPhones Pro Max. (Just compare the specifications of the Galaxy Z Fold 8 with the Galaxy S26 Ultra.) I’m almost positive I won’t want to carry two displays around in my pocket, especially because I’ll have to open the phone up when I truly want a good experience. I’m almost positive I don’t want to spend $2,000 for worse cameras and battery life. And I’m almost positive I’m in the overwhelming majority.

I’ll refrain from passing judgment on the foldable iPhone until it’s announced, but I can judge the Galaxy Z Fold 8 — and I think it exposes too many compromises with this device class. None of this is Samsung’s fault, of course, but it does a great job illustrating why foldable phones will probably never be ready for primetime. There was a time many years ago when I was bullish on the folding phone, hoping technology would progress far enough that they’d be equivalent in price and features to their non-folding counterparts. That time has not come yet, and I’m not confident it ever will. Samsung and Apple have tried addressing the biggest drawback to folding phones, the form factor, this year. But the Galaxy Z Fold 8 proves that it’s just not enough.

Chance Miller, reporting for 9to5Mac:

Apple has officially announced Apple Upgrade, a new product leasing program available starting today in the United States.

Apple Upgrade, which is backed by Klarna, lets users lease iPhone, Apple Watch, Mac, and iPad purchases, with the option to easily upgrade at the end of the lease term. Here’s how it works.

Apple Upgrade is available across Apple’s product lines, including the latest iPhone 17 lineup, MacBook Air, Apple Watch Series 11, and much more.

iPhone and Apple Watch are available with 12-month and 24-month leasing terms, while Mac and iPad are available with 24-month and 36-month terms.

• iPhone leases start at $17.99 per month for iPhone 17e
• Apple Watch leases start at $11.99 per month for Apple Watch Series 11
• Mac leases start at $24.99 per month for MacBook Air
• iPad leases start at $15.99 per month for iPad mini

On the surface, this looks like a great deal. People can now lease any Apple product — including Macs with custom specifications — and upgrade their device at the end of the lease. They can also buy it, but then they’ll have to pay the remaining cost: Leasing a $2,000 MacBook Pro for 36 months only costs $39 a month, meaning someone would have to pay nearly $600 at the end of their term to own the product. At that point, you might as well just upgrade at no cost. These leases accrue no interest, either, so it seems like a win to lease a product like this and invest the money somewhere. That’s the pro-Apple Upgrade argument, at least.

I don’t like these leasing programs. I never used the now-discontinued iPhone Upgrade Program, despite buying a new iPhone every year, and this is the same reason why I encourage everyone I know to never purchase an iPhone through a carrier contract, even if they’re “handing them out for free.” There’s a monetary aspect to this — people living above their means; this program will make some people likely to purchase a device they can’t afford and become delinquent on their payments — but also a societal one. Why can’t we own anything anymore? Why is it that houses are so expensive that people are better off renting in most markets? Why are video games going digital-only, with software licenses that stipulate that you don’t actually own the games?

There are undoubtedly people who will benefit from this program. If Apple Upgrade lets you buy a computer that kickstarts your career, by all means, enjoy it. (Just please don’t buy a computer you couldn’t afford if push comes to shove.) But I take issue with not being able to own my smartphone — I don’t want a tool that only costs a thousand dollars to be tied to a lender who could theoretically take it away at any moment. That’s a dangerous precedent; at what point will everything we know and love be reduced to installment payments? Someone somewhere must draw the line. We have leases on cars because they cost tens of thousands of dollars — few people have that much in cash. But have we made it so far south in society that people need to lease computers?

This program rubs me the wrong way. Maybe it doesn’t for you — and that’s completely fine. But if it doesn’t, maybe you really will own nothing and be happy.

Apple Newsroom:

Apple and Ford today announced that Apple Maps will be integrated directly into Ford’s upcoming Universal Electric Vehicle (UEV) Platform through Apple’s new MapKit for Automotive SDK. Coming to Ford’s UEV Platform in 2027, this integration will deliver a beautiful and easy-to-use navigation experience powered by Apple Maps directly to the vehicle’s displays. Road-level Maps information will also enable Ford’s Latitude AI team to build a seamless hands-free driving experience.

Leveraging Apple’s new MapKit for Automotive SDK, Ford’s Universal Electric Vehicle Platform will offer drivers turn-by-turn directions using natural language, real-time traffic and incident information, intuitive search featuring detailed place cards, and routing options to help users easily find the best route to their destination. Additionally, Ford UEV drivers will benefit from an intelligent EV routing functionality, including battery preconditioning. Ford will also use road-level information from Apple Maps as part of the development of its next-generation BlueCruise hands-free highway driving capability to deliver a more seamless on-ramp-to-off-ramp experience.

Apple services have historically been sold as complements to Apple hardware: Apple Maps, for a decade, had been limited to Apple devices, replacing Google Maps. That is no longer the case; Apple TV is a canonical example of Apple’s interest in broadening the Apple services market. Similarly, this new MapKit SDK — short for software development kit — is an intentional expansion of Apple’s services market following the abject failure of CarPlay Ultra, a version of CarPlay meant to consume the entire car software experience. Even CarPlay’s most fervent supporters, like BMW and Ford, haven’t adopted CarPlay Ultra because it exerts too much control over a driver’s experience. The CarPlay Ultra gambit was clearly an effort to make something out of the Apple Car project, also a failure.

Ultimately, I think the CarPlay Ultra fiasco is indicative of the two opposing yet symbiotic forces within Apple: the product people and the services people. The product people want Apple to own as much of the “stack” as possible: the hardware, the software that hardware runs, and the services that software sells. They wanted to build a car, make software for it, and sell services through that software: that was Project Titan, the car project, in a nutshell. That is fundamentally the same strategy that governs the Apple Watch, MacBook Neo, even the iPhone. The services people, like those in charge of Apple TV and its content acquisitions like Formula 1 and Major League Soccer, don’t believe in that because they’d rather make money through advertisements and subscriptions. They paid hundreds of millions of dollars in upfront costs for MLS and F1 to sell more subscriptions, even to people who have never owned an Apple device.

The services people won here, largely because the product-driven CarPlay Ultra / Project Titan strategy — to own as much of the software experience as possible — failed. No car manufacturer was interested in that. Perhaps consumers would’ve been, since CarPlay by itself is overwhelmingly popular by Apple’s numbers, but it didn’t matter anyway because the difference in experience for iPhone users and non-iPhone users was too stark. (Not to mention, it was too much work for very little tangible benefit on the manufacturers’ end.) So now, Apple Maps — just like Apple Music in Tesla, General Motors, and Rivian vehicles — is a service built to make money independently. It doesn’t matter whether someone owns an iPhone or not, because they’ll still be forced to use Apple Maps in their Ford vehicle. And most importantly, they’ll be forced to look at Apple’s advertisements coming to Apple Maps soon.

The ads part is a tragedy because it signals a definite end to Apple’s product-driven mindset. Before Apple started putting ads in Apple services, they were also Apple products — you buy a subscription to Apple Music. Now, Apple services are partially ad-driven enterprises, where your use of the service itself draws revenue. In creating the MapKit for Automotive SDK, Apple doesn’t care about people spending money at the Apple Store or on in-app purchases. Apple isn’t delivering a product to consumers as much as it’s guaranteeing engagement to ad buyers. The consumers are not the primary consumers; corporations who pay Apple are. This is against the very philosophy Apple in many ways was founded upon: making high-quality products for consumers willing to pay premium prices. Modern Apple would probably object to the characterization that ads in Apple services cheapen the experience, but it’s true: ads in Apple Maps do not make for a premium experience.

The new Apple doesn’t seem to care about that. It’s uninterested in delivering a premium experience, and it’s uninterested in asking for your money to deliver that experience. Ergo, the MapKit for Automotive SDK.

Ashley Capoot, reporting for CNBC:

U.S. Treasury Secretary Scott Bessent on Tuesday said the Trump administration will look into whether Chinese artificial intelligence models have been distilled from American models, stating that the government does not support “IP theft.”

Chinese open-weight models are gaining steam against leading offerings from American companies like OpenAI and Anthropic, sparking concerns from tech executives and government officials about the durability of the U.S. lead in the AI race. Moonshot AI, a Chinese startup, released a model called Kimi K3 earlier this month that outperforms those companies across some industry benchmarks. Open weight refers to models whose final trained parameters are publicly released for download, while the underlying code and training data remain private.

“If we see, especially that overseas models are stealing from our great companies, we have the ability to sanction them because of this theft,” Bessent told Fox Business’ “Mornings with Maria” on Tuesday.

Bessent said the technical term for this theft is called distillation, which is an AI training method where a smaller, less capable model is built using outputs from an existing, stronger model. Anthropic sent a letter to the U.S. Senate Committee on Banking, Housing, and Urban Affairs last month alleging that the Chinese tech company Alibaba had carried out the “the largest known distillation attack” against it to date.

If distillation — training on data that doesn’t belong to the Chinese labs — is a sanctionable offense, then why isn’t pre-training? How is it fully legal for Chinese companies to use training data published by American citizens on the internet? This whole argument is bogus, and it’s quite evident that Bessent knows very little, if anything, about what he’s talking about. AI models are built on the idea that training a computer on the open internet is fair use — that pre-training is transformative enough under fair use doctrine, not “stealing.” American companies can train their models on Chinese text and vice versa because pre-training is inherently transformative, an argument I’m quite sympathetic to. I think that if we built a time machine back to 2022, a permission or compensation structure should’ve been created, but alas, this is the system we’re stuck with. The world’s copyright system is not suited for AI pre-training.

Back to the Bessent argument. Anthropic, and perhaps OpenAI, are perturbed that Chinese models — like Moonshot’s Kimi K3 open-weight large language model — were trained via distillation. Kimi K3 is cheaper than Claude Opus 4.8 and GPT-5.6 Sol, yet almost matches GPT-5.6 Sol in overall intelligence and beats Opus 4.8 entirely. Kimi K3 comes just shy of Claude Fable 5, a model over three times the price. While Anthropic can’t even be compelled to offer Fable 5 access to some of its paying customers, Kimi K3 offers similar performance at a fraction of the cost — but it was built by distilling Anthropic’s models. Anthropic’s view, which it has surely expressed to the government, is that this is an adversarial nation subsidizing AI development, stealing the secrets of American AI labs, and building a compelling product for much cheaper. From that perspective, Moonshot and China look guilty.

But that’s a pacifist view; Anthropic is wailing for pity from a government that has treated it abysmally. Just Tuesday, a judge approved a billion-dollar settlement between Anthropic and a litany of authors after it pirated books to train its models on — is that not “stealing?” Is Anthropic not one of the most blatant copyright infringers of the modern era? It’s quite obvious here that Anthropic is crying wolf not because China gained some unfair advantage in its training process, but because Anthropic is so upset that it wasted perhaps billions of dollars in subsidized tokens all for its users to prefer a foreign competitor’s clearly superior model. The problem here was never about morality or copyright or distillation; the AI labs are morally bankrupt, and they know that. If they didn’t, they wouldn’t be cutting billion-dollar checks to authors.

So where do we go from here? I think the solution is quite obvious: Anthropic must start distilling its own models. Train a massively expensive competitor to Fable 5, distill a new version of Opus on that model’s reasoning traces, and ship the new Opus at a much lower cost. We’re reaching a point in the AI industry where cost is a massive factor in the models enterprises and individuals use, as reasoning traces become more expensive. Yes, pre-training is currently the most expensive part of releasing a new model, but we’re already seeing the shift toward inference and post-training. New model releases nowadays are not new pre-training runs; GPT-5, the last “major” AI model from OpenAI, was a heavily post-trained GPT-4o from spring 2024. As LLMs mature and reasoning tokens become more valuable, inference will be the biggest operating cost, not pre-training. Train one model and distill three others, then offer inference at a competitive price. Distillation — from China and by the American labs themselves — is in the AI industry’s best interests. It saves on pre-training costs and leaves more room to make healthy margins on inference.

Marcus Mendes, reporting for 9to5Mac:

According to The Information, Apple has been exploring potential acquisitions of semiconductor startups to “boost its efforts to build server chips for running AI.”

From the report:

In recent months, the iPhone maker has talked with bankers about possible deals. It has also approached semiconductor startups to gauge their interest in selling themselves, the people said. Apple’s hunt for chip acquisitions comes as the company struggles with the performance of its own internal AI servers, which currently run on internally designed M2 Ultra chips.

The Information says Apple’s next-generation server chip, code-named Baltra, has slipped past its planned 2026 debut. In the meantime, Apple is using M2 Ultra-based systems for some of its own AI processing, while the more demanding tasks are handled by the Gemini-based model powering the new Siri, which runs on Nvidia GPUs in Google Cloud.

A big acquisition would be a departure from Apple’s usual M.O. of buying smaller startups from time to time, but it wouldn’t be unprecedented.

It would indeed be unusual for Apple to purchase a Silicon Valley start-up specializing in artificial intelligence processors, when Apple arguably makes the best consumer AI chips. As Bloomberg has reported extensively, Apple’s consumer processor strategy — for high-end Mac models, at least — has shifted considerably toward AI. People like buying Mac Studios and Mac minis to do local AI inference — they’ve become popular as cloud computers and mini data centers. Per The Information’s reporting, Apple’s internal processors are also on that trajectory, albeit delayed for unclear reasons. Apple’s processors aren’t just fast and capable of AI inference, but they’re extremely efficient, which makes them relatively inexpensive to use in the long run. It’s no wonder why Apple has retaken the No. 1 market capitalization, surpassing Nvidia on Friday.

Regardless, this news is quite interesting because it proves Apple is intent on shipping more powerful, capable models in the future — perhaps ones that can write code or perform agentic tasks. It wants people to be able to run those models on their own devices — hence why the company is testing Mac Studios with 1.5 terabytes of memory and skipping high-end M6-generation chips entirely — and to eliminate its reliance on Google Cloud, or maybe even Google altogether. If Apple were to buy such a company, it could probably pre-train its own models: a lack of compute was one of the key limitations that led to the Google partnership. Apple’s new leadership doesn’t see AI as a fleeting trend. It is finally taking it seriously, something we couldn’t say about the AI team under John Giannandrea, the machine learning chief who was stripped of his responsibilities and replaced by Mike Rockwell, the executive previously in charge of Apple Vision Pro.

I think Apple should lean into efficient, low-cost AI inference on both the hardware and software fronts. Siri AI clearly emphasizes on-device processing, and the company’s future Apple silicon plans do, too. Readers of this blog know that my single biggest qualm with the AI industry for now is that its economics aren’t rooted in logic. Anthropic is compute-constrained, so much so that they’re under heavy competition from Chinese AI labs that can offer inexpensive tokens and relatively the same performance as Anthropic’s best models. OpenAI is deathly unprofitable, leading some pundits to believe that its economics will spell its demise. Compute is the biggest story of Silicon Valley this summer, whether it’s skyrocketing memory prices for consumer products or unusual deals like Meta selling compute to Anthropic.

Whatever happens here — if Apple chooses to buy a compute start-up or not — the fact that it is even entertaining the idea is proof that it sees Apple silicon as its golden ticket in the AI space. As open-weight models get smaller and more powerful, people will buy more powerful Macs marketed as the best for AI inference; as the frontier AI labs become more compute constrained — and their flawed economics catch up to them — people will look to Apple’s models and products. Siri AI is merely the beginning of the Apple AI story.

Mark Gurman, reporting for Bloomberg:

OpenAI’s much-anticipated push into consumer devices is slated to begin with a mobile, screen-free smart speaker designed to be a new type of home computer for the AI era, according to people familiar with the matter.

The product — still under development — is meant to serve as a humanlike AI companion that lives in the home, said the people, who asked not to be identified because the project hasn’t been announced. It will help control smart-home appliances, play media, answer questions, respond to messages and tap into the range of capabilities offered by OpenAI’s ChatGPT, they said.

Though the new product resembles a speaker, OpenAI internally describes it as the first of its kind: a computer built for AI to help make busy people more productive. It includes a camera and other sensors that help it understand a user’s surroundings and context, as well as advanced AI models beyond those available on conventional smart speakers.

Remember Jibo? Jibo, developed by a professor at the Massachusetts Institute of Technology after a successful Kickstarter campaign, was an animated voice robot that would move around with a motorized base and use its camera to detect facial expressions and gestures. Jibo came years before the modern large language model, and its use was limited, but I’d imagine this device from OpenAI to be much like it. Like Jibo, this is just not a breakthrough consumer product. It’s a Bluetooth smart speaker with a motorized base — which Gurman describes as “mechanical elements that can move on their own” — and ChatGPT built in.

You can already buy a smart speaker with an LLM for just $100: it’s the Google Home Speaker, and — news flash — it’s not a revolutionary product. It’s certainly not revolutionary enough to warrant buying Jony Ive’s hardware company and poaching trade secrets from Apple. But none of this even considers how unfeasible it will be to have a hardware product from OpenAI — a company almost universally taken with distrust — listening and peering into people’s homes all day long. I’d be hard-pressed to find a single person who wants that. There are people on the streets irate about OpenAI data centers being built in their backyards; on what planet will those people put an OpenAI product in their homes?

OpenAI has spent billions of dollars on this hardware venture. It has upended the technology industry — it has decimated entry-level jobs, transformed computer science education, and sowed doubt in tech as a whole. People are down on artificial intelligence and technology writ large. For this product — and OpenAI as a company — to be successful, it must transform not only its public image, but that of the technology it wants to sell. I have a hard time believing a Bluetooth smart speaker designed by Ive with ChatGPT built in is a serious solution to that problem. Maybe it’s the most beautiful speaker in the world. Maybe it’s made with gold or some opulent frills. That doesn’t change the fact that OpenAI has a gargantuan favorability problem.

OpenAI also has a money problem. People do not like paying for AI. Only a small fraction of ChatGPT users are paying subscribers, and most of those people are on the lowest subscription tiers. The people who do pay heavily for AI burn subsidized tokens so hard that Sam Altman, the company’s chief executive, is holding back on an initial public offering until the company’s finances are more stable. What company that is struggling to sell consumers on a $20 subscription and enterprises at base rates for its models could possibly think it could sell hardware? The one popular product OpenAI makes, ChatGPT, is not profitable. It can’t even persuade people to pay for its flagship innovation, let alone a designer smart speaker.

I really don’t want to be Steve Ballmer. “$500? Fully subsidized? With a plan?” But I have a feeling this take will fare much better than my take from last year. Over a year later, Apple doesn’t look bad anymore; OpenAI does.

Chance Miller, reporting for 9to5Mac:

Apple has filed a lawsuit against OpenAI today, accusing the company of trade secret theft. Specifically, Apple alleges that its former employees have stolen trade secrets “for the benefit of OpenAI.”

“This case is about Apple’s former employees stealing Apple’s trade secrets for the benefit of OpenAI. Apple brings this suit to put a stop to it,” the lawsuit says…

The complaint, filed in the U.S. District Court for the Northern District of California, alleges that Tan used insider knowledge of Apple’s confidential projects to grill job candidates in interviews. Additionally, Tan directed job candidates still working at Apple to bring actual Apple hardware components and samples for “show and tell” sessions.

Furthermore, Apple says a candidate began “screenshotting and downloading files relating to a highly confidential Apple project” hours before interviewing with Tan, who then “solicited more information about that same Apple project” once the interview started. This became an “established pattern,” Apple says.

Tan also allegedly possessed and distributed an internal Apple “Need to Know” document to new OpenAI hires before they gave their notice to Apple. The document included Apple’s departure security protocols. As part of its investigation, Apple found a “pattern by employees who depart for OpenAI of taking steps to evade the security processes intended to protect Apple’s confidential information.”

I read the full complaint. Some notes:

• Chang Liu, an ex-Apple employee who now works for OpenAI, allegedly (a) failed to return all of his company-provided devices before he left, (b) used an exploit to access Apple’s internal files, and (c) downloaded them while working for OpenAI.

• Tang Tan, OpenAI’s chief hardware officer — and Jony Ive’s right-hand man at OpenAI’s “io” hardware division — allegedly tells potential employees during interviews to bring in unreleased Apple hardware for “show and tell.” And as Miller notes, Liu and other ex-Apple employees suggested new hires “prepare” for their OpenAI interviews by studying unreleased Apple products.

• Tang and Liu only got caught after they used work-provided devices to — in some cases — brag about their actions.

• Over 400 ex-Apple employees work at OpenAI.

• OpenAI allegedly contacted an Apple hardware supplier and asked them to “perform Apple’s proprietary, trade secret processes for OpenAI’s benefit.”

I’m not really surprised at any of this. There seems to be bad blood between the two companies — OpenAI’s models weren’t spoken about once during the Worldwide Developers Conference State of the Union in June — and OpenAI had been loosely threatening legal action even before WWDC. Moreover, OpenAI has never come across as a particularly honest corporation. Sam Altman, its chief executive, is a seasoned liar and manipulator; OpenAI employees are known for being narcissistic online; and the company doesn’t seem to attract very honest, forthcoming fans or workers.

But it does seem illuminating that OpenAI has such an inflated image of itself that it thought it could successfully evade one of the most litigious and secretive companies in the world. Apple does not let such behavior go unpunished — it never has and it never will. Everyone knows not to mess with Apple Global Security, except, clearly, OpenAI. The OpenAI people clearly have become accustomed to a privileged position where they feel untouchable. They were handed an inconceivable amount of free cash and thought it could protect them from anything, including immoral and illegal behavior. Maybe it will, but it doesn’t seem likely.

The only solution to OpenAI’s immoral behavior — and there are so many instances of it — is to force them to start turning a profit. It will happen eventually; the investors will get tired of losing money, and they’ll put pressure on the company. Perhaps this lawsuit is a step closer to that reality.

OpenAI, on X:

Introducing ChatGPT Work, a new agent in ChatGPT powered by Codex and GPT-5.6. It can take action across your apps and files, stay with a project for hours if needed, and turn a goal into finished work. It’s a whole new way to get work done.

ChatGPT Work is powered by GPT-5.6. GPT-5.6 makes ChatGPT state of the art at reasoning through complex tasks and creating materials that match your templates, reference files, and preferred style. Just describe the outcome you want, without having to spell out every step to get there.

On web and mobile, ChatGPT Work is rolling out today for Pro, Enterprise, and Edu plans. It will roll out to Plus and Business plans over the next few days. In the ChatGPT desktop app, Chat, Work, and Codex are available on every plan, including Free, and is available globally to download on Windows and Mac.

Codex app users can update their app as usual — it will become the new ChatGPT desktop app.

I fear OpenAI’s employees have lost the plot. The old, native ChatGPT app for macOS still exists and is renamed “ChatGPT Classic” after updating to the latest version. The Codex app, after updating, is renamed “ChatGPT.” The unfortunate side effect of this is that if you update the Codex app before the ChatGPT Classic app, the two names will conflict, and macOS will refuse to open the Codex app. This happened to me; I had to reinstall the Codex app from the OpenAI website to fix the issue.

Now I have two ChatGPT apps on my Mac: ChatGPT Classic and ChatGPT, née Codex. The ChatGPT Classic app has languished for years now, but when it was announced, it truly was incredible. It’s beautifully crafted with care, down to the little details. There’s even a mode to let ChatGPT peek into your apps like BBEdit or TextEdit — this is how we used to code with artificial intelligence before Codex and Claude Code! The Codex app is made with Electron, but I’ve always regarded it as one of the best Electron apps on the Mac. It’s not perfect, but superior to Claude in every dimension.

The new update ruins months of good favor with the Codex app. It quite literally benefits nobody. There are now two primary modes in the ChatGPT app: Codex and ChatGPT Work. Codex is the same; Work is just a simpler version of Codex, similar to Claude Cowork. I don’t even know why this mode exists — Codex has always been simple enough for non-technical people to use anyway. It’s also redundant in the cloud (iOS and the web) because it’s only limited to using plugins, which the standard ChatGPT mode can do as well. There’s almost no end-user benefit to using ChatGPT Work on the web or on iOS.

The actual ChatGPT interface — what the app is named for! — is hidden in a mini-window accessed from the sidebar. This is the most absurd, counterintuitive user interface OpenAI has ever conceived. If the app is literally named “ChatGPT,” how is ChatGPT not the main interface? Does OpenAI see ChatGPT Work as the replacement for ChatGPT, and if so, why doesn’t it make that clear? And to make matters worse, there’s no consistency in the models across interfaces. Work and Codex have GPT-5.6 Sol, Luna, and Terra — the three sizes of GPT-5.6 — while ChatGPT only exposes the Instant, Medium, and High reasoning levels. Medium and High are GPT-5.6 Sol, though that is not indicated in the interface.

The ChatGPT app doesn’t open ChatGPT anymore, and the models once again make no sense. Here’s a handy chart of the models and their reasoning options across ChatGPT modalities:

I haven’t heard from a single person happy with Thursday’s changes. Codex users are upset because their app has been renamed; ChatGPT users on the Mac are upset because the new ChatGPT app really isn’t ChatGPT at all. The only people seemingly pleased with this “work” are OpenAI employees themselves, who seemingly don’t understand anything about marketing or communications. But I’m supposed to believe this company is worth a trillion dollars.

A correction was made on July 13, 2026, at 5:30 a.m.: Previous versions of this post stated that GPT-5.6 Terra and GPT-5.6 Luna were available in ChatGPT Chat. This is incorrect; these models are limited to ChatGPT Work and ChatGPT Codex. Free users — and paid ones who select the Instant reasoning effort — are defaulted to GPT-5.5 Instant in ChatGPT Chat. In ChatGPT Work and Codex, free users are limited to GPT-5.6 Terra and GPT-5.6 Luna. Plus and Pro users can use GPT-5.6 Sol in ChatGPT Work, ChatGPT Chat, and Codex. Chart:

Mark Zuckerberg, Meta’s chief executive, at a Meta town hall reported by Katie Paul and Courtney Rozen at Reuters:

In retrospect, he said, the “trajectory of the agentic development over at least the last four months hasn’t really accelerated in the way that we expected,” and ​that the company’s bets on the new structure “haven’t come to fruition yet.” Zuckerberg was referring to AI agents, automated systems that can ​execute tasks on behalf of a user.

Conversations he was having “with our top people” when they started planning the restructuring in January and February “were that they were worried that we weren’t going to move fast enough to adapt,” Zuckerberg said.

At the time, he said, executives were “super optimistic” about tools like Claude Code from AI startup Anthropic.

The self-created tragedy of Meta is that the company is loath to invent new products. Instead, Meta’s management more or less relies on “vibes” to govern its decisions, and those vibes are often either wrong or far too late. The most pertinent example of the former is the ill-fated metaverse, which was developed solely on the (unbelievable) whim that the pandemic would last forever — or at least far longer than it actually did — and people would become accustomed to replacing in-person interaction with virtual reality. It was precisely at this moment, roughly around mid-2020, that Meta (then Facebook) disintegrated from a social media company into a Ship of Theseus that still technically operated its core social platforms but fundamentally was distracted by a red herring. Vibes-based management.

As I wrote in my now infamous “Meta-stasizing Cancer of Indirection” piece, Zuckerberg did not learn from this disastrous failure as the artificial intelligence boom kicked off in 2023. Long story short: Zuckerberg threw his company into turmoil because he was too late to identify that the metaverse was an abysmal failure. By the time he did, the AI boom was already in full swing, and Meta was thoroughly left out. This strategic failure, coupled with Zuckerberg’s arguably incompetent management style, left employees either out of employment, directionless, or both. It is just impossible to run a company on a whim — the metaverse was a distraction, and so was AI because Meta was far too late and improperly organized. Vibes-based management.

Zuckerberg yet again plunged his company into chaos after the success of Claude Code in December 2025. Knowing the company was behind in developing AI products after observing the rise of agentic coding, Zuckerberg effectively put Alexandr Wang, the chief of Meta’s AI division, in charge of the entire company. The only thing Wang did was wrongly determine that all human programmers were a waste of time and money and that it would be better to fire them and spend the freed-up cash on talented AI engineers who would unwittingly develop their own replacements. So that’s exactly what Zuckerberg did, per Wang’s hunch: he fired thousands of employees, put AI in charge of content moderation, and mandated that the remaining Meta workers install spyware that would track their computer use to train an agent that could take their job. Vibes-based management.

I can’t tell if Zuckerberg is dimwitted or just evil. The problem during the first era of the AI boom (circa 2023) was indeed that Meta was too slow to identify the metaverse flub. But that was no longer Meta’s problem entering the agentic coding era: The problem, rather, was that Meta had no coherent strategy. The last thing it should’ve done was “move fast enough to adopt” because “adopting” was not the answer to Meta’s problems. AI-assisted programming has developed in the last six months — contrary to Zuckerberg’s claim that it “hasn’t really accelerated” — but indeed not in the way Meta expected, because Meta’s vibes-based management this time was just plain wrong. AI never had the potential to replace so many workers at an instant. The vibe was — unlike in 2023 — not late, but wrong entirely. And I’m confident in saying only a fool could have lent credence to that laughably incorrect theory.

I’d say getting fired by Meta is like catching the last plane out of Vietnam, even in this ruthless job market.

Marko Zivkovic, reporting for AppleInsider:

For the U.S. variant of the iPhone 18 Pro, which will feature mmWave compatibility, Apple seemingly plans to use Qualcomm modem hardware.

Multiple Qualcomm components, including the SDX80M, SDR875, QDM8771, QDM8720, PMK75, PMX75, and QET7100A, are referenced in a bill of materials related to the iPhone 18 Pro model Apple plans to sell in the United States.

As for the iPhone 18 models which will be sold elsewhere, Tata documentation suggests these configurations will use Apple’s proprietary C2 modem. While this approach may sound unusual, there is at least one possible explanation.

Apple’s current in-house modems, the C1 and the C1X, do not support 5G mmWave, and it looks as though the C2 will continue this trend. Until Apple develops a modem compatible with mmWave, it looks as though the company will offer mmWave support to iPhone 18 Pro users by using Qualcomm hardware.

I think Apple made the right choice in developing the C2 modem without support for 5G millimeter wave (“mmWave”), the technology that enables ultra-high-bandwidth connections in limited areas. Millimeter-wave signals — known by carriers as ultra-wideband — are extremely high-frequency and can be interrupted by even atmospheric attenuation. They cannot permeate through walls or people and do not work across long distances. This makes them unsuitable for most cellular transmissions; carriers instead use the lower-frequency C-band to transmit slightly slower but more reliable 5G signals. (Confusingly, carriers also refer to this as “ultra-wideband.”) The three major carriers — Verizon, AT&T, and T-Mobile — have installed 5G ultra-wideband antennas in city downtowns across the United States. Some sports arenas and airports have also been outfitted with the technology to limited success.

During Apple’s “Hi, Speed” October 2020 keynote, which introduced iPhone 12 with 5G, the company incessantly touted 5G ultra-wideband as the future of mobile communication. So let’s take a step back for a minute: Was the rollout of 5G ultra-wideband all that successful? Is it really everywhere? For one, Verizon, with which Apple partnered during the keynote, has since removed the map on its website that showed where 5G millimeter-wave was available. The coverage map now only marks certain metropolitan areas as “5G ultra-wideband capable” cities, while refusing to discriminate between the much slower C-band and millimeter-wave connectivity. There is, however, a map buried on a subdomain (gismaps.verizon.com) that shows the millimeter-wave rollout, and it’s quite underwhelming.

The map shows that Verizon still has not rolled out 5G millimeter-wave on even some of the most population-dense Manhattan streets. This is not malfeasance: It’s more likely that Verizon, sometime in the last six years, determined that it was either impractical or impossible to bring 5G millimeter-wave to most streets and instead slowly phased out the advertising. Nowadays, Verizon hardly even mentions 5G because it is, even on C-band, mostly a waste of battery. I have never once connected to millimeter-wave in these six years — despite living in an “ultra-wideband capable city” — and I assume most Americans are the same. If not for New York, where would people be most likely to take advantage? 5G millimeter-wave was a profound waste of everyone’s time and money, and the carriers know it. Betteridge’s law of headlines strikes again.

What isn’t a waste of time and money, though, is Apple’s C-series modems, which have performed equally as well as the Qualcomm modems — if not a bit better — while using less energy. If the carriers, Apple, and customers all somewhat agree that 5G millimeter-wave is a profound waste of resources, why even ship it at all? Carriers don’t even make a distinction between the two flavors of ultra-wideband anymore, and almost no one who buys iPhone 18 Pro will even know the difference. How many people are standing in Times Square running internet speed tests? I think people, including the carriers, would be happy to trade a technology hardly anyone uses for an hour of extra battery life a day with the C2 modem. I think it’s a mistake that Apple hasn’t recognized this and used the C2 in all iPhone models.

Hartley Charlton, reporting for MacRumors:

After temporarily taking it down earlier today, Apple’s online store is back up with a series of product price increases. The changes are as follows:

• HomePod mini: $129, up from $99 (+$30)
• HomePod: $349, up from $299 (+$50)
• Apple TV: $199, up from $129 (+$70)
• iPad: $449, up from $349 (+$100)
• iPad mini: $599, up from $499 (+$100)
• iPad Air: $749, up from $599 (+$150)
• iPad Pro: $1,199, up from $999 (+$200)
• MacBook Neo: $699, up from $599 (+$100)
• MacBook Air: $1,299, up from $1,099 (+$200)
• MacBook Pro: $1,999 up from $1,699 (+$300)
• iMac: $1,499, up from $1,299 (+$200)
• Mac mini (M4 Pro): $1,599, up from $1,399 (+$200)
• Mac Studio (M4 Max): $2,499, up from $1,999 (+$500)
• Mac Studio (M3 Ultra): $5,299, up from $3,999 (+$1,300)
• Vision Pro: $3,699, up from $3,499 (+$200)

I am humbled to admit I was wrong in my post earlier in June about these price increases: I predicted they wouldn’t take effect until new products were announced and that the iPhone (and Apple Watch) would be the first to take the hit. The iPhone and Apple Watch did not receive price increases on Thursday, perhaps in anticipation of the new models in September. Every other product, however, saw preemptive double-digit percent increases. I’m not willing to bet anything on it, but I feel like this indicates that most of these products — including the Apple TV and HomePod mini — won’t be updated until late in the fall, or maybe even next year. I don’t believe the (somewhat sensible, if not credible) theory that Apple is increasing prices to “get people used to” the higher price tags before new models are released later this year. (I’ll return to product cycles in a bit.)

Apple makes exceptional margins on its products, close to 40 percent excluding Services revenue. (Including Services, it makes about a 45 percent margin.) Some memory prices have increased by 100 percent year-over-year, but Apple has locked-in contracts with RAM manufacturers dating back years. It’s undeniable that despite that, Apple’s margins have taken a severe hit in recent months due to the RAM shortage — so much so that it may hinder research and development — but Thursday’s news seems to indicate that the company wants to return its margins to those industry-leading levels, not meet somewhere in the middle. I think that’s highly unrealistic, and Wall Street seems to agree, at least preliminarily: Apple’s stock dropped 6 percent after the news broke.

There are two sides to this coin if you’re Apple’s chief executive. If Apple raises prices, people will save their money and keep their existing Apple products, which work reliably for years, causing the company’s profit to tank in the upcoming quarters. But if Apple doesn’t raise prices, or raises them less heavily, its profits would also fall, and it might have to raise them even more aggressively in the future anyway just to maintain any profitability. Apple’s C-suite evidently opted for the short-term blow, hoping that people would accept the price increases in the months ahead. Wall Street, however, did not run Apple stock into the ground whenever the market rate for RAM increased (i.e., when Apple’s margins declined) — it believed, somewhat convolutedly, that maintaining prices and taking a (perhaps temporary) hit on margins would still be more profitable in the long run. It instead tanked the stock on Thursday.

I tend to agree with Wall Street here. These price increases are genuinely unconscionable. $250 for an Apple TV with Ethernet, whether it runs Apple Intelligence or not, is ludicrous. The iPad Pro is not worth $1,200. And Apple simultaneously increased prices on its refurbished products — which it does not have to pay to manufacture — while maintaining trade-in values for customers who wish to upgrade. On the surface, especially to anyone not well-versed in RAM supply-and-demand economics, these price increases look like the most blatant cash grab in Apple history. Especially for a company known worldwide for its historic profit margins. An M5 Max MacBook Pro now costs $4,100 without any memory and storage upgrades — that’s a $500 price delta overnight. Apple products, for a short while, were the most price-competitive on the market, but they are no longer.

I think even Apple knows hardly anyone is in the market for a $7,000 MacBook Pro with a modest amount of memory and storage. From Mark Gurman at Bloomberg, just a while after the news broke:

The company, currently on its M5 series, plans to debut a base M6 processor as early as this year for entry-level Macs, according to people with knowledge of the matter. But in a first, the company will skip higher-end versions of that chip, said the people, who asked not to be identified because the plans are private.

Apple instead aims to introduce its next Pro and Max chips with more advanced computing and graphics power in 2027 as part of a new M7 generation, according to the people.

Apple was, and maybe still is, heavily rumored to announce new high-end MacBooks Pro with organic-LED touchscreens in the fall. But it appears Apple has either gotten into a fight with Taiwan Semiconductor Manufacturing Company over pricing and/or determined it won’t be able to ship enough units at these updated prices for manufacturing them to be worth it. Either Apple fully delays the new MacBooks Pro to late 2027, which would be truly remarkable as it would be over an 18-month gap between revisions, or it will ship them with M5 Pro and M5 Max processors this fall anyway. It’s undeniable that the price increases — both on the supplier and consumer sides — will have some effect on product timelines in the short term.

One final note on this debacle: The RAM problem will likely get worse before it gets better, and I can see this sparking massive backlash to artificial intelligence development. It is hard to describe an aspect of modern life that AI-powered chatbots have not shattered: price increases for computers and video game consoles, a horrible job market, and a loss of creativity in media are all notable consequences of AI companies’ incompetent (and uncharismatic) leadership and inflated valuations. If this isn’t the final nail in the coffin for the AI industry, I’m not really sure what is.

A correction was made on June 25, 2026, at 9:10 p.m.: An earlier version of this article stated that the M5 Max MacBook Pro’s price increased by $600. It was actually $500. I regret the error.

Mike Isaac and David Yaffe-Bellany, reporting for The New York Times:

Polymarket and Kalshi, prediction markets where users can bet on outcomes as varied as the Super Bowl and the length of the State of the Union address, have been some of the fastest-growing destinations on the internet.

Mark Zuckerberg has noticed — and he wants in on the action.

Mr. Zuckerberg, the chief executive of Meta, recently dispatched a small team at his company to create a smartphone app similar to Polymarket and Kalshi, two employees with knowledge of the matter said. Users would not wager money, and the app would probably rely on a video-game-like points system instead, one person said, though the company had not ruled out the eventual use of real money betting.

My first thought was that Zuckerberg is the most blatant and prolific intellectual property thief in Silicon Valley. But that’s hardly the most important news here: The world’s most famous social media company is about to launch a gambling app for billions of people.

Prediction markets have taken hold of the United States unlike any modern social product. The FIFA World Cup broadcast is littered with advertisements from Polymarket and Kalshi, and in states where they’re legal, sports betting companies buy out nearly all of the mid-match advertising slots. America clearly has a gambling problem. The premise is somewhat enticing: bet on real events, like sports or politics, and win some money. These “markets” require no experience or specialized knowledge and can potentially pay out thousands of dollars. Kalshi and Polymarket have even positioned themselves as an alternative to political polling by littering the internet with shady, scantly disclosed news sponsorships.

But this is about Meta, one of the richest and most disreputable companies in Silicon Valley. If Meta wanted, it could buy Kalshi and Polymarket, turn them into a billion-user monopoly, and turn the globe into a mess of young gamblers in a matter of months. Knowing Zuckerberg and his history of building snide gimmicks into Instagram and Facebook — so much so that his company lost a lawsuit against those gimmicks — I wouldn’t be surprised if this is the game plan for “Arena,” this new prediction market app. Meta’s apps have always functioned as high-risk, high-reward social platforms, and Arena would be yet another.

The “points system” will probably be how the app works, but that’s not to say real money won’t be involved. (Real money will always be involved; points are useless for Meta’s flailing stock price.) I think Meta would sell those points for a fee through an in-app purchase, or perhaps require people to watch advertisements to earn more. This is how questionable “free-to-play” mobile games became the crown jewel of the App Store — they litter their apps with dark patterns to force people to buy “gems” or “coins.” This is clearly Meta’s overall business strategy, leveraging the wealth of information it has on people from their Instagram and Facebook usage patterns to devise clever bait.

I wouldn’t be surprised if this app launches in the fall, right as the midterm election season begins. It only seems natural for a company like Meta to use its inordinate power to sway an election that could have disastrous consequences for the company.

Rolfe Winkler, reporting for The Wall Street Journal (Apple News+):

Apple plans to raise prices on its products to offset the surging costs of memory and storage chips, Chief Executive Tim Cook said in an exclusive interview with The Wall Street Journal.

“Unfortunately, price increases are unavoidable,” he said. “We’re doing our best to mitigate the huge increases that are being passed to us, and we’ve been trying to shield our customers from the increases, but the situation has become unsustainable.”

Cook declined to offer details on the timing or scale of the planned price increases, nor which products will be affected. Apple’s next major product launch is likely to be in September when it releases the iPhone 18 lineup, expected to include a new foldable iPhone.

The memory shortage in particular has been debilitating for the tech industry. A new Raspberry Pi — a small computer with 4 gigabytes of memory — costs $150. Similar models used to cost around $100. The shortage, driven by a supply-and-demand issue of RAM manufacturers diverting resources to artificial intelligence servers, has already hit Apple. Earlier this year, it was forced to discontinue the base-model Mac mini and high-end configurations of the Mac Studio with 128 gigabytes of memory and higher storage capacity. It is unprecedented for Apple to flat-out discontinue an existing computer with no mention of its return — Cook’s supply chain prowess ensures that even high-demand configurations will always be in stock at some point. (Just take the MacBook Neo as an example.)

There are two basic, first-year economics solutions to this: decrease demand or increase supply. One is better for consumers than the other. If the AI bubble pops after the initial public offerings of the major AI companies, RAM prices will steadily decrease as data center construction grinds to a halt and the demand for inference slows. Perhaps this could even happen sooner than we initially thought because OpenAI can’t afford to build new data centers. If the bubble never pops, however, we’ll see more capital investment in RAM and storage production to meet demand, and prices may slowly come down. The former situation will have a much more immediate, drastic effect, however, as there’s not much incentive for RAM manufacturers to lower their prices at all if demand keeps rising. (The RAM industry operates as an oligopoly, and increased demand for inference only encourages it to form a cartel.)

While the game plays out, this ought to be quite unfortunate for iPhone and Mac buyers in the fall. I expect iPhone prices to go up by at least $100 in September — and a real price increase at that, not a storage bump like last year due to tariffs. The new MacBook Pro (or, maybe, MacBook Ultra) will probably see even steeper price hikes, though Apple may try to justify them with the new organic-LED touchscreen and new design. And I also wouldn’t be surprised if Apple discontinues more base-model products, like the cheapest MacBook Neo, older-model iPhones, and base-model iMac. If the price of RAM and storage really begins to devour Apple’s margins, I could even see the base-model MacBook Air being discontinued. All of these changes will be unfortunate.

Hugo Lowell, Lily Hay Newman, and Maxwell Zeff, reporting for Wired (Apple News+):

Trump administration officials concluded talks with Anthropic on Monday without lifting export controls that were imposed last week on the company’s most advanced AI models in response to jailbreaking concerns, according to three people briefed on the matter.

The administration continues to believe that there are ways to disable some of the guardrails on Anthropic’s Claude Fable 5, effectively allowing users to access the more powerful cybersecurity capabilities of the company’s Mythos model, the people said.

Anthropic has said for days that the administration’s concerns are overblown, a position it reiterated in working group meetings held at the Commerce Department with government researchers from the Center for AI Standards and Innovation and the Office of the National Cyber Director, Sean Cairncross, one of the people said.

There are a few angles to this conundrum:

1. Why did the Commerce Department suspend Claude Fable 5?
2. Was Anthropic’s “fearmongering” responsible?
3. Does the Trump administration have the legal right to impose export controls in this way?

First, why? The Trump administration’s official word is that the guardrails on Claude Fable 5 — which prevent users from using the model for certain biological and cybersecurity problems — can be easily jailbroken. Amazon, one of Anthropic’s key inference and investment partners, discovered the guardrails and, instead of reporting them to Anthropic directly, went straight to the Commerce Department. This is uneducated speculation, but that sounds like intentional sabotage to me. Either way, the Trump administration, after hearing about the jailbreak, ordered Anthropic to suspend Claude Fable 5 for all non-U.S. nationals, including those legally in the United States.

This reaction is nonsensical: For one, it is virtually impossible to enforce a domestic export control like this. (I’ll elaborate on this in a moment.) Second, Americans are absolutely capable of sabotaging U.S. military action and compromising national security. What stops a foreign adversary from bribing an American who has access to Claude Fable 5? So the rationale for this is clearly not national security or genuine concern, and fortunately, the Trump administration isn’t tight-lipped on culture-war issues. Defense Secretary Pete Hegseth posted this incredible message on X right after the export controls were hastily announced:

Three months ago, @DeptofWar kicked @AnthropicAI out of our building—forever.

Every passing day proves why that was the right move.

The U.S. government is waging a war against an American company. Media outlets have been caught up in the technical detail of the export controls — and, to an extent, so have Anthropic representatives negotiating — because they have “Silicon Valley brain.” Washington journalists know what’s happening here: the Trump administration is exacting revenge after Anthropic refused to let the Defense Department use Claude models for “all lawful purposes.” There is zero ambiguity here for why the Commerce Department decided to levy such a punitive, impossible punishment. This is not a matter of national security — this is the defense secretary laying it all out in the open.

So I think that makes the second angle moot, but only to an extent: Was Anthropic’s “fearmongering” about Claude Mythos responsible? I think yes, but not in the most direct way. Regardless of whether Anthropic said Claude Mythos and Claude Fable 5 were dangerous or not, they’re the most capable large language models ever created, in every benchmark. Third-party security researchers would inevitably try to jailbreak them because of their capability, not Anthropic’s advertising. But Anthropic has also advocated heavily for government oversight under the Trump administration, with Dario Amodei, Anthropic’s chief executive, saying the administration should have the power to cancel the deployment of its models if it deemed such action necessary. This is the only argument from the pro-Trump administration camp I find convincing: Anthropic wanted this. From Amodei’s essay titled “Policy on the AI Exponential”:

Frontier AI models, like airplanes, should be required to go through technical testing and auditing, and their release should be blocked or reversed as a threat to public safety if they do not meet high standards of safety. I am grateful to see the Trump administration’s Executive Order move incrementally towards a greater role for government in AI, though Anthropic’s proposal recommends even further action.

There are really two ways to approach artificial intelligence regulation: the OpenAI approach and the Anthropic one. OpenAI has no morals, ethics, or responsibilities. Its only goal is to make as much money as possible and turn the Great Plains into one gigantic data center. If the U.S. military wants unfettered access to OpenAI models, OpenAI will happily provide it. If the Trump administration wants to tune out “woke” information in the models’ weights, OpenAI will oblige gracefully. OpenAI will do anything to score an extra government contract and inch one step closer to world domination. It has always been that way.

Historically — before this passage in Amodei’s essay — the Anthropic approach has been quite meritocratic. It welcomed the government’s thoughts — particularly around protecting users’ economic and civil rights — but ultimately, it felt the final decisions of how those models were made and distributed should be in the hands of experts, not the government. Anthropic would rather lose government contracts worth billions of dollars than have its models make autonomous decisions in war — that was its red line and it refused to cross it. But after the kerfuffle with the Defense Department in February, I feel Anthropic emerged unnerved. It learned what happens to companies that oppose the administration. It silently abandoned this staunch authoritarian stance and loosened its grip on its models. So now, we’re here, where Anthropic is split between controlling its own models and letting the government regulate them. Anthropic had a good thing going and allowed the U.S. government to destroy it.

So, the third angle: Is any of this even legal? I am not a lawyer, but I err toward no. The government appears to be relying on the Export Administration Regulations, a set of laws that govern export controls. The EAR affects products that have dual military and civilian uses, such as LLMs. The government then imposes an export restriction on a usually narrow scope of countries, like China or North Korea. These restrictions may also be applied to foreign nationals from those countries. The Commerce Department has instead used the EAR to issue a blanket ban on all foreign use of Claude Fable 5, including many of Anthropic’s own employees who worked on the model. This is an outlandish interpretation of this law.

It hasn’t been well-conceived, either. Do dual citizens count? And how does an export restriction in the first place ensure foreign nationals don’t use the model? How does a company enforce such a restriction domestically? The most likely timeline is that the government wanted to punish Anthropic by kneecapping its flagship model, realized it didn’t have a law that allowed it to — thanks to the First Amendment — and used export controls inappropriately to achieve the same effect. I reckon that if Anthropic sued the government, it would win at least a temporary injunction. (Again, I am not a lawyer.) Banning people legally in the United States from using a private company’s technology is truly unprecedented. This whole thing is unprecedented — but it might just be Anthropic’s fault.

Apple Newsroom, shortly after this year’s Worldwide Developers Conference:

Apple today introduced Siri AI, an entirely new version of Siri, powered by Apple Intelligence. Unfortunately, due to the Digital Markets Act (DMA), Apple will not be able to ship Siri AI in the European Union with the release of iOS 27 and iPadOS 27. Over the past several months, EU regulators did not accept any of Apple’s proposed solutions to bring Siri AI to the EU while safely supporting other virtual assistants.

“We’re deeply disappointed that our EU users won’t have Siri AI on iPhone or iPad when we share our new software releases later this year,” said Craig Federighi, Apple’s senior vice president of Software Engineering. “Our hope is to eventually bring Siri AI to the EU, and we will continue to engage with EU regulators on a path forward. However, their refusal to engage constructively on solutions that preserve privacy and security means we do not currently have a timeline for Siri AI’s availability on iOS and iPadOS in the EU.”

The DMA — or, at least, the European Commission’s interpretation of it — demands Apple allow any external large language model-powered chatbot access to the same information and plugins that Siri AI does. Siri AI has, among many other tools, access to the app toolbox and semantic index to use a person’s personal context and App Intents to personalize responses. Third-party LLM extensions, such as ChatGPT’s existing one, do not have access to these features, as there is no practical way to keep that data on-device if it were offered to third parties.

And yes, Siri AI does support third-party extensions, though they’re (probably intentionally) quite barebones. People can really only just chat to external chatbots through the Siri interface — they can’t do most of the things Siri AI can. The only reason this is even in the operating systems is most likely to stave off regulatory pressure from both the commission and the U.S. government, which filed an antitrust lawsuit against Apple during the Biden administration in 2024. But clearly, for the European Union, it isn’t enough. So why isn’t it?

The short answer is that I think the European Union doesn’t know what Apple is even talking about. They’re too decrepit to understand the intention of their law, how Apple is trying to comply with it, and what’s best for consumers. They, frankly, just want Apple to “figure it out.” The commission doesn’t fundamentally understand what on-device inference is, how Private Cloud Compute keeps user data private, and how Apple and OpenAI’s approaches to artificial intelligence differ. I don’t believe they think it’s all the same, but more like they think it’s all just kids playing in the yard. They can’t possibly be bothered with this “nerd stuff.”

Apple does not have access to people’s personal data. It is end-to-end encrypted if they so choose — a feature both the European Union and the United Kingdom have tried to eliminate — and always off-limits if a person decides not to store it in iCloud. Apple could not, even if it wanted to, read someone’s on-device Apple Notes. Siri AI can read those notes because they usually don’t need to be sent to Apple’s servers for processing — the inference is also done on-device. And if the inference does need to be sent to the cloud, it is encrypted in transit, decrypted using a special two-way handshake between the client and the server, and immediately erased the second it leaves the server. Apple could not, even if it wanted to, peek into the server.

By contrast, a request to OpenAI’s servers is very different. None of it is encrypted or on-device. As soon as a person hits Return on a query, it is sent to OpenAI’s servers, stored there for at least 30 days — if not longer — and trained on by default to improve future models. Human reviewers at OpenAI regularly monitor conversations and suspend users’ accounts for terms-of-service violations. Nothing about the ChatGPT experience is private — OpenAI itself tells its users not to share sensitive data with ChatGPT. If Apple gave ChatGPT access to a user’s private, on-device notes, it would be perhaps the biggest privacy scandal of the modern era.

Unlike the original suite of Apple Intelligence features, I truly think Europeans are missing out on something incredible here. Siri AI is the most private, environmentally conscious AI system on the planet. These are not considerations for a place like China — where Apple Intelligence is also unavailable due to regulation — but they seem like they would strongly appeal to Europe’s abundantly liberal politics. I don’t expect protests on the street from angry Belgians or whatever, but Siri AI seems like the first AI system really made for Europeans. I strongly respect Europe’s commitment to regulation, and in some ways, I think Apple does, too. That’s why the European Union’s regulatory action got a whole press release, while China’s only received a footnote. Europe is a liberal democracy worth fighting for.

Tim Hardwick, reporting for MacRumors:

In macOS 27 Golden Gate, Apple has removed many of the menu item icons that are so prevalent throughout macOS 26 Tahoe, as spotted by Nikita “Tonsky” Prokopov (via Daring Fireball). The developer shared before-and-after screenshots on Mastodon to evidence the reversal.

Tahoe was the first version of macOS to place a small icon next to nearly every entry in the menu bar across Apple’s apps, but the change drew swift criticism from designers and developers. Many of the icons are inconsistent and often difficult to understand on their own, with different Apple apps showing different icons for the same menu items.

Most system menus in macOS Golden Gate no longer have icons at all, and the ones that do are consistent across system apps. For instance, the Share button always has a share icon (square.and.arrow.up). Third-party apps that previously adopted menu item icons no longer display them on macOS Golden Gate — developers must programmatically specify that icons are required for particular menu items. (They still appear in macOS 26 Tahoe, even when compiled on the macOS Golden Gate software development kit.) Apple appears to adopt icons for major controls: Passwords and Finder use them for views listed in the sidebar, for instance.

I suppose most Mac developers will leave all icons off because that’s now the default behavior. (To override this behavior, as Apple does, developers should use .labelStyle(.titleAndIcon) in SwiftUI and NSMenuItem.preferredImageVisibility in AppKit.) Developers who do choose to adopt the new guidance will have to do it with intention. Every app will be different and choose to use icons in different menu items. This is not an inconsistency — it appreciates that every app is different and requires various user interface considerations. The old icons were ambiguous because they assumed every app needed an icon for every menu. The new system permits choice, and, ergo, tasteful UI design. And it’s not like apps that choose to eschew icons entirely will look dated, either.

The same goes for the new, tighter corner radius. All apps, regardless of their UI framework, use a single corner radius. It looks amazing in macOS Golden Gate — one of those tweaks you recognize as soon as you boot up the computer for the first time. macOS Tahoe looked like it was designed by a child with Fisher-Price blobs and rounded rectangles throughout. The new windows, combined with the more Aqua-like Liquid Glass elements, feel “grown-up.” They look like they’ve been designed with care and by someone who knows something — anything — about UI design. Again, it’s instantly recognizable and striking.

There are lots of other tweaks, too, like the new sidebars that no longer float over the window. They’re just great. They look every bit as Liquid Glass as the previous version, but they feel like they take up less space. Your eyes are forced to focus on fewer specular highlights and disoriented corner radii. Fundamentally, there’s less happening in the interface. Toolbars just look normal again — they don’t float over the content as they did in macOS Tahoe. The toolbar is unabashedly a toolbar, and the sidebar is unashamedly a sidebar. Whoever thought elements explicitly marked as “bars” should be part of the main content was not thinking straight. macOS Golden Gate might be my favorite operating system this year.