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Apple in China Is Its Greatest Opportunity and Hardest Test

By: Jack
2 August 2026 at 15:40

Apple in China occupies a position unlike the company’s presence in any other country. China is simultaneously a major consumer market, a critical manufacturing center, an extensive developer economy and the home of Apple’s most determined hardware competitors.

That combination creates an opportunity few technology companies can ignore. China has hundreds of millions of affluent mobile users, a strong appetite for premium devices and a digital economy built around smartphones.

It also creates unusual complexity. Apple must compete with Huawei, Xiaomi, Oppo and Vivo while satisfying Chinese regulations, navigating tensions between Beijing and Washington and reducing its manufacturing dependence without damaging the supplier network that helped make the iPhone possible.

The latest market figures show why Apple cannot treat China as a business it has already lost. IDC estimated that Apple captured 18.1 percent of Chinese smartphone shipments during the second quarter of 2026, placing it second behind Huawei at 22.6 percent.

Apple’s shipments increased by 24.4 percent from the previous year even as the wider Chinese smartphone market contracted. The recovery demonstrated that Chinese demand for the iPhone remains substantial when product design, storage, performance and pricing align with consumer expectations.

The same figures also show why the position can never be considered secure. Huawei remains ahead, local brands respond quickly and a few percentage points can separate several major vendors.

Apple in China Still Has Room to Grow

China is already one of Apple’s largest markets, but its scale means that even established product categories contain room for expansion.

The country has a large premium smartphone segment, extensive 5G coverage and consumers accustomed to using mobile devices for communication, payments, shopping, entertainment, transport and work.

An iPhone purchase can also lead to AirPods, Apple Watch, iPad, Mac, iCloud storage and paid applications. The commercial opportunity is therefore larger than the initial handset transaction.

Apple’s strongest advantage is its integrated ecosystem. An iPhone can share passwords, photographs, messages and files with a Mac or iPad, while AirPods and Apple Watch extend the experience without requiring separate accounts and setup systems.

That continuity becomes more valuable as households accumulate devices. Replacing one iPhone is relatively easy. Leaving an ecosystem containing several products, purchased applications, cloud storage and shared family services involves greater friction.

Apple also benefits from a premium identity that remains recognizable in China. Local manufacturers now produce sophisticated flagship phones, but the iPhone continues to operate as both a personal computer and a luxury consumer product.

The importance of that status should not be exaggerated. Chinese buyers are technically informed and increasingly willing to support domestic brands. Brand recognition can attract attention, but it does not excuse weak features or an uncompetitive product cycle.

China Flag

Recent iPhone Demand Shows the Opportunity

Apple’s 2026 recovery offers a useful example of how quickly its position can improve.

China’s smartphone shipments fell 4.3 percent during the second quarter as memory and component costs pushed several manufacturers toward higher prices. Apple and Huawei held prices more stable, giving buyers a reason to purchase while competing brands became more expensive.

The iPhone 17 generation also addressed several areas where Apple’s standard models had appeared conservative beside Chinese flagships. Stronger base specifications made the regular iPhone more competitive without requiring every customer to move into the Pro tier.

This matters in a market where consumers compare display technology, camera systems, storage, battery life, charging and AI features closely. Apple cannot depend entirely on iOS loyalty when domestic companies introduce visible hardware improvements at several price levels.

The rebound does not establish a permanent trend. Smartphone demand in China remains affected by economic confidence, upgrade cycles, government incentives and the timing of major shopping festivals.

Apple’s position can also look different according to the research firm and whether a report measures shipments or consumer sales. Quarterly rankings should be treated as evidence of momentum rather than a final judgment on the market.

The important signal is that Chinese consumers have not broadly rejected the iPhone. Demand can return rapidly when the product and price create a convincing upgrade.

Huawei Makes China Apple’s Hardest Market

Huawei gives Apple a competitor with advantages unavailable to most global smartphone manufacturers.

The company combines strong national recognition with advanced cameras, communications technology, custom chips, local services and an expanding HarmonyOS ecosystem. Its return to premium smartphones removed the opening Apple had gained when U.S. restrictions disrupted Huawei’s access to important components.

Huawei can also position its products as part of China’s technological self-reliance. That message carries commercial and political weight beyond a conventional comparison between two phones.

Apple must therefore compete against product quality and national sentiment simultaneously. An iPhone can offer strong performance and still lose a purchase to a domestic flagship viewed as technically capable and strategically important.

Xiaomi, Oppo and Vivo add different pressures. They move quickly across price categories, experiment with folding designs, adopt larger batteries and provide features adapted to local applications and buying habits.

Chinese phone makers also operate inside a retail and software environment they understand directly. They can build relationships with local platforms, carriers and commerce services without translating a global strategy into Chinese requirements.

Apple follows a more centralized product model. That consistency protects the identity of the iPhone, but it can make the company slower to answer features gaining popularity inside one country.

A sleek Apple Store with a minimalist design, featuring a large illuminated Apple logo at the entrance. People casually walk around the spacious interior with wooden tables displaying Apple products and brightly lit walls adorned with images. Significant iPhone discounts in China have driven a sales surge.

Services Depend on Local Rules

Apple in China is not only an iPhone business. The installed device base creates demand for applications, cloud storage, entertainment, subscriptions and digital purchases.

China has an enormous developer community producing games, commerce platforms, social services, education tools and productivity software. The App Store connects those developers with high-value iPhone and iPad customers.

The relationship is commercially important but politically complicated. Apple must operate the mainland App Store according to Chinese law, including rules affecting games, generative AI, communications services and content.

Applications available elsewhere may be absent from the Chinese storefront. Developers may also need licenses or regulatory approval before distributing certain categories of software.

Apple changed commission rates and related policies for the mainland China storefront in March 2026. The company described the adjustments as part of maintaining a strong business opportunity for Chinese developers.

Regulatory and developer pressure has not disappeared. Complaints involving commissions, distribution restrictions and payment policies continue to challenge Apple’s control of the platform.

The company cannot simply copy its response from another region. European rules focus heavily on alternative marketplaces and interoperability, while China combines competition concerns with content regulation, data localization and licensing requirements.

Every concession must therefore be designed for a distinct legal environment without fragmenting iOS into an unmanageable collection of regional systems.

China Is Also Part of the Product

Apple’s relationship with China extends far beyond the devices sold there.

For more than two decades, Apple and its manufacturing partners built a dense network of factories, component suppliers, engineers, logistics operators and toolmakers across the country.

That network does more than provide low-cost labor. It can place specialists from several suppliers near an assembly site, modify production lines quickly and increase output to enormous volumes during a product launch.

China’s infrastructure also supports the less visible stages of manufacturing. Components require precision tooling, testing equipment, chemicals, packaging, subassemblies and experienced quality-control teams before final assembly begins.

Apple has expanded iPhone production in India and moved parts of its Mac, iPad, Apple Watch and AirPods supply chains to countries including Vietnam. It is also increasing semiconductor and component commitments in the United States.

Those investments reduce the danger of relying on one country, but they do not recreate China’s complete manufacturing environment immediately.

A factory in another region may assemble an iPhone while still depending on Chinese machinery, materials, subcomponents or engineering support. Production diversification is therefore a gradual redistribution of individual stages rather than a clean departure.

Apple must reduce concentration risk without weakening the manufacturing system responsible for its product quality, scale and launch schedules.

Several new smartphones in various colors are displayed upright on stands, with their screens facing forward. The background is blurred, drawing focus to the phones amid discussions around Apple EU antitrust regulations.
Image Credit: AFP Photo

Trade Tensions Turn Efficiency Into Risk

The same China supply chain that provides Apple with extraordinary efficiency also exposes the company to political decisions outside its control.

Tariffs can raise the cost of devices exported from Chinese factories. Export restrictions can limit access to materials or production equipment, while sanctions may affect suppliers and technology partners.

Chinese government policies can influence the use of foreign devices inside state agencies and companies. U.S. rules can restrict the technologies available to Chinese firms that also participate in Apple’s supplier network.

Apple cannot solve these problems through product design alone. It must maintain relationships with two governments whose technology policies increasingly emphasize security, domestic production and strategic independence.

Moving more assembly to India gives Apple additional flexibility, particularly for iPhones destined for the United States. China nevertheless remains important as a production center and consumer market.

An aggressive withdrawal could damage supplier relationships and local sales. Moving too slowly could leave Apple vulnerable to another trade disruption.

The company is trying to preserve Chinese capabilities while creating enough capacity elsewhere to keep a political dispute from becoming a worldwide product shortage.

Retail Stores Give Apple a Direct Relationship

Apple’s physical stores remain an important advantage in China because they give the company direct contact with customers.

The stores allow buyers to compare models, receive technical support, attend educational sessions and enter the ecosystem without depending entirely on a carrier or reseller.

That experience is particularly valuable for premium products. A customer considering a Mac, Apple Vision Pro or high-end iPhone may need more explanation than someone replacing an inexpensive handset.

Retail locations also communicate long-term commitment. A prominent store represents more than a sales channel; it signals that Apple intends to remain part of the local technology market.

Online commerce is equally important. Chinese consumers are accustomed to large shopping festivals, aggressive promotions and rapid delivery through domestic platforms.

Apple must balance its controlled global pricing with a market where discounts can change quarterly rankings. Too little flexibility makes the iPhone appear expensive, while frequent reductions can train customers to delay purchases and weaken its premium image.

The strongest 2026 performance came partly from avoiding price increases while component costs were forcing rivals to reconsider their pricing. That advantage may disappear when competitors adjust their supply chains or launch another cycle of promotions.

Chinese Consumers Set a Higher Product Standard

China is often discussed as a sales problem for Apple, but it also functions as a demanding test of the iPhone.

Domestic flagship phones compete through larger batteries, rapid charging, advanced camera hardware, folding displays and deep integration with local digital services.

Features considered experimental elsewhere can become established expectations more quickly in China. Apple’s slower adoption cycle may look disciplined in one market and conservative in another.

The company must decide which expectations represent durable improvements and which are temporary specification contests. Copying every local feature would weaken Apple’s focused product strategy, but ignoring major changes creates openings for rivals.

This pressure can benefit Apple globally. Competition in China forces the company to defend the value of its standard iPhone, improve battery efficiency, strengthen cameras and make software features more useful outside English-speaking markets.

The opportunity is therefore not limited to selling more devices. China can reveal where Apple’s global assumptions no longer match the most competitive part of the smartphone industry.

The post Apple in China Is Its Greatest Opportunity and Hardest Test appeared first on AppleMagazine.

Bloody Awful Work Creeps in When Standards Are Relaxed

2 August 2026 at 11:00

The Jason Arday scandal is just the latest symptom of a much bigger problem in UK universities: collapsing standards, poor scholarship and a system that has let it happen, says Dr David McGrogan.

The post Bloody Awful Work Creeps in When Standards Are Relaxed appeared first on The Daily Sceptic.

Apple’s AirTag 2 four-pack hits record low of $89

30 July 2026 at 19:00
Apple introduced the new AirTag, now with an expanded finding range and a louder speaker.
Apple’s new AirTag (second generation), now with an expanded finding range and a louder speaker.

Apple’s second-generation AirTag is currently available at its lowest price ever: $89 for a four-pack, down from the usual $99. The deal matches the previous all-time low first spotted during Amazon’s Prime Day event and remains one of the strongest discounts on the newer model.

A single AirTag 2 is also discounted to $27 (from $29). While that price isn’t quite as aggressive as some earlier promotions, it still ranks among the better current offers for buyers who only need one unit.

The AirTag 2 is a compact Bluetooth tracker that helps users locate everyday items like keys, wallets, bags, or luggage through Apple’s Find My network, showing the last known location on a map and enabling Lost Mode to lock the tag and display a custom contact message via NFC when found by someone else.

AirTag 2 offers Precision Finding with a second-generation Ultra Wideband chip that provides directional arrows, distance readouts, and haptic/audio cues from up to 50% farther away (on compatible iPhone 15 or later models, excluding certain variants), plus the first-time ability to use this feature on Apple Watch Series 9 or later and Ultra 2 or later; an upgraded Bluetooth chip for expanded proximity range; a 50% louder speaker with a distinctive new chime that can be heard from twice as far; “Left Behind” alerts; sharing location access with family or friends; temporary secure sharing with airlines for luggage recovery; a user-replaceable CR2032 battery lasting over a year; IP67 water and dust resistance; and built-in privacy protections including frequent Bluetooth ID rotation and end-to-end encryption so only the owner can access location data.

MacDailyNews Take: Get ’em while they last here.


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The post Apple’s AirTag 2 four-pack hits record low of $89 appeared first on MacDailyNews.

Framework Laptop 13 Pro review: Much better battery, much worse price

27 July 2026 at 16:02

I've liked the Framework Laptop 13 since the first time I used it, partly because I just think the idea of a repairable and upgradeable laptop is cool and partly because it's not Yet Another Ultraportable Trying To Be A MacBook Air Clone. But the design has always had real shortcomings—the most noticeable and serious being its mediocre battery life.

Enter the Framework Laptop 13 Pro. While all previous Laptop 13 refreshes have tinkered around the edges with the original design (a tweaked lid design here, new hinges or new speakers there), the Laptop 13 Pro is as close as we've gotten to a second-generation revision for the original design.

This means that it breaks backward compatibility for some (but not all) Laptop 13 components, most notably the bottom case, the keyboard and trackpad, and the original 55 WHr and 61 WHr battery designs. But by allowing itself to make larger changes to the design, Framework has made major strides in battery life and general fit and finish.

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© Andrew Cunningham

VPN, antivirus, données personnelles : ce pack Surfshark passe en promo

25 July 2026 at 10:00
Surfshark One+ réunit VPN, antivirus et outils de protection des données dans une seule offre.Une solution pensée pour renforcer la confidentialité en ligne sans multiplier les abonnements.

Wildfire forces evacuation of NASA's Deep Space Network complex in Spain

24 July 2026 at 23:28

A fast-moving wildfire, one of many raging across Spain, bore down on the Madrid Deep Space Communications Complex on Friday, forcing an evacuation and temporarily suspending operations at one of NASA's most important tracking stations.

The tracking station is part of NASA's Deep Space Network, operating in concert with similar facilities in California and Australia to provide global coverage as Earth's rotation brings the planets, stars, and deep space probes in and out of view. The network supports more than 40 missions from the Moon to the edge of the Solar System, including Artemis, the James Webb Space Telescope, and NASA's twin Voyager spacecraft.

A NASA spokesperson confirmed the tracking station in Spain, located in the hills nearly 40 miles (65 kilometers) west of central Madrid, was evaluated Friday "due to ongoing wildfires in the region. Photos and video from the area showed flames and smoke plumes rising over the ground station's antenna array, anchored by a 230-foot-diameter (70-meter) radio dish and a collection of smaller 112-foot (34-meter) antennas.

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© Gabri Solera/Europa Press via Getty Images

Wildfire forces evacuation of NASA's Deep Space Network complex in Spain

24 July 2026 at 23:28

A fast-moving wildfire, one of many raging across Spain, bore down on the Madrid Deep Space Communications Complex on Friday, forcing an evacuation and temporarily suspending operations at one of NASA's most important tracking stations.

The tracking station is part of NASA's Deep Space Network, operating in concert with similar facilities in California and Australia to provide global coverage as Earth's rotation brings the planets, stars, and deep space probes in and out of view. The network supports more than 40 missions from the Moon to the edge of the Solar System, including Artemis, the James Webb Space Telescope, and NASA's twin Voyager spacecraft.

A NASA spokesperson confirmed the tracking station in Spain, located in the hills nearly 40 miles (65 kilometers) west of central Madrid, was evaluated Friday "due to ongoing wildfires in the region. Photos and video from the area showed flames and smoke plumes rising over the ground station's antenna array, anchored by a 230-foot-diameter (70-meter) radio dish and a collection of smaller 112-foot (34-meter) antennas.

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© Gabri Solera/Europa Press via Getty Images

ChatGPT Voice está agora disponível no app reformulado para desktop

24 July 2026 at 00:08

Pouco mais de sete meses após descontinuar o modo de voz no então aplicativo do ChatGPT para desktop (atualmente, chamado de ChatGPT Classic), a OpenAI anunciou hoje que a mais nova versão do app do chatbot agora suporta o ChatGPT Voice, alimentado pelo novíssimo e versátil modelo GPT-Live.

Graças a essa versatilidade, o novo modo de voz pode fazer bem mais que apenas conversar. Além de poder ser usado em chats, ele também está integrado ao Work e ao Codex — o que significa que você pode usá-lo para coordenar e acompanhar tarefas, sem usar texto.

ChatGPT Voice is now in the desktop app.

Control your computer and direct multiple agents running in ChatGPT Work or Codex, using just your voice.

It's powered by GPT-Live, so it can speak, listen, and coordinate work in the app at the same time.

Rolling out globally today… pic.twitter.com/ODZWKqecCf

— OpenAI (@OpenAI) July 23, 2026

Para usar a novidade, é necessário abrir um novo chat ou uma nova tarefa vazia no app e selecionar a opção “Iniciar nova conversa por voz”. As conversas ou tarefas precisam necessariamente ser iniciadas nesse modo — caso contrário, apenas o ditado por voz estará disponível.

O ChatGPT Voice oferece suporte a uma alternância natural entre as falas. Você pode interromper o ChatGPT durante uma resposta, fazer uma pergunta complementar ou mudar de direção. Se o ChatGPT começar a executar uma tarefa, continue falando para verificar o progresso ou orientar o trabalho.

Além disso, a OpenAI destaca que é possível iniciar conversas separadas para conversas mais longas, enviar ao app uma screenshot para apresentar o contexto do que está na tela, bem como usar o recurso pelo Remote do iOS com o iPhone emparelhado ao computador.

O ChatGPT Voice no desktop está sendo disponibilizado gradualmente para os planos Plus, Pro, Business, Edu e Enterprise. Nos dois últimos, há um período inicial de duas semanas com acesso antecipado antes de o recurso ser ativado por padrão.

É possível baixar o novo app do ChatGPT para macOS nessa página.

Whisper and SpeechAnalyzer

22 July 2026 at 21:34

Om Malik (2023):

One of the key advantages of MacWhisper, as it utilizes the Whisper technology, is its superior accuracy in transcriptions compared to other services I have used. I was an early adopter of Rev.com and eventually switched to Otter.ai, for which I paid approximately $100/year. However, I have since canceled my subscription.

[…]

After comparing the audio transcripts from MacWhisper and Otter, I found that while Otter’s formatting is superior, there is hardly any difference in the transcriptions. I started with the free model, which was sufficient for my needs, and eventually upgraded to the large models. Nowadays, I primarily use MacWhisper to transcribe my voice memos, which I then import into Lex.Page.

Bon Adamson:

Whisper, which is made by OpenAI, has the distinct advantage of allowing you to transcribe audio in almost any language you may ever need to. For the time being, Otter can only transcribe English. The benefits of better accuracy and accurate punctuation that the service already holds over Siri hold up across other languages as well. If you’re looking to transcribe non-English audio accurately, Whisper is definitely the best option available on Mac.

Dan Moren:

By taking advantage of OpenAI’s Whisper framework, Audio Hijack can now take any audio it’s recording and generate a text transcript. While this process was possible before—see Jason’s lengthy post about his workflow—it required a lot of fiddling and several different tools to accomplish; it’s certainly a lot easier to simply drop Audio Hijack’s block into your existing session. If you record multiple sources, it can even appropriately label each one—though if you record multiple people via one input, say the other end of a Zoom call, it can’t distinguish between the various participants.

Inscribe (2026, Hacker News):

Apple’s new SpeechAnalyzer is the most accurate on-device speech engine we tested. It beat every Whisper model we ship, including Whisper Small, on both the clean and the noisy half of LibriSpeech, while running roughly three times faster than Small. And the API it replaces, SFSpeechRecognizer, came last on clean speech: behind even Whisper Tiny, a 40MB model.

[…]

The new API cuts word error rate by 3.5 to 4x on the same audio: from 9.02% to 2.12% on clean speech, and from 16.25% to 4.56% on noisy speech. There is no accuracy trade-off to weigh; the new API wins everywhere we measured, and it produces punctuated, cased text where the legacy engine’s output is rougher.

[…]

All five engines ran comfortably faster than real time: between roughly 12x and 40x on the M2 Pro, meaning an hour of audio transcribes in about 1.5 to 5 minutes on-device. SpeechAnalyzer was about 3x faster than Whisper Small per second of audio while beating it on accuracy.

Yuki:

SpeechAnalyzer’s ReportingOption.fastResults reads like a knob you’d reach for when you want to trade power for latency. That framing is what cost me the afternoon.

[…]

If a recording matters — and in a notes app, a lost meeting is the worst thing that can happen to a user — then the container you write while recording has to be PCM in CAF. Not m4a, and not AAC-in-CAF either.

[…]

AVAudioEngine’s inputNode silently ignores your device selection

[…]

I wanted summarization to run on-device. Everything else in Nib’s transcription path does, the audio never leaves the machine, and it would have been a much cleaner story to tell.

But 4,096 tokens for the Foundation Models isn’t enough.

Previously:

Apple Foundation Models in appleOS 27

16 June 2026 at 20:35

Apple:

At the heart of this architecture is our third generation of Apple Foundation Models (AFM), a family of five foundation models custom-built in collaboration with Google. These span from on-device models to server-based models running on Private Cloud Compute.

Apple Foundation Models are built to unlock a wide range of helpful experiences for our users, like an entirely new Siri and intelligent tools that make everyday apps smarter and more useful.

Hartley Charlton:

“The amount of the Google Assistant we use is none,” Federighi said, explaining that Apple uses none of the Gemini models deployed to Google’s customers, none of Google’s client-side code, and no Google Search infrastructure as the knowledge backbone.

Federico Viticci:

The cloud models hosted on Private Cloud Compute are interesting: they’re not “Gemini” models; they’re Apple Foundation Models trained using proprietary data via RL, which were then “refined” with data from Google’s “frontier” models.

[…]

I’ve been covering the AFM family of models for a while now, and AFM Core Advanced is one of the most interesting on-device models I’ve read about in a while, especially in the context of model size for mobile devices and built-in multimodality with support for text, images, and audio. I’m very keen to play around with this model and understand how it holds up in practice. I wonder if the new CLI (!) for AFM will let you test this one.

Awni Hannun:

It’s very cool that Apple shipped a 20B parameter on-device.

You can’t put 20B parameters in RAM at any reasonable precision. To make it work they are using pretty exotic architecture by today’s standards.

A small model predicts from the query (or prompt) which experts to load from Nand into RAM. The key distinction from a typical MoE is that you do this once per query and then generate all the tokens with the same experts (instead of switching the experts for every token).

Greg Pierce:

Looks like there’s still a 4K context size on local FoundationModels. Pretty limiting.

Kyle Howells:

Really disappointed SwiftUI’s result builder syntax has infected FoundationModels API too.

How did a million modifier methods become the default way to build APIs?

It’s horrible for discoverability, code completion, documentation.

Steve Troughton-Smith:

FoundationModels is one of the highlights of this WWDC; I think it’s now finally what we hoped we were getting two years ago, and thought we were getting last year (just the models themselves were barely up for it then). I finally feel like I can build features with it, though I really don’t like the Sword of Damocles Apple is holding above Private Cloud Compute and how it can permanently lock you out of using the models forever across all your apps if you hit a download threshold. Poison pill

John Gruber (Mastodon):

These strict limits don’t seem to be getting as much attention as they should. It’s nice that for small developers who meet the above criteria, access to PCC has no cost. But there’s no way (yet?) to buy your way out of these limits.

[…]

The “fewer than 2 million first-time app downloads from any of their apps” restriction is particularly notable. It’s not 2 million installations for apps that are using PCC, but 2 million downloads for any app the developer has ever released.

Chad Podoski:

Is there a real time count somewhere of total lifetime downloads for a developer account, so one can plan if they at risk of the switch tripping? Reminds me of the small business qualifications. I had to try to figure out if an employers developer account was going to exceed the revenue threshold for the year. I was left trying to determine it from sales reports, not to mention sales date versus pay out date confusion. I think I botched the calculation in the end.

Anthropic (Hacker News):

Claude for Foundation Models is a Swift package that makes Claude available as a server-side language model in Apple’s Foundation Models framework. The package conforms Claude to the framework’s LanguageModel protocol, so you drive it with the same LanguageModelSession API you use for Apple’s on-device model: respond(to:), streaming, guided generation, and tool calling all work the same way.

Requests go directly from your app to the Claude API; Apple is not in the request path and does not see prompts or responses. Usage is billed to your Anthropic account at standard API pricing.

Previously:

Update (2026-06-17): Simon B. Støvring:

Apple is literally stopping me from building a brand new app using Private Cloud Compute because I made a successful app a few years ago.

The new app might be a success, or it might be a complete flop. Nobody knows yet.

I would understand it if Apple were to limit developers once an app reaches a certain number of downloads or active users, but that’s not what’s happening here.

Instead, they’re blocking developers before they’ve even had a chance to build and ship the app.

Siri AI Announced

10 June 2026 at 21:00

Apple (Hacker News):

Siri AI is an entirely new version of Siri deeply integrated into iPhone, iPad, Mac, Apple Watch, and Apple Vision Pro. It can draw on personal context understanding to search across messages, emails, photos, and more, and get things done across apps with even more systemwide app actions. Additionally, Siri AI can answer questions related to the content on a user’s screen or go out to the web to get up-to-date information using broad world knowledge and generate a helpful answer. A dedicated Siri app allows users to revisit a past conversation or kick off a new one — all in one place — and uses iCloud to privately sync conversational history across a user’s products.

Apple (MacRumors, MacStories):

Powered by the next generation of Apple Intelligence, Siri AI is a completely reimagined version of Siri that is more helpful, more capable, and more intelligent. With detailed, engaging responses and natural back-and-forth conversation, Siri AI helps users get more done than ever.

[…]

Siri has been rebuilt from the ground up with powerful AI at its core. It takes full advantage of the bold new architecture for Apple Intelligence, including the next generation of Apple Foundation Models that run on device and on servers using Private Cloud Compute. When Private Cloud Compute is handling users’ requests, their personal data is not stored nor made accessible to Apple or anyone else. Outside experts can continue to verify this privacy promise at any time. Additionally, Siri AI uses the system orchestrator to tap into core capabilities like the Spotlight index and App Toolbox, which work entirely on device to keep users in control of their data.

[…]

For products that support Apple’s most advanced on-device model ever, Siri AI offers even more expressive voices, as well as a major boost in accuracy with systemwide dictation. Users have the ability to customize the expressiveness and pace of Siri’s voice so it’s just right for them. Dictation now captures what users say as polished text with greater precision, automatically handling capitalization, punctuation, and formatting as they speak. With improved speech understanding, users can speak naturally and trust that their words will appear clearly, accurately, and as intended.

I remain uninterested in these more advanced Siri features. They matter in that Apple needs to show that they’re not “behind” and that they can actually deliver on what they announce and advertise. But I don’t find the use cases compelling and wouldn’t trust the results.

If you really care about a particular concert, would you believe Siri about how the tickets work and that it will auto-create a reminder at the right time? Why should I believe that it can figure out whether a particular irregularly shaped object can fit inside an irregularly shaped container when said shapes are probably not even published on the Web? Can it really dig into my e-mail to find the right flight info? An answer without being able to see the sources is not useful. And I certainly don’t want it to pick for itself which vacation photos to send out.

I just want the basic features—from a decade or so ago, like music controls, reminders, and access to my purchases—to work quickly, reliably, and offline to the extent possible. I did not hear anything to suggest that this was a focus. Instead, everyone is celebrating how slow the demos were because that proves they weren’t fake.

Ben Thompson:

It’s actually super important that the Siri demo was kind of slow, because it emphasized it was real. Would be even better if it were live, though.

Mark Gurman:

The other interesting thing to note from the keynote: watching the demos, there is ZERO doubt these are real, recorded demonstrations on live devices. There will be no confusion about what is real or fake like there was at WWDC 2024 and the initial attempt at the new Siri.

John Gruber:

In fact, I think most of them were single takes of multiple demos back-to-back. That’s the way it should be, even when they feel a little slow.

Jonathan Wight:

Who the fuck wears a $4000 VR headset to find out if their boots will fit in their fucking backpack?

THATS the best example they could come up for that feature?

Rob Terrell:

also I wouldn’t trust the answer anyway

Kyle Howells:

These Siri demo’s feel like OpenAI demo’s from a view years ago. However, this is built in to the operating system.

Much like Dropbox vs iCloud, I feel like long term, once it’s good enough Apple will succeed in making AI a “feature” rather than a product.

Simon B. Støvring:

Apple needed to show that they could make a version of Siri that wasn’t three years behind. They didn’t succeed.

Ben Thompson (Hacker News):

And, if your standards are the state of the art in AI circa June 2024, when Apple took their first crack at answering the question, they did quite well.

[…]

What’s fascinating about this specific demo is that it also showed just how far behind Apple is.

[…]

Still, the bubble was strong enough to convince OpenAI to make the exact same mistake Dropbox did: the company somehow convinced itself that it could make enough money selling subscriptions to consumers; Anthropic, meanwhile, realized that it was enterprises who were willing to pay for AI’s massive productivity benefits, even as OpenAI failed to capitalize on their consumer market penetration by refusing to build an advertising product.

This is a long-winded way of saying that I don’t think that Apple’s agentic shortcomings are a big deal, at least for now. Agents help you do work and be more productive, and consumers don’t want to work or care about being productive. What they do want to do is watch short-form video, and an iPhone is simply much better at that than any other device ever will be; in that context, Siri being good enough is enough, and it appears that Apple crossed that bar.

John Gruber:

They need to execute, they need to prove this can scale, and most of all, they need to get third-party apps on board with App Intents and App Schemas. But it seems like they’re doing all of that. This is not a done deal but it is very realistic.

Steve Troughton-Smith:

Siri doesn’t have access to the filesystem or tool-calling, so it’s completely unable to do the kinds of tasks you might easily do with Codex or Claude. It’s a good start, but the state of the art has already dramatically shifted over the past year. The question is will Siri move in this direction, or stick to providing answers from the web?

Will Apple introduce its own distinct Codex-style agentic programming model that can do all this, and work with Xcode? You would hope so…

Aaron Pearce:

Have new Siri now. Siri still can’t do “turn lamp off and turn plug on” in one command.

Joe Rossignol:

The revamped version of Siri that is officially named “Siri AI” will be available to test in the iOS 27, iPadOS 27, macOS 27, and visionOS 27 developer betas starting today, and it is coming to the Apple Watch in a future watchOS 27 beta. “Siri AI” will also be included in the public betas of each platform that are launching in July.

“Siri AI” requires a device that is compatible with Apple Intelligence.

Hartley Charlton:

Apple senior vice president of software engineering Craig Federighi has explained why the company launched a standalone Siri app in iOS 27, after previously characterizing a dedicated chatbot as contrary to its Apple Intelligence strategy.

[…]

“We see Siri not as a separate chatbot, just an unintegrated place you go and chit-chat, but rather as an integral, conversational tool that you use in the moment, deeply integrated into your experience.”

Clear as mud.

ldt:

How to bypass the new Siri waitlist (Mac only)

See also: New Siri Waitlist.

Previously:

Update (2026-06-11): famebot:

…And playlists, contacts, settings and preferences. Peel off the agentic slop bandwagon and focus on core performance, smarter caching, and resilience under adverse network conditions.

Joe Fabisevich:

Love the new Siri, sick.

Update (2026-06-12): Juli Clover has a hands-on video.

Nick Heer:

Though this is a test conducted on the very first version of Siri A.I. from a fixed point in Calgary, it seems to work quite well. So far, it is better than any version of Siri Apple has released yet and, as you can see above, it is almost as good as the original 2010 demo, before Apple acquired the company.

Update (2026-06-16): Riccardo Mori:

On the one hand, if Siri has indeed become this reliable at understanding queries like those demoed so far, it’s indeed impressive. On the other hand, I can’t help but ask myself, once again, whether people at Apple even know how regular people actually use their phones and devices.

Jeff Johnson:

Apple executives downplay and obfuscate the role of Google in Siri AI. The Siri AI announcement didn’t even mention Google or Gemini once! Does anyone actually believe Apple’s BS? The argument seems to be that since Google made a bespoke implementation for Apple, Google is not really involved, and it’s all Apple. Ridiculous.

Jeff Johnson:

It’s really odd to me that Apple is getting so much credit for Google’s work. Siri now “works” to the extent it does because Siri is to a very large extent Gemini, and Apple has wrapped that in a bow.

Apple didn’t “nail” anything. Apple failed at its own internal efforts and was forced to outsource.

This is the advantage of being a platform: you can fail and still win.

Chance Miller (via John Gruber):

Apple’s Siri team, led by Craig Federighi, held a post-WWDC keynote tech talk with members of the press this afternoon to talk through iOS 27 and the new Siri AI.

During the talk, Federighi shared more details about Apple’s collaboration with Google.

Matthew Green (Lobsters):

Apple looks like it will use some combination of Google Gemini models, combined with Google’s Confidential Inference and Apple’s own Private Cloud Compute for private hosting. These systems will process both your queries and evaluate private data from your devices.

[…]

Apple has since “expanded” PCC to encompass Google’s hardware as well. I will confess that I find the details of the new “expanded” PCC just a bit vague. It sounds a lot like Apple is primarily going to rely on Google’s existing confidential compute (running in Google datacenters) to process this data, but they’re bolting on a new layer of technical security to control which models are actually running. In any case: security experts can argue about whether this is good enough to keep Cozy Bear away from your data. What I will grant is that it’s probably good enough to keep Google and Apple from accessing your stuff, which is what most people are worried about in the first place.

So why am I so nervous?

[…]

So far we’ve discussed two adversaries: the misaligned designers of private agents (such as search operators), and the possibility of remote prompt injection attacks. But of course, in any discussion of technical privacy systems we need to talk about the last elephant in the room: your government.

Previously:

“Apple Upgrade”: empresa poderá bloquear apps por pagamentos atrasados

22 July 2026 at 13:32

Ontem, falamos aqui sobre o rumor de que a Apple estaria prestes a lançar, nos Estados Unidos, um programa de assinatura de iPhones, iPads, Macs e Apple Watches, dando aos consumidores mais formas de acessar seus dispositivos.

Logo depois, o 9to5Mac encontrou, no código da beta do iOS 27, menções a um novo framework que serviria para gerenciar dispositivos alugados por meio de assinaturas como essa.

Chamado App Managed Features, ele permitirá, ao que tudo indica, que um aplicativo autorizado de financiamento ou de prestação de serviços — e não apenas o “Apple Upgrade”, como a solução proprietária está sendo chamada — registre um iPhone e realize verificações contínuas de status.

Caso haja algum problema com o registro (como pagamentos atrasados), o iPhone será colocado automaticamente em um estado intitulado “Restricted Mode” (“Modo Restrito”, em tradução livre), que bloqueia o acesso a uma série de apps do iOS, incluindo:

  • Leitor de Acessibilidade (Accessibility Reader)
  • App Store
  • Saúde (Health)
  • Lupa (Magnifier)
  • Telefone (Phone)
  • Relógio (Clock)
  • Ajustes (Settings)
  • Carteira (Wallet)
  • Senhas (Passwords)
  • A interface do “Restricted Mode” em si

Como é possível notar, alguns apps mais “críticos”, como o Mensagens (Messages) e o Casa (Home), poderão continuar disponíveis mesmo quando esse bloqueio estiver ativo. Segundo o 9to5Mac, no entanto, o provedor do aparelho será capaz de escolher quais apps ficarão (ou não) de fora dessa lista.

Embora restrinja o acesso aos apps do aparelho, o recurso não parece modificar assinaturas da App Store, o que significa que o usuário continuará sendo cobrado pelos seus apps e serviços mesmo após ter sido colocado no “Restricted Mode”.

Além disso, o código do iOS 27 não lista um número limite de pagamentos atrasados como condição para o bloqueio dos apps, o que significa que ficará a cargo dos serviços de assinatura decidir quando impor essas restrições de acordo com os seus termos e condições.

Há, no entanto, menções a um novo tipo de Bloqueio de Ativação (Activation Lock) chamado “Partner Finance Lock”, criado com o objetivo de impedir que usuários apaguem, vendam ou desmontem um aparelho alugado para revender suas peças.

Ainda segundo as informações, o App Managed Features faz parte do app Buscar (Find My), embora o provedor não tenha acesso à localização do dispositivo. Ao que tudo indica, essa integração existe apenas para garantir que o bloqueio continue de pé mesmo que o usuário apague ou redefina o aparelho.

Embora essas referências não tenham sido encontradas na versão Release Candidate (RC) do iOS 26.6, é possível que elas sejam adicionadas à versão final do sistema, já que, segundo a Bloomberg, o “Apple Upgrade” será anunciado na semana que vem.

Keynote 15.3, Numbers 15.3, and Pages 15.3

6 July 2026 at 18:07
Keynote 5 icon
Enables direct image editing in Pixelmator Pro for Apple Creator Studio subscribers. ($129.99 annual Apple Creator Studio subscription, various sizes, macOS 15.6+)

macOS Hidden Treasures: Typing Exotic Characters

Como gerar imagens usando o Creator Studio no Pages, Numbers e Keynote [iPhone, iPad e Mac]

19 July 2026 at 22:00

O Apple Creator Studio desbloqueia vários recursos bacanas de aplicativos já conhecidos pelos usuários de dispositivos da Maçã.

Dentre os exemplos, estão os apps Pages, Numbers e Keynote. Com eles, assinantes do Creator Studio podem gerar imagens e adicioná-las aos seus documentos, planilhas e apresentações de slides.

Veja como fazer isso nos parágrafos a seguir! ✨

Como gerar imagens usando o Pages, Numbers ou Keynote pelo iPhone/iPad

  1. Com um dos apps abertos, abra o arquivo onde deseja anexar a imagem.
  2. Escolha o ícone roxo (na barra superior) e vá em “Gerar Imagem”.
  3. Selecione o estilo, a forma de visualização e a proporção desejadas.
  4. Descreva a imagem no campo da parte inferior da tela.

Após ela ser gerada, você pode fazer outras edições e salvá-la, por exemplo.

Como gerar imagens usando o Pages, Numbers ou Keynote pelo Mac

  1. Com o arquivo aberto, clique no ícone de explorar biblioteca (na barra superior) — ou, na barra de menus, vá até Inserir » Gerar Imagem.
  1. Em seguida, escolha “Gerar Imagem”.
  1. Siga os passos a seguir para gerar, aprimorar e anexar a imagem desejada.

Apple Intelligence On-Device Is Winning the AI Race

18 July 2026 at 20:45

Apple Intelligence on-device processing remains Apple’s most convincing argument in artificial intelligence. Rivals may lead in public model rankings, chatbot adoption and the speed of releasing experimental features, but Apple is building AI inside devices people already use for their most personal work.

That distinction changes the definition of winning.

Apple does not need every iPhone owner to open a separate chatbot app. It can place intelligence inside Messages, Mail, Photos, Notes, Shortcuts, Siri and third-party apps. Local models can operate on private information without automatically transferring that information to an external server.

The strategy appeared slow while the AI market measured progress through chatbot launches and model size. It looks more competitive as the industry confronts cloud costs, privacy concerns, unreliable connectivity and the difficulty of turning general-purpose AI into useful daily actions.

In his video “Apple Lost the AI Race,” Marques Brownlee captures the contradiction in one concise line:

“Apple lost the AI race. Actually, Apple won the AI race.”

The apparent reversal describes Apple’s current position well. Apple may have lost the first race for public perception. It is increasingly prepared for the longer contest over where AI runs, how it reaches users and who controls the personal data required to make it useful.

Apple Intelligence On-Device Changes the AI Relationship

Most popular generative AI products began as cloud services. A user sends a request to a remote model, the provider processes it in a data center and the answer returns through an app or browser.

That structure supports enormous models but creates dependence on internet access, server capacity and continuing infrastructure expense. It also means personal prompts leave the device, even when the provider uses strong security and privacy policies.

Apple Intelligence on-device begins from the opposite direction. The iPhone, iPad or Mac first attempts to handle the request locally using Apple Foundation Models optimized for Apple silicon.

That local model does not need to know everything available on the internet. It needs to understand the user’s request, work with relevant personal context and complete common tasks efficiently.

The difference is similar to owning a capable computer rather than renting every calculation from a distant server. Cloud systems remain useful for difficult workloads, but they no longer need to participate in every interaction.

For Apple, local processing is also a product advantage. The company controls the chip, operating system, model architecture, memory system and apps. Each layer can be designed around the others rather than assembled from unrelated services.

A glowing, abstract, multicolored loop forms a star-like shape on a black background, blending orange, yellow, pink, purple, and blue hues with a soft neon effect—perfect as an AI iPhone or iPhone 20 wallpaper.
Image Credit: Apple Inc.

Privacy Becomes a Technical Feature

Technology companies frequently describe privacy as a policy. Apple is trying to make it part of the AI architecture.

When a request runs entirely on an iPhone, the associated data does not need to leave the device. A model can work with messages, appointments, photos or app content without uploading that personal context to a conventional cloud account.

That structure is especially relevant to Siri AI. A truly personal assistant needs access to information that users may never place willingly inside an ordinary chatbot: private conversations, travel plans, health-related details, work documents and relationships between people.

An assistant becomes more useful as it gains context. It also becomes more invasive when the same context is stored, analyzed or used for model training outside the device.

Apple Intelligence on-device allows Apple to expand personal context while maintaining a stronger boundary around it. The assistant can understand information locally, perform an action and discard temporary processing data without building a permanent advertising or training profile.

This is difficult for competitors whose businesses depend on cloud services, large-scale data collection or engagement inside separate AI products. Apple’s hardware business gives it different incentives.

Private Cloud Compute Extends the Model

Not every AI task can fit within the power and memory limits of an iPhone. Apple uses Private Cloud Compute when a request requires a larger model.

Private Cloud Compute is designed to extend the privacy architecture of Apple devices into the cloud. User information is processed only for the request, is not stored and is not made available to Apple for unrelated purposes.

Independent researchers can inspect software images used by the system, creating an unusual level of outside visibility into the cloud environment. Apple has also expanded the architecture while maintaining control over the software and privacy protections used for processing.

This creates a layered system rather than a simple choice between local and cloud AI.

Apple Intelligence first determines whether the device can handle the request. More complex work can move to Private Cloud Compute. External models may be offered separately when the user chooses to involve them.

The user does not need to understand the technical path behind every answer. The system chooses the smallest and most private environment capable of completing the task.

A glowing blue cloud icon is superimposed on a digital circuit board background, symbolizing private cloud computing and technology. Orange lines and nodes indicate data flow, creating a dynamic and futuristic network visualization that elevates your data management strategy.

Apple Silicon Was an AI Investment

Apple’s control of its processors has become one of its largest advantages in the AI era.

The Neural Engine first appeared years before generative AI became a consumer obsession. It supported Face ID, photography, speech recognition and other machine-learning tasks. Apple continued expanding that hardware across the iPhone, iPad and Mac.

Those investments now provide a large installed base of devices designed to run machine-learning workloads locally. Recent Apple chips combine CPU, GPU, Neural Engine and unified memory in one architecture that can move information efficiently between different types of processing.

The same design helps foundation models run without requiring the power consumption or separate memory systems associated with conventional data-center hardware.

Apple also controls the operating systems that schedule those workloads. A model can be optimized for the exact processors, memory limits and energy behavior of supported devices.

Competitors can build excellent models, but they often need to support hardware from several manufacturers with inconsistent capabilities. Apple can decide that an AI feature requires a specific generation of silicon and design the complete experience around it.

Developers Gain a Local Model

The Foundation Models framework extends Apple Intelligence on-device beyond Apple’s own apps. Developers can use the system model through native Swift tools rather than shipping a separate large model or paying for every cloud request.

An app can generate structured content, interpret natural language or use tool calling while keeping supported processing on the device. Apple handles model delivery and system integration.

This can reduce operating costs for developers. A cloud-based AI feature creates an ongoing expense each time a user submits a request. Local inference uses hardware the customer already owns.

It can also improve reliability. Features may remain available without an internet connection and respond without waiting for a remote service.

The framework encourages a quieter form of AI adoption. Apps do not need to add a prominent chatbot tab or redesign themselves around a conversational interface. Intelligence can appear inside existing workflows as a useful capability.

That is where Apple’s strategy may reach scale. Millions of apps can incorporate small AI functions that users experience as normal software behavior rather than as visits to an AI destination.

A rounded square icon with a stylized neural network diagram in the center, featuring interconnected nodes connected by lines, represents Hidden Apple Intelligence on a light gray background.
Image Credit: Apple Inc.

The Installed Base Is Apple’s Distribution Advantage

The AI race is often discussed as a contest between models. Consumer adoption also depends on distribution.

Apple can deliver new intelligence features through operating-system updates across the iPhone, iPad, Mac and Vision Pro. Users do not need to create another account, choose a provider or transfer their personal information into a new service.

Siri already occupies the system interface. Apple Intelligence can work across first-party apps. Developers can connect their own features through Apple frameworks.

The scale is difficult to reproduce. A model provider may have stronger benchmark scores but still need users to download an app and consciously open it. Apple can introduce AI during actions people already perform: replying to a message, locating a photo, organizing a note or completing a shortcut.

This does not guarantee success. Apple must make Siri AI reliable, keep feature availability consistent and prove that local models can deliver enough capability to satisfy users accustomed to powerful cloud assistants.

The distribution advantage only becomes meaningful when the experience works.

Winning Without Building the Loudest Chatbot

Apple has made mistakes during its AI transition. Siri improvements arrived later than promised, regional regulations delayed features and competitors established powerful consumer brands before Apple completed its new system.

Those setbacks explain why the claim that Apple lost the AI race became persuasive.

They do not settle the outcome.

The first stage rewarded companies that released chatbots quickly and demonstrated increasingly large models. The next stage may reward systems that can integrate AI into ordinary life without demanding constant cloud access, high subscription costs or broad collection of personal information.

Apple Intelligence on-device is built for that stage. It uses hardware already in the user’s hand, protects more personal context locally and gives developers access to intelligence without requiring every interaction to become a server transaction.

Apple does not need to win every benchmark or release the most talkative assistant. It needs AI to become a reliable part of the devices people already trust.

Brownlee’s title works because both statements can be true. Apple lost the visible sprint that defined the early generative AI market. By concentrating on local processing, silicon, privacy and operating-system integration, it may already be positioning itself to win the race that follows.

The post Apple Intelligence On-Device Is Winning the AI Race appeared first on AppleMagazine.

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Apple Intelligence on-device processing gives Apple an AI advantage built around privacy, speed, personal context and hundreds of millions of devices.

Why More Businesses Are Choosing Cheaper Chinese AI Models

17 July 2026 at 22:03
Chinese AI models are gaining business interest as companies weigh lower costs, open-weight flexibility, performance trade-offs, and enterprise risks.
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