Introduces a new MCP server that enables you to use natural language prompts to perform complex tasks. ($74.99 new, free update, 143.8 MB, macOS 11+)

China’s cyberspace regulator has officially registered Apple’s on-device generative AI service, Apple Intelligence, for use in the country. This marks a significant step toward the long-awaited launch of the feature for Chinese consumers.

According to Reuters, “China’s cyberspace regulator said on Wednesday that Apple’s on-device generative AI service, Apple Intelligence, has been registered for use on iPhones in China, paving the way for the long-anticipated rollout of the service in the country.”

China mandates that companies register large language models and generative AI services with regulators before making them available to the public. This approval positions Apple to finally introduce its AI capabilities in one of its most important markets.

The service will integrate local AI expertise. Reuters reports, “Apple Intelligence will incorporate capabilities from AI models developed by Baidu and Alibaba, a source familiar with the matter said, speaking on condition of anonymity.”

Alibaba confirmed its involvement in a statement to Reuters: “Its Qwen model will be integrated into Apple Intelligence across Apple’s iPhone (iOS), iPad (iPadOS), Mac (macOS) and Vision Pro (visionOS) operating systems in China.”

A Baidu spokesperson also noted, “Apple is also working with Baidu to develop Apple Intelligence features for Chinese iPhone users.”

The regulator’s statement provided no specific launch date for Apple Intelligence in China.

This development comes at a crucial time for Apple in China, where the company reported a 24.4% year-on-year increase in shipments in the second quarter. The rollout of Apple Intelligence could further strengthen its competitive position in a market where consumers have eagerly awaited these AI features.

MacDailyNews Take: Clearly good news for Apple and should be for Apple’s – and Alibaba’s – stock prices, too.

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Apple is exploring new ways to keep AI processing on users’ devices, prioritizing speed, privacy, and reduced reliance on the cloud. The company is in early discussions with PrismML, a startup developing technology that dramatically compresses large AI models to fit and run efficiently on iPhones.

According to PrismML CEO Babak Hassibi, who spoke to CNBC, Apple and other companies have been evaluating the startup’s models, measuring their speed, energy efficiency, and performance on devices. “They’re really evaluating our technology right now,” Hassibi said of Apple. He described the discussions as very early but noted that “things are progressing nicely.”

Shrinking Massive Models for Everyday Devices

PrismML, a Khosla Ventures-backed spinout from the California Institute of Technology, recently released compressed versions of Alibaba’s open-source Qwen model. The company reduced the model from roughly 54 GB to less than 4 GB, enabling all 27 billion parameters to run on an iPhone 15 or newer.

The compression technique simplifies how internal information is stored—reducing values from 16 bits to just one or three possible values. PrismML claims the compressed models use 10 to 15 times less memory, generate responses six to eight times faster, and consume three to six times less energy than conventional versions.

Hassibi acknowledged a small performance trade-off: “PrismML’s models typically lose a few percentage points of overall performance, with factual recall weakening before skills such as reasoning, math and coding.” Despite this, the company is releasing two compressed versions for free, designed to run on iPhones, MacBooks, and Nvidia-powered PCs.

Boosting Siri and On-Device Capabilities

This development aligns closely with Apple’s ongoing efforts to enhance Siri. Just before PrismML’s release, Apple opened the public beta of iOS 27, introducing a major overhaul aimed at making Siri more competitive with offerings from xAI, OpenAI, and Anthropic — while emphasizing on-device processing for personal data.

Running more AI locally would bring several benefits:

• Reduced latency compared to cloud requests
• Lower cloud computing costs
• Support for features that work offline
• Stronger privacy protections, especially for sensitive health, medication, or personal information

Carolina Milanesi, president and principal analyst at Creative Strategies, told CNBC: “The more you can do on device, the better it is,” highlighting applications like computational photography, video generation, and health tools.

Analysts note Apple’s integrated hardware-software approach gives it an edge in optimizing these models. Horace Dediu of Asymco explained that Apple aims to keep most common Siri interactions on-device while routing only the most demanding tasks to the cloud. “They’re trying to figure out how big a model and how clever a model they can fit on the device,” he said.

Potential Industry Impact and Caveats

If PrismML’s technology proves effective at scale, it could influence memory requirements and datacenter demands. However, analysts caution that real-world performance — especially on lengthy prompts, multitasking, battery life, and millions of queries — remains to be fully validated.

Tarun Pathak of Counterpoint Research emphasized: “The ultimate test will be millions of queries, thousands of device combinations and robust testing at scale.” Phil Solis of IDC pointed to power consumption as a key open question for always-on or agent-like features.

Hassibi sees broader applications beyond phones, including robotics and autonomous systems where fast, local intelligence is critical: “It’s very important that the intelligence be local and that it can run fast.”

Pathak summed up the balanced future: “The combination of cloud and on-device AI can serve a more complete, efficient and privacy-centric AI experience. Complex tasks will be offloaded to the cloud, whereas sensitive, latency-critical and privacy-relevant tasks will be executed on-device.”

MacDailyNews Take: Apple’s interest in technologies like PrismML underscores its commitment to privacy as a core differentiator while pushing the boundaries of what smartphones can achieve with AI. As testing continues, this could mark a significant step toward more capable, personal, and private intelligent assistants.

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The post Privacy-focused Apple in talks with startup to run more powerful AI models directly on devices appeared first on MacDailyNews.

While many Big Tech peers chase high-risk AI growth, Apple stands out for its stability and resilience. The company is projected to grow free cash flow in 2026 — a rarity among its counterparts — positioning its stock as a defensive haven traditionally reserved for consumer staples, utilities, and healthcare names.

Nate Wolf for Barron’s:
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“No one admits they like or want to buy more AAPL,” Mizuho Securities analyst Jordan Klein wrote Friday. “But I get why more folks [are] looking at AAPL as a hedge or long idea.”

“Analysts estimate Meta Platforms, Oracle, and Amazon will have negative free cash flow in 2026 because of their AI investments. Meanwhile, Apple is expected to produce $143 billion in free cash flow, up from $109 billion last year, per FactSet. Its capital expenditures will likely decline in 2026.

“[Apple] has definitely been out of favor, but carries a lot less direct near-term execution risk,” Klein wrote.”

But Apple is one of the few high-profile tech names that isn’t a primary consumer or supplier of AI compute, and that differentiation has value… If Apple’s share price is any indication, plenty of investors want to keep at least some money away from the AI trade.

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MacDailyNews Take: As we wrote back on February 18 when Apple shares closed at $264.11 ($50 per share ago):

Just wait until Apple begins to release Apple Intelligence features underpinned with — but privacy-protected from — Google Gemini and things like Siri begin to actually work as well as, or even better than, people expect them to work in 2026. The sky’s the limit for Apple stock!

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Apple is in discussions with PrismML, a Khosla Ventures-backed startup that claims to have achieved a major breakthrough in running exceptionally large AI models directly on iPhones without relying on cloud servers, Aaron Tilley reports for The Information. The company says it has successfully compressed and executed a 27-billion-parameter model on the latest iPhone hardware, marking what it describes as the largest AI model ever run fully on-device.

PrismML, which emerged from stealth earlier this year as a Caltech spinout, specializes in extreme model compression techniques, particularly 1-bit and ternary weight architectures. These methods drastically reduce memory footprints while aiming to preserve performance. According to the startup, its technology allowed Alibaba’s open-source Qwen 3.6 (27B parameters) — which normally requires about 54 GB in standard precision — to shrink to under 4 GB. The compressed model reportedly ran with all parameters active simultaneously on an iPhone 17 Pro, enabling more complex on-device tasks like advanced reasoning and software development assistance.

This development aligns with Apple’s long-standing push to enhance Apple Intelligence with more powerful on-device capabilities. By keeping AI processing local, Apple can improve privacy, reduce latency, and lessen dependence on cloud infrastructure and external partners. Sources familiar with the matter indicate Apple has held talks with PrismML about potential integration of its compression technology to expand what future iPhones can handle natively.

The Technical Leap: 1-Bit Models and Intelligence Density

Traditional large language models use 16-bit floating-point precision, leading to massive memory requirements. PrismML’s approach uses 1-bit weights (essentially on/off states) and ternary variants (weights of -1, 0, or +1). The company’s flagship open-source “Bonsai” family includes:

• Bonsai 8B: An 8-billion-parameter model that fits in roughly 1 GB (versus ~16 GB for a typical 16-bit equivalent), while delivering competitive results on benchmarks like MMLU, GSM8K, and HumanEval.

• Smaller variants (4B and 1.7B) optimized for even greater efficiency.

PrismML claims these models offer up to 14× smaller memory use, 8× faster inference, and 5× better energy efficiency compared to full-precision counterparts, resulting in over 10× “intelligence density.” The startup has open-sourced its models under Apache 2.0 and released custom kernels for Apple’s Metal framework, making them compatible with iPhone and Mac hardware.

Co-founders, including Caltech professor Babak Hassibi and other PhDs, emphasize that the breakthrough stems from years of research into neural network compression. Investors include Khosla Ventures, Cerberus Capital, and Caltech itself, with the company raising $16.25 million in seed funding. Vinod Khosla has praised the work as a “mathematical breakthrough” that could shift AI from data-center dominance to efficient edge deployment.

Implications for Apple and the Industry

For Apple, adopting such technology could supercharge features in iOS and Apple Intelligence, enabling more sophisticated AI agents, real-time coding help, or advanced multimodal capabilities without constant server calls. It also addresses growing concerns around energy consumption and data privacy in AI.

PrismML positions its tech not just for consumer devices but for robotics, wearables, and industrial edge applications. By open-sourcing core models, the company hopes to accelerate adoption and invite community improvements.

While independent verification of all performance claims is still emerging, the reported iPhone demo and Apple’s interest signal strong validation. As the AI race intensifies, solutions that pack more intelligence into everyday devices — without ballooning costs or power draw — could prove transformative.

PrismML plans further releases and is expected to continue engaging with major device makers.

MacDailyNews Take: For Apple, which has invested heavily in on-device AI silicon like the Neural Engine, this could represent a key for the next-gen of truly personal, secure, and private artificial intelligence.

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Enables direct image editing in Pixelmator Pro for Apple Creator Studio subscribers. ($129.99 annual Apple Creator Studio subscription, various sizes, macOS 15.6+)

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.

2. Em seguida, escolha “Gerar Imagem”.

3. Siga os passos a seguir para gerar, aprimorar e anexar a imagem desejada.

Depois de já termos publicado vários vídeos sobre as novidades do iOS 27, chegou a vez de começarmos a cobertura em vídeo do macOS Golden Gate 27 em nosso canal. E não tem jeito melhor de abrir essa série do que falando sobre a mudança mais aguardada do sistema: a Siri AI.

Neste primeiro vídeo, mostramos como funciona o novo app da Siri, os ajustes de voz disponíveis, as melhorias na busca do Spotlight, os recursos da Inteligência Visual a partir de screenshots e as ferramentas de escrita e revisão de texto integradas ao sistema.

Esse é só o primeiro de vários vídeos que estamos preparando sobre o macOS 27. Fique de olho no canal do MacMagazine para não perder os próximos! 😄

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Apoio: UPDF

Este vídeo tem o apoio do UPDF, aplicativo equipado com inteligência artificial (IA) que já analisamos em detalhes aqui no site. Conheça mais esse belo editor de PDFs, obtenha-o com um desconto exclusivo e tenha acesso total ao UPDF Pro no Mac, no Windows, no iPad, no iOS e no Android pagando cerca de um quinto da suíte da Adobe!

The social media giant Meta just added a major safety feature to its digital assistant. When younger users have conversations that involve thoughts of suicide or hurting themselves, the company will step in. Instead of just showing crisis hotlines on the screen, the system will now send a direct notification right to a linked parent […]

The post Meta AI Updates Its Chatbot To Alert Parents About Teen Self-Harm appeared first on The Mac Observer.

If you want an artificial intelligence tool to book a flight or buy an audiobook, it usually needs to log into your personal accounts. Sharing your private login details directly with a chatbot feels risky, but a new software update changes that process entirely. The popular password manager 1Password just built a clever way for […]

The post 1Password Now Lets Claude Log In Without Seeing Your Passwords appeared first on The Mac Observer.

The European Commission just told Google to stop giving its own artificial intelligence assistant special treatment on smartphones. Regulators declared that the company must give competing software the same system permissions currently used by Gemini. This order falls under the Digital Markets Act, forcing the tech giant to open up deep phone controls that were […]

The post The EU Orders Google to Give Rival AI Apps Equal Android Access appeared first on The Mac Observer.

OpenAI recently teamed up with Work Louder to release a physical tool for developers. Reports show OpenAI is selling $230 Codex Micro hardware product units on its website now. The keyboard brings your digital agent workspace straight to your desk. It helps users manage active chats and keep track of tasks through live lighting feedback. […]

The post OpenAI Is Selling $230 Codex Micro Hardware Product With Work Louder appeared first on The Mac Observer.

If you have an iPhone, the AI music maker Suno just updated its software to make it much easier to share custom tracks with your friends. With a recent software update, Suno now lets iPhone users generate songs directly in iMessage without ever having to leave the chat window. You can easily turn your everyday […]

The post Suno App Now Lets You Generate AI Songs Directly in iMessage appeared first on The Mac Observer.

“The Lord of the Rings: The Hunt for Gollum,” will de-age actors using AI, the actor and director Andy Serkis confirmed to Variety.

“There’s a little bit of de-aging for some of the characters and machine learning is part of the process,” Serkis, who is both directing the new film and reprising his famous role as Gollum, told Variety.

AI is an incredibly contentious topic in Hollywood. Some studios, like A24, have leaned into generative AI. Others in the industry, from actors to directors and writers, have lambasted the tech, with many fearing that AI will be used to replace industry jobs or simply result in lower-quality work. As the tension between the pro-AI and anti-AI — or perhaps AI-resigned — factions deepen, the industry and its leaders, Serkis included, are publicly grappling with the technology and what it means for a key creative industry.

In addition to Serkis, returning actors from past films include Elijah Wood as Frodo, Ian McKellen as Gandalf, and Lee Pace as Thranduil — all of whom are markedly older than when the original “Lord of the Rings” trilogy and the prequel franchise “The Hobbit” were filmed. Beyond de-aging, though, Serkis said that “at present,” there are no other plans to use AI in the making of the new movie.

“We’re not creating AI shots in our movie, every shot is created in a traditional way,” said Serkis. “One of the things actually that I really wanted to do with this film was to bring back all of the great filmmaking skills, from miniatures to prosthetics and marry them up, because that’s my taste.”

Serkis didn’t nix the idea of using AI altogether. He noted that Peter Jackson, who famously directed the previous live-action movies in the celebrated franchise, worked with the software engineer Stephen Regelous to develop the AI-powered special effects software known as MASSIVE back in the early 2000s.

“When you think about it, in the original ‘Lord of the Rings’ films, Peter created MASSIVE, which was a program which allowed thousands of orcs to all have their own individual mindset,” said Serkis. “So that is a brilliant example of an incredible use of AI.”

He added that AI can be a “valuable” creative tool “as long as it’s not exploitative and as long as it’s not harming anybody or defaming anybody or telling mistruths.”

“When it becomes exploitative and people are not remunerated for the work that they’ve done, or it’s used in nefarious, or mean-spirited or pornographic ways, then of course, that’s terrible and we’ve only brought it upon ourselves,” he added. “I’ve said this before and I mean it — we are the parents of AI, and we have to be good parents and teach AI well. And if we teach AI well, then it can help us across many industries.”

As The Tab noted, many Lord of the Rings fans responded positively, drawing a line between machine learning-infused virtual effects software and generative AI tools that churn out text, audio, and imagery.

“AI is perfect for de-aging,” wrote one commenter. “It should get a complete and utter free pass for that. Having an artist sit and de-age someone must be a horrific chore. Let them work on something fun instead.”

“Every single VFX tool these days uses AI for some part of the processing,” added another. “This isn’t generative AI.”

Other famous filmmakers’ AI stances, meanwhile, haven’t received the same warm reception from fans.

More on AI and movies: Film Community Aghast as Martin Scorsese Extolls AI Startup, Says He Now Uses AI for Storyboards

The post “The Lord of the Rings: The Hunt for Gollum” Will Use AI to De-Age Actors appeared first on Futurism.

Safari Notify Me gives Apple’s browser a useful new role in online shopping: watching a product page after the shopper has closed it. Instead of repeatedly returning to check whether an item is available or whether its price has changed, users can ask Safari to monitor the page and send an alert when the requested update appears.

The feature arrives as online shopping becomes increasingly fragmented. Prices can change several times during a promotion, popular items disappear within minutes and retailers often require shoppers to join separate mailing lists for availability alerts. Dedicated tracking apps can help, but each adds another account, extension or subscription.

Safari Notify Me places the monitoring tool inside the browser already being used to view the product. It is simple enough for occasional purchases while potentially useful for expensive electronics, limited releases, event registrations and products that move in and out of stock.

Safari Notify Me Watches the Page for You

Safari Notify Me is designed to monitor changes on a specific webpage. The user identifies what should be watched, such as a lower price, a product returning to stock or registration becoming available. Safari then checks the page and sends a notification after detecting the relevant change.

Apple has presented price changes and product restocks as central examples, though the feature is not restricted to shopping. It may also help with reservations, ticket availability, enrollment openings or other pages where one detail changes over time.

For shopping, the advantage is immediate. A customer can leave the product page without relying on memory, leaving dozens of tabs open or refreshing the site throughout the day.

The browser becomes temporarily responsible for the follow-up.

This differs from a retailer’s own email alert. Store notifications usually depend on the business offering the feature, and they may focus only on inventory. Safari can monitor the page according to the user’s request, potentially covering price and availability without requiring another marketing subscription.

How Safari Price Alerts Help

Online prices are rarely as stable as the label suggests. Retailers adjust discounts, respond to competitors, launch short promotions and change prices according to stock levels.

A shopper interested in a Mac accessory, appliance or expensive display may not want to purchase immediately at the listed price. Checking the page every day is inefficient, while joining a store mailing list can produce far more promotional email than useful information.

Safari price alerts create a quieter alternative. The user can identify the product and wait for the browser to report a meaningful change.

The feature does not replace price history. Safari may detect that the amount has dropped, but that does not necessarily prove the new price is the lowest offered during the year. Dedicated price-tracking services may still provide charts, comparisons and retailer-specific history.

Safari Notify Me is better understood as a page-change assistant. It tells the shopper that something requested has happened. The decision to purchase remains with the user.

Restock Alerts May Be Even More Useful

Restock monitoring may become the feature’s strongest shopping use. Limited products can return without warning and sell out before a retailer’s email reaches every subscriber.

This often happens with game consoles, graphics hardware, collectibles, seasonal products, concert merchandise and popular configurations of newly released devices. Size and color variations can also return separately, making a general product alert less useful.

Safari restock alerts can focus on the page the user is already viewing. A notification provides a reason to return without requiring the tab to remain open.

The browser cannot reserve the item or guarantee that inventory will remain available. A notification may also arrive after other buyers have begun ordering. Safari removes the repeated checking, but it does not control the retailer’s inventory system.

That limitation is reasonable. Notify Me helps users notice the opportunity; it does not turn Safari into an automated purchasing bot.

Using Safari Notify Me

The feature is intended to require little setup. Users begin on the relevant product or registration page and tell Safari which change they want it to watch.

To create a Safari Notify Me alert:

Open the webpage in Safari > Select Notify Me > Describe the price, availability or page change to monitor > Allow Safari notifications when requested

The exact options shown may depend on the device, webpage and software version. Apple is introducing the feature with its new operating-system releases, and availability may vary by language or region.

A useful request should be specific. Asking Safari to report when the item returns to stock is more actionable than asking for any page change. For price monitoring, the user may request a reduction or watch for a particular target when the page supports enough information.

Once the alert is active, there is no need to keep the product page open. Safari sends a notification after detecting the requested update, allowing the user to return directly to the page.

A Better Use for Apple Intelligence

Safari Notify Me is a practical example of Apple Intelligence operating as an assistant rather than a writing tool. It interprets what the user wants, watches for a future condition and reports back when that condition appears.

The feature does not need to generate a long answer or place a chatbot beside every shopping page. Its value comes from removing a repetitive task.

That restrained approach fits Safari. The browser already manages passwords, private browsing, tab organization, Reader and tracking protections. Monitoring a page extends that utility without turning Safari into a retailer or shopping marketplace.

It may also reduce the need for third-party extensions among casual users. Someone who occasionally watches one product does not necessarily need a dedicated deal platform with wish lists, affiliate links and account registration.

Specialized services will remain useful for serious bargain hunting. Safari covers the simpler request: tell me when this exact page changes in the way I care about.

Notifications Need Restraint

Any feature built around alerts can become noisy when used too freely. Monitoring every product considered during casual browsing could fill Notification Center with price changes and restocks that no longer feel relevant.

Safari Notify Me works better when reserved for purchases with genuine intent. A few focused alerts are easier to understand and act upon than dozens of loosely defined page watches.

Users should also remove alerts after buying the item or losing interest. A notification for a product purchased weeks earlier adds clutter without saving time.

Safari notifications can be managed through the device’s normal notification settings. Disabling all Safari alerts may also silence other useful browser notifications, so reviewing individual watches inside Safari is preferable when available.

Price Is Not the Only Shopping Decision

A lower price can encourage a quick purchase, but shoppers should still review the seller, return policy, warranty and delivery estimate. Notify Me reports a page change; it does not evaluate whether the store is reliable or whether the offer has hidden conditions.

A product may return through a third-party marketplace seller at a higher price. A discount may apply only after a membership, coupon or trade-in. Limited inventory can also create pressure to buy before reading the terms.

Safari’s privacy protections and fraud warnings remain relevant, but users should confirm that the page belongs to the intended retailer before entering payment information.

The alert is a starting signal, not an endorsement.

Safari Becomes More Useful After the Tab Closes

Browsers traditionally stop being helpful once users leave a page. Safari Notify Me changes that relationship by allowing selected pages to remain useful without remaining visible.

For shoppers, that means fewer repeated searches, fewer forgotten products and less dependence on promotional email. Price and restock alerts can operate quietly until there is a reason to return.

The feature will not replace advanced shopping trackers, and it cannot guarantee inventory. Its appeal is that most users do not need those larger systems for every purchase.

Sometimes the entire shopping problem is waiting for one price to fall or one button to change from unavailable to buy. Safari Notify Me allows the browser to handle that wait.

The post Safari Notify Me Makes Online Shopping Easier appeared first on AppleMagazine.

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.

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.

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.

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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EU tech regulation, Digital Markets Act, Apple Europe sales, Apple regulation, European Union, Siri AI, iPhone features, device interoperability, App Store changes, alternative marketplaces, iPhone Mirroring, AirPods translation, Apple privacy, iPhone security, app sideloading, platform competition, DMA compliance, Apple Intelligence, European technology, government control

EU tech regulation is no longer limited to App Store payment rules or competition disputes hidden from ordinary consumers. It is beginning to determine which features reach European devices, how quickly they arrive and how deeply third-party companies can interact with the iPhone, iPad and Mac.

The Digital Markets Act was designed to reduce the control of large technology platforms over software distribution, payments, browsers, digital assistants and connected hardware. For Apple, compliance has already produced alternative app marketplaces, web distribution, third-party payment options, additional default-app controls and expanded access to iPhone technologies.

The next phase reaches much deeper into the operating system. European regulators want competing accessories, cloud services and AI assistants to receive access to capabilities traditionally reserved for Apple’s own products.

Apple argues that some of those demands could weaken privacy and security. The European Commission says the company is responsible for creating compliant systems that preserve both competition and user protection.

Between those positions sits a large and commercially significant group of customers. Europe generated $28.06 billion in Apple sales during the quarter ending March 28, 2026, up from $24.45 billion one year earlier. Six-month European sales reached $66.20 billion, compared with $58.32 billion during the same period of fiscal 2025.

Europe therefore represented more than one-quarter of Apple’s latest quarterly revenue. It is too valuable to leave behind, but increasingly difficult to serve with the same software experience available elsewhere.

EU Tech Regulation Is Splitting Feature Availability

Regional differences once centered mainly on language support, licensing agreements or local services. EU tech regulation is creating a more structural divide.

Apple has blamed Digital Markets Act requirements for delaying Siri AI across the European Union. The company says regulators expect competing AI assistants to receive extensive access to personal information, apps and device actions before Apple can reserve those capabilities for its own assistant.

The disagreement concerns more than answering questions. Siri AI is designed to read personal context, understand onscreen information and complete actions across apps. That may include finding messages, accessing files, making purchases or sending information on the user’s behalf.

Opening those capabilities to outside AI systems requires new permission structures, technical interfaces and safeguards. Apple says it cannot release its assistant first and add competing access later without risking regulatory action. The Commission says Apple had sufficient time to design an interoperable solution.

Other delayed European features have included iPhone Mirroring on Mac, Live Translation through AirPods and certain location-based Maps capabilities. Each feature touches a different part of the ecosystem, but all depend on privileged communication between Apple devices, software and services.

The consequence is becoming visible at purchase. Two customers can buy the same iPhone model at similar prices and receive different capabilities because one lives inside the European Union.

Feature Adoption Becomes Slower and Less Predictable

Delayed availability can weaken the adoption of new hardware features even when the devices themselves continue selling well.

Siri AI is intended to become a central part of newer iPhones, iPads and Macs. Buyers who cannot access it lose part of the justification for newer chips, additional memory and on-device AI processing. Developers also face a smaller addressable audience for apps built around the new assistant.

AirPods Live Translation presents a similar problem. A feature designed to demonstrate the combination of iPhone processing, microphones and wearable audio becomes unavailable in a region built around dozens of languages and frequent cross-border travel.

iPhone Mirroring affects the relationship between iPhone and Mac. Users outside the EU can interact with the phone from macOS, while European users may receive notifications without gaining the complete experience.

These differences do not necessarily stop hardware sales. Apple’s newest results show strong European demand despite years of regulatory conflict. They can, however, reduce the speed at which customers use the ecosystem’s newest capabilities.

The effect may grow as software becomes a larger part of hardware differentiation. A faster processor has limited emotional value when the feature designed to demonstrate it is unavailable.

Apple Sales Show Why Europe Cannot Be Ignored

Apple does not report European Union revenue separately. Its Europe segment also includes countries outside the bloc, along with India, the Middle East and Africa. The official segment remains the best regularly published measure of the region’s commercial weight.

European sales rose approximately 15% year over year in Apple’s latest reported quarter. During the first six months of fiscal 2026, the segment expanded by roughly 14%.

Those figures weaken the argument that regulation is already driving customers away from Apple hardware. Demand remains strong, supported by the iPhone 17 family, Mac sales, services and the company’s installed base.

The financial risk is more gradual. Regional software fragmentation can raise engineering costs, delay launches and make European devices less competitive against products able to offer complete feature sets.

Apple must maintain separate distribution rules, payment systems, browser options and eligibility checks. Developers must decide whether alternative stores, external payments or EU-specific business terms justify additional work. Support teams must explain why features differ between countries using the same operating-system version.

A market responsible for more than $28 billion in one quarter can absorb considerable compliance expense. It can also influence Apple’s global product decisions when regulators demand interfaces that cannot be restricted to Europe easily.

A Slow Transfer of Ecosystem Control

The escalating regulatory environment also creates a more fundamental concern: control over complex technology ecosystems can gradually move away from the companies that designed them and toward government committees, regulatory bodies and administrative processes.

That transfer rarely happens through one dramatic order. It develops through repeated obligations covering app distribution, payment systems, browser engines, digital assistants, hardware access, data portability and interoperability. Each requirement may appear narrow when considered alone. Together, they can redefine who determines how the ecosystem operates.

Apple built its platform around tight integration between hardware, software, services and security. Regulators increasingly treat parts of that integration as market power that must be opened to competitors. The danger is that an ecosystem designed as one coordinated environment becomes subject to decisions made by committees that do not carry direct responsibility for product quality, reliability or long-term maintenance.

This can become a slow trap. Once a platform is required to expose one layer, regulators may use that access as the basis for demanding another. A payment exception can be followed by alternative app stores. Alternative stores can lead to broader installation rights. Device interoperability can expand into access for AI assistants, personal data and system actions.

The boundaries of the platform are then set less by engineering judgment and more by regulatory negotiation.

Government agencies have legitimate authority to address competition and consumer harm. The concern appears when regulation shifts from preventing abusive conduct to directing product architecture. At that point, public authorities begin influencing feature design, release timing, software permissions and the relationship between first-party and third-party services.

That creates consequences beyond Apple. Any company considering a tightly integrated product may decide that deep integration invites intervention. Businesses could avoid building ambitious ecosystems if successful coordination later becomes grounds for forced access.

Innovation then becomes shaped by what regulators are likely to permit rather than by what engineers believe will produce the safest or most coherent experience.

Competition Gains Come With Real Consumer Choices

EU policy has produced benefits that Apple rarely emphasizes. Users can install apps through alternative marketplaces or directly from authorized developers. Developers can offer external payment methods, promote different prices and avoid relying entirely on Apple’s distribution system.

Alternative browser engines can compete with WebKit, while users have more control over default apps. Contactless payment access has expanded beyond Apple Pay, allowing competing wallet providers to use the iPhone’s NFC technology under approved conditions.

Interoperability requirements could also improve third-party accessories. Smartwatches, headphones and other devices may gain better notification access, background connectivity and proximity pairing with the iPhone.

These changes can increase competition and reduce the advantage Apple gives its own services and accessories. A third-party smartwatch should not become artificially less useful simply because it was not made in Cupertino.

The difficulty is separating legitimate platform access from unlimited access. A notification interface is one thing. An autonomous AI assistant capable of reading messages, accessing files and acting across apps introduces a different level of sensitivity.

Privacy and Security Risks Are Not Theoretical

Alternative app distribution increases user choice, but it also moves some responsibility away from the App Store. Apple continues to notarize apps distributed through approved alternative channels, checking for known malware and severe fraud. That process is narrower than a complete App Store review.

Purchases made outside Apple’s payment system also fall outside its normal refund and billing support. Users may need to resolve disputes directly with the developer or payment provider.

A malicious marketplace, deceptive payment page or compromised developer account can create opportunities for fraud. Enterprise users face additional concerns when employees install software from sources their organization has not approved.

The AI question reaches further. A third-party assistant may need permission to access messages, photos, calendars, documents and app controls. Even a reputable provider can collect more information than the user expects or introduce vulnerabilities through poorly designed integrations.

Apple can build permission prompts, app isolation and revocation controls, but technical access always creates some exposure. Security depends on how narrowly permissions are defined, how visibly they are used and whether the operating system can stop unauthorized actions.

The Commission maintains that interoperability and privacy can coexist. Apple maintains that regulators are demanding access before adequate protections are ready. Both positions contain a legitimate concern: dominant platforms should not block competition, and competition should not require users to surrender control of personal data.

Government-Controlled Architecture Creates Accountability Gaps

When regulators require a company to alter its architecture, responsibility can become blurred.

Apple remains the company customers blame when an iPhone feature fails, a third-party marketplace distributes a harmful app or an outside assistant misuses personal data. Regulators may have required the access, but they do not operate the device, provide technical support or repair the damage to the platform’s reputation.

This creates an accountability gap. Government committees can mandate openness without assuming the commercial and security consequences of that openness. Apple must comply, maintain the system and explain the outcome to users.

The same problem applies to delayed features. Regulators may argue that Apple chose not to release a service, while Apple may argue that the required conditions made the launch unsafe or technically impractical. Customers are left with less functionality and no simple way to determine who caused the delay.

Over time, the ecosystem can become a negotiated compromise rather than a product with one coherent direction. That may satisfy formal compliance while producing a weaker experience for everyone involved.

The risk is not that governments will literally operate Apple’s software. It is that committees increasingly define the conditions under which Apple can design, connect and release its own features. Control shifts through constraints.

The Industry Will Follow Europe’s Experiment

The consequences extend beyond one company. Google, Meta, Microsoft, Amazon and other platform operators face related European obligations. Hardware makers must consider whether ecosystem advantages can survive when core services are required to support rivals.

Smaller developers may gain new distribution and payment choices, but they may also inherit more compliance, customer-service and security responsibilities. Accessory companies could compete more effectively while becoming accountable for handling sensitive device data.

Other governments are watching. Rules introduced in Europe can influence legislation elsewhere, particularly when companies decide that maintaining one global technical framework is easier than operating several regional versions.

Apple is unlikely to abandon Europe or stop adapting its products. Its sales provide too much evidence of the region’s importance. The company will continue negotiating, appealing decisions and building compliance systems while withholding features it considers unsafe under current demands.

European customers may receive more app stores, payment choices and accessory compatibility. They may also wait longer for headline features included with the same hardware elsewhere.

The deeper consequence may be a technology industry that becomes more cautious about building tightly integrated products. Companies may design around anticipated regulatory demands from the beginning, limiting exclusive features, reducing private-system integration or avoiding innovations that depend on controlled access.

EU tech regulation began as an effort to constrain dominant platforms. Its long-term effect may be to transfer part of the power to shape those platforms from companies and users to regulatory institutions.

That shift deserves scrutiny equal to the market power it is intended to correct. Competition rules can restrain abuse. They can also become a slow mechanism for placing product design, security choices and ecosystem evolution under government supervision.

Shady Control and Bureaucracy

The danger grows when regulatory discretion becomes buried beneath permits, approvals, negotiations and technical committees that operate beyond meaningful public scrutiny.

The more power officials hold over which features, contracts or technologies may proceed—and when—the greater the opportunity for lobbying, favoritism and selective enforcement to influence outcomes. What begins as oversight can gradually become a system in which delay itself is leverage, while responsibility disappears inside layers of administration.

For the technology industry, that risks replacing transparent product decisions with political access, negotiated exceptions and regulatory influence exercised far from the consumers expected to live with the consequences.

The post EU Tech Regulation Creates a Costly Split for Apple appeared first on AppleMagazine.

Meta executives claimed that a controversial facial recognition feature didn’t “exist.” Fast forward a few weeks later, and they’re describing the feature in public — and in detail.

In June, a Wired investigation revealed that Meta had quietly infused unreleased facial recognition tech into its “AI Glasses,” the tech giant’s chatbot and camera-equipped smart glasses. While the feature, dubbed NameTag, was inaccessible to consumers, it was designed to register faces encountered by Meta glasses wearers “into unique biometric signatures, commonly known as faceprints, and check each one against faceprints stored on the user’s phone,” according to the magazine.

It’s safe to say that Meta executives were furious after Wired published its investigation. After all, the company has a long track record of data privacy violations. The revelation that its “pervert glasses,” as some have taken to calling Meta’s controversial smart glasses, could soon be using facial recognition tech — not unlike the eyewear being used by Immigration and Customs Enforcement (ICE) agents — fueled an existing PR disaster.

Andy Stone, the tech giant’s spokesperson and VP of communications, declared on X that Wired’s reporting was “intellectually dishonest” and “advocacy-driven click bait.” What’s more, according to Stone, NameTag was fully nonexistent.

“Here’s a thing: Wired reports Meta didn’t answer several questions about how this will work,” Stone added in a follow-up post. “How could we? The feature doesn’t exist!”

In response to Stone, another Meta executive, chief technology officer Andrew “Boz” Bosworth, jumped in.

“Incredibly misleading from Wired,” he wrote. “Absolutely dishonest.”

Yet despite company leaders reassuring us that the feature doesn’t exist, Bosworth discussed it in detail during an interview with The Atlantic CEO and podcaster Nick Thompson. Bosworth’s comments in the interview, which was published last week, seemingly contradicted his fellow executives, revealing that the feature did indeed exist.

NameTag, Bosworth told Thompson, would be “encrypted locally to your device,” and would catalog people who smart glasses wearers “met in person, with your glasses on, who introduced themselves, or you said, ‘okay, this is David, remember this person.'”

This information is “only available to you, when you are wearing your glasses,” Bosworth added. He emphasized that the data captured by NameTag wouldn’t be stored in a centralized database.

“This is a person you’ve met before. Here’s their name. They’re right in front of you. That’s… what we call a NameTags feature,” said Bosworth. “I think people get confused because they hear face recognition and they think, ‘oh, there’s a central face database that everyone’s being scanned constantly into.’ It’s not that.”

In addition to supporting blind or low-vision smart glasses wearers, said Bosworth, NameTag could solve what Meta calls “the cocktail party problem,” saving wearers from any awkwardness that may arise when encountering people at parties who they’re sure they’ve met before, but can’t quite place.

“It’s a very universally human problem,” Bosworth said. “Nearly every human I talk to, no matter what their status of their vision or their memory, understands that this is a problem that would help them feel more comfortable in social situations if they had it.”

To be clear, Wired never suggested that the facial recognition feature it uncovered was being used to build a “central face database” by way of Meta’s smart glasses. Indeed, in line with what Bosworth said in the podcast appearance, Wired reported that “code discreetly added to Meta’s AI app over multiple updates this year shows that the feature, internally called ‘NameTag,’ identifies people captured by the glasses’ camera and, when activated, alerts the wearer when it recognizes someone.” The story also repeatedly noted that the feature was unreleased and inaccessible to glasses wearers.

When journalists and others called out the contradiction between Meta’s past and recent statements, Stone — the comms executive who said that Wired couldn’t answer questions about the feature because it “doesn’t exist” — jumped back in the comments section.

“We have said for months we’re exploring such features, even as nothing has shipped to consumers,” the spokesperson said in response to a post by The Intercept journalist Sam Biddle. “No secret there despite the conspiratorial thinking.”

There’s a big difference between a feature not existing and a feature that exists — if still unfinished — and has yet to be released. Meta appears to be arguing that if a feature remains inaccessible to consumers, it’s technically nonexistent, even if the company has gone as far as to issue multiple updates inserting code for the feature into products that are already in consumers’ hands. (Meta quietly deleted the NameTag code after its existence was made public.)

During the podcast interview, Bosworth took care to emphasize that Meta is considering the privacy implications of a facial recognition-powered feature like NameTag. He noted that it’s likely illegal in states like Illinois and Texas, and that it “has to be done in a way that people feel comfortable.”

Meanwhile, Meta continues to fight an ongoing consumer harm lawsuit, prompted by an investigation by a pair of Swedish newspapers. The publications found that Meta collected recordings by smart glasses wearers and passed them along to human data labelers, despite promising consumers that their recordings would be stored only on their devices.

“Designed for privacy,” reads a webpage for Meta’s smart glasses, “controlled by you.”

More on Meta’s smart glasses: Meta Furious Over Bombshell Smart Glasses Revelation

The post Top Meta Exec Describes Controversial Facial Recognition Feature in Detail After the Company Claimed It Didn’t Exist appeared first on Futurism.

Despite a financial situation more reminiscent of a Ponzi scheme than a technological revolution, the data center boom is continuing at a rapid pace, bringing novel kinds of biological contamination, ear-splitting noise, and unprecedented levels of pollution to communities across the US.

Those environmental burdens also come with a financial one: skyrocketing demand for electricity, which is increasing the cost of utilities for renters and homeowners alike.

According to a report by Monitoring Analytics, an independent monitor for the largest transmission company in the US, PJM, data center demand is expected to drive over $23 billion in customer price increases by 2028. That eye-watering figure, first spotted by Fortune, is a direct result of the country’s old and confusing electrical infrastructure, which ultimately leaves regular people, not the tech industry, holding the bag.

Whether they’re data centers, factories, or other large facilities, Fortune points out that local regulators and transmission companies like PJM have a hard time figuring out who’s responsible for rising energy demand. While a small power line from a data center campus to a nearby substation is easily billed to the data center, figuring out who to invoice gets harder further on down the line, particularly with shared infrastructure like the substation itself, or the long-distance transmission lines connecting to it.

Though utility companies can and do charge data centers for the electricity they use, Fortune observes that the facilities undergirding the AI boom can “fine tune” their electricity use minute-by-minute, gaining an edge that the average consumer could only dream of.

Because many utility companies charge based on a system of “peak demand” — a measure of a customer’s energy usage at the exact moment the collective grid hits peak demand — data centers have gotten into the habit of scaling down right when the grid measures highest demand. That’s not because they’re actually trying to use less power, but because that narrow window is what determines how high their bill will be. In reality, their overall usage remains the same.

This is more or less the scenario that played out in a Bitcoin mining operation in Texas, where the company Riot Platforms agreed to cut its power use on hot summer days, only to ramp back up massively at night. In exchange, the company negotiated for a lower flat electricity rate overall, and even snagged some state subsidies meant to encourage responsible energy use.

Load-shifting like this can genuinely help the grid, but it also means companies with the ability to game the system get rewarded with subsides that an average household will never get. And because companies are merely changing when they suck their juice — not how — subsidized load-shifting ends up being a poor strategy for reducing electrical use overall.

And while data centers are just the most contemporary example of this practice, the shrewd manipulation of US energy markets by for-profit corporations dates back decades. That may not be comforting news for citizens scrambling to hold data center firms accountable in the here-and-now, but it should at least give them an idea of where to start looking for inspiration.

More on data centers: New York Becomes First State to Ban AI Data Centers

The post Data Centers Are Making Electricity Brutally Expensive for the Public appeared first on Futurism.

Meta patented AI tech that constantly analyzes your voice and surroundings in order to detect your emotional state. Finally, exactly what we were all asking for: Meta being granted constant access to our offline lives.

As first caught by Patentlyze, a patent published on July 2 describes a system that records all the user’s “audible communications” and combines it with “contextual factors” like “time of day, location, user activity, or digital interaction.” Audio may be “transcribed, and an emotional-state machine learning model may interpret verbal and nonverbal cues to determine emotional indicators.”

In other words, the system listens to you and everything you do, combines it with other data, and feeds it all to a mood-predicting AI.

“The system increases the precision and reliability of emotional inference by aligning multimodal sensor inputs on synchronized timelines, which creates a novel data structure that supports richer emotional analysis,” reads the patent. “These combined features deliver a technical improvement in automated audio interpretation, enabling continuous emotional monitoring on everyday devices.”

According to the patent, the goal of this extraordinarily intrusive system would be to better tailor users’ workouts to their emotional state, as “personal trainers cannot provide the level of precision in guidance, such as correcting a pose and/or body movement,” as well as Meta’s imagined device could.

It’s not surprising to see Meta pitch this kind of surveillance technology as a fitness device. Health-tracking wearables have become wildly popular, despite the extraordinary amount of physical data about individual consumers they collect and store.

The key difference in Meta’s case, is that rather than crunch biological metrics, it’s an AI-powered fly-on-the-wall attempting to measure a person’s emotional state by listening in on the world around them, and possibly then connecting that information to all other available data.

“The AI assistant may listen to a user(s) at predefined times to hear various types of communication, such as sighs, laughter, and/or the tone(s) of a voice(s),” reads the patent. “The AI assistant may use these inputs to quantify the user’s emotional state or generate other insights about the user.”

The patent also discusses connecting audio inputs to information like when a user takes their medicine, proposing that “the AI assistant may take multiple inputs in addition to audio inputs (e.g., of a user’s voice) to provide a summary of emotional trends based on various inputs (e.g., a happier emotional state associated with a particular time of day or at a time when medication is taken, etc.)”

It’s worth noting that fellow tech giant Amazon tried and failed to market a similar system. In 2020, the company launched the Halo Band, a fitness band with a built-in microphone that was designed to listen in on users and conduct what Amazon described as a “tone of voice analysis.” Following public backlash in 2021, Amazon nuked the microphones when it launched a next-generation version of the band. It discontinued the product line altogether in 2023.

Whether we’ll ever see Meta attempt to launch a similar mood-tracking device is unclear. In a statement to 404 Media, a Meta spokesperson said that “like other companies, patents at Meta are often filed to disclose concepts that may or may not be implemented, and a granted patent does not guarantee that Meta has pursued or will pursue the technology described.”

The existence of the patent, though, shows that such a device is certainly on Meta’s mind — and is yet another Meta-made product that stands to strengthen the bridge between our online and offline worlds.

More on Meta products: The Backlash Is So Strong That People With “Pervert Glasses” Are Afraid to Use Them in Public

The post Meta Patents Technology to Detect Your Mood by Constantly Analyzing Your Tone of Voice appeared first on Futurism.