Se você rolou pelos feeds das principais redes sociais na manhã de hoje, percebeu que já começaram a pintar os primeiros reviews do iPhone Duo, cujo lançamento ocorrerá nesta sexta-feira (23/10).

Horas antes de o embargo cair, contudo, uma série de vídeos de unboxing e hands-on começaram a pipocar internet afora, nos dando uma chance de conferir o mais novo smartphone da Apple um pouco mais de perto.

Um dos veículos a divulgar vídeos do iPhone Duo foi o canal do YouTube Kingmi Mobile, que publicou não só um, mas dois vídeos de unboxing — um para o modelo na cor branco-estrela (star white) e outro para a versão na cor céu noturno (night sky):

Em um terceiro vídeo, o canal mostra elementos como o vinco e a câmera interna sob a tela do iPhone Duo com mais detalhes:

O dobrável também aparece em outros vídeos publicados em redes sociais como o X:

Primeiros reviews

Como dito, o embargo estabelecido pela Apple para a publicação de vídeos a respeito do iPhone Duo caiu às 9h da manhã, e as primeiras impressões acerca do dobrável já estão pipocando na internet.

Entre os criadores de conteúdo que puderam colocar as mãos no dobrável antecipadamente, estão os YouTubers Marques “MKBHD” Brownlee e Matti Haapoja, bem como a jornalista Joanna Stern (ex-Wall Street Journal) e o site The Verge:

Como era de se esperar em se tratando de um smartphone de primeira geração, as opiniões sobre o aparelho até agora têm sido um tanto mistas, embora elas tendam a pender para um lado mais favorável — o que indica que a Apple acertou na execução, ainda que haja espaço para melhorias.

Um dos aspectos mais elogiados do iPhone Duo até agora é, sem dúvida, a sua tela interna com o acabamento nano-texture, que torna a utilização do aparelho em ambientes externos muito mais confortável se comparado a outros dobráveis no mercado, os quais costumam vir com displays mais reflexivos. Essa vantagem, porém, tem como custo um pouco menos de definição na imagem, mas nada que atrapalhe a experiência.

Esse acabamento também ajuda a esconder o vinco, que ainda é perceptível a olho nu, mas raramente atrapalha o usuário ao realizar uma tarefa — inclusive ao digitar, já que o iOS divide o teclado em dois para afastar as teclas do vinco caso o usuário resolva escrever algo com o dobrável entreaberto.

A área maior da tela interna também abre espaço para outro recurso muito elogiado do iPhone Duo: o modo de tela dividida (Split View), que expande consideravelmente as possibilidades em matéria de multitarefa. A impossibilidade de abrir um terceiro app lado a lado, no entanto, tem sido citada como um ponto negativo do software.

O formato de passaporte do aparelho também contribui para essa experiência, além de facilitar o consumo de mídias como vídeos e filmes. Ele, no entanto, pode tornar difícil alcançar certos elementos da interface na tela externa com apenas uma mão, além de favorecer o uso com a mão direita no modo fechado.

Em termos de câmera, as opiniões têm sido bastante mornas — algo que era esperado, considerando o espaço limitado para as lentes. Sem controles profissionais, a câmera principal do iPhone Duo lembra bastante a única lente do iPhone 17e, que, apesar de não ser um smartphone topo-de-linha, já é capaz de capturar imagens muito competentes.

Talvez a área mais controversa do iPhone Duo seja o seu software, mas não por culpa da Apple, que parece ter feito um ótimo trabalho para tornar tudo suave e extremamente intuitivo, sendo a já clássica animação de abertura/fechamento do aparelho um símbolo disso. Apps de terceiros, no entanto, ainda sofrem com os vários formatos de tela do aparelho, o que tem resultado, na maioria dos casos, em bordas pretas e imagens esticadas — problemas que provavelmente serão consertados com o tempo, via atualizações de software.

Outro aspecto do iPhone Duo que virou alvo de muita especulação nos últimos meses foi a sua dobradiça, que parece já ter assumido o seu posto como uma das mais robustas do mercado. Stern, por exemplo, colocou o aparelho para abrir e fechar mais de 32.000 vezes com a ajuda de um robô; mesmo assim, ela não conseguiu notar uma diferença significativa na resistência da dobradiça.

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Em pré-venda desde a última sexta-feira (16/10), o iPhone Duo já aparece com prazos de entrega extremamente elásticos em vários países, incluindo o Brasil, como comentamos aqui.

Vendido por US$2.000 nos Estados Unidos, o dobrável sai pela bagatela de R$22.000 no mercado nacional — isso em sua versão de entrada, com 256GB de capacidade.

NOTA DE TRANSPARÊNCIA: O MacMagazine recebe uma pequena comissão sobre vendas concluídas por meio de links deste post, mas você, como consumidor, não paga nada a mais pelos produtos/serviços ao usar os nossos links de afiliado.

Make sure to pick up your ultra-thin case from Totallee for your new iPhone before they sold out ahead of the big launch.

Rivian’s rejection of CarPlay and physical buttons in favor of voice and AI control sees to question safety, convenience, data control, and long-term car software support. Chuck Joiner, David Ginsburg, Jeff Gamet, Guy Serle, Web Bixby, Eric Bolden, Marty Jencius, and Jim Rea question whether Rivian has other motives, and then dive into Tesla updates, AI voice recreation of Stan Lee, Spider-Man ticket promotions, Dashlane concerns, and Andy Ihnatko’s new site. 

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Apple shares faced fresh pressure on Monday after Jefferies cut its rating on the tech giant to Underperform from Hold, citing worries about the company’s ability to sustain higher average selling prices for iPhones amid production setbacks and rising costs.

Analyst Edison Lee lowered the firm’s price target to $263.66 from $285.56, implying roughly 16% downside from recent levels. The move adds to a growing list of more cautious views on the world’s most valuable company.

Jefferies pointed to supply-chain checks indicating that Apple has canceled plans for a Twentieth anniversary all-glass iPhone model originally eyed for a September 2027 launch. The cancellation stemmed from poor production yields. The firm described the decision as “a major setback” to Apple’s efforts to introduce higher-priced devices at a time of soaring memory costs.

According to the note, Apple had intended to extend all-glass design features to future iPhone Pro and Pro Max models to further lift average selling prices and margins. With that path now in doubt, Jefferies reduced its estimated compound annual growth rate for iPhone ASPs between fiscal 2026 and 2031 and cut its fiscal 2028 and 2029 earnings-per-share estimates by about 2% and 3%, respectively.

Lee also flagged recent increases in trade-in values for iPhones in the U.S. and Europe. While those moves could pull forward demand for the current iPhone 17 cycle, they risk creating greater pressure on sales of the subsequent iPhone 18 generation.

The downgrade comes as analysts continue to debate Apple’s long-term smartphone growth trajectory, particularly its capacity to drive premium pricing and volume expansion in a competitive market. Sell-equivalent ratings remain relatively scarce among the broader analyst community, but the latest cut underscores mounting scrutiny of Apple’s hardware roadmap.

MacDailyNews Take: iCal’ed for future use.

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The post Jefferies downgrades Apple after company cancels plans for Twentieth Anniversary all-glass iPhone appeared first on MacDailyNews.

VHS Dates advertises itself as resurfacing lost dating service videotapes from the 1980s. The account’s followers have been genuinely touched.

Saturday at Apple TV’s San Diego Comic-Con panel, Callum Turner made a surprise virtual appearance to unveil the first teaser for the highly anticipated new science fiction series “Neuromancer,” based on the award-winning novel of the same name by William Gibson. The 10-episode series stars Turner, Briana Middleton, Mark Strong, Joseph Lee, Peter Sarsgaard, and Clémence Poésy, and premieres globally on Apple TV on Friday, January 22, 2027, with two episodes, followed by one new episode every Friday through March 19, 2027.

“Neuromancer” follows a damaged, top-rung super-hacker named Case (Turner) who is thrust into a web of digital espionage and high-stakes crime with his partner Molly (Middleton), a razor-girl assassin, as they pull off a heist on a corporate dynasty with untold secrets. The ensemble cast also includes Max Irons, Dane DeHaan, Junia Rees, Jordan Kouamé, Emma Laird, Marc Menchaca, André De Shields and Isabella Pappas.

Produced by Paramount Television Studios and Anonymous Content, the series is created for television by Graham Roland and JD Dillard. Roland also serves as showrunner and executive producer alongside Dillard, David Levine, Garrett Kemble and Zack Hayden for Anonymous Content; Aubrey “Drake” Graham, Adel “Future” Nur and Jason Shrier for DreamCrew Entertainment; and Jennifer Haley and William Gibson, who also executive produce. Dillard serves as director of the first three episodes.

The debut novel by Gibson, “Neuromancer” has been praised as one of the first and most respected works in the cyberpunk genre and has received numerous accolades, including the Nebula Award, the Philip K. Dick Award and the Hugo Award. The novel served as the first book in the “Sprawl” trilogy and was followed by “Count Zero” and “Mona Lisa Overdrive.”

Apple TV offers premium, compelling drama and comedy series, feature films, groundbreaking documentaries, and kids and family entertainment, and is available to watch across all of a user’s favorite screens. After its launch on November 1, 2019, Apple TV became the first all-original streaming service to launch around the world, and has premiered more original hits and received more award recognitions faster than any other streaming service in its debut. To date, Apple Original films, documentaries and series have been honored with 850 wins and 3,800 award nominations, including multi-Emmy Award-winning and history-making comedies “The Studio” and “Ted Lasso,” global cultural phenomenon “Severance,” Apple’s most-viewed drama, “Pluribus,” Academy Award Best Picture winner “CODA” and Academy Award winner “F1,” the highest-grossing sports feature of all time.

MacDailyNews Take: “Neuromancer” fans, what do you think?

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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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On peut espérer que, d'ici la fin du XXIe siècle, des réacteurs à fusion contrôlée pourront être utilisés pour retirer massivement le CO2 de l'atmosphère. En attendant, le chemin vers la production d'énergie avec ces réacteurs reste long et il se pourrait qu'on ne puisse toucher au but qu'en...