O iPhone 17e é o atual smartphone de entrada da Apple. Lançado no início do ano, ele traz várias funções interessantes para quem quer um iPhone, mas não pode/deseja investir em modelos mais caros (como o iPhone 17, 17 Pro, etc.).
Entre as suas características, temos uma tela de 6,1 polegadas, uma câmera 2-em-1 Fusion de 48 megapixels, além do processador A19 e o botão de Ação (Action button). Ele também suporta o MagSafe e é plenamente compatível com a Apple Intelligence.
Se levarmos em conta que o preço tabelado desse modelo aqui no Brasil é de R$5.799, estamos diante de um desconto de 25%! Esse valor pode ser parcelado em até 10x no cartão de crédito, se preferir.
Para chegar a esses valores, aplique o cupom AMODESCONTO no carrinho.
Todos os descontos de promoções divulgadas pelo MacMagazine são calculados com base nos preços sugeridos pela Apple ou por outras fabricantes. Pode ser que um determinado produto seja comumente encontrado por valores inferiores em redes varejistas, mas a nossa base de comparação é sempre em cima das tabelas oficiais.
Se você não é louco, é claro que gosta de economizar. E, para isso, o MacMagazine tem diversas opções para ajudar você a conseguir comprar o seu produto Apple pagando menos!
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 mais pelos produtos/serviços usando os nossos links de afiliado.
Em mais um capítulo da batalha travada entre a Apple e o governo do Reino Unido sobre a exigência de um ponto de acesso (ou backdoor) à criptografia do iCloud, a empresa apresentou uma contestação judicial contra a tentativa, por parte do governo britânico, de acessar os dados criptografados de usuários, segundo o Financial Times.
Na ação protocolada junto ao Investigatory Powers Tribunal (IPT), no mês passado, a Apple afirmou que não criou e não pretende criar uma backdoor para os dados dos seus usuários, argumentando que a ferramenta enfraqueceria a segurança do iPhone.
A exigência iniciada com base na Technical Capability Notice (ou Notificação de Capacidade Técnica, uma ordem governamental que prevê a interceptação, por parte do governo do Reino Unido, de dados de usuários mantidos pelas grandes empresas de tecnologia) ordenava que a Apple fornecesse informações dos usuários do iCloud protegidas pela Proteção Avançada de Dados (Advanced Data Protection), obrigando a empresa a redesenhar seu serviço caso optasse por acatar as demandas estatais britânicas.
A abrangência dos usuários impactados também foi motivo de disputa: como a determinação inicialmente impactava integralmente a base instalada do iCloud, o governo dos Estados Unidos optou por pressionar o Reino Unido a desistir de aplicá-la a todos os usuários americanos, o que de fato ocorreu posteriormente. O recuo, porém, não durou muito, e uma segunda ação — muito semelhante à primeira — foi protocolada em outubro de 2025.
In the summer of 15 BC, Emperor Augustus’ two stepsons, Tiberius and Drusus, brought the Central Alps and the Swiss Plateau under Roman control. That campaign concluded decades of efforts to link the Gallic provinces with Illyricum and secure the routes between northern Italy and the Danube. However, while the western and eastern routes of […]
MacBook Neo sales have given Apple something the Mac rarely achieved through its premium models: immediate access to the enormous market for affordable everyday notebooks.
The new line arrived in March 2026 with a launch price of $599, or $499 through education pricing. That placed a current MacBook within reach of buyers who previously depended on discounted older models, inexpensive Windows laptops or Chromebooks.
Price opened the door, but appearance helped people walk through it. MacBook Neo entered the market in blush, indigo, silver and citrus, avoiding the visual compromises commonly associated with entry-level computers. The aluminum enclosure, color-matched keyboard and 13-inch Liquid Retina display made it look like a deliberate new Mac rather than a reduced MacBook Air.
Those choices changed the conversation around an affordable Apple notebook. Buyers could select a computer according to personality and style before considering processor benchmarks. Students could carry something visibly different from institutional gray and black laptops. Families could distinguish multiple computers by color, while first-time Mac owners received a product with its own identity.
Early shipment estimates suggest that strategy worked. IDC data shared with TechCrunch placed MacBook Neo shipments at approximately 1.1 million units during the March quarter, even though the computer had been available for only about three weeks. Apple does not disclose sales by individual Mac model, so the figure remains an independent market estimate rather than an official unit count.
The pace was nevertheless substantial enough to make MacBook Neo one of the strongest recent Mac introductions. It also pushed the story beyond one successful product launch. Apple had entered a price segment responsible for tens of millions of notebook purchases each year and found customers who had never seriously considered macOS.
Image Credit: Apple Inc.
MacBook Neo Sales Started With a Missing Price Tier
Apple spent years concentrating the MacBook line above the mainstream notebook market. MacBook Air became the accessible model, but its price still placed it beyond many students, families and buyers in countries where local income and currency conversion make Apple hardware especially expensive.
Discounted older MacBook Air generations partially filled that gap. Retailers could keep M1, M2 or M3 models available after newer versions arrived, offering buyers lower prices without Apple designing a dedicated entry-level computer.
That approach had limitations. Availability depended on remaining inventory, configurations varied among retailers and the product still looked like a previous generation being cleared from the channel. It could attract value-conscious buyers, but it did not establish a permanent starting point for the Mac.
MacBook Neo created that starting point. Apple designed the model around an A18 Pro chip rather than the M-series processors used by MacBook Air and MacBook Pro. The base configuration included 8GB of unified memory and 256GB of storage, enough for browsing, school assignments, communication, streaming and everyday productivity without competing directly with higher-performance Macs.
The model retained features that buyers encounter every day: an aluminum body, a 13-inch high-resolution display, a Magic Keyboard, a large Multi-Touch trackpad, a 1080p FaceTime HD camera and a fanless design. Apple rated its battery for as long as 16 hours under its testing conditions.
Performance headroom, memory capacity and external-display support remain more limited than on a MacBook Air. Those compromises are easier to accept when the computer is purchased for writing, research, web applications, video calls and media consumption rather than professional video production or complex development work.
IDC estimated that the sub-$700 segment represented about 75 million annual notebook shipments, close to 40% of global notebook volume. Windows and ChromeOS historically controlled more than 95% of that tier. Apple had been competing for a small premium section of the market while a far larger pool of buyers purchased elsewhere.
MacBook Neo sales gave the company a way into that pool without placing an old design or plastic enclosure at the entrance to the Mac line. A buyer comparing computers at similar prices could now choose macOS without first accepting a major premium.
Color Gave the Affordable MacBook an Identity
Low-cost laptops are frequently designed to disappear. Dark plastic, conservative finishes and generic bodies keep manufacturing simple and reduce the risk that one color will remain unsold. MacBook Neo took the opposite approach by making color one of the most recognizable parts of the product.
Silver preserves a familiar Mac appearance, while indigo offers a darker alternative without returning to standard black. Blush gives the line a softer finish, and citrus creates the visual signature that separates Neo from every other MacBook on a table.
The colors do more than decorate an inexpensive computer. They prevent the model from being defined entirely by what it lacks. Instead of asking why it has an A18 Pro rather than an M5, buyers can begin with which finish they want.
That distinction is valuable among younger customers. IDC described reactions from teenagers who focused on the display, weight and appearance rather than memory specifications or processor architecture. Their interest centered on how the computer would look at school compared with the Windows laptops and Chromebooks already around them.
Apple used a similar strategy when color helped turn the original iMac into a cultural object. Later iBook models carried bright finishes into portable computing, while colorful iMac and MacBook designs made personal computers feel less institutional. MacBook Neo revisits that idea for a generation accustomed to selecting colors for phones, headphones, cases and watches.
The approach also avoids making affordability look like punishment. A lower price does not force the buyer into an anonymous product with a visibly cheaper exterior. Neo has limitations, but its design gives owners something exclusive to the line instead of presenting the computer as a substitute for the MacBook they could not afford.
Color alone did not produce MacBook Neo sales. The launch price, battery life, macOS integration and recognizable MacBook construction carried more purchasing weight. Color made those advantages easier to notice and gave stores a product that could attract attention before a salesperson explained its specifications.
First-Time Buyers Changed the Mac Equation
Apple said customer response exceeded its expectations and connected the launch with record participation from people buying their first Mac. That audience may prove more valuable than existing owners choosing a less expensive replacement.
A first Mac purchase can introduce a customer to applications and services that become part of daily work. People who already use an iPhone can access Messages, FaceTime, Photos, iCloud, AirDrop and iPhone Mirroring from the computer without rebuilding their digital routines.
That familiarity lowers one of the barriers to changing computer platforms. A person may have used Windows throughout school or work while carrying an iPhone for years. MacBook Neo makes the switch less financially demanding, while the connected features reduce the amount of relearning required after purchase.
MacBook Neo sales also challenge the assumption that low-cost notebook buyers care only about the lowest available price. Many customers are willing to spend more than the cost of an entry Chromebook when the difference provides a better display, metal construction, longer useful life or closer integration with a phone.
The line is therefore competing on perceived value rather than absolute cheapness. A $599 launch price remains expensive beside the least costly education laptops, but it enters the same purchasing discussion as many mainstream Windows models. It no longer requires a buyer to stretch directly toward MacBook Air pricing.
Education represents a particularly large opportunity. Schools and families make purchases around durability, battery life, software management, support requirements and the number of years a computer can remain useful. A lower acquisition price gives the Mac a better chance of surviving the first stage of that calculation.
Small businesses face similar decisions. A company that previously reserved Macs for designers or executives can consider Neo for administrative work, communication and browser-based services. Wider Mac deployment then becomes possible without assigning a premium notebook to every employee.
MacBook Neo sales may also protect Apple from depending entirely on upgrades. Mature computer owners can keep a capable Mac for many years, extending replacement cycles. Bringing new people onto the platform creates additional demand without waiting for an existing MacBook Air or MacBook Pro to become obsolete.
Worldwide Adoption Is the Larger Story
The geographic distribution of the first units shows both progress and unfinished work. IDC estimated that 44% of March-quarter shipments went to the United States. That concentration is unsurprising for an Apple launch, but the larger opportunity sits in markets where Mac adoption has remained limited by price.
India offers an early example. Approximately 18,000 units reportedly shipped there during the short March launch period, while retailers later experienced difficulty obtaining enough inventory. The local starting price of ₹69,900 remained above the direct currency conversion of the U.S. price, yet it sat far below the ₹119,900 entry point reported for MacBook Air at the time.
Older MacBook Air generations had previously generated Indian sales when retailers offered substantial discounts. Neo gives Apple and its partners a current model to promote throughout the year rather than depending on irregular clearance inventory.
Availability timing will influence adoption elsewhere. The computer reached some markets later than the initial launch, including Indonesia in May. Local taxes, currency movements, distribution capacity and supply allocation can produce a very different value proposition from one country to another.
Independent forecasts remain optimistic despite severe pressure across the PC industry. TrendForce projected Apple notebook shipments could grow 7.7% during 2026 and estimated that MacBook Neo could reach between 4 million and 5 million units. IDC later said stronger-than-expected demand from the model contributed to an upward revision of its notebook forecast.
Those gains are occurring while memory shortages and rising component costs are pushing much of the computer industry toward higher prices. IDC expects worldwide PC shipments to contract during 2026, making Apple expansion unusual in a market where many manufacturers are reducing configurations and protecting margins.
Supply control helped Apple enter the lower tier at a difficult moment. The company already designs the A18 Pro, uses a highly standardized configuration and purchases components at enormous scale. That structure gave it more room to assemble a focused notebook without relying on a separate processor vendor for the central chip.
Recent Mac price increases caused by rising memory costs may test how much of the early advantage Apple can preserve. Neo depends on remaining close enough to mainstream notebooks that first-time buyers continue placing it on the same shortlist. A widening price gap would return the Mac to the premium territory the new line was created to escape.
The next evidence will arrive through education purchasing cycles and expansion in price-sensitive countries. A personal citrus or blush MacBook can win attention in a store, but deployments across schools and small businesses will depend on supply, local pricing, management costs and useful life. The first semester filled classrooms with individual Neo buyers; the coming academic year will reveal whether entire institutions are ready to replace rows of gray laptops with macOS.
Falls among older adults often begin with changes too subtle to be noticed during an ordinary walk. A person may still appear steady while moving through a familiar environment, yet struggle when asked to divide attention between walking and another task. A new study by researchers Dong, Hu, Guo and colleagues examines whether machine-learning techniques can identify this hidden vulnerability in community-dwelling older adults by analyzing how gait changes during dual-task walking. Published in BMC Geriatrics in 2026, the research focuses on a potentially powerful combination of digital movement measurement and artificial intelligence: spatiotemporal gait parameters recorded while people walk and perform a second mental or motor activity.
Walking is not a single, automatic action. It requires continuous coordination between the brain, muscles, sensory systems and balance mechanisms. When a person walks while counting backward, answering questions or carrying an object, the nervous system must distribute attention between locomotion and the competing task. This is known as dual-task walking. Older adults who have limited cognitive or physical reserve may respond by slowing down, shortening their steps, widening their base of support or becoming more irregular in their timing. These adaptations can provide clues about fall susceptibility that may remain invisible during conventional clinical walking tests.
The study’s central idea is that gait should be evaluated under realistic cognitive pressure rather than only in ideal, distraction-free conditions. Spatiotemporal gait parameters describe measurable features of movement across time and space, including walking speed, stride length, step time, cadence, stance duration and the variability between consecutive steps. In a dual-task setting, researchers can also examine the degree to which these variables change compared with normal walking. This difference, often called dual-task cost, can reveal how much a person’s mobility is affected when attention is divided. A larger cost may indicate reduced ability to manage competing demands while remaining stable.
Machine learning offers a way to analyze these patterns simultaneously. Traditional clinical assessment may focus on one or two measurements, such as walking speed or the number of previous falls. A machine-learning model can process many variables at once and search for combinations associated with elevated risk. Depending on the model design, the system may learn from labeled examples, in which participants’ gait data are linked to fall-related outcomes, and then estimate risk for new individuals. Algorithms can detect nonlinear relationships that are difficult to capture with conventional statistical methods, although their usefulness depends heavily on the quality, size and representativeness of the data used for training.
The community setting is especially important. Many studies of balance and falls are conducted in hospitals or specialist laboratories, where participants may be healthier, more closely supervised or less representative of the broader older population. Community-dwelling adults live independently and encounter the complex conditions that make falls more likely: distractions, uneven surfaces, hurried movement, household obstacles and the need to perform several tasks at once. By focusing on this group, the research addresses a practical question for preventive medicine: can accessible gait testing identify people who appear independent but may require additional support before a serious fall occurs?
A potential advantage of this approach is its ability to move fall-risk assessment toward objective, repeatable measurement. Gait sensors, pressure-sensitive walkways, wearable devices or camera-based systems can convert movement into numerical data. Those data may be more sensitive than a brief visual observation, particularly when they capture step-to-step variability and changes induced by a secondary task. In the future, similar measurements could potentially be collected in clinics, rehabilitation centers or even at home. However, a prediction tool would need to be tested across different ages, health conditions, walking environments and technology platforms before it could be trusted for widespread use.
The research also highlights the technical challenges behind apparently simple predictions. Falls are influenced by numerous factors, including muscle strength, vision, medication use, reaction time, fear of falling, neurological disease and environmental hazards. Gait features alone cannot explain every incident. A machine-learning model may also perform impressively on the data used to develop it but less reliably on people from another population, a problem known as limited generalizability or overfitting. For clinical adoption, researchers must therefore evaluate calibration, sensitivity and specificity, test the model on independent datasets and make its decisions understandable to health professionals and patients.
Although the citation identifies the study’s objective and methodology, it does not provide detailed numerical findings such as sample size, predictive accuracy or the specific algorithm used. Those results will determine how close this technology is to practical deployment. Even so, the study reflects a broader shift in geriatric care: fall prevention is increasingly being treated as a problem of measurable, dynamic performance rather than a simple checklist of past incidents. By combining dual-task gait analysis with machine learning, the researchers are investigating whether the body’s response to distraction can serve as an early warning signal—one that could eventually help clinicians intervene before a dangerous fall changes an older person’s independence.
Subject of Research: Fall-risk prediction in community-dwelling older adults using machine learning and dual-task spatiotemporal gait parameters.
Article Title: Machine learning-based fall risk prediction in community-dwelling older adults using dual-task spatiotemporal gait parameters.
Article References: Dong, G., Hu, H., Guo, Y. et al. “Machine learning-based fall risk prediction in community-dwelling older adults using dual-task spatiotemporal gait parameters.” BMC Geriatrics (2026). https://doi.org/10.1186/s12877-026-07998-3
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