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Hindustan Times
2 hours ago
- Hindustan Times
iPhone 18 may never launch: Apple reportedly planning major shakeup after iPhone 17 5G phone
Apple could be preparing to drop the base iPhone 18 model altogether as part of a major revamp of its iPhone lineup, according to new reports. Industry insiders suggest that following the launch of the iPhone 17 series this year, the company may introduce its first foldable iPhone in 2026, pushing the standard iPhone 18 release to a later date or removing it entirely. Following the launch of the iPhone 17 series this year, the company may introduce its first foldable iPhone in 2026.(REUTERS) What happens after the iPhone 17 launch? Apple's iPhone 17 lineup, expected to launch in September 2025, will include: iPhone 17, iPhone 17 Air (an ultra-thin model replacing the Plus variant), iPhone 17 Pro and iPhone 17 Pro Max. Among these, the iPhone 17 Air is expected to draw attention with its ultra-slim design, reportedly just 5.6mm thick. However, its compact form may come at the cost of battery size and camera performance. In contrast, the iPhone 17 Pro Max will reportedly get thicker, allowing for a bigger battery and improved hardware. 2026: No iPhone 18, but a foldable instead? In a major shift, Apple is likely to skip the base iPhone 18 in the fall 2026 lineup. According to reports from Wayne Ma and Ming-Chi Kuo, Apple plans to introduce a foldable iPhone alongside: iPhone 18 Air, iPhone 18 Pro, iPhone 18 Pro Max and iPhone 18 Fold The foldable iPhone is rumoured to feature a 7.8-inch inner display and a 5.5-inch external screen, along with a crease-free, book-style folding design. This new device could become the most expensive iPhone ever, positioned as a premium flagship model. 2027: Six iPhones and a return of the base model In 2027, Apple is expected to launch as many as six iPhone models, including: Spring: iPhone 18 and iPhone 18e (delayed from the previous year) Fall: iPhone 19 Air, iPhone 19 Pro, iPhone 19 Pro Max, iPhone 19 Fold Some 2027 models, especially the Pro versions, may feature a completely cutout-free display, potentially marking Apple's first true all-screen iPhone, coinciding with the 20th anniversary of the original iPhone.
The Hindu
2 hours ago
- The Hindu
Samsung, Apple and OnePlus led 60% value growth in premium category during Amazon Prime Day 2025
Premium smartphone segment (₹30,000+) witnessed over 60% growth in value during the three-day Prime Day 2025 sale and nearly 70% of this growth came due to demand form Tier 2 and beyond cities. Samsung, Apple and OnePlus led this growth in the premium segment, shared Amazon India. Consumer electronics and PC witnessed strong growth across all categories, with AI laptops, premium tablets, health-focused wearables, and action cameras emerging as customer favourites, while premium audio segments saw strong double-digit growth and increased adoption in Tier 2 cities. The e-commerce platform saw a surge in the premium TV category with a 2X increase in TVs priced upwards of ₹1 lakh. Amazon Fire TV Stick HD was the third most-purchased electronics item. The demand for premium products is on the rise due to increased affordability through options like No Cost EMI, instant bank discounts, exchange offers, and additional coupon discounts. (For top technology news of the day, subscribe to our tech newsletter Today's Cache) 1 out of 4 spends this Prime Day were on EMI. and 9 out of 10 EMI purchases were driven by No Cost EMI for the purchase of smartphones, electronics and large appliances. Amazon witnessed more than 30% growth in No Cost EMI. This 2025 Prime Day happened between July 12-14. Prime Members placed more than 18,000 orders in a single minute which was more than 50% compared to Prime Day 2024. More Prime members shopped with Amazon Pay this Prime Day, of which more than 60% were from Tier 2 and 3 cities and towns. More than 50% customers used 'Amazon Pay Later' during Prime Day'25. Notably, 70% of new Prime sign-ups before the event came from Tier 2 and Tier 3 cities and towns.
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Business Standard
3 hours ago
- Business Standard
Inside Apple's new AI models: How it works, where it gets its training data
Apple unveiled upgraded AI models designed to power Apple Intelligence features across iPhones, iPads, and Macs at WWDC 2025. These include both on-device and cloud-based models. Now, Apple has published a detailed technical report titled "Apple Intelligence Foundation Language Models Tech Report 2025", outlining how these models work and where their training data comes from. Here's a breakdown of the key points: What are Apple's new AI models Apple introduced two foundation models that support Apple Intelligence across apps and services. The first is a compact 3-billion-parameter model designed to run directly on Apple devices powered by Apple Silicon. The second is a more powerful server-based model hosted on Apple's Private Cloud Compute (PCC) infrastructure. Both models are multilingual and multimodal, meaning they understand multiple languages and can process different types of content, including text and images. Apple said that they were trained using large-scale datasets sourced through licensed content, web crawling, and synthetic data generation. How do these new AI models work? On-device model: Starting with the on-device AI model, Apple split this model into two parts to reduce memory usage and make it faster: Block 1: Handles most of the processing. Block 2: Skips some operations to save memory and boost speed. This architecture helps the model respond faster without losing quality, making it more suitable for real-time features like text suggestions or summarisation. Cloud-based model: The cloud-based model uses a more advanced architecture called Parallel-Track Mixture-of-Experts (PT-MoE). Instead of processing every task with the full model, PT-MoE routes each task to the most relevant "experts"—specialised mini-models trained for specific content types. So, for example, if you ask it to plan a vacation, only the travel-related experts get activated. This not only speeds things up but also makes the model more efficient. Apple also created a new kind of Transformer (a type of neural network) that processes multiple parts of a request in parallel, reducing bottlenecks and improving performance. What are the benefits of these new AI models? One of the biggest improvements is expanded multilingual support. Apple increased the portion of training data in non-English languages from 8 per cent to 30 per cent. It also expanded the model's vocabulary from 100,000 to 150,000 tokens. This means Apple Intelligence can now better understand and respond in more languages, with improved fluency and accuracy. Apple said that it has also tested this using prompts written by native speakers, ensuring the models performed well across different cultures and languages. With this, features like Writing Tools should now work more reliably outside of English. Apple has also opened access to its on-device model for third-party developers, allowing them to use AI-powered features like summarisation or rewriting directly within their apps, without sending data off the device. From where did Apple source its data? Apple said that it trained its AI models using a wide range of high-quality data, but it does not use your private information or personal device activity. Instead, Apple said it relied on the following main sources: Licensed content from publishers Publicly available and open-source data Web content collected by Applebot, Apple's own web crawler Apple said that its web crawler respects ' rules that let websites opt out of being used for training. Publishers can also limit which pages are accessible while still being included in Apple services like Siri and Spotlight search. Text data: A big part of Apple's training data came from websites. The company said that Applebot crawled billions of web pages across different topics and languages and used smart tools to load full pages, interact with dynamic content, and extract useful information. To ensure quality, Apple used AI-based filtering instead of rigid rules, which helped retain more relevant content while avoiding low-quality or inappropriate data. Image data: To help its models understand visuals, Apple trained them on image-text pairs. It used licensed images, public images with captions, and AI-generated image descriptions. Apple also included visual materials like infographics, tables, and charts. For example, it used AI to create sample data, generate charts, and then produce related questions for training.
