# 31 : Apple Uses M4 to Showcase Commitment to Embracing AI

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Weekly Comment

On May 7, Apple finally updated the iPad series after a year and a half, with the highlight being the new iPad Pro equipped with the latest M4 chip. According to leaked benchmark data online, the M4 significantly outperforms the M2 and even M3 chips.

Apple claims that the M4 chip has significantly improved machine learning performance, especially enhancing the performance of the Neural Processing Unit (NPU). The full display of its AI capabilities may still need to be paired with the new system and APIs released at WWDC 2024. By debuting the latest M-series chip on the iPad Pro, Apple breaks tradition and fully demonstrates its determination to outpace other manufacturers in the AI era.

With the introduction of the M4 chip, I am full of anticipation for Apple’s potential Mac product line this year. All signs point to Apple unveiling several AI-related updates, new features, and services at WWDC 2024. As a developer in the Apple ecosystem, I not only look forward to experiencing the convenience brought by AI during development but also hope Apple will introduce more secure and user-friendly APIs to help developers provide excellent AI services in their apps.

Given Apple’s consistent emphasis on privacy, it is expected that most AI functionalities will run locally on devices. This not only poses higher demands on the device’s AI capabilities but also presents a significant challenge in terms of energy consumption. After all, users do not want to see a significant reduction in battery life after updating to a new system. I am eager to see how Apple balances AI performance, energy consumption, privacy, development convenience, and user experience.

Although generative AI is currently experiencing a surge in popularity, and there are continuous reports of Apple’s collaborations with top generative AI service providers, I firmly believe that everyday AI functions should primarily operate on local devices, using smaller models to serve users in an almost imperceptible manner. In the age of AI, energy-efficient hardware is crucial.

The iPad Pro equipped with the M4 chip will be more focused on scenarios that highlight its “Pro” level positioning. For most users, the new iPad Air, powered by the M2 chip and offering decent AI capabilities with a higher cost-effectiveness, may be a more suitable choice.

Whether or not you are focused on AI, it is undeniable that AI will spark a new wave of device upgrades and application experience innovations (at least at the marketing level). As developers, we must be prepared for this, even if we may not immediately offer or apply AI services, we should have a grasp of the basic operations and application scenarios of AI development.


Mastering the containerRelativeFrame Modifier in SwiftUI


The containerRelativeFrame modifier starts from the view it is applied to and searches up the view hierarchy for the nearest container that fits within the list of containers. Based on the transformation rules set by the developer, it calculates the size provided by that container and uses this as the proposed size for the view. In a sense, it can be seen as a special version of the frame modifier that allows for custom transformation rules. This modifier simplifies some layout operations that were previously difficult to achieve through conventional methods.

This article will delve into the containerRelativeFrame modifier, covering its definition, layout rules, use cases, and relevant considerations. At the end of the article, we will also create a backward-compatible replica of containerRelativeFrame for older versions of SwiftUI, further enhancing our understanding of its functionalities.

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