Apple unveiled iOS 18 at the Worldwide Developers Conference (WWDC) in June 2024. Showcasing a focus on integrating artificial intelligence (AI) into the iPhone experience. Early indications suggest this emphasis on AI might translate to a tangible performance improvement in machine learning tasks.
Apple iOS 18 Benchmarks Hint at Significant Machine Learning Performance Boost
One developer, @lafaiel on the social media platform X, ran benchmarks on the Core ML engine. A key component of iOS responsible for on-device machine learning computations. The tests were conducted on an iPhone 15 Pro Max running iOS 17.5.1 and then again after updating to the iOS 18 beta.
The results were promising. The iPhone 15 Pro Max achieved a score of 6,249 in the Geekbench ML Score test on iOS 17.5.1. After updating to iOS 18, the score jumped to 7,816, representing an impressive 25% increase.
While benchmark scores are valuable indicators, it’s important to acknowledge that they don’t always directly translate to real-world user experiences. The specific tasks and applications that leverage machine learning can vary significantly. And the impact of a performance boost might not be uniform across all use cases.
Geekbench Scores Reveal iOS 18’s Stunning ML Performance Boost
However, the benchmark results from @lafaiel provide compelling evidence that iOS 18 optimizes the iPhone’s hardware and software for machine learning tasks. This optimization can translate into several potential benefits for users:
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- Enhanced AI Features. A more powerful Core ML engine paves the way for richer and more robust AI features within iOS 18. This could encompass advancements in areas like image and speech recognition, natural language processing for improved voice assistants and dictation, and personalized user experiences tailored to individual preferences.
- Improved App Performance: Many third-party applications increasingly leverage on-device machine learning for various functionalities. A more efficient Core ML engine could lead to faster performance and smoother user experiences within these apps.
- Battery Efficiency: Optimizing machine learning tasks can also contribute to improved battery life. By streamlining the way the iPhone processes these tasks, iOS 18 could potentially reduce overall power consumption.
Apple‘s commitment to on-device machine learning aligns with the growing industry trend of prioritizing user privacy. By processing data locally on the device rather than relying on cloud-based solutions, iOS 18 potentially offers a more secure and privacy-conscious approach to AI functionalities.
It’s important to note that the benchmarks were conducted on the latest iPhone 15 Pro Max. While the performance gains are likely to be present to some degree on older iPhone models once they receive the stable iOS 18 update in September alongside the iPhone 16 launch, the magnitude of the improvement might vary depending on the specific hardware capabilities of each device.
Overall, the early benchmarks for iOS 18 offer promising insights into Apple’s focus on machine learning within the mobile operating system. While real-world user experiences will ultimately determine the true impact of these improvements, the potential for faster, more efficient, and privacy-focused AI features on iPhones is certainly exciting. With the official release of iOS 18 approaching, it will be interesting to see how developers and users leverage these advancements to create innovative and enriching experiences on Apple’s mobile platform.
