Apple Reportedly Replacing Core ML with 'Core AI'
Apple is planning to replace its Core ML framework with a new, modernized "Core AI" framework in iOS 27, according to a report. The move signals a fundamental shift in how developers will integrate AI into apps, likely enabling much more sophisticated on-device intelligence.
Core ML, first introduced by Apple at its 2017 Worldwide Developer Conference, was designed for on-device machine learning. This focus on local processing was a key differentiator, prioritizing user privacy over the cloud-based AI solutions offered by competitors at the time. The framework allows apps to use pre-trained machine learning models for tasks like image recognition and natural language processing directly on iPhones, iPads, and other Apple hardware. Over the years, Core ML has seen significant updates. Core ML 2, released in 2018, focused on optimizing model sizes and performance, and introduced the ability for developers to create custom models. A major leap came with Core ML 3 in 2019, which added support for on-device model training, giving apps the ability to learn from user input without sending data to the cloud. The shift to "Core AI" reflects a broader industry trend toward more powerful and efficient on-device artificial intelligence. Competitors like Google and Samsung have been heavily investing in their own on-device AI capabilities. Google's Gemini Nano is a lightweight, on-device large language model, and Samsung's Galaxy AI, introduced in early 2024, integrates both on-device and cloud-based processing for a range of features. This move is part of Apple's larger, and often secretive, AI strategy, which has included numerous acquisitions. Since 2017, Apple has acquired more AI startups than Microsoft, Meta, or Google, including the $200 million purchase of Xnor.ai for its expertise in on-device processing. In 2023 alone, Apple acquired 32 AI startups. More recently, in January 2026, Apple made its second-largest acquisition ever, purchasing the Israeli AI startup Q.ai for approximately $2 billion. Q.ai specializes in using AI and machine learning to solve audio challenges and has patented technology that can analyze facial micro-movements to detect speech and emotions. This technology could lead to more advanced and privacy-focused communication features in future Apple products. The move toward more capable on-device AI is driven by several key advantages: privacy, low latency, and offline functionality. By processing data directly on the device, sensitive user information remains secure, and AI-powered features can respond instantly without relying on an internet connection. This approach also reduces the costs associated with cloud-based AI processing.
