Apple has filed for a patent (US 20240273335 A1) for a customizable chip for artificial intelligence (AI) applications. It involves processors for running Macs, iPads, and iPhones using the upcoming Apple Intelligence features.
The company is planning to begin rolling out Apple Intelligence to customers as part of software updates coming by October, according to Bloomberg’s Mark Gurman. That means the AI features will arrive a few weeks after the initial iOS 18 and iPadOS 18 releases planned for September. In fact, users will have to wait until 2025 to see the fully revamped Siri with Apple Intelligence features.
Apple Intelligence will be deeply integrated into the upcoming updates of macOS, iOS, and iPadOS. It harnesses the power of Apple silicon to understand and create language and images, take action across apps, and draw from personal context to simplify and accelerate everyday tasks. Here are all the features of Apple Intelligence as listed by Apple in a press release.
About the patent filing
The patent filing relates to a neural network implemented as a customized integrated circuit. A neural network is a system of interconnected artificial “neurons” that exchange messages between each other.
In the patent filing Apple notes that object detection and identification/classification are important aspects of many systems. These functions are based on the processing and interpretation of images and are used in many applications and settings involving image, object, and pattern recognition, typically as part of a decision process. Example applications include security, access control, identification/authentication, machine vision, artificial intelligence, engineering, manufacturing, robotics, systems control, autonomous vehicles, and other situations involving some form of object or pattern recognition, object detection, or automated decision-making based on an image.
Summary of the patent filing
Here’s Apple’s (very technical) abstract of the patent filing: “In one embodiment, a computing device includes an input sensor providing an input data; a programmable logic device (PLD) implementing a convolutional neural network (CNN), wherein: each compute block of the PLD corresponds to one of a multiple of convolutional layers of the CNN, each compute block of the PLD is placed in proximity to at least two memory blocks, a first one of the memory blocks serves as a buffer for the corresponding layer of the CNN, and a second one of the memory blocks stores model-specific parameters for the corresponding layer of the CNN.”
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