macOS Sequoia 15.3 embraces Genmoji functionality.
The recent developer beta version of macOS Sequoia unveils support for Genmoji, having previously launched on iPhone and iPad platforms. Here’s a breakdown of the essentials.
On Monday, Apple unveiled the initial developer beta of macOS Sequoia 15.3. Although there are minimal visual adjustments in this software update, it introduces an exciting feature — support for Genmoji. This innovation made its first appearance with iOS 18.2 and allows users to craft personalized emoji through Apple’s advanced intelligence system.
With Genmoji, individuals can articulate their desired emoji designs—whether derived from a known object or a person—and Apple Intelligence transforms those descriptions into unique creations. Users have the option to utilize source images from their Photos library or select basic emoji figures as starting points. Furthermore, these custom emojis sync seamlessly via iCloud, making them accessible across all compatible devices like iPhones and iPads within the user’s sticker archive.
On Mac systems, creating and accessing Genmoji is straightforward via the emoji picker integrated into macOS Sequoia 15.3. The possibilities are numerous—Genmojis can take inspiration from both real-world items and fantastical concepts—all hinging on user imagination.
Alongside this latest update for macOS Sequoia 15.3 beta, Apple also rolled out developer betas of iOS 18.3, iPadOS 18.3, along with visionOS 2.3 on the same day; these updates bring no significant interface changes but do provide various enhancements in performance stability overall as part of their upgrades—the release notes specifically confirm minor adjustments related to both Genmoji features and Writing Tools.
Looking ahead to future developments in Apple’s technology landscape, additional AI-driven capabilities are anticipated for introduction in early 2025—with upcoming plans indicating that the forthcoming iOS version (i.e., update number not yet determined) could significantly evolve Siri’s functionalities utilizing large language models (LLMs).
