Apple Introduces Genmoji For iOS, A New AI Powered Way To Interact

Apple is elevating the emoji experience by introducing a groundbreaking “Genmoji” feature, allowing iPhone users to design their own emojis using artificial intelligence.

This innovative feature, revealed in June alongside other Apple Intelligence and AI enhancements, will be accessible starting December 11.

Distinct from other custom emoji apps, Apple’s “Genmoji” leverages generative AI to create unique emojis.

The feature will roll out with iOS 18.2, compatible with the iPhone 15 Pro, iPhone 15 Pro Max, iPhone 16, iPhone 16 Pro, and later models. It will also support iPadOS 18.2 on iPads equipped with an A17 or M1 chip or newer.

How Does ‘Genmoji’ Work?

To create a “Genmoji,” users can navigate to the emoji keyboard and select the “Create new emoji” option.

Apple iOS 18.2

By entering a description of the desired emoji, the system generates a custom design instantly. For instance, typing “a cat that’s an astronaut” will produce an astronaut cat emoji on the spot.

Special Features of ‘Genmoji’

One standout capability of “Genmoji” is its ability to create emojis from photos stored in the user’s photo library. This includes personal photos of oneself, friends, or family members, making it a versatile and personalized tool.

Restrictions on ‘Genmoji’

Apple has implemented safety measures to prevent the generation of emojis containing nudity, gore, or violence.

If a user attempts to create an emoji with prohibited content, a notification will appear stating the emoji cannot be made.

Furthermore, all “Genmojis” are generated and stored locally on the user’s device, eliminating the need for cloud storage or external processing, according to Apple.

John Edward
John Edward
John Edward is a distinguished market trends analyst and author renowned for his insightful analyses of global financial markets. Born and raised in New York City, Edward's early fascination with economics led him to pursue a degree in Finance from the Wharton School at the University of Pennsylvania. His work is characterized by a meticulous approach to data interpretation, coupled with a deep understanding of macroeconomic factors that influence market behavior.
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