How Apple is already using machine learning and artificial intelligence in iOS

Apple#039;s Siri

Apple may not be as aggressive as other companies in introducing AI features, and it doesn't have there's so much drama around what he does. However, the company already has a lot of features scattered across iOS and macOS. That's where.

Apple doesn't go out of its way to mention “artificial intelligence” or AI in a meaningful way, but the company isn't shying away from the technology. Machine learning has become Apple's go-to tool for its artificial intelligence initiatives.

Apple uses artificial intelligence and machine learning in iOS and macOS in several notable ways.

What is machine learning?

Several years have passed since how Apple began using machine learning in iOS and other platforms. The first real use case was Apple's software keyboard on the iPhone.

Apple used predictive machine learning to understand which letter the user was pressing, improving accuracy. The algorithm also sought to predict what word the user would type next.

Machine learning, or ML, is a system that can learn and adapt without explicit instructions. It is often used to identify patterns in data and produce specific results.

This technology has become a popular field of artificial intelligence. Apple has also been implementing these features for several years now.

Places where machine learning is used

In 2023, Apple will be using machine learning in almost every corner of iOS. It's present in how users search for photos, interact with Siri, see event suggestions, and much, much more.

On-device machine learning systems benefit the end user in terms of data security and privacy. This allows Apple to store important information on the device rather than relying on the cloud.

To speed up machine learning and all other key automated processes in iPhone, Apple created the Neural Engine. It was launched with the iPhone A11 Bionic chip, which helps with some camera functions as well as Face ID.


From a technical point of view, Siri is not artificial intelligence, but it relies on artificial intelligence systems to operate. Siri uses a deep device neural network (DNN) and machine learning to analyze requests and provide responses.

Siri says hi

Siri can handle a variety of voice and text requests, from simple questions to control of built-in applications. Users can ask Siri to play music, set a timer, check the weather, and more.

TrueDepth camera and Face ID

Apple introduced the camera TrueDepth and Face ID ID with the launch of iPhone X. The hardware system can project 30,000 infrared dots to create a depth map of the user's face. Spot projection is also combined with 2D infrared scanning.

This information is stored on the device, and the iPhone uses machine learning and DNN to analyze every scan of a user's face when they unlock their device.


This extends beyond iOS, as the stock Photos app is also available on macOS and iPadOS. This app uses multiple machine learning algorithms to help with key built-in features, including photo and video curation.

Apple Photos uses machine learning

Face recognition in images is possible thanks to machine learning. The People album allows you to search for identified people and edit images.

The on-device knowledge graph, powered by machine learning, can learn a person's frequently visited places, related people, events, and more. It can use the collected data to automatically create curated collections of photos and videos called “Memories.”

Camera app

Apple regularly works to improve the camera experience for iPhone users. This goal is achieved in part through software and machine learning.

Apple Deep Fusion optimizes detail and low noise in photos

Neural Engine enhances the camera experience with features like Deep Fusion. It was launched with the iPhone 11 and is present in the new iPhones.

Deep Fusion is a type of neural image processing. When taking photos, the camera takes a total of nine frames. Immediately before pressing the shutter button, two bursts of four frames are taken, followed by one shot at a longer shutter speed when the button is pressed.

A machine learning process powered by the Neural Engine will run and find the best possible shots. The result leans more towards sharpness and color accuracy.

Portrait mode also uses machine learning. While high-end iPhone models rely on hardware elements to help separate the user from the background, the 2020 iPhone SE relied solely on machine learning to get the portrait blur effect right.


Machine learning algorithms also help clients automate their common tasks. ML allows you to receive smart suggestions regarding potential events that may interest the user.

For example, if someone sends an iMessage containing a date or even just a suggestion to do something, iOS can do it. suggest an event to add to the Calendar app. All it takes is a few taps to add an event to the app so it's easy to remember.

iOS 17 will come with new features based on machine learning:

Standard keyboard and iOS 17

One of Apple's first uses of machine learning was the keyboard and auto-correct, and they got better in iOS 17. In 2023, Apple announced that the standard keyboard will now use a “transformer language model,” which will significantly improve word prediction.

The Transformer language model is a machine learning system that improves prediction accuracy as the user types. The software keyboard also remembers frequently typed words, including obscene words.

New Journal app and iOS 17

Apple introduced an all-new Journal app when it announced iOS 17 at WWDC 2023. This new app will allow users to reflect on past events and journal for as long as they want within its own app.

Standard Apple Journal app

Apple uses machine learning to inspire users when adding posts. These suggestions can be obtained from a variety of resources, including the Photos app, recent activities, recent workouts, people, places, and more. etc.

This feature is expected to appear with the release of iOS 17.1.

Apple will also improve dictation and language translation using machine learning.

Notable mentions beyond iOS

Machine learning — it's also present in watchOS, with features that help track sleep, hand washing, heart health, and more.

As mentioned above, Apple has been using machine learning for many years. This means that the company has technically been using artificial intelligence for many years.

People who think Apple is behind Google and Microsoft only consider ChatGPT and other similar systems. At the forefront of public opinion regarding AI in 2023 will be Microsoft's Bing and Google's Bard.

Apple will continue to rely on machine learning for the foreseeable future. In the future, the company will find new ways to implement the system and expand user functions.

Rumor has it that Apple is developing its own GPT-like chat that could greatly improve Siri at some point in the future. In February 2023, Apple held a summit entirely dedicated to artificial intelligence, a clear sign that the company is sticking with the technology.

Apple car rendering

Apple can rely on systems it's introducing with iOS 17, such as the Transformer language model for AutoCorrect, extending functionality beyond the keyboard. Siri is just one way in which Apple's ongoing work in machine learning could provide value to users.

Apple's work in artificial intelligence will likely lead to the creation of the Apple Car. Regardless of whether the company actually produces a car, an autonomous system designed for cars will need a brain.

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