Innovation is not a strange word when it comes to Apple’s product development team. Be it in design, compute hardware, or software, with every launch of their iPhones, Apple makes a mark on the smartphone industry. While many would disagree, over the years, Apple has led the way in smartphone innovation. While sometimes they may be late to the party, their implementation of hardware and software in iPhones never fails to match or exceed the existing industry standards. Take the example of AI.
History recalls Apple as being at the forefront of integrating artificial intelligence (AI) into its devices. From launching Siri with the iPhone 4S to Apple Intelligence, Apple has left an indelible mark on the smartphone market. On the eve of the launch of Apple’s first smartphones powered by their latest and greatest AI innovation, Apple Intelligence, I took a trip down memory lane to have a look at Apple’s tryst with AI on iPhones.
Apple had the vision of creating on-device AI since the 1980s, with the then CEO of the company, John Sculley, commissioning an advertisement set in September 2011, showcasing what the future of AI on Apple devices would look like. It was called “Knowledge Navigator”. It was like a window into the future, as in September 2011, Apple announced its first wave of what would become some of the most cutting-edge AI applications on smartphones.
What has come to be a staple in the workflow of most iPhone users today, Siri, was Apple’s first dig at integrating an artificial intelligence-enabled feature into its iPhones.Released over a decade ago, in 2011, Apple’s Siri was first seen on the iPhone 4S. At the time, the voice assistant’s capabilities were nothing compared to what we know it to be today, but for the time, it was definitely a great technological leap for the Cupertino-based tech giant Apple.
Siri’s life began as a startup based in San Jose, California, right outside Apple’s backyard in Cupertino. Apple acquired Siri and shipped it with the iPhone 4S. Later, in 2012, Apple expanded Siri’s presence as it made its way into the third-generation iPad with iOS 6 before making it a staple in all the upcoming iPhones.
When it was launched for the first time, Siri faced its own share of struggles. Google had started the Voice Assistant hype train, and Apple was latching on, and the expectations were sky-high. One of the biggest hurdles for Siri to work around was that of the human language. To get an accurate response, the users needed to word their commands with clinical precision, and the voice assistant also struggled to recognise different accents that came in with the iPhone’s wide user base.
However, after refinement, Siri has come to be one of the best performers across the board, and super-charged with Apple Intelligence, it has the capabilities to execute tasks that would have been deemed impossible by many at the time of Siri’s launch. It functions mostly on iPhones, and as we move along the way, you will see how Apple has evolved Siri.
Once Siri had made its way on to iPhones, Apple added additional functionality to their already popular voice assistant, the highlight of which was the proactive suggestions feature. In this feature, Siri would proactively look for actionable suggestions based on user behaviour and present them as notifications on the screens.
This has been refined over the years and can still be seen in today’s iPhones. If you are an iPhone user, you will see the notification bubbles come up on your screens from time to time. These can be annoying from time to time, but for routine management of device behaviour, a case can definitely be made for them being extremely useful.
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A year after adding Proactive Suggestions via Siri to iPhones, Apple announced improvements to the Photos app for iPhones which came in with a slew of new features, including a Photo Analysis feature. With the addition of this, Photos was now capable of automatically identifying faces and scenes.
In sync with iCloud Photos, the categorisation and synchronisation of photos across devices in the Apple Ecosystem was easier than ever. You can click a picture on your iPhone, and it will be categorised and stored on iCloud, enabling you to access it at any given moment by looking up the relevant tag. You could also create personalised libraries of pictures, categorised using Apple’s Photos app and share them with whoever you wanted to.
After harbouring the AI ship in its backyard, Tim Cook led Apple geared up to increase the ability of their iPhones by adding even more AI-related hardware and software features into their iPhones. Apple iPhone X pioneered AI on iPhones with the introduction of the Neural Engine in its A11 Bionic chip. Subsequently, with every launch and announcement, Apple’s AI prowess grew stronger.
Arguably, one of the biggest leaps by Apple towards integrating AI and ML-enabled software and services on their iPhones came with the launch of the iPhone X. Apple announced that their latest iPhone, which in itself brought in one of the most defining designs in the industry, the notched display, would be powered by the A11 Bionic Chip with Neural Engine.
Neural Engine was Apple’s label given to their NPU, which was in their iPhones. It unlocked the doors for iPhones to house more powerful localised applications powered by AI and ML algorithms. As Apple mentioned in their marketing material for the iPhone X – A11, the Bionic neural engine is designed for specific machine learning algorithms and enables Face ID, Animoji and other features.
The A11 Bionic chip ushered in a new era of iPhones where they grew increasingly powerful every year and their AI and ML algorithms enabled Apple to run a host of applications natively on iPhones, including their groundbreaking FaceID. Siri also got a boost, with increased processing capabilities offered by the A11 Bionic Chip on iPhones.
When looking back, there were many opinions floating on the internet around this launch, and many came true, including predictions of brands like Samsung and Google following suit and pushing their chip manufacturers to include dedicated NPUs on the chips processing their phones. Cut to 2024; we have almost every hardware manufacturer floating their big claims of running AI locally on their phones. But remember, the journey of bringing NPUs to the mainstream began with iPhones and their Neural Engine.
Introduced in 2017 with the iPhone X, Face ID was a groundbreaking feature that marked Apple’s shift toward facial recognition technology as a primary method of unlocking the iPhone. Unlike traditional fingerprint-based authentication, Face ID uses the TrueDepth camera system to create a detailed 3D map of a user’s face, ensuring that even subtle changes—like growing a beard or wearing glasses—don’t affect its accuracy. The technology employs over 30,000 invisible dots to create this facial map, enabling secure device unlocking, authentication for purchases, and even enabling features like Animoji.
Apple made privacy a central pillar of Face ID. According to Apple’s privacy policy, the facial data used by Face ID is stored securely on the device, encrypted, and never shared with third parties. As Face ID matured, its efficiency and accuracy improved, further reinforcing its position as one of the most secure and convenient biometric authentication methods in modern smartphones, pushing iPhones to the top step when it comes to facial authentication.
Launched alongside the iPhone X, Animoji was a fun, playful feature that demonstrated the potential of the TrueDepth camera system used by Face ID. Animoji uses advanced facial mapping to transform your facial movements into animated emoji characters, creating a more personalised and interactive way to send messages. It tracks over 50 different facial muscle movements in real-time, enabling characters like a unicorn or robot to mirror your expressions and even lip-sync your voice.
While some dismissed Animoji as a novelty, it showcased Apple’s commitment to integrating sophisticated hardware and AI to elevate user experiences. In a light-hearted way, Animoji also demonstrated the strength of Apple’s facial recognition technology, showing just how accurately the iPhone X could interpret facial expressions.
In 2018, Apple introduced Smart HDR with the iPhone XS and XS Max, elevating the camera experience for iPhone users by leveraging AI and machine learning to deliver better images. Unlike traditional HDR, Smart HDR uses the power of Apple’s A12 Bionic chip to analyse multiple photos taken at different exposures and combine the best elements from each into a single, high-quality image. The AI-driven approach allows Smart HDR to capture fine details in both bright and shadowy areas, creating balanced, vibrant images even in challenging lighting conditions.
With Smart HDR, users don’t need to worry about manually adjusting settings; the AI handles everything in the background. The feature excels in portrait photography, allowing for a more natural representation of skin tones and textures, and even adjusts the background blur to give a professional touch to images.
Having already consolidated their stronghold in smartphone AI, Apple moved on and, with the increased discussions around data privacy in AI applications, strengthened its grip over making iPhones that were, arguably, ahead of their time.
Apple’s advancements in computational photography came into the spotlight with the iPhone 12 series. With the introduction of Night Mode and Deep Fusion, Apple harnessed AI to improve low-light photography and image detail significantly. Night Mode automatically activates in darker environments, capturing multiple frames and combining them into a bright, clear photo without the need for a flash. Deep Fusion, on the other hand, works behind the scenes to analyse pixel-by-pixel data to enhance texture and detail and minimise noise. These features demonstrated how AI has transformed the iPhone into a powerful photography tool, enabling users to take stunning shots effortlessly, regardless of the lighting or conditions.
In 2020, Apple made significant strides in improving Natural Language Processing (NLP) across its devices, enhancing features such as dictation, translation, and voice commands. With on-device processing and improved machine learning algorithms, iPhones can now understand and process human language more naturally and contextually. Whether dictating a message, setting reminders, or using real-time translation, Apple’s NLP capabilities aim to make the interaction more seamless and accurate for users . This advancement in NLP is particularly evident in Apple’s Translate app, which was introduced in 2020, allowing for instant translations between multiple languages without requiring an internet connection.
With growing concerns around data privacy, Apple reinforced its commitment to safeguarding user information by processing more data locally on the device. In 2020, Apple doubled down on privacy-focused AI, ensuring that features like Siri, Face ID, and machine learning models for apps run on-device, reducing the need to share data with external servers. This approach not only improves response times but also ensures that sensitive data like facial recognition maps and message content remain encrypted and secure. Apple’s privacy-centric design in AI has earned it widespread praise, especially as the tech world grapples with issues related to data breaches and unauthorised surveillance.
From 2021 onward, Apple continued to refine and enhance its AI-powered features. Real-time text translation became more accurate and integrated into core apps, while automatic scene detection enabled iPhones to intelligently adjust camera settings to suit various environments. AI-powered personalisation also improved, offering users more tailored app recommendations, news updates, and even music suggestions, all processed securely on the device.
These advancements reflect Apple’s continued drive to innovate using AI while maintaining a strict focus on user privacy and security. The most recent addition to Apple’s iPhone-centered AI applications is Apple Intelligence. Apple Intelligence is a suite of AI-driven features and services that enhance the iPhone experience by seamlessly integrating artificial intelligence into daily tasks. With Apple Intelligence, iPhones can learn from user behaviour, providing personalised experiences like smart photo curation, predictive text suggestions, and enhanced app recommendations. One of the key pillars of Apple Intelligence is its ability to process data locally on the device, ensuring user privacy while delivering powerful performance.
Whether it’s detecting objects in a photo or suggesting relevant shortcuts, Apple Intelligence leverages machine learning to make interactions more intuitive. For instance, users can search for images using keywords like “beach” or “dog,” and Apple Intelligence will automatically surface relevant photos based on content analysis. Additionally, the system powers real-time Siri suggestions and proactive features, all designed to anticipate user needs without compromising personal data.
With the iPhone 16 series set to hit the shelves soon, Apple Intelligence continues to evolve and it will be interesting to see what the future holds. Will Apple set a new industry standard or implement already existing features in a way that hasn’t been seen before? Only time will tell.
