In December Patently Apple posted a report titled “Apple Supplier TSMC ahead of Schedule on Chips for AI, Machine Learning and more.” According to TSMC 7nm opens the door for dedicated AI, 5G chips and more. Yesterday we were first to report that TSMC’s 7nm capabilities would be ready for the second half of 2018. That could signal that Apple’s next generation iPhone will sport this processor. With Apple introducing one of the first AI chips in this year’s iPhone X via their Neural Engine, Apple’s next generation processors are bound to advance their AI capabilities even further ahead of the competition. Apple’s Neural Engine currently processess tasks linked to FaceID facial recognition, understanding voice commands for Siri, image-processing and powering Animoji.
This week Gartner published a report about ten uses for AI-Powered smartphones. The report noted that Artificial Intelligence (AI) features will become a critical product differentiator for smartphone vendors that will help them to acquire new customers while retaining current users.
As the smartphone market shifts from selling technology products to delivering compelling and personalized experiences, AI solutions running on the smartphone will become an essential part of vendor roadmaps over the next two years.
Gartner predicts that by 2022, 80% of smartphones shipped will have on-device AI capabilities, up from 10 percent in 2017. On-device AI is currently limited to premium devices and provides better data protection and power management than full cloud-based AI, since data is processed and stored locally.
CK Lu, research director at Gartner stated in the report that “Future AI capabilities will allow smartphones to learn, plan and solve problems for users. This isn’t just about making the smartphone smarter, but augmenting people by reducing their cognitive load. However, AI capabilities on smartphones are still in very early stages.”
While Apple will be continually using AI in custom ways that support new iPhone features and apps to differentiate their smartphone, there will be some general themes coming to AI-powered smartphones by 2022.
Roberta Cozza, research director at Gartner begins this segment by noting that “Over the next two years, most use cases will still exploit a single AI capability and technology. Going forward, smartphones will combine two or more AI capabilities and technologies to provide more advanced user experiences.” Gartner has identified 10 high-impact uses for AI-powered smartphones to enable vendors to provide more value to their customers.
10 Uses for AI-Powered Smartphones
1) “Digital Me” Sitting on the Device
Smartphones will be an extension of the user, capable of recognizing them and predicting their next move. They will understand who you are, what you want, when you want it, how you want it done and execute tasks upon your authority.
Angie Wang, principle research analyst at Gartner added that “Your smartphone will track you throughout the day to learn, plan and solve problems for you. It will leverage its sensors, cameras and data to accomplish these tasks automatically. For example, in the connected home, it could order a vacuum bot to clean when the house is empty, or turn a rice cooker on 20 minutes before you arrive.”
2) User Authentication
Password-based, simple authentication is becoming too complex and less effective, resulting in weak security, poor user experience, and a high cost of ownership. Security technology combined with machine learning, biometrics and user behavior will improve usability and self-service capabilities. For example, smartphones can capture and learn a user’s behavior, such as patterns when they walk, swipe, apply pressure to the phone, scroll and type, without the need for passwords or active authentications.
3) Emotion Recognition
Emotion sensing systems and affective computing allow smartphones to detect, analyze, process and respond to people’s emotional states and moods. The proliferation of virtual personal assistants and other AI-based technology for conversational systems is driving the need to add emotional intelligence for better context and an enhanced service experience. Car manufacturers, for example, can use a smartphone’s front camera to understand a driver’s physical condition or gauge fatigue levels to increase safety.
4) Natural-Language Understanding
Continuous training and deep learning on smartphones will improve the accuracy of speech recognition, while better understanding the user’s specific intentions. For instance, when a user says “the weather is cold,” depending on the context, his or her real intention could be “please turn up the heat.” As an example, natural-language understanding could be used as a near real-time voice translator on smartphones when traveling abroad.
5) Augmented Reality (AR) and AI Vision
With the release of iOS 11, Apple included an ARKit feature that provides new tools to developers to make adding AR to apps easier. Similarly, Google announced its ARCore AR developer tool for Android phones. This segment will be one of most used applications.
6) Device Management
Machine learning will improve device performance and standby time. For example, with many sensors, smartphones can better understand and learn user’s behavior, such as when to use which app. The smartphone will be able to keep frequently used apps running in the background for quick re-launch, or to shut down unused apps to save memory and battery.
7) Personal Profiling
Gartner notes that “Smartphones are able to collect data for behavioral and personal profiling. Users can receive protection and assistance dynamically, depending on the activity that is being carried out and the environments they are in (e.g., home, vehicle, office, or leisure activities). Service providers such as insurance companies can now focus on users, rather than the assets. For example, they will be able to adjust the car insurance rate based on driving behavior.”
Is it just me or is that a little disturbing? How will insurance companies be able to monitor our driving behavior? Is it that we’ll be forced to have the insurance company’s AI app on our smartphones or AI built into our vehicles? Obviously AI will also have a dark side and this is one of those examples.
8) Content Censorship/Detection
Restricted content can be automatically detected. Objectionable images, videos or text can be flagged and various notification alarms can be enabled. Computer recognition software can detect any content that violates any laws or policies. For example, taking photos in high security facilities or storing highly classified data on company-paid smartphones will notify IT.
9) Personal Photographing
Personal photographing includes smartphones that are able to automatically produce beautified photos based on a user’s individual aesthetic preferences. For example, there are different aesthetic preferences between the East and West — most Chinese people prefer a pale complexion, whereas consumers in the West tend to prefer tan skin tones.
10) Audio Analytic
The smartphone’s microphone is able to continuously listen to real-world sounds. AI capability on device is able to tell those sounds, and instruct users or trigger events. For example, a smartphone hears a user snoring, then triggers the user’s wristband to encourage a change in sleeping positions.
For more specifics, Gartner clients could read the full report titled “Market Insight: 10 Use Cases for AI-Powered Smartphones to Generate New Business Opportunities,” by signing up here.
At the end of the day, AI will be pushing new kinds of apps like those noted in this report. More importantly, we’re only on the cusp of a new and exciting wave of features, apps and capabilities coming our way and without a doubt Apple will remain a major contributor on this front going forward.
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