Research firm Gartner says 80 percent of smartphones will have Artificial Intelligence (AI) capabilities by 2022 against 10 percent in 2017.
AI solutions running on the smartphone will become an essential part of vendor roadmaps over the next two years.
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, said 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.”
10 uses for AI-powered smartphones
“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.
Password-based, simple authentication is becoming 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.
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.
Training and deep learning on smartphones will improve the accuracy of speech recognition, while better understanding the user’s specific intentions. Natural-language understanding could be used as a near real-time voice translator on smartphones when traveling abroad.
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. Google announced its ARCore AR developer tool for Android and plans to enable AR on about 100 million Android devices by the end of next year.
Google expects almost every new Android phone will be AR-ready out of the box next year. One example of how AR can be used is in apps that help to collect user data and detect illnesses such as skin cancer or pancreatic cancer.
Machine learning will improve device performance and standby time. Sensors will assist smartphone to 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.
Smartphones can 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.
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.
Personal photographing includes smartphones that are able to automatically produce beautified photos based on a user’s individual aesthetic preferences.
The smartphone’s microphone is able to listen to real-world sounds. AI capability on the device is able to tell those sounds, and instruct users or trigger events.