Cross-Industry Disruption AI You may not be aware that there many smartphone functions that actually driven by artificial intelligence (AI). Recently, AI continues to receive public scrutiny and is a tool that uses the most advanced technology. Now that AI has become such an integral part of mobile apps that chipmakers need to continue developing AI chips dedicated to machine learning and deep learning tasks for faster processing.
Here are the different ways AI is being use on mobile
1. AI in voice assistant
The basic functionality of a mobile voice assistant involves the use of AI. Siri, Google Assistant, and Bixby made to process and understand more than just commands, like “Hey Google” and “Hey Siri”. They instantly process complex questions and respond by constructing clear sentences just like humans do. These sentences turne out to be not store responses. AI assistants are traine with linguistic rules to help them build sentences, similar to chatbots like ChatGPT.
2. AI in photography
AI in imaging ensures that your shots look great in any setting. works its magic by enhancing images, sharpening blurry elements, reducing noise for images taken in low light, adding bokeh effects and much more. Is especially useful in smartphone cameras as it helps make up for hardware deficiencies with software processing and improves quality significantly.
3. AI in facial recognition
Android smartphones do support facial recognition, but they encourage users to use fingerprint technology. Meanwhile, iOS prioritizes facial recognition. First launched on the iPhone X in 2017, this technology replaces Apple’s Touch ID fingerprint scanning system.
Now facial recognition is available on all the latest iPhones. AI works when the iPhone checks the facial scans against the ones you have set up and stored on the device to see if they match. AI also helps Face ID adapt to changes in your appearance such as wearing makeup.
4. AI in augmented reality (AR) applications
Special smartphone chips have state-of-the-art AI processors known as neural processing engines or similar that support augmented reality (AR) experiences on devices. As VR gains traction, AI continues to demonstrate its capabilities in real-time object tracking and recognition.
Scene recognition through the camera lens is an example of a practical application of AI. Devices now have the ability to distinguish between different types of scenes, such as animals, views such as sunsets, and images containing text.