How does a smartphone use AI to obtain a response from users?

When you hear the word technology, Artificial Intelligence or AI is one those technologies that hit one's mind at first. With AI transforming each and every sector today, it is believed to be one of the greatest transformations that has occurred in recent times.

One of the major impact that AI has made is in the smartphone industry. Starting with voice recognition Siri or Google Assistant to Face recognition passwords and many more, AI has transformed smart phone industry into a whole new technology.

AI in smartphones can be found in :

Powerful AI chips 

Apple, Samsung, and Huawei have all introduced smartphones with powerful AI chips that can perform up to 5 trillion operations per second and use significantly less power to accomplish tasks. With AI, these phones provide features from Face ID to Augmented Reality. AI is even used to improve photo quality, with an AI-recognition of depth that enables digital image post-production editing of blur and sharpness.

Camera with an AI assistant

Cameras built into phones with AI-enabled chip sets benefit from a more intelligent camera app. For instance, the Huawei Mate 10 is capable of spotting up to 13 different popular framed scenes and optimizing for them. These include a skyline, pet pictures of your cat or dog Fido, snowy winter scenes, and even snapshots of text. Auto modes can self-identify what’s being viewed through the camera lens with the phone swapping to the most relevant mode for better composition, exposure and lighting built-in.

There are many more applications in a smartphone which use AI, like Siri, Google Assistant, Google Maps, photo editing applications like Prisma, etc.

But AI itself is a huge terminology, it consists of many fields. We'll see what exactly is used in a smartphone. 

Machine Learning 

Machine learning is the concept of having computers learn from data with less or minimal programming.

It includes both supervised and unsupervised learning. Deep learning is also a subset of machine learning.

For example :

• Face detection in a photo using image recognition.
• Speech recognition using voice search or voice dialing.
• Enhanced visual search.
• Automated photo and video tagging.
• User-generated content moderation.
• Object detection.

Deep Learning

Deep Learning is the ability of a program to learn how to learn. It uses more complex algorithms to carry out tasks with little or no human supervision. 

For example :

• On-device speech recognition
• Increased efficiency with gesture recognition.
• Immersive capabilities of Augmented Reality (AR).
• Higher quality photographs.
• Increased Security and Privacy.
• More Accuracy in Image Recognition.

Natural Language Processing (NLP)

Natural Language Processing (NLP) can help to make apps smarter, by automatically analyzing the meaning of content and taking appropriate actions on behalf of their users. It is the process a program uses to recognize patterns and grammar rules within large datasets, and to manipulate language, in both speech and text, in a natural way.

For example :

• Autocomplete.
• Spellcheck.
• Spam Filters.
• Google Assistant, Siri, Alexa, etc.
• Voice text messaging.
• Related keyword search.

These are the most used AI fields in a smartphone. They make a smartphone much smarter than it appears to be. It is a creative field and it keeps on changing with new innovations and bright ideas.