Machine learning (ML) requires massive computational power and, hence, requires specialized processors. But if the power of ML can be brought to mobile devices that lack such processing power and also work in offline mode, there will be enormous opportunities and an entire new business category with a whole gamut of innovative useful mobile applications that are very hard to imagine otherwise. The entire way customers and businesses connect with each other would be reshaped.

Mobile devices have become extended organs of human beings these days. It is hard to find anyone without a mobile phone with them always. If a mobile phone is going to be a part of the human being, then, just as the eyes, nose, legs, and so on know what we do daily and have got accustomed to our lifestyle, in a similar manner, mobile phones can also understand the ins and outs of our daily routine and can bring out so many key data points, which we may not have had the time to analyze ourselves.

Moreover, a mobile device can have so many applications installed on it by different organizations that it is easy for third parties to get a deeper insight into our lifestyle, life pattern, and deep secrets, and take many different actions based on the key pointers gathered. There may be possibilities that not only benefit these third parties, but may also benefit us. They can try to make us aware of things that we were ignorant of as regards ourselves or suggest better ways to perform certain activities we do, thus improving our life overall. The possibilities are infinite and left to our imagination on how ML in mobile can be achieved and implemented. 

We are also seeing an internet of things explosion. This is another dimension, where ML in mobile devices becomes key. The sensors sending out different information from time to time can be kept close to the sensor, rather than transmitting all the way to a server. Different protocols could be used to communicate between the sensors and mobile devices for such data exchange and timely actions could be taken swiftly. Here, again, the possibilities are innumerable, groundbreaking innovations are happening, and this is just the tip of the iceberg.

In this chapter, we are going to gain insights into the following topics:

• Key ML mobile applications 
• Key innovation areas
• Opportunities for stakeholders—what are the key stakeholders in the mobile ML ecosystem doing?