Machine Learning and Mobile Technology: Amalgamation for the Future

Machine learning is the technology of the future; it is just the beginning of its implementation in today's world. It is a part of artificial intelligence that has grown substantially for its usage in diverse fields and is proving worthy every day with new utilizations in daily life. Machine learning is estimated to have a market share of $153 Billion, which is quite big a number for a something that is still an emerging technology.

What makes machine learning such an important technology is the ease of its implementation in various fields like Health, Automobile, Smartphones, Food, etc. Almost anything you can think of can be supervised by machine learning. Furthermore, it is not dependent on any platform as it can be implemented for any device such as Desktop, Laptop, Tablet, and Smartphone and is executable on various Computer Languages such as Java, Python, big data etc. ML as of now has not established any boundaries or parameters for its usage in any particular field, it is very flexible to execute and is customizable for the desired results.

The amalgamation of mobile technology and machine learning is already proving to be a huge success, as it is making the mobile usage very convenient for the user and is making huge profits for the online business that exists, thus creating a win-win situation for everybody. While the current usage is just evolving according to the necessity of the everyday use, the future prospects hold implementations in almost all of the fields that you can think of Machine learning has a long way to go as it works on data and identifies the useful data and works on it to get better usability. The mobile technology is filled with data from Smartphone usage through the internet apps and the search engine, thus ensuring that it is the best implementation platform for machine learning.

Various mobile technologies engaged in machine learning:

• Word suggestion

Machine learning adapts according to the users Smartphone and helps to complete sentences by suggesting words and giving spell check.

• Translation

It helps in getting the translation of one language to the other on the go, online and offline.

• Virtual Assistants

Artificial intelligence based assistants like SIRI on the phone and Google assistant on Android helps you find an instant solution by listening to your voice input and responding to it by doing tasks for you or searching something for you.

• Geo location

Tracking your GPS position and learning about your time of stay at places mobile can suggest routes and address the location as home, workplace etc.

• Images tracking

Mobiles can put time and location stamps on the pictures you click on your mobile and also delete any repetitive images by learning their patterns. Machine learning can also recognize facial features to help tag you in the photos and other people in the pictures.

• E-commerce

E-commerce is another such platform which has evolved with the aid of machine learning, from helping users 1^st gets recommendation to providing assistance 24*7 to interact with the customer machine learning just paddles away through any task thrown at it.

• Relevant product search

Machine learning enables in understanding the user input and then providing the related products to buy, sometimes a user might not be sure of the exact details of a product, but machine learning takes over the confusion and provides the best possible solutions according to the inputs and past search etc.

• Product recommendation

Machine learning understands the e-commerce data and explains the product sales which help in suggesting products that would be the best combination with a chosen product by the user like suggesting a mobile case with a chosen mobile.

• Analysis

Keeping track of what products you search and the purpose of the goods, e-commerce platforms can hit you with offers and deal to make it a sweeter shopping experience for the customer.

• Security

Safety is the number one priority in mobiles these days as it contains sensitive data from images, personal data, bank account details and the connectivity in apps which could lead to be potentially harmful when it reaches wrong hands, so the latest security features like fingerprint detection, face recognition enables machine learning to help secure devices.

• Chatbots

Chatbots for mobile apps are another example of machine learning capabilities; it enables an intensive interaction with the customer and can provide the solution to queries and help in engaging customer.

Chatbots become more and more useful as they feed on the frequently asked questions and could provide a better solution in future scenarios. Chatbots also help collect the customer data like name, email, phone number to be contacted later for further help or converting the lead for revenue generation. The bots now available don't need grammatically correct questions to respond, after spending some time with data and doing analysis bot can learn the human language and understand from the broken sentences and accordingly provide a solution.

Advertisement on the mobile application is another great example of machine learning implementation, tracking user's specific search and location ads related to recent search on products, places, things can be displayed to attract the customer. The advertisement could also put on geo-specific location to promote places like restaurants etc. data can be tracked from apps and search engines to follow the present needs of a user, and the ads could be displayed on apps, games, browser etc. to keep reminding the stuff to the customer resulting in a potential sale over time. It is a better way of informing or getting in touch with the consumer rather than spamming them on emails and calls. It doesn't take time to respond and is always found online when the user has time to work with.

To wrap it all up, the machine learning and mobile technology are together going to change the Smartphone experience for users as well as anyone looking to work via Smartphone, as it enhances the reach ability and gives a better understanding of the user.