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How machine learning elevates mobile technologyBy CIOAdvisor Apac | Monday, January 14, 2019
Machine learning (ML) makes computer systems to make them better at performing tasks through exposure of data instead of through explicit programming. ML demands massive computational power, cloud-based computer servers outfitted with specialized processors. But today emerging trends are bringing the power of machine learning to mobile devices. The amalgamation of mobile technology and machine learning is proving to be a success as ML makes mobile usage very convenient for the user and huge profit for online businesses. The mobile technology is filled with data from smartphone usage through the internet apps and the search engines that ensure it is the best implementation platform for machine learning. Following are some of the mobile technologies engaged in machine learning:
Word prediction: A common activity in the smartphone platform is text generation that can be physically demanding and slow. Word prediction methods are used to assist in the task. The tool aids by reducing the effort and time needed to write texts. The prediction algorithm is based on machine learning methods improve the prediction quality, save keystrokes, and predict correctly.
Translation: Translation apps (application) support users in a different place where they can't depend on their native language. This app gives an immediate translation to a different language on demand. Users can input the line or word to translate by speaking, typing or a picture using the smartphone camera.
Chatbots: Chatbots are becoming very useful because they are able to answer the frequently asked queries and provide a better solution. Also, they help collect customer data as name, email, phone number for further assisting. Online businesses are using chatbots to improve customer satisfaction and engagement.
Geo-Location: The Geo-Location helps in determining and identifying the exact location of any device as smartphone, tablet, or laptop. The technology utilizes the cell triangulation to detect the location.
Image tracking: Smartphones put time and location stamps on the pictures that have been taken from that device and delete any repetitive image by leaning the patterns. With the help of machine learning the devices also can recognize facial features.
Relevant searching: Machine learning is able to understand user input and provide the related products to buy. The technology takes over the confusion from user-side and delivers the best possible solutions according to the inputs and past search.
Product recommendation: Machine learning takes e-commerce data and explains the sale of the products that helps to have suggestions about the best combination of the products by using previous input data.
Analysis: Machine learning algorithm keeps track of the searching products and purpose it and hits the user with offers and deals to make it a greater shopping experience for the customers.
Security: Mobiles contains sensitive data form images, personal data, financial accounts details and the connectivity in the apps, which cloud lead to be potentially harmful. Machine learning-driven security features as fingerprint detection, face recognition help to secure devices.
The marriage of machine learning and mobile technology transforms the smartphone experience for users, enhances the ability and delivers a better understanding of the user.