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According to a new report, published by KBV research, The Global Mobile Artificial Intelligence Market size is expected to reach $22.5 billion by 2024, rising at a market growth of 28.8% CAGR during the forecast period.
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Scientists are making leaps in the field of artificial intelligence and machine learning every day. The larger-than-life technologies we see in movies such as James Bond and Iron Man might not be too far from becoming a reality with the many developments in the field.
There have been some exciting developments in the world of Machine Learning and Artificial Intelligence! Let’s check out some of them:
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What is Artificial intelligence?
It makes a computer work as human beings do. It facilitates tasks that normally require human interaction, such as voice recognition, visual perception, decision making and translation between languages.
What is Machine learning?
It is about educating computer systems to recognize patterns in the way human brains understand them.
Few more important terms to consider that are directly related to the topic are:
Deep learning: can be understood as a way to make neurons understand how to solve a particular programming problem.
Neural network: involves the interconnection of several networks or artificial nodes or neurons. The output of a neuron acts as an input to the next neuron in the network.
Logistic regression: involves modelling a binomial result with one or more explanatory variables.
Linear regression: implies a linear relationship between individual input variables.
Now, let's see how machine learning and artificial intelligence have innovated and eventually transformed the development of mobile applications:
1) Trend forecast
AI filters enabled in smartphone applications help forecast the weather. Funny filters help to animate the photos in the image gallery, detect the customer's face, locate facial features and add filters, etc.
2) Security / Quick authentication
Facial and fingerprint sensors enabled with AI functions to help determine essential security functions within applications
3) Predict user behaviour
ML even helps marketing professionals understand user preferences and purchase patterns in the application.
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