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Xiaomi announced that it plans to begin mass-producing smartphones outfitted with its under-show camera technology one year from now.

The company says that This is actually the third era of the innovation Xiaomi has created, and, although the first and second forms it delivered presently can't seem to discover their way into a mass-market customer device.Xiaomi says that the zone of the display over the camera has similar pixels density as the remainder of the screen, so it can perfectly disguise the selfie camera underneath.

According to Xiaomi, its most recent variant of the technology works by permitting the selfie camera to see through the gaps in the sub-pixels of the display, which are the green, red, and blue spots that consolidate to make every pixel.

It includes that the selfie camera itself should coordinate the presentation of more typical front-facing cameras.

However, it says that in the area of the screen the camera should coordinate the color accuracy brightness and color gamut of the rest of the display.

The blog post of Xiaomi doesn’t specify whether the panel itself is LCD, or OLED, or what sort of goal we can anticipate that it should be.Smartphone manufacturers have been prodding under-display cameras for a brief period now, but so far the innovation is yet to see legitimate commercialization.

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With the arrival of cloud computing and multi-core machines - we have enough compute capacity at our disposal to churn large volumes of data and dig out the hidden patterns contained in these mountains of data.

These algorithms use all the collected “past” data to learn patterns and predict results or insights that help us make better decisions backed by actual analysis.

Credit scoring, which helps the banks to decide whether to grant the loans to a particular customer or not - based on their credit history, historical loan applications, customers’ data and so on

Or the latest technological revolution from right from science fiction movies - the self-driving cars, which use Computer vision, image processing, and machine learning algorithms to learn from actual drivers’ behavior.

In all these examples, machine learning is used to build models from historical data, to forecast the future events with an acceptable level of reliability.

This concept is known as Predictive analytics.

Artificial Intelligence (AI) is the proficiency of a computer program or a machine that is to learn or think.

The main concept of Artificial Intelligence is based on the idea of building or generating machines such as capable of thinking, acting, and learning like humans.

This is the total a technique for machines that is to exhibiting of certain parts of human idea and knowledge.

Machine learning and deep learning are two subsets of artificial intelligence that have received a lot of attention over the past two years.

A subset of machine learning, where algorithms are created and operated similar to machine learning, but there are many layers of these algorithms — each providing a different interpretation of the data it feeds.

I've tried to put those definitions in the simplest way possible, but if this doesn't help you make any difference, here's an example.

The data is sufficient to learn the machine learning algorithm, and then it works on the labels it understands and classifies millions of other images of two animals according to the properties learned by the labels mentioned.

This is similar to how our human brain works to solve problems - by sending questions through different series of concepts and related questions to find answers.

Once the data is processed through layers in deep neural networks, the system will find enough identifiers to classify the two animals from their images.