It seems that at least in the field of computational biology, computers are getting closer to humans.

This Tech provides suppliers information about the satisfaction of their products and services; it is no doubt that in this way we witness better provision of present goods and services.

Indeed Salesforce company at the time of the TrailheaDX conference unveiled three robotic tools which make it easier probing the satisfaction of products and favors remotely discerned when a customer is consuming them behind the private computer feeling angry about possible problems.

Salesforce’s artificial intelligence technology, called Einstein, can also be added to the market analysis tool and is therefore highly flexible.

The algorithm of this system investigates small, almost indistinguishable human movements and notices one’s emotions.

This technology performs by analyzing facial movements associated with a range of human emotions that occur in places like interviews, groups and public places such as press conferences.

Artificial intelligence technology controls human behavior from moment to moment and compares each piece of emotion to determine how an individual feels when purchasing something online.

This emotion realization technology focuses on subtle behavioral traits associated with happiness, trust, fear, surprise, sadness, disgust, anger, and human deviance.

In this process, the system has invented a kind of intermediate processing stage that focuses on the degree of rotation and angle of the face, not the reverse.

simply put, the system can perform identification even when the face image is rotated.

The other profit of this Tech would be organizing all typed texts in the format of negative, positive or neutral classifications.

Thus it makes it easy to categorize emails and customer messages about a company to expand the quality of service and product offerings upcoming.

Additionally, it can be used to organize clients’ requests based on their intentions to provide more accurate and personalized responses to each individual.

The growth rate of face recognition depends on the speed of maturation of a machine learning called deep learning.

Deep learning utilizes huge computational nodes (roughly similar to brain connections) to identify patterns in data; This method is nowadays capable of recognizing patterns with extremely high accuracy.

Tasks, where in-depth learning works with great accuracy, including identifying objects or faces of people even in low-quality images and videos.

This Tech can bring elements of risks, threats, and abuse but some reckon that advantages of this tech outweigh its disadvantages.

The advent of this technology arouses privacy activist concerns who have confidence in the fact that this Tech can because of wrong and fanatical judgments of persons because this technology may not have reasonable accuracy.

In reality in European champions league final held in Cardiff City, audiences were under surveillance operation that nothing went well; 2000 people were recognized as an offender by mistake.

It argued the point that privates should be warned whenever face detection systems are used and that people should have the right to refuse to use such technology; no question implementing such proposals can be challenging and difficult.

In the end, it argued that if we have proper control over technological use then this Tech would be practical from many aspects also the impression of possessing it is noteworthy and we ought to draw attention to this importance of how humanizing technology would take us to new steps.