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AI and Its Complexity: Breaking The Ice

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Training an Artificial Intelligence model is similar to teaching a child

Copyright by www.analyticsinsight.net

SwissCognitive, AI, Artificial Intelligence, Bots, CDO, CIO, CI, Cognitive Computing, Deep Learning, IoT, Machine Learning, NLP, Robot, Virtual reality, learningArtificial Intelligence has changed our lives for better. Be it in the form of robots, automated cars, or voice based applications like and Siri, we have seen it all. Without a doubt, is that one technology that makes the best use of human intelligence to take up tasks that earlier could only be performed by humans. Machines now stand the potential to learn and put the knowledge gained in the best possible use. All the human-like tasks are now performed using .

There are several aspects to Artificial Intelligence and so are the fields within this splendid technology. Some of them that have successfully garnered attention and appreciation equally from every corner of the world are (), computer vision, and Machine learning is that sub field of that mainly revolves around analysing data and making predictions out of the analysed data. Needless to say, all this relies heavily on human supervision.

SMU Assistant Professor of Information Systems, Sun Qianru, talks about how training an Artificial Intelligence model has so much in similarity to that of how parents teach their child to identify objects.

and its complexity

Considering the complexity that Artificial I is associated with, Professor Sun’s research mainly talks about –

Well, not just that. The research also revolves around the application of all of these in recognizing images and videos.

The research, “Fast-Adapted Neural Networks (FANN) for Advanced Systems” is currently in its early stage. The research revolves around computer vision. This aspect of computer vision employs algorithms that rely on CNNs (Convolutional neural networks). The areas under scrutiny are , image processing, etc. All of this work is funded by the Agency for Science, Technology and Research (A*STAR).

Building the reasoning level of model adaptation based on statistical-level knowledge learning is the hypothesis of FANN. Here’s everything that the research talks about –

• Knowing the fact as to how complex is, Sun’s research talks about how critical it is to train model that is in line with the current trends in the field. […]

Read more: www.analyticsinsight.net

 

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