Training an Artificial Intelligence model is similar to teaching a child
Copyright by www.analyticsinsight.net
Artificial Intelligence has changed our lives for better. Be it in the form of robots, automated cars, or voice based applications like Alexa and Siri, we have seen it all. Without a doubt, AI 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 AI.
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 natural language processing (NLP), computer vision, and deep learning. Machine learning is that sub field of deep learning 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.
AI and its complexity
Considering the complexity that Artificial I is associated with, Professor Sun’s research mainly talks about –
- Meta learning
- Semi-supervised learning
- Deep convolutional neural networks
- Incremental learning
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 AI 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 recognition, 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 AI is, Sun’s research talks about how critical it is to train AI model that is in line with the current trends in the field. […]
Read more: www.analyticsinsight.net