Long way before AI systems take over humans jobs: Study

Researchers at university of California, Los Angeles (UCLA) in the US conducted various experiments which showed that it is easy to fool the deep learning neural networks.​​​​​​​"The machines have severe limitations that we need to understand," said Philip Kellman, a UCLA professor and senior author of the study published in the journal PLOS Computational Biology 

 


Artificial intelligence (AI) systems have a long way to go before they can take over tasks and jobs traditionally performed by people, say scientists who highlighted the severe limitations of deep learning computer networks. 


Researchers at university of California, Los Angeles (UCLA) in the US conducted various experiments which showed that it is easy to fool the deep learning neural networks."The machines have severe limitations that we need to understand," said Philip Kellman, a UCLA professor and senior author of the study published in the journal PLOS Computational Biology 

 

According to Kellman, machine vision has drawbacks. 

 

In the first experiment, researchers showed colour images of animals and objects to one of the best deep learning networks, called VGG-19. 


However, the images had been altered. For example, the surface of a golf ball was displayed on a teapot; zebra stripes were placed on a camel; and the pattern of a blue and red argyle sock was shown on an elephant. 


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