PLOS Computational Biology/Rubylane.com
Artificial intelligence networks did poorly in identifying glass figurines. Most of the top responses seemed odd, such as one network’s choice of ’can opener’ for this polar bear.
Science + Technology - UCLA psychologists' experiments demonstrate severe limitations of 'deep learning' machines - Stuart Wolpert How smart is the form of artificial intelligence known as deep learning computer networks, and how closely do these machines mimic the human brain? They have improved greatly in recent years, but still have a long way to go, a team of UCLA cognitive psychologists reports in the journal PLOS Computational Biology. Supporters have expressed enthusiasm for the use of these networks to do many individual tasks, and even jobs, traditionally performed by people. However, results of the five experiments in this study showed that it's easy to fool the networks, and the networks' method of identifying objects using computer vision differs substantially from human vision. "The machines have severe limitations that we need to understand," said Philip Kellman, a UCLA distinguished professor of psychology and a senior author of the study. "We're saying, 'Wait, not so fast.'" Machine vision, he said, has drawbacks. In the first experiment, the psychologists showed one of the best deep learning networks, called VGG-19, color images of animals and objects. The images had been altered.
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