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Researchers study why neural networks are efficient in their predictions

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Artificial intelligence, machine learning and neural networks are terms that are increasingly being used in daily life. Face recognition, object detection, and person classification and segmentation are common tasks for machine learning algorithms which are now in widespread use. Underlying all these processes is machine learning, which means that computers can capture the essential properties or the key characteristics of processes in which the relationships between objects are very complex. The learning process involves good and bad examples with no previous knowledge about the objects or the underlying laws of physics.

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New perception metric balances reaction time, accuracy

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Researchers at Carnegie Mellon University have developed a new metric for evaluating how well self-driving cars respond to changing road conditions and traffic, making it possible for the first time to compare perception systems for both accuracy and reaction time.

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