Neural networks have shown, for example, that they can be unreliable and unpredictable. As statistical pattern matchers, they sometimes home in on oddly specific patterns or completely incorrect ones. A deep learning model might recognize pedestrians only by the crosswalks underneath them and fail to register a person who is jaywalking. It might learn to associate a stop sign with being on the side of the road and miss the same sign extended on the side of a school bus or being held by a crossing guard. Neural networks are also highly sensitive to changes in their training data. Feed them a
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