How does AI-powered visual testing work, and how does it differ from pixel-by-pixel screenshot comparison? What types of defects does it catch that functional tests miss?

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AI-powered visual testing uses computer vision and machine learning algorithms to detect meaningful visual changes in an application's interface. It represents a significant advancement over traditional pixel-by-pixel screenshot comparison, which was plagued by false positives…