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Survey Highlights Data Bottlenecks In Physical AI
A survey of 700 professionals identifies data collection and labeling as the primary friction points for visual and physical AI. These teams struggle with model failure rates during the transition from simulation to reality. The findings suggest that data engineering, not model architecture, currently limits production speed for IEEE Spectrum readers.