dailyai.report

Over 700 professionals surveyed reveal that data collection remains the primary hurdle for visual and physical AI systems. These teams struggle with model failures during production due to poor data quality. The findings highlight a persistent gap between lab performance and real-world deployment. Practitioners must prioritize robust data pipelines over model architecture to improve reliability.