Artificial intelligenceHow Data Bottlenecks Slow Down Physical and Visual AI Development
A new study surveying over 700 experts in visual and physical AI uncovers systemic issues hindering real-world AI adoption. Experts highlight data-related flaws as the primary barrier to scaling models capable of interacting with the physical world. The findings emphasize the urgent need to rethink training and validation approaches for AI algorithms.
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