FiftyOne Search: Multimodal Data Search for Physical AI

FiftyOne Search is a dataset search and exploration tool for physical AI teams working with large, temporal, multimodal recordings containing data such as camera feeds, LiDAR, radar, trajectories, and sensor signals. It creates persistent dataset indexes and embeddings that allow users to search across recordings through natural-language descriptions, visual similarity, derived time-series events, and metadata filters, with these methods usable in combination. Segment-level embeddings enable retrieval of brief relevant moments within long recordings, such as failed robot grasps or unusual driving interactions, rather than treating entire episodes as a single unit. Search results open in synchronized multimodal visualizations that connect camera, 3D, signal, annotation, and prediction data on a shared timeline, helping teams investigate model failures and behavior. The platform also supports dataset curation by identifying recurring failures, coverage gaps, and underrepresented scenarios, allowing teams to improve training and evaluation data and prioritize future collection efforts, including for formats such as MCAP.

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