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This lecture presents SCIM, a method for simultaneous clustering, inference, and mapping to achieve open-world semantic scene understanding. The instructor discusses generating scenarios for novel object discovery, domain adaptation of known classes, detection of unknowns, anomaly segmentation, and autonomous optimization of clustering parameters.