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Robots can now autonomously figure out where to make contact for complex manipulations, opening the door to more versatile and robust automation.
Training AI to identify audio effects in speech is now possible, thanks to a new dataset that precisely labels how effects are applied.
By reinterpreting unsupervised anomaly detection through the lens of Retrieval-Augmented Generation, RAID achieves state-of-the-art performance by using retrieved normal samples to guide noise suppression in anomaly map generation.
