Teaching AI to Move: GRUs in Sequence Modeling

How does AI learn to predict and generate realistic human motion? In this episode, we dive into the power of Gated Recurrent Units (GRUs) for sequence modeling. Discover how this advanced RNN architecture captures long-term dependencies, predicts motion data point by point, and generates lifelike movements. From speech synthesis to machine translation, GRUs are proving their versatility—tune in to see how they’re reshaping AI’s ability to understand and create dynamic sequences.

Link to research paper-

https://arxiv.org/abs/1501.00299

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