Gated Recurrent Units (GRUs), introduced in 2014 by Kyunghyun Cho and his team, are streamlined alternatives to LSTMs, designed for handling sequential data with greater computational efficiency. GRUs excel in tasks like speech recognition, time-series prediction, and natural language processing, making them ideal for real-time applications.
