👉 A temporalizer is a type of neural network that is designed for tasks where long-range dependencies (e.g., attention, memory) are important. These networks can be used to improve the performance of recurrent neural networks by learning to focus on specific parts of input sequences over time. For example, in image recognition tasks, a temporalizer might be used to extract features from images that capture the spatial relationships between different pixels or regions within an image. This is useful because it allows the network to focus on