Layer Interaction

Layer interaction in neural networks focuses on improving communication and information flow between different layers to enhance model performance and efficiency. Current research explores various methods, including dynamic attention mechanisms that adapt feature interactions, sparse interaction modules for efficient processing of large datasets, and novel layer collaboration strategies within alternative training algorithms like the forward-forward approach. These advancements aim to optimize model architectures for tasks ranging from image recognition and object detection to natural language processing, ultimately leading to more powerful and resource-efficient AI systems.