Bottleneck Architecture

Bottleneck Architecture is a design strategy used in neural networks to improve efficiency. It involves inserting a narrow layer (the "bottleneck") between wider layers, which compresses the data. This reduces the number of parameters and computational load, making the model faster and more memory-efficient. The bottleneck encourages the network to learn essential features and discard unnecessary information. Think of it like a funnel: it allows only the most important information to pass through, enhancing the model's ability to focus and generalize better while keeping it lightweight.