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Convolutional Neural Networks (CNNs) are a specialized class of deep learning neural networks designed to process grid-structured data, such as images and time-series data. CNNs are composed of layers, including convolutional layers, pooling layers, and fully connected layers, that work together to extract features from input data automatically. The architecture enables CNNs to effectively learn spatial hierarchies of features through the use of filters or kernels in the convolutional layer. This hierarchical feature learning facilitates image classification, object detection, and speech recognition tasks among others. As a result, CNNs play a vital role in advancing technology and artificial intelligence applications, particularly within the domains of artificial intelligence algorithms and speech recognition.