Capsule Networks are a type of artificial neural network designed to better capture spatial relationships and hierarchies in data, such as images. Unlike traditional neural networks, capsules group neurons together to represent different properties of an object, like its position and orientation. This structure helps the network understand the whole object and its parts, making…

Attention mechanisms are methods used in artificial intelligence that help models focus on the most relevant parts of input data, such as words in a sentence or regions in an image. They allow the model to weigh different pieces of information differently, depending on their importance for the task. This makes it easier for the…

Contrastive learning is a machine learning technique that teaches models to recognise similarities and differences between pairs or groups of data. It does this by pulling similar items closer together in a feature space and pushing dissimilar items further apart. This approach helps the model learn more useful and meaningful representations of data, even when…

Latent space refers to a mathematical space where complex data like images, sounds, or texts are represented as simpler numerical values. These values capture the essential features or patterns of the data, making it easier for computers to process and analyse. In machine learning, models often use latent space to find similarities, generate new examples,…