Variational Autoencoders are a type of generative model used in unsupervised learning. VAEs learn a low-dimensional representation of input data and can generate new data samples similar to the training data. They have applications in tasks such as image generation, anomaly detection, and data compression.
Edge Computing brings computing resources closer to the source of data generation, reducing latency and improving response times. By processing and analysing data locally…