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.
Robotics involves designing, building, and programming machines that can perform tasks autonomously or interact with humans. By combining AI with physical systems, businesses can…