Unlike GANs, diffusion models require only a single model for training and image generation, making them less complex and more efficient for image generation applications.
The current state of generative AI is filled with exciting possibilities, albeit accompanied by challenges. The industry’s concerted efforts in overcoming these hurdles promise a future where generative AI technology becomes an integral part of our everyday lives.
A machine learning algorithm is a set of mathematical rules and procedures that allows an AI system to perform specific tasks, such as predicting output or making decisions, by learning from data.
Bayesian networks are graphical models utilizing a Directed Acyclic Graph (DAG) to represent a group of random variables and their probabilistic relationships.
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