Top 3 Aspects of Generative AI

The following are the top three aspects of generative AI:

Transformer Models - These models are neural networks that learn via identifying and tracking relationships in sequential data, such as words in a sentence. They are the foundation to a vast many Generative AI applications, enabling the generation of coherent and contextually relevant text.

Generative Adversarial Networks (GANs) - GANs consist of two neural networks, a generator and a discriminator, which work against each other. Such a setup enables the generation of highly realistic images, videos, and other types of media. 

Variational Autoencoders (VAEs) - VAEs are used to generate new content by analyzing patterns in a dataset. They are utilized for tasks that involve the generation of new, original content based on existing data, such as images or music.