Generative AI comes in various forms, each with unique applications.
Generative Adversarial Networks (GANs) involve two networks—the generator and discriminator—working together to create highly realistic outputs, such as lifelike product images in eCommerce.
Recurrent Neural Networks (RNNs) handle sequential data by retaining information from previous steps, making them great for generating text or sequences. In eCommerce, they’re used for personalized product recommendations and crafting chatbot responses.
Transformer Models, such as GPT, use attention mechanisms to generate text or code, making them ideal for automating tasks like product descriptions or personalized emails.
Lastly, Diffusion Models add noise to data and reverse the process to create high-quality outputs, which is especially useful for generating high-resolution images for product catalogs.