So, what is Generative AI?

Generative AI is a branch of artificial intelligence that leverages machine learning models to generate new, previously unseen outputs within the same statistical properties as the training data. Unlike other AI models that take an input and return a simple response, generative AI can create something entirely new.

At its core, generative AI uses algorithms to predict the next sequence based on a given input. One of the most common models used in generative AI is the Generative Adversarial Network (GAN). Essentially, a GAN consists of two neural networks: the ‘generator’ that produces the outputs and the ‘discriminator’ that critiques these outputs. They work together to produce highly realistic results, improving with each iteration.

For example, generative AI has been used in creating realistic human faces, composing music, writing scripts, and even designing buildings. RunwayML and Dall-E are popular examples of using generative AI in creating artwork.

In digital marketing, generative AI can be used to create new content, such as blog posts, social media posts, ads, etc., based on the data it has been trained on. For instance, given a brief, a generative AI can produce a range of marketing copy options, thus saving time and allowing for greater efficiency.