What is Generative AI?

Generative AI represents a departure from traditional artificial intelligence paradigms, which predominantly rely on existing data for tasks like categorization. Unlike the conventional approach of evaluating known patterns, generative AI empowers machines to create novel content, showcasing a form of creativity inspired by learned models.

Unlike discriminative AI models adept at categorizing and predicting based on input data, generative AI algorithms play a more creative role. They draw inspiration from learned patterns to generate entirely new content across various formats, including text and images.

To illustrate, consider the Shazam app example. While Shazam, utilizing a discriminative AI model, scans its data library to identify a playing song, a generative AI algorithm could amalgamate patterns from various songs it has learned to create an entirely new song upon request. For instance, if trained on songs by The Smiths, it might produce a new composition reminiscent of Morrissey's style, even though that specific song never existed before.

Generative AI's ability to innovate and create original content opens up new possibilities, from artistic endeavors to innovative problem-solving, signifying a substantial shift in artificial intelligence capabilities beyond conventional data-driven approaches.