What is generative AI? Generative AI refers to deep-learning models that can generate high-quality text, images, audio, synthetic data and other content based on the data they were trained on.

Generative AI is a type of AI that creates new things like text, images, music, or videos. It learns from existing data and uses that knowledge to make something new and original, instead of just analyzing, sorting or filtering data. chatGPT is an example of generative AI.

Gemini says: “Unlike traditional AI, which is designed to analyze or categorize existing data, generative AI models learn the underlying patterns and structures within a dataset and then use that knowledge to produce something entirely new. Think of it as an AI that can learn the “rules” of images, text, or music and then compose its own variations.”

Gemini goes on to say: “At the heart of generative AI are models like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). GANs, for example, involve two neural networks: a generator and a discriminator. The generator creates new data, while the discriminator tries to distinguish between real and generated data. They play a constant game of cat and mouse, with the generator getting better at creating realistic outputs and the discriminator getting better at spotting fakes. This adversarial process drives the model to produce increasingly convincing results. VAEs, on the other hand, encode data into a compressed representation and then decode it back into a new sample, allowing for smoother and more controlled generation.”