Introduction to Generative AI

Generative AI refers to algorithms that can create new data similar to existing data. It encompasses a variety of techniques used to generate text, images, music, and other media, enabling machines to produce creative content autonomously.

Generative Adversarial Networks (GANs)

GANs are a class of generative models consisting of two neural networks, a generator and a discriminator, which are trained simultaneously. The generator creates new data, while the discriminator evaluates its authenticity, leading to high-quality generated outputs.

Variational Autoencoders (VAEs)

VAEs are generative models that use neural networks to encode input data into a compressed representation and then decode it to generate new data. They are used for tasks like image generation, anomaly detection, and data compression.

Transformers and Language Models

Transformers are a type of neural network architecture that has revolutionized natural language processing. Large language models like GPT-3 use transformers to generate human-like text, enabling applications in text completion, translation, and content creation.