Introduction to Generative AI

Introduction to Generative AI

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Generative AI, also known as generative adversarial networks (GANs), is a type of artificial intelligence that creates new data instances or samples that resemble a given dataset. In simpler terms, generative AI can generate new images, texts, or even music based on patterns it has learned from existing data.

These AI systems work by training two neural networks simultaneously: a generator and a discriminator. The generator creates new data samples, while the discriminator evaluates these samples and determines if they are real or fake. Through this iterative process of generating and evaluating data, the AI learns to create increasingly realistic and accurate outputs.

Generative AI has a wide range of applications, including image generation, text generation, and even drug discovery. It has been used to create realistic images of non-existent celebrities, generate natural language text, and even compose music in the style of famous composers.

In this post, we will explore the basics of generative AI, how it works, and some of the exciting possibilities it offers for the future. Stay tuned for more in-depth discussions and examples of generative AI in action!
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