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New to gen ai? Read our complete Guide to Generative AI.

What is Gen AI?

Gen ai refers to artificial intelligence systems that can generate brand new data, such as text, images, audio or video. It works by learning patterns from training data, then leveraging that knowledge to create new, original data.

How Does Gen AI Work?

Gen ai models use machine learning algorithms trained on large datasets. The algorithm analyzes the relationships and patterns in the training data in order to generate new data that resembles the original data.

Here are some key techniques used in gen ai:

  • GANs (Generative Adversarial Networks) - A generator network creates content, a discriminator evaluates it. The two networks train each other.
  • VAEs (Variational Autoencoders) - Encode data into a latent space and decode it again. Useful for generation tasks.
  • Diffusion Models - Add noise to data and remove it over time to generate realistic outputs.

Gen AI Applications

Here are some real-world gen ai use cases across different industries:

  • Art & Design: Creating original digital art, 3D models, product designs
  • Healthcare: Drug discovery, medical image analysis
  • Entertainment: Automatically generating video game assets, VR environments
  • Robotics: Simulating training environments
  • Marketing: Generating customized ad images

We are still just scratching the surface of gen ai's potential. As the algorithms continue to advance, gen ai will unlock new possibilities across industries.

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