Cool but how does AI generate images?

AI’s ability to generate images is disrupting many industries such as stock photos, publishing, advertising. The models keep getting more advanced and generate ever more realistic and creative images.

There are several ways that artificial intelligence (AI) can generate images, and the specific approach used may depend on the type of image being generated and the desired level of control over the output. Some common techniques for generating images with AI include:

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1. Generative Adversarial Networks (GANs): GANs are a type of neural network that consists of two components: a generator and a discriminator. The generator is trained to produce new images that are similar to a dataset of real images, while the discriminator is trained to distinguish between real and fake images. The two components are trained together, with the generator attempting to produce images that fool the discriminator, and the discriminator trying to correctly identify real and fake images.
2. Variational Autoencoders (VAEs): VAEs are a type of neural network that can generate new images by encoding an input image into a latent space, sampling from that latent space, and then decoding the sample back into an image. This allows VAEs to generate new images that are similar to the input image, but with…