AI generated images and Stable Diffusion explained for non-nerds

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Stable Diffusion is an Artificial Intelligence (AI) model that can understand and generate a wide range of images. It is a powerful tool that can be used for a variety of tasks. But how does Stable Diffusion work? In this article, we will explain the basics of Stable Diffusion in a way that people who are not familiar with IT can understand it.

First, it’s essential to understand that Stable Diffusion is a type of machine-learning model called a neural network. Neural networks are a type of computer program that is designed to simulate the way the human brain works. They are made up of layers of interconnected “neurons” that process information.

Stable Diffusion is trained on a vast dataset of internet text and images, allowing it to understand and generate a wide range of content. This dataset is fed into the neural network, and the network is then “trained” to understand the patterns and relationships in the data. This process is called “training,” It allows the neural network to learn how to understand and generate new content based on the patterns it has learned from the data.

Once the neural network is trained, it can then be used to generate new content. For example, if you give Stable Diffusion a text description of an image, it will generate an image based on the description. This process is called “inference,” and it allows the neural network to generate new content based on the patterns it has learned during the training process.

The most exciting feature of Stable Diffusion is its ability to generate images from text descriptions. This is achieved by the neural network understanding the text description and using the patterns it has learned from the training data to generate an image that matches the description. It can create new images by combining concepts from different images; it can also generate novel images that have never existed before.

It’s important to note that Stable Diffusion is not capable of understanding the real-world context of the images, it is just able to generate images based on the patterns it has learned from the data it was trained on, and the generated images may not always make sense in the real world. While it is a powerful tool, it’s important to remember that Stable Diffusion is a machine, and its output should always be supervised and validated by humans.