Welcome to this lesson on AI image generation. In this session, you will explore how artificial intelligence can be used to create images based on textual descriptions. This lesson is designed to provide you with a foundational understanding of image generation techniques.

In this lesson you will learn the principles of AI-generated images, the role of prompts in guiding the AI, and how to utilise free online tools to produce your own creations. It is important to approach this activity with responsibility, ensuring that AI is employed as a tool for positive creativity and not for any form of harm or misinformation.

Lesson Objectives

• To understand the concept of AI-generated imagery and its practical applications.
• To learn about prompts and their function in image creation.
• To explore safe, free AI tools and generate images using them.
• To consider ethical issues and the credibility of images in the digital age.
• To complete a final project by creating an AI-generated image.

AI-generated imagery refers to visual content produced by artificial intelligence systems, rather than through traditional methods such as human illustration or photography. These systems employ advanced algorithms that have been trained on extensive datasets of images to generate new visuals based on user inputs.

How Does It Work?

Artificial intelligence models, such as those used in image generation, analyse patterns, styles, and elements from millions of existing images during their training phase. When provided with a description, the AI combines these learned elements to create original images.

For instance, if you describe "a cartoon image of a dragon flying over a castle at sunset", the AI interprets the text and constructs a corresponding visual representation.

Another example: if you asked for "a portrait of Albert Einstein", the AI could use its understanding of his likeness to generate a realistic or stylised image — even one that never existed before.

This process is akin to an automated artist that responds to textual instructions, producing results efficiently and creatively. Importantly, the AI does not directly copy existing works but synthesises new compositions from its trained knowledge.

Key Concepts

• Training Data: The foundation of AI imagery, consisting of vast collections of images that teach the system about shapes, colours, and compositions.
• Generation Process: The AI uses mathematical models to interpret inputs and output images, often refining them through iterative steps.
• Applications: From artistic creation to practical uses in design and education.

AI image generation has numerous applications in the real world, enabling individuals and organisations to create visual content rapidly and innovatively. This technology is transforming various industries by providing efficient tools for visualisation and design, while encouraging creative expression.

Key Applications

Below are some formal examples of how AI-generated images are utilised in professional settings. These demonstrate the practical benefits of the technology, such as cost savings, time efficiency, and enhanced creativity.

• Marketing and Advertising: Businesses employ AI to produce compelling advertisements, such as product posters or promotional graphics, without the need for professional photographers or extensive photoshoots. This allows for quick iterations and customised visuals tailored to specific campaigns.
• Game Development: Designers use AI to generate characters, environments, and entire game worlds, accelerating the development process. For instance, AI can create diverse backgrounds or fantasy creatures, helping developers prototype ideas more swiftly.
• Education: Educators leverage AI to develop illustrative materials for teaching, including diagrams of scientific concepts, reconstructions of historical events, or visual aids for complex topics. This makes lessons more engaging and accessible for students like you.
• Film and Entertainment: In the film industry, AI assists with concept art and storyboarding, allowing creators to visualise scenes before production begins. This can include generating images of futuristic settings or special effects elements.
• Healthcare and Science: Professionals use AI to create visual representations of data, such as models of molecules or anatomical illustrations, aiding in research and patient education.

In AI image generation, a prompt serves as a textual description or set of instructions that guides the artificial intelligence in creating an image. It is typically composed of one or more sentences that specify the desired visual elements, style, and composition.

What is a Prompt?

A prompt functions as the primary input for AI image generation tools. It communicates your vision to the AI, which then interprets the words and generates a corresponding image. The clarity and specificity of the prompt directly influence the accuracy and quality of the output.

Examples of Prompts

Consider the following example of a basic prompt:

• 'A red apple resting on a wooden table.'

In this case, the AI would analyse the description and produce an image that matches the specified object, colour, and setting.

For a more complex prompt:

• 'A majestic mountain landscape at dawn, with mist rising from the valleys and a clear blue sky overhead.'

This prompt provides additional details about the scene, atmosphere, and time of day, enabling the AI to create a more detailed and evocative image.

How Prompts Work in AI Image Generation

AI tools for image generation are trained on vast datasets that include both images and associated textual descriptions. This training allows the AI to understand natural language and translate it into visual representations. When you submit a prompt, the AI processes the text using advanced algorithms to synthesise an original image. The effectiveness of the result depends on the prompt's precision; a well-structured prompt yields more reliable and impressive outcomes.

The level of detail and structure in your prompt significantly influences the output of an AI-generated image. A vague or general prompt may lead to unpredictable or varied results, whereas a precise and detailed prompt is more likely to produce an image that closely matches your intended vision.

Examples of Prompt Variations

To illustrate this concept, consider the following examples:

• Basic Prompt: 'A cat' – This could result in an image of any type of cat, with no specific characteristics defined, leading to a broad range of possible outputs.
• Detailed Prompt: 'A fluffy black cat sitting on a windowsill during a rainy day, in a cartoon style' – This provides specific details about the cat's appearance, setting, weather, and artistic style, resulting in a more targeted and refined image.

By incorporating additional descriptors, such as colours, actions, environments, or styles, you can guide the AI more effectively towards the desired outcome.

The Impact of Modifying a Single Word

A small change in wording can alter the entire composition and mood of the generated image. The table below demonstrates how modifying one word in a prompt affects the result: