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A diffusion model is a type of generative AI that creates new data (typically images) by learning to reverse a gradual noising process. It starts with random noise and iteratively refines it into a coherent output guided by a text or image prompt.
Diffusion models power the latest wave of AI image generators and are rapidly expanding into video, audio, and 3D content creation.
Midjourney uses a diffusion model to generate photorealistic images and artwork from simple text descriptions provided by users.
Generative Adversarial Network (GAN)
A generative adversarial network consists of two neural networks — a generator and a discriminator — that compete against each other. The generator creates synthetic data while the discriminator tries to distinguish it from real data, and through this competition both improve.
Content Generation
Content generation is the use of AI to create text, images, audio, video, or other media automatically. Generative AI models learn the patterns and structures of existing content and produce new, original material based on prompts.
Foundation Model
A foundation model is a large AI model trained on broad, diverse data that can be adapted for a wide range of downstream tasks. These models serve as a starting point — or foundation — that can be fine-tuned or prompted for specific applications.
Our programme follows a structured Level 4 curriculum with project-based learning, practical workflows, and guided implementation across business and career use cases. Funded route available for UK citizens and ILR holders.