The basic architecture of generative AI systems
At the heart of generative AI systems is a massive FM. FMS are large-scale, pre-trained models that have been trained on vast datasets and can be fine-tuned or adapted for a wide range of tasks and applications. To understand the architecture of generative AI systems, let’s break it down into simple components:
- Generator: The core element that generates new data, whether it’s images, text, music, or other forms of content. The generator learns patterns and relationships from existing data and uses this knowledge to produce new, similar content. For example, the generator takes random noise in image generation and produces images that resemble the training data.
- Latent space: A conceptual space where the model represents data in a compressed form. It’s like a compact representation of the data that the generator uses to create new content. This is a lower-dimensional vector space from which the generator...
