What are FMs?
Most of the generative AI models today are powered by the transformer-based architecture. In general, these generative AI models, also widely known as FMs, employ transformers due to their ability to process text one token at a time or entire sequences of text at once using self-attention. FMs are trained on massive amounts of data with millions or billions of parameters, allowing them to understand relationships between words in context to predict subsequent sequences. While models based on the transformer architecture currently dominate the field, not all FMs rely on this architecture. Some models are built using alternative techniques, such as generative adversarial networks (GANs) or variational autoencoders.
GANs utilize two neural networks pitted against each other in competition. The first network is known as the generator and is tasked with generating synthetic samples that mimic real data. For example, the generator could produce new images, texts, or audio...
