The key characteristic of Large Language Models (LLMs) is their ability to understand and generate human language. LLMs based on transformer architecture are mainly of three types i.e., Mask Language Model (predict the masked words based on the surrounding context), Causal Language Model (predict the next word in a sequence given the preceding words) and Seq-to-Seq Model (translation, summarization etc.)

In this post, we’ll delve deep into Generative Adversarial Networks (GANs) architecture, its loss function and evaluation metrics. We’ll also explore the diverse types of GANs and its alternatives that have been pushing the boundaries of what’s possible in AI.