Large Language Models (LLM) are advanced Machine Learning algorithms that are trained on a vast amount of text data. They are designed to understand and generate human-like text based on the input they receive. LLMs are capable of tasks such as translation, question answering, and text generation, among others. They are a significant component of natural language processing and are instrumental in the development of AI applications that require a deep understanding of human language.
Modern LLMs vary by architecture, training data, model parameters, context window, and inference behavior. Some systems use transformer alternatives such as Mamba, sparse architectures such as sparse expert models, or specialization techniques such as domain-specific LLMs.
The LLM Knowledge Base is a collection of bite-sized explanations for commonly used terms and abbreviations related to Large Language Models and Generative AI.
It's an educational resource that helps you stay up-to-date with the latest developments in AI research and its applications.