Latest Large-Language-Models Articles

AI tokens are the units that large language models process instead of raw words or characters. Prompts, generated responses, conversation history, retrieved documents, and tool results are converted into tokens before they enter a model.

AI prompt engineering is the practice of designing the instructions and context given to an AI model so that it produces useful, predictable, and appropriately constrained results. In production systems, a prompt is not merely a question written in natural language. It acts as part of the applicatio

Retrieval-Augmented Generation (RAG) is an AI architecture that retrieves relevant information from an external knowledge source and provides that information to a language model as context before generating an answer. Instead of relying only on knowledge encoded in model parameters, the application

Large Language Models (LLMs) are deep neural networks trained on large collections of text, code, and other data to understand and generate language. They power chat assistants, code-generation tools, document processing, semantic search, retrieval-augmented generation, AI agents, and many other mod

Retrieval-Augmented Generation (RAG) and fine-tuning solve different problems in AI applications. RAG supplies external information to a model at inference time, while fine-tuning changes the model itself by training it on additional examples.