Transformer
The neural network architecture introduced in the 2017 paper "Attention Is All You Need" that underlies almost every modern LLM. Its key idea is the attention mechanism, which lets the model weigh the relationships between all words in a text simultaneously.
See also
LLM (Large Language Model)
A neural network trained on massive amounts of text that can understand and generate human language. Examples include GPT, Claude, Gemini, and Grok. It powers most modern chatbots and AI assistants.
Prompt Engineering
The art and practice of crafting prompts to an AI so that it produces the most accurate and useful response. It includes phrasing the task clearly, adding examples and context, and specifying the desired output format.
RAG (Retrieval-Augmented Generation)
A technique where the model first retrieves relevant documents from an external knowledge base, then uses them as context to generate its answer. It reduces hallucinations and lets the model answer questions about recent or highly specialized data.
Fine-tuning
Additional training of an already-trained model on a narrow dataset to adapt it to a specific task or style — for example, legal documents or a brand's tone — without training the model from scratch.