A Large Language Model (LLM) is a type of Artificial Intelligence (AI) trained on vast amounts of text data to understand, generate, and manipulate human language. These models are typically built using Transformer architectures and contain billions of parameters, allowing them to capture complex patterns in syntax, semantics, and context.
Key Characteristics of LLMs:
- Massive Scale: Trained on petabytes of data from books, articles, and websites.
- Probabilistic Nature: They predict the next token (word or character) in a sequence based on statistical likelihood.
- Few-Shot Learning: They can perform tasks they weren't explicitly trained for simply by being given a few examples in a prompt.
Common examples include Google Gemini, GPT-4, and Claude. In the modern tech stack, LLMs serve as the "reasoning engine" for chatbots, code assistants, and automated research tools.