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Large Language Model (LLM)

A Large Language Model (LLM) is an AI model trained on massive amounts of text data using enormous computational resources, designed to understand and generate natural language. Also referred to as "LLMs," they are at the center of the recent generative AI boom. These models read the context of input text, understand its meaning, and automatically generate the words and sentences that follow — giving them the versatility to handle a wide range of natural language processing tasks, including question answering, summarization, translation, code generation, and creative writing. Representative large language models include: • GPT series (OpenAI) • Claude (Anthropic) • Gemini (Google DeepMind) • Llama (Meta) • PaLM (Google) These models contain billions to hundreds of billions of parameters, enabling sophisticated language understanding and generation that was impossible with earlier AI. Most LLMs are developed by combining pre-training with fine-tuning, and can be adapted for chat-based interactions and domain-specific customization. Large language models are used across a wide range of practical scenarios — search engines, chatbots, automated business document creation, and programming assistance — and are often discussed as nearly synonymous with "generative AI." They are set to play a central role in AI development and real-world deployment going forward.

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