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Plain-language AI glossary

Term 01FundamentalsMeaning / context / connections

Fundamentals / Definition

Large Language Model (LLM)

A neural network trained on massive text datasets that can generate, understand, and reason about human language.

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01

MeaningThe one-sentence definition.

02

ContextHow the idea works in practice.

03

UsesWhere the concept becomes useful.

01 / Plain-language context

How Large Language Model (LLM) works.

LLMs like GPT-5, Claude, and Gemini are the foundation of modern AI applications. They work by predicting the next token (word or subword) in a sequence, but through scale (billions of parameters) and training on internet-scale data, they develop emergent capabilities like reasoning, coding, and following complex instructions. In production, LLMs are accessed via APIs from providers like OpenAI, Anthropic, and Google.

02 / Practical uses

Where it helps.

  1. 01Chatbots and virtual assistants
  2. 02Content generation
  3. 03Code completion
  4. 04Document analysis
  5. 05Translation
03 / Keep exploring
TransformerThe neural network architecture behind all modern LLMs, using self-attention mechanisms to process sequences in parallel.Fine-TuningThe process of further training a pre-trained AI model on your specific data to improve performance on domain-specific tasks.Prompt EngineeringThe practice of crafting effective instructions for AI models to produce desired outputs consistently.TokenizationThe process of breaking text into smaller units (tokens) that an AI model can process, typically subwords or word pieces.