What is a large language model?

A large language model is a neural network (typically Transformer-based) with billions of parameters, trained on massive text corpora to generate and understand language. GPT-4, Claude 3, Gemini, and Llama 3 are prominent examples.

How do LLMs know so much?

LLMs learn from patterns in their training data, which may include Wikipedia, books, academic papers, code, and web pages. They develop internal representations of world knowledge that can be retrieved at inference time.

What is the difference between LLMs and chatbots?

Traditional chatbots used rules or retrieval to generate responses. LLMs generate responses by predicting the most contextually appropriate text given a conversation history, enabling far more flexible, nuanced, and capable dialogue.

Are LLMs the same as AI?

No. LLMs are a specific type of AI model specialised in language. AI is a broad field encompassing computer vision, robotics, reinforcement learning, and more. LLMs are a particularly prominent category of AI in 2023-2025.

Models

Large Language Models (LLMs)

Large language models (LLMs) are AI systems trained on vast amounts of text data to understand and generate human language. Built on Transformer architectures with billions to trillions of parameters, LLMs exhibit emergent capabilities — skills not explicitly trained for — including reasoning, coding, translation, and question answering.

How Large Language Models Works

LLMs are pre-trained using self-supervised learning: given a sequence of text, the model learns to predict the next token. This is done at massive scale using hundreds of billions of tokens of internet text, books, and code. After pre-training, models are typically fine-tuned with human feedback (RLHF) to align outputs with helpful, harmless, and honest responses. At inference time, the model generates text token-by-token using sampling strategies.

Key Use Cases

Conversational AI and chatbots
Code generation and debugging
Document summarisation
Translation and localisation
Search and question answering
Legal and medical document analysis
Content creation and editing

Frequently Asked Questions

What is a large language model?: A large language model is a neural network (typically Transformer-based) with billions of parameters, trained on massive text corpora to generate and understand language. GPT-4, Claude 3, Gemini, and Llama 3 are prominent examples.
How do LLMs know so much?: LLMs learn from patterns in their training data, which may include Wikipedia, books, academic papers, code, and web pages. They develop internal representations of world knowledge that can be retrieved at inference time.
What is the difference between LLMs and chatbots?: Traditional chatbots used rules or retrieval to generate responses. LLMs generate responses by predicting the most contextually appropriate text given a conversation history, enabling far more flexible, nuanced, and capable dialogue.
Are LLMs the same as AI?: No. LLMs are a specific type of AI model specialised in language. AI is a broad field encompassing computer vision, robotics, reinforcement learning, and more. LLMs are a particularly prominent category of AI in 2023-2025.