Overview
A Large Language Model (LLM) is an artificial intelligence system trained on vast amounts of text data to understand and generate human-like language. LLMs use deep learning techniques, particularly transformer architectures, to recognise patterns in text, predict words, and produce coherent responses. Examples include GPT-3, GPT-4, and GPT-5.
Key Characteristics
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Scale: LLMs are trained on billions or even trillions of words, giving them broad general knowledge.
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Transformer architecture: This neural network design allows it to handle context across long passages of text.
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Generative ability: LLMs can create new content rather than only classifying or retrieving existing text.
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Adaptability: They can be fine-tuned for specific industries or tasks, such as law, healthcare, or customer support.
How They Are Used
- Conversational AI: Powering chatbots, virtual assistants, and interactive agents.
- Content creation: Writing articles, reports, code, or creative works.
- Research and analysis: Summarising papers, drafting briefs, or assisting in data interpretation.
- Education: Providing tutoring, explanations, and interactive learning experiences.
Considerations
While powerful, LLMs have limitations. They can generate incorrect or biased outputs and may lack real-world understanding beyond their training data. They also raise ethical concerns around misinformation, intellectual property, and fairness. Responsible use requires guardrails, human oversight, and transparency.
