Definition #
A type of artificial intelligence model trained on massive datasets to understand, generate, and manipulate human language. LLMs use deep learning architectures like transformers to predict text sequences.
Key Characteristics #
- Trained on terabytes of text data
- Uses transformer neural networks
- Generates coherent paragraphs or code
- Fine-tuned for specific tasks (e.g., translation)
Why It Matters #
Powers tools like ChatGPT and GitHub Copilot. Used by 83% of enterprises for content creation (Gartner 2023).
Common Use Cases #
- Chatbots and virtual assistants
- Code generation and debugging
- Document summarization
Examples #
- GPT-4 (OpenAI)
- PaLM 2 (Google)
- LLaMA 2 (Meta)
FAQs #
Q: How do LLMs differ from regular chatbots?
A: LLMs understand context and generate original text, while rule-based chatbots follow predefined scripts.
Q: Can LLMs replace human writers?
A: No—they assist with drafts and ideation but lack human creativity/ethics judgment.