What is a Large Language Model?
A Large Language Model (LLM) is a type of artificial intelligence trained on massive amounts of text data to understand and generate human language. These models use deep learning architectures (typically transformers) with billions of parameters to capture patterns in language.
How LLMs Work
- Pre-training: Learn language patterns from large text corpora
- Fine-tuning: Adapt to specific tasks or domains
- Inference: Generate responses based on input prompts
- RLHF: Align with human preferences (optional)
Key Characteristics
- Billions of parameters
- Trained on diverse text sources
- Can perform many tasks without task-specific training
- Generate contextually relevant responses
- Exhibit emergent capabilities at scale
Popular LLMs
- GPT-4, GPT-4o (OpenAI)
- Claude (Anthropic)
- Gemini (Google)
- Llama (Meta)
- Mistral
Applications
- Conversational AI and chatbots
- Content generation
- Code assistance
- Translation
- Summarization
- Question answering
- Analysis and reasoning
Limitations
- Can hallucinate (generate false information)
- Knowledge cutoff dates
- Context length limitations
- Computational costs
- Potential for bias