Large Language Model
An AI system trained on vast amounts of text data that can understand and generate human language for various applications.
Detailed Definition
A Large Language Model (LLM) is an artificial intelligence system trained on massive text datasets to understand, generate, and work with human language. LLMs power modern AI assistants and document processing tools.
Capabilities: - Natural language understanding - Text generation and summarization - Question answering - Translation and paraphrasing - Code generation - Document analysis
Applications in mining and land management
Document processing: - Extracting information from deeds and legal documents - Summarizing lengthy reports - Answering questions about document contents - Translating technical terminology
Research assistance: - Answering regulatory questions - Explaining complex procedures - Drafting correspondence - Summarizing research findings
Data extraction: - Parsing unstructured text - Identifying entities (names, dates, locations) - Extracting legal descriptions - Converting narrative to structured data
Knowledge management: - Creating searchable documentation - Answering employee questions - Training material development - Procedure documentation
Examples of LLMs: - GPT-4 (OpenAI) - Claude (Anthropic) - Gemini (Google) - LLaMA (Meta)
Considerations: - Accuracy verification required - Privacy and confidentiality - Domain-specific fine-tuning - Integration with existing systems
LLMs are increasingly used to automate document-heavy workflows in title research and land management.
Related Terms
Artificial Intelligence
Computer systems designed to perform tasks that typically require human intelligence, such as pattern recognition and decision-making.
Workflow Automation
The use of technology to automate repetitive business processes, reducing manual effort and improving consistency.
Natural Language Processing
A branch of AI focused on enabling computers to understand, interpret, and generate human language.