LLMs in action: Strategies for crafting solutions
By Dr. Karthika Vijayan, Shruti Dhavalikar
October 18, 2024
Summary- While LLMs can be trained for various domains, they may still require domain-specific data to overcome generic generalization strategies.
- Effective solutions with LLMs rely on understanding ontology and entity definitions, enabling the capture of specific entities and properties.
- Data annotation and enrichment are crucial steps in making LLMs more generic, but these processes require significant effort and resources.
- The importance of domain knowledge is highlighted when training LLMs with a specific objective, necessitating the narrowing down of knowledge graphs for accurate answers.
Generated using GPT-4o-mini.
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