Publication date: Jul 14, 2023
On the other hand, its easy for knowledge graph users to find and correct the misinformation, should the LLM infer something incorrectly. Thats because knowledge graphs have full transparency. Knowledge graphs and vector databases are the two primary contenders as potential solutions for implementing retrieval augmented generation. Knowledge graphs retrieve and return the exact answer, and nothing more. They help you identify misinformation in data, trace back the pathway of the query, and make corrections to it, which can help improve LLM accuracy. This means it isnt possible to undo it or even understand the source of the error. Enterprises want to infuse Large Language Models (LLMs) into their mission-critical applications.
| Concepts | Keywords |
|---|---|
| Ceo | Answer |
| Graphs | Database |
| Hallucinationsknowledge | Databases |
| Months | Example |
| Neo4js | Graph |
| Graphs | |
| Infer | |
| Limit | |
| Llm | |
| Predefined | |
| Product | |
| Relationships | |
| Return | |
| Team | |
| Vector |