Part 1 Foundations of hybrid intelligent systems
The convergence of knowledge graphs (KGs) and large language models (LLMs) marks a pivotal moment in the development of intelligent systems. This part of the book lays the foundation for understanding how these complementary technologies can work together to create more powerful and effective solutions.
The integration of these technologies addresses the key limitations of each approach while amplifying their strengths. KGs provide the explicit, verifiable, and updatable knowledge representation that LLMs often lack; and LLMs offer the natural language understanding and generation capabilities that make complex knowledge structures more accessible. This synergy enables the development of intelligent systems that can
- Handle both structured and unstructured data effectively
- Combine multiple types of reasoning strategies
- Provide explainable and verifiable results
- Continuously update their knowledge base
- Interact naturally with users while maintaining accuracy and reliability
Chapter 1 introduces the powerful combination of KGs and LLMs, establishing their complementary nature and illustrating how they can enhance each other's capabilities through concrete examples and use cases. It sets the stage for understanding the transformative potential of this hybrid approach.