Since ChatGPT's launch in November 2022, Large Language Models (LLMs) have captured the overwhelming attention of the global public. LLMs have exhibited human-like, and in some cases, exceptional performances on a vast spectrum of natural language tasks. Despite various ethical and societal concerns, the world is not reversing this trend..
In the ever-expansive realm of information technology, two powerful catalysts have emerged, fundamentally altering our approach to data processing and analysis: Large Language Models (LLMs) and Graph Databases. While LLMs have showcased remarkable capabilities in understanding and generating natural language, the concerns and criticisms around them have also cast shadows on their applicability in serious business contexts.
Nevertheless, the synergy between LLMs and graphs holds the promise of mitigating the limitations associated with LLMs. By harnessing the explicit and structured representation of relationships provided by graphs, this harmonious integration anticipates a forthcoming era in data processing and problem-solving. In this envisioned future, the inherent strengths of both technologies will collaborate to overcome existing challenges and obstacles.