The development of Knowledge Graphs (KG) is closely linked to the advancements in Artificial Intelligence (AI) agents. Starting from their static origins, knowledge graphs have evolved to include dynamic, temporal, and event-driven paradigms, each unlocking new capabilities for AI systems. This article explores their evolution and how Large Language Models (LLM) integrate into these advancements. … Read more
Reprinted with permission from AI TIME Discussion Author: Liu Zhiyuan Editor: Gege “Language is like amber, preserving many precious and wonderful thoughts safely inside.” Since the dawn of humanity, natural language has carried the wisdom of generations, accumulating endless knowledge. This rich treasure of knowledge has attracted many curious AI researchers to cultivate, explore, and … Read more
This article is an excerpt from Chapter 3 of Teacher Nick’s “A Brief History of Artificial Intelligence”: From Expert Systems to Knowledge Graphs. It provides a comprehensive review and in-depth commentary on the development of knowledge graphs, from the first expert system DENDRAL to the semantic web and Google’s open-source knowledge graph. Nick once worked … Read more
Introduction Many product managers and engineers familiar with RAG often complain, “It only takes a week to produce a demo with RAG, but it takes at least six months to reach a production-level standard!” This is a realistic issue for the current industrial implementation of RAG. The RAG framework is very simple and understandable, and … Read more