Bridging Knowledge and Innovation in AI

This chapter explores the intersection of traditional knowledge graphs with modern language models, emphasizing the evolution of understanding in science and data analysis. It critiques the reliance on computational power over thoughtful problem-solving while addressing the disparity between public excitement and practical challenges in AI. Additionally, it highlights the significant impact of data representations on the development of artificial general intelligence and the philosophical inquiries surrounding language and consciousness.