Keyur Faldu

The recent advances in artificial intelligence are mainly attributed to deep learning models, which are intrinsically data-hungry and compute-hungry. Moreover, such deep learning models also suffer from black-box-ness, vulnerable understanding and reasoning ability, and intrinsic bias. All these factors limit its domain application. Explicit knowledge represented in knowledge graphs has a lot to offer. It could potentially drive the next surge in AI by addressing all of the above concerns. Let us brainstorm "Role of Knowledge Graphs in AI" with the education domain case study researched and developed at Embibe.