Why should I build a knowledge graph?

Knowledge graphs have emerged as a core AI technology in recent years, starting from the Google Knowledge Graph. Now, most major companies, such as Uber and Amazon, implement some form of knowledge graph technology, and numerous start-ups have emerged in this space as well. This talk will speak to what knowledge graphs 'mean', in various communities and corporations, and what kinds of problems can be attacked using knowledge graphs. Ultimately, the talk will present a set of compelling reasons why you should build a knowledge graph for tackling various problems.

Who is this presentation for?
This presentation is for business leaders and technical managers who might be thinking of building and deploying knowledge graphs, but are not completely sure if it's the right fit for their problems.

Prerequisite knowledge:
Some managerial and technical knowledge (especially pertaining to AI) will be useful, though not a prerequisite. There are no technical prerequisites.

What you'll learn?
The talk will help clarify what knowledge graphs are, what value they can add to your business and AI workflows, and ultimately help you be a more effective decision maker with regards to knowledge graph investments.

Dr. Mayank Kejriwal is a research assistant professor at the University of Southern California (USC), and a research lead in the USC Information Sciences Institute's Center on Knowledge Graphs, with a passion for developing real-world AI systems that can be used for cracking formidable socio-technical problems. His research is funded by DARPA and has been applied to important problems such as fighting human trafficking, and mobilizing resources effectively after natural disasters, all using AI-driven predictive analytics. Dr. Kejriwal was nominated as a 2019 Forbes 30 under 30 in the Science category, and is serving as a red judge for the IBM AI XPrize competition.