Connecting the Dots with Knowledge Graphs — Opening Statement

Posted August 10, 2022 | Technology | Amplify
Connecting the Dots with Knowledge Graphs
The increasing realization that deep learning alone cannot be the solution to build robust, reliable artificial intelligence (AI) systems, coupled with the ever-increasing need to make use of heterogeneous data sources for decision making, has led to a recent resurgence of knowledge graphs (KGs). KGs are now playing a seminal role in the emergent field of neuro-symbolic AI, which aims to integrate domain knowledge into AI systems. By combining AI’s statistical/machine learning (ML) side with KGs, we get more effective, more explainable cognitive results and begin creating logic-based systems that get better with each application. In other words, we can build the next generation of AI models, ones that support better human-machine collaboration.
About The Author
Michael Eiden
Michael Eiden is a Cutter Expert, Partner and Global Head of AI & ML at Arthur D. Little (ADL), and a member of the ADL’s AMP open consulting network. Dr. Eiden is an expert in machine learning (ML) and artificial intelligence (AI) with more than 15 years’ experience across different industrial sectors. He has designed, implemented, and productionized ML/AI solutions for applications in medical diagnostics, pharma, biodefense, and consumer… Read More
Don’t have a login? Make one! It’s free and gives you access to all Cutter research.