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Connecting the Knowledge Ecosystem Founded in 2019 at Columbia University, The Knowledge Graphs Conference is emerging as the premiere source of learning around knowledge graph technologies. We believe knowledge graphs are an underutilized yet essential force for solving complex societal challenges like climate change, democratizing access to knowledge and opportunity, and capturing business value made possible by the AI revolution.
KGC bridges the gap between industry, which is increasingly recognizing the necessity of integrated data, and academia, where semantic technologies have been developing for over twenty years. Our events, education, content, and community efforts facilitate meaningful exchange between diverse groups, and increase awareness, development and adoption of this powerful technology.
Conference – bridging the gap between research and industry
We organize workshops and tutorials to progress a number of Tech4Good themes, targeting objectives such as the United Nations Sustainable Development Goals and the development of a COVID-19 vaccine. At our most recent conference, 530 attendees participated, representing over thirty industries across forty-two countries. Speakers ranged from Bell Labs pioneer John Sowa to Morgan Stanley, AstraZeneca, and leading academics from Europe and USA. A variety of workshops and tutorials were also given, including several on tech4good themes–from the UN SDGs to personal health graphs and fake news.
KGC Vision and Values
Our goal is to build the community and become a leading source of learning around knowledge graphs.
We will achieve this by engaging and convening industry leaders and innovators, across sectors.
We will focus on the diversity of perspectives:
Professional Diversity: Industry practitioners, Business Users, Faculty, Scientists, Students
Gender & Age diversity
We will gather, share and publish content to increase learning.
We will build the community online and in-person through our content, meetups and conferences.
Live stream preview
Dan McCreary | Graph Hardware Is Coming!
In this presentation we will show how current general-purpose CPU hardware fails to deliver high performance graph analytics. We show that by doing a detailed analysis of the actual hardware functionally needed by graph queries (pointer jumping), we can redesign hardware that is optimized for fast graph traversal. We will also show how by combining graph and machine learning that an entire new generation of “sparse matrix” processing will move large enterprise graphs to an entire new level of capabilities. We combine an innovative use of graphics, metaphors and storytelling to help even non-technical staff understand and remember these concepts.
After this session participants will:
Understand the limitations of today’s current hardware for graph analytics
Understand the hardware and software needs of large graph analytics workloads
Understand how hardware can be redesigned for faster performance and lower power consumption
Notes for the program committee
This will not be a sales pitch for any current or future products. This will focus on understanding the concepts required for cost-effective sustainable enterprise-scale knowledge graphs.
Dan McCreary is a Distinguished Engineer working for the Optum Advanced Technology Collaborative (ATC). He has a background in AI, Graph, and NoSQL technologies. In the past, Dan has helped build data strategies for the ATC and other business units of Optum and UHG. He is the co-author of the books “Making Sense of NoSQL” (Manning Publications) and "The State of Healthcare Technologies" (O'Reilly). His personal mission is to help organizations create objective ways to matching business problems with emerging technologies. In the past, Dan worked for Steve Jobs at NeXT Computer and Bell Labs as an integrated circuit designer. In 2018 Dan lead the Optum graph technologies project within the ATC which has resulted in the creation of the world’s largest healthcare graph. Dan continues to lead research on AI, knowledge representation, graph machine learning and graph hardware.
Nikhil M. Deshpande is the Director of AI / HPC Product Development in Data Platforms Group at Intel. He leads several advanced technology incubations and development in High Performance Compute, AI and Security. Nikhil has been invited speaker and panelist at numerous conferences and has 15+ US and international patents He holds M.S. and Ph.D. in Electrical and Computer Engineering from Portland State University. He also has M.S. in Technology Management from Oregon Graduate Institute.
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