How Graph Technology is Changing AI

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Graph enhancements to Artificial Intelligence and Machine Learning are changing the landscape of intelligent applications. Beyond improving accuracy and modeling speed, graph technologies make building AI solutions more accessible. Join us to hear about 4 areas at the forefront of graph enhanced AI and ML, and find out which techniques are commonly used today and which hold the potential for disrupting industries.

We’ll provide examples and specifically look how: – Graphs provide better accuracy through connected feature extraction – Graphs provide better performance through contextual model optimization – Graphs provide context through knowledge graphs – Graphs add explainability to neural networks


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About Jake Graham

Jake Graham is Neo4j's Lead Product Manager for Artificial Intelligence and Analytics, helping guide development of graph algorithms and machine learning for enterprise analytics applications. Prior to joining Neo4j, he worked as Director of Product Management for Saffron AI: an artificial intelligence platform built on a graph database acquired by Intel in 2015. While there Jake worked on developing and deploying AI solutions with many of the world's largest organizations.

Alicia Frame
About Alicia Frame

Alicia Frame is the Senior Data Scientist on Neo4j's Product team, where she is responsible for algorithm development and analytics strategy. She earned a PhD in computational biology from the University of North Carolina at Chapel Hill and a BS in biology and mathematics from the College of William and Mary in Virginia, and has over 8 years experience in enterprise data science at BenevolentAI, Dow, and the EPA.