Graphs at Scale with Ray for AI in Manufacturing

Explore the application of graph technologies and Ray for AI in manufacturing in this 33-minute talk from Anyscale. Discover how graph models provide optimal representation for manufacturing data, including bill of materials, product information, supplier networks, production planning, and customer data. Learn about the transformation of the graph space, including advancements in graph neural networks, GPU-augmented visualizations, and large-scale algorithm applications. Examine the integration of various graph technologies through the open-source 'kglab' project and its adoption by major manufacturing firms. Investigate the use of Ray for scaling graph computations to billion-node levels in industrial applications. Analyze critical bottlenecks in AI for manufacturing and how Ray addresses them, particularly in data preparation and graph algorithm execution at scale. Consider the advantages of using Ray on Kubernetes for managing large graphs in secure enterprise environments, as an alternative to costly graph database solutions.