Knowledge Graphs 2.0: High Performance Computing Emerges - insideBIGDATA

They're the most effective means of preparing data for statistical AI, creditable knowledge graph platforms utilize supervised and unsupervised learning to accelerate numerous processes, and their smart inferences are a form of machine intelligence. Coupling knowledge graphs with high performance computing enables organizations to not only avail themselves of sophisticated techniques to optimize AI, but also employ it at the scale and speed of contemporary data demands. According to Katana Graph CEO Keshav Pingali, "There is a need for high performance graph computing…in two ways. One is the volume of data, and the other is time to insight." Scaling knowledge graphs with high performance computing is a means of rapidly analyzing the tremendous data quantities organizations routinely contend with for informed, low latent action across numerous use cases including "intrusion detection, fraud detection, and Anti-Money Laundering," Pingali noted.