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The Amazing Applications of Graph Neural Networks

In this contributed article, editorial consultant Jelani Harper points out that a generous portion of enterprise data is Euclidian and readily vectorized. However, there’s a wealth of non-Euclidian, multidimensionality data serving as the catalyst for astounding machine learning use cases.

Better, Faster Graph Processing

A team from MIT CSAIL has developed a new programming language for graph processing that could help. Dubbed “GraphIt,” the new domain-specific language has been shown to outperform existing frameworks by a factor of nearly 5x while also reducing the lines of code by almost an entire order of magnitude.