Knowledge Graphs

Vol. 17 No. 2 – March-April 2019

Knowledge Graphs

Overly Attached

Know when to let go of emotional attachment to your work.

A smart, senior engineer couldn't make logical decisions if it meant deprecating the system he and his team had worked on for a number of years. Even though the best thing would have been to help another team create the replacement system, they didn't want to entertain the idea because it would mean putting an end to something they had invested so much in. It is good to have strong ownership, but what happens when you get too attached?

by Kate Matsudaira

GAN Dissection and Datacenter RPCs

Visualizing and understanding generative adversarial networks; datacenter RPCs can be general and fast.

Image generation using GANs (generative adversarial networks) has made astonishing progress over the past few years. While staring in wonder at some of the incredible images, it's natural to ask how such feats are possible. "GAN Dissection: Visualizing and Understanding Generative Adversarial Networks" gives us a look under the hood to see what kinds of things are being learned by GAN units, and how manipulating those units can affect the generated images. February saw the 16th edition of the Usenix Symposium on Networked Systems Design and Implementation. Kalia et al. blew me away with their work on fast RPCs (remote procedure calls) in the datacenter. Through a carefully considered design, they show that RPC performance with commodity CPUs and standard lossy Ethernet can be competitive with specialized systems based on FPGAs (field-programmable gate arrays), programmable switches, and RDMA (remote direct memory access). It's a fabulous reminder to ensure we're making the most of what we already have before leaping to more expensive solutions.

by Adrian Colyer

Industry-scale Knowledge Graphs: Lessons and Challenges

Five diverse technology companies show how it's done

This article looks at the knowledge graphs of five diverse tech companies, comparing the similarities and differences in their respective experiences of building and using the graphs, and discussing the challenges that all knowledge-driven enterprises face today. The collection of knowledge graphs discussed here covers the breadth of applications, from search, to product descriptions, to social networks.

by Natasha Noy, Yuqing Gao, Anshu Jain, Anant Narayanan, Alan Patterson, Jamie Taylor