Communications of the ACM
Latest Practice
From Communications of the ACM
FPGAs in Client Compute Hardware
Despite certain challenges, FPGAs provide security and performance benefits over ASICs.
From Communications of the ACM
Interpretable Machine Learning: Moving from Mythos to Diagnostics
A path forward for the ML community to address a stark disconnect.
From Communications of the ACM
Declarative Machine Learning Systems
The future of machine learning will depend on it being in the hands of the rest of us.
From Communications of the ACM
Toward Confidential Cloud Computing
Extending hardware-enforced cryptographic protection to data while in use.
From Communications of the ACM
The History, Status, and Future of FPGAs
Hitting a nerve with field-programmable gate arrays.
From Communications of the ACM
Is Persistent Memory Persistent?
A simple and inexpensive test of failure-atomic update mechanisms.
From Communications of the ACM
The Best Place to Build a Subway
Building projects despite (and because of) existing complex systems.
From Communications of the ACM
The Effects of Mixing Machine Learning and Human Judgment
Collaboration between humans and machines does not necessarily lead to better outcomes.
From Communications of the ACM
DAML: The Contract Language of Distributed Ledgers
A discussion between Shaul Kfir and Camille Fournier.
From Communications of the ACM
Industry-Scale Knowledge Graphs: Lessons and Challenges
Five diverse technology companies show how it's done.
From Communications of the ACM
Research for Practice: Troubling Trends in Machine-Learning Scholarship
Some ML papers suffer from flaws that could mislead the public and stymie future research.
From Communications of the ACM
Identity by Any Other Name
The complex cacophony of intertwined systems.
From Communications of the ACM
Research for Practice: Edge Computing
Scaling resources within multiple administrative domains.
From Communications of the ACM
Corp to Cloud: Google's Virtual Desktops
How Google moved its virtual desktops to the cloud.
From Communications of the ACM
Research for Practice: Knowledge Base Construction in the Machine-Learning Era
Three critical design points: Joint learning, weak supervision, and new representations.
From Communications of the ACM