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Declarative Machine Learning Systems
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.

What Went Wrong?
From Communications of the ACM

What Went Wrong?

Why we need an IT accident investigation board.

Biases in AI Systems
From Communications of the ACM

Biases in AI Systems

A survey for practitioners.

Toward Confidential Cloud Computing
From Communications of the ACM

Toward Confidential Cloud Computing

Extending hardware-enforced cryptographic protection to data while in use.

The History, Status, and Future of FPGAs
From Communications of the ACM

The History, Status, and Future of FPGAs

Hitting a nerve with field-programmable gate arrays.

Is Persistent Memory Persistent?
From Communications of the ACM

Is Persistent Memory Persistent?

A simple and inexpensive test of failure-atomic update mechanisms.

The Best Place to Build a Subway
From Communications of the ACM

The Best Place to Build a Subway

Building projects despite (and because of) existing complex systems.

The Effects of Mixing Machine Learning and Human Judgment
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.

Open Source Firmware
From Communications of the ACM

Open Source Firmware

Step into the world behind the kernel.

DAML
From Communications of the ACM

DAML: The Contract Language of Distributed Ledgers

A discussion between Shaul Kfir and Camille Fournier.

Industry-Scale Knowledge Graphs
From Communications of the ACM

Industry-Scale Knowledge Graphs: Lessons and Challenges

Five diverse technology companies show how it's done.

Research for Practice
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.

Identity by Any Other Name
From Communications of the ACM

Identity by Any Other Name

The complex cacophony of intertwined systems.

Research for Practice: Edge Computing
From Communications of the ACM

Research for Practice: Edge Computing

Scaling resources within multiple administrative domains.

Corp to Cloud: Google's Virtual Desktops
From Communications of the ACM

Corp to Cloud: Google's Virtual Desktops

How Google moved its virtual desktops to the cloud.

Research for Practice
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.

The Mythos of Model Interpretability
From Communications of the ACM

The Mythos of Model Interpretability

In machine learning, the concept of interpretability is both important and slippery.

Workload Frequency Scaling Law
From Communications of the ACM

Workload Frequency Scaling Law: Derivation and Verification

Workload scalability has a cascade relation via the scale factor.

Research for Practice
From Communications of the ACM

Research for Practice: FPGAs in Datacenters

Expert-curated guides to the best of CS research.

Research for Practice: Prediction-Serving Systems
From Communications of the ACM

Research for Practice: Prediction-Serving Systems

What happens when we wish to actually deploy a machine learning model to production?
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