Systems and Networking
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Human Resources departments are taking advantage of the workforce management capabilities provided by artificial intelligence.
Owning Computing’s Environmental Impact
It is time for the computing community to face up to computing's growing environmental impact—and take responsibility for it.
Wearable mobile machines integrate people and machines to assist the movement-impaired, and amplify the capabilities of industrial and defense workers while protecting them from injury.
How researchers are improving energy storage devices for power generated from renewable sources like solar and wind.
Demand is expected to spike over the next few years, leading to higher prices and international trade issues.
An Interview with William Hugh Murray
A discussion of the rapidly evolving realm of practical cyber security.
Technical Perspective: Borrowing Big Code to Automate Programming Activities
"Predicting Program Properties from 'Big Code'" presents new techniques for leveraging big code to automate two programming activities: selecting understandable names for JavaScript identifiers and generating type annotations for JavaScript variables.
Understanding Database Reconstruction Attacks on Public Data
These attacks on statistical databases are no longer a theoretical danger.
A Hitchhiker’s Guide to the Blockchain Universe
Blockchain remains a mystery, despite its growing acceptance.
The Compositional Architecture of the Internet
A new model for describing the Internet reflects today's reality and the future's needs.
Blogging Birds: Telling Informative Stories About the Lives of Birds from Telemetric Data
The system transforms raw telemetric data into engaging and informative blog texts readily understood by all.
The Seven Tools of Causal Inference, with Reflections on Machine Learning
The kind of causal inference seen in natural human thought can be "algorithmitized" to help produce human-level machine intelligence.
Metamorphic Testing of Driverless Cars
Metamorphic testing can test untestable software, detecting fatal errors in autonomous vehicles' onboard computer systems.
The need for deeply understanding when algorithms work (or not) has never been greater.
Predicting Program Properties from ‘Big Code’
We present a new approach for predicting program properties from large codebases (aka "Big Code").
Guiding Computers, Robots to See and Think
Fei-Fei Li, co-director of Stanford University's Human-Centered AI Institute, wants to create algorithms that can learn the way human babies do.
A Deterministic Parallel Algorithm for Bipartite Perfect Matching
In this article, we give an almost complete derandomization of the Isolation Lemma for perfect matchings in bipartite graphs.
Technical Perspective: Isolating a Matching When Your Coins Go Missing
Whether there exists a deterministic parallel algorithm for bipartite matching remains an outstanding question at the frontiers of our understanding of the role of randomness in computation. The question has been (nearly) recently resolved in "A Deterministic Parallel Algorithm for Bipartite Perfect Matching."
Artificial Intelligence Informs Eating
How deep learning food recognition can take the hassle out of watching what you eat.
Bees With Backpacks: The Next Army of Data Collectors?
Researchers are outfitting insects, natural marvels of engineering that roboticists have been unable to duplicate, with sensors to collect data in the wild.
The Web-based AmpleHarvest.org platform connects home and community gardeners to nearby food pantries, to help individuals in need.
Governance and Oversight Coming to AI and Automation: Independent Audit of AI Systems
Independent Audit of AI Systems is the next evolution of governance for artificial intelligence and automation.
Software-Defined Power Cuts Costs
Hyper-scale datacenters need more efficient control of their electrical use.
Shape the Future of Computing
ACM encourages its members to take a direct hand in shaping the future of the association. There are more ways than ever to get involved.
Get InvolvedCommunications of the ACM (CACM) is now a fully Open Access publication.
By opening CACM to the world, we hope to increase engagement among the broader computer science community and encourage non-members to discover the rich resources ACM has to offer.
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