Side-channel attacks, such as Spectre, rely on properties of modern CPUs that permit discovery of microarchitectural state via timing of various operations. The Weird Machine concept is an increasingly popular model for characterization of execution that ...$$$$$$$$

In each issue of Communications, we publish selected posts or excerpts from the many blogs on our website. The views expressed by bloggers are their own and not necessarily held by Communications or the Association for Computing Machinery.

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The cryptography-threatening Shor algorithm for quantum computing sees its greatest theoretical advance in more than 25 years.

In each issue of Communications, we publish selected posts or excerpts from the many blogs on our website. The views expressed by bloggers are their own and not necessarily held by Communications or the Association for Computing Machinery.

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Quantum entanglement provides a new direction in navigation.

As autonomous systems increasingly become part of our lives, it is crucial to foster trust between humans and these systems, to ensure positive outcomes and mitigate harmful ones.

Uniting data-centric perspectives and concepts to trace the foundations of DCAI.

Communications efficiency helps bring photonics to artificial intelligence.

The case for in-memory inferencing of quantized CNNs at the edge.

Examining the implicit bias in training neural networks using gradient-based methods.

Leveraging scalable pointer analysis, value analysis, and dynamic analysis.

Advances in artificial intelligence permit computers to converse with humans in seemingly realistic ways.

Cryptographers seek algorithms quantum computers cannot break.

Ideas for quantum computing change the way we think about space and time.

Combining neural networks with symbolic representations might make them more versatile and dependable.

Despite certain challenges, FPGAs provide security and performance benefits over ASICs.

A deep dive into the quantum Internet's potential to transform and disrupt.

Kernel methods clarify why neural networks generalize so well.

Standardizing computational reuse and portability with the Common Workflow Language.