Is Computing a Discipline in Crisis?
One of our professional societies should act as convenor and moderator for a community-wide conversation about the future of AI.
July 2024 - Vol. 67 No. 7
Features
Zero-Knowledge Proofs and Their Role within the Blockchain
An examination of the intricate world of zero-knowledge proofs and how they may be used to enhance blockchain security and privacy.
Many major digital payment systems have known security issues, and present a constant, attractive attack surface for hackers and malicious actors.
The chip industry chases advances in lithography to support the next generation of computing devices.
The Rise of the AI Co-Pilot: Lessons for Design from Aviation and Beyond
Co-pilot is a useful metaphor for describing how AI technology is intended to act in relation to human users.
The BPC Relevance of Common Assessment in the Introductory Sequence
Common assessment is a core institutional change that supports broader participation in computing.
How to Think About Remedies in the Generative AI Copyright Cases
Lawsuits charging developers of generative AI technologies with copyright-related violations are likely to influence legislation about generative AI copyright issues.
Age Verification Systems Will Be a Personal Identifiable Information Nightmare
Online age verification requirements for websites are a disaster for privacy, and pose a cybersecurity risk.
Adopting and Sustaining Microservice-Based Software Development
The microservice approach to software development offers an alternative to the conventional monolith style.
From Open Access to Guarded Trust
Engineers stand at a unique confluence, where the exhilarating promise of innovation meets the sobering responsibility of trust stewardship.
Visualizing Progress in Broadening Participation in Computing: The Value of Context
Standard analysis of a CS degree data does not account for the changing demographics of the undergraduate population.
Security Challenges of Intent-Based Networking
Intent-based networking allows operators to describe the high-level intent of what they want a network to do.
The most popular explainable AI (XAI) approaches offer no guarantees of rigor.
Technical Perspective: Solve for x
Peng and Vempala have pushed through a barrier that has stood for decades. How far will their momentum carry us?
Solving Sparse Linear Systems Faster than Matrix Multiplication
In this paper, we present an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2.
