The Lean Data Scientist: Recent Advances Toward Overcoming the Data Bottleneck
A taxonomy of the methods used to obtain quality datasets enhances existing resources.
Software Engineering and Programming Languages
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Proving Data-Poisoning Robustness in Decision Trees
We present a sound verification technique based on abstract interpretation and implement it in a tool called Antidote, which abstractly trains decision trees for an intractably large space of possible poisoned datasets.
Koby Mike and Orit Hazzan consider why multiple definitions are needed to pin down data science.
Computational Linguistics Finds Its Voice
Advances in artificial intelligence permit computers to converse with humans in seemingly realistic ways.
Can AI Demonstrate Creativity?
When fed a sufficient amount of training data, artificial intelligence techniques can be used to generate new ideas in several different ways. Is that creativity?
Building Machine Learning Models Like Open Source Software
Proposing a community-based system for model development.
Software Engineering of Machine Learning Systems
Seeking to make machine learning more dependable.
Extracting the Essential Simplicity of the Internet
Looking past inessential complexities to explain the Internet's simple yet daring design.
Technical Perspective: Beautiful Symbolic Abstractions for Safe and Secure Machine Learning
"Proving Data-Poisoning Robustness in Decision Trees," by Samuel Drews et al., addresses the challenge of processing an intractably large set of trained models when enumeration is infeasible in a clean, beautiful, and elegant manner.
Small-scale CAD/CAM tools are among the high-tech capabilities being added to the arsenals of increasingly digital dentists.
Inorganic Growth In Tech: Getting Shredded with Acquisitions
Acquisitions happen quite often in the tech industry and are far more complicated to pull off successfully than popping a pill.
ACE: Toward Application-Centric, Edge-Cloud, Collaborative Intelligence
Constructing a unified platform for the scalable, reliable, robust, and efficient development and deployment of ECCI applications.
Democratizing Domain-Specific Computing
Creating a programming environment and compilation flow that empowers programmers to create their own DSAs efficiently and affordably on FPGAs.
A Linearizability-based Hierarchy for Concurrent Specifications
Two linearizability-style correctness conditions that can be used to argue safety properties of progressively more concurrent behaviors of objects.
From Quantum Computing to Quantum Communications
Attempting to disentangle mechanical principles.
Are Software Updates Useless against Advanced Persistent Threats?
Considering the conundrum of software updates.
The end of classical computer science is coming, and most of us are dinosaurs waiting for the meteor to hit.
The AI Ethicist’s Dirty Hands Problem
Attempting to balance sometimes-conflicting interests.
Research for Practice: Crash Consistency
Keeping data safe in the presence of crashes is a fundamental problem.
What Do ChatGPT and AI-based Automatic Program Generation Mean for the Future of Software
ChatGPT is game-changing, the kind of thing that you witness once in a generation.
On the Evolution of Languages: Natural, Mathematical, and Computational
Comparing the evolution of natural languages, which are used by people all over the world, with two artificial languages: the language of mathematics and programing languages.
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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