Boosting Fuzzer Efficiency: An Information Theoretic Perspective
In this paper, we take the fundamental perspective of fuzzing as a learning process.
Theory
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Technical Perspective: What’s All the Fuss about Fuzzing?
"Boosting Fuzzer Efficiency: An Information Theoretic Perspective," by Marcel Böhme, Valentin J.M. Manès, and Sang Kil Cha, presents a novel twist to fuzzing that is shown to increase the central metric of the number of bugs found.
The barriers to information generation and sharing have plummeted; information consumers can choose among billions of potential sources. This is information at scale.
Generative AI as a New Innovation Platform
Considering the stability and longevity of a potential new foundational technology.
Generating and Exploiting Automated Reasoning Proof Certificates
Moving toward a full suite of proof-producing automated reasoning tools with SMT solvers that can produce full, independently checkable proofs for real-world problems.
Historic Algorithms Help Unlock Shortest-Path Problem Breakthrough
By revisiting key algorithms from computing, a team unlocked hidden efficiency in a long-standing computer science problem.
The Smallness of Large Language Models
There is so much more to language and human beings than large language models can possibly master.
Dilemma of the Artificial Intelligence Regulatory Landscape
Navigating the complex and varying AI regulatory landscape.
Research for Practice: OS Scheduling
Better scheduling policies for modern computing systems.
A Year Embedded in the Crypto-NFT Space
Carlos Baquero investigates cryptocurrencies and non-fungible tokens.
Model Counting Meets Distinct Elements
In this work, we seek to investigate whether bridging the seeming communication gap between two different domains of computer science may pave the way to richer fundamental insights.
Technical Perspective: Tapping the Link between Algorithmic Model Counting and Streaming
"Model Counting Meets Distinct Elements," by A. Pavan et al., gives a surprising connection between model counting and streaming, providing a generic transformation of data stream algorithms for F0 estimation to algorithms for model counting.
Machine Learning: The Road to Artificial Intelligence?
Machine learning, as it is practiced, has little, if anything to do with AI and the more encompassing endeavor that we call Cognitive Science.
Computer-Assisted Proofs Take on Fluid Flow
Researchers use computers to show that equations can "blow up."
For a More Transparent Governance of Open Source
Seeking the best governance models for FOSS projects.
SI and Binary Prefixes: Clearing the Confusion
Considering the emergence of non-standard acceptance of SI prefixes.
The Principles of Data-Centric AI
Uniting data-centric perspectives and concepts to trace the foundations of DCAI.
"Write a 700-word obituary for Vint Cerf." I tried this "prompting" text on a publicly available chatbot. The output? There was a considerable degree of invented but false statements about my life and work.
AI Bias: Challenges and Solutions
Where does bias in artificial intelligence come from; once we find it, how can we reduce or eliminate it?
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