Quesma Releases OTelBench: Independent Benchmark Reveals Frontier LLMs Struggle with Real-World SRE Tasks

New benchmark shows top LLMs achieve only 29% pass rate on OpenTelemetry instrumentation, exposing the gap between ...
GitHub

Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection

07.2025: Dinomaly has been integrated in Intel open-edge Anomalib in v2.1.0. Great thanks to the contributors for the nice reproduction and integration. Anomalib is a comprehensive library for ...
Visual Studio Magazine

Microsoft Expands Quantum Development Kit with New Open-Source Tools, VS Code Integration

Microsoft released new open‑source quantum development tools that deepen VS Code and Copilot integration while targeting real ...
IEEE

Detectability Driven Recommendation of Anomaly Detection Models for Time-Series Data

Abstract: Anomaly detection for time-series data has been viewed widely in many practical applications and caused lots of research interests. A popular solution based on deep learning techniques is ...
IEEE

Anomaly Detection Model in Network Security Situational Awareness Based on Machine Learning: Limitation, Techniques, and Future Trends

Abstract: This study focuses on the anomaly detection problem in Network Security Situational Awareness (NSSA). We systematically review traditional approaches and recent advancements based on Machine ...
InfoWorld

PythoC: A new way to generate C code from Python

PythoC lets you use Python as a C code generator, but with more features and flexibility than Cython provides. Here’s a first look at the new C code generator for Python. Python and C share more than ...
Hackaday

Simple Tricks To Make Your Python Code Faster

Python has become one of the most popular programming languages out there, particularly for beginners and those new to the hacker/maker world. Unfortunately, while it’s easy to get something up and ...
Futurism

Malware Is Now Using AI to Rewrite Its Own Code to Avoid Detection

Researchers at Google’s Threat Intelligence Group (GTIG) have discovered that hackers are creating malware that can harness the power of large language models (LLMs) to rewrite itself on the fly. An ...
Hacker

An Overview of Log-Based Anomaly Detection Techniques

5.1 RQ1: How does our proposed anomaly detection model perform compared to the baselines? 5.2 RQ2: How much does the sequential and temporal information within log sequences affect anomaly detection?
Frontiers

Anomaly detection in netflow traffic: workflow for dataset preparation and analysis

Information and communication technology (ICT) is crucial for maintaining efficient communications, enhancing processes, and enabling digital transformation. As ICT becomes increasingly significant in ...
Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...