These Tools Say They Can Spot A.I. Fakes. Do They Really Work?

Artificial intelligence detectors are increasingly used to check the veracity of content online. We ran more than 1,000 tests ...
The New York Times

Students Are Skipping the Hardest Part of Growing Up

Mr. Shirky, a vice provost at New York University, has been helping faculty members and students adapt to digital tools since 2015. Back in 2023, when ChatGPT was still new, a professor friend had a ...
IEEE

Towards Opcode-Based Smart Contract Reentrancy Vulnerability Detection Using Explainable Deep Learning

Abstract: The rapid growth in blockchain technology adoption has highlighted the significance of security in Ethereum smart contracts. Due to its immutable nature, post-deployment rectification is not ...
blockchain

Google DeepMind Launches CodeMender AI Agent Using Gemini Deep Think for Automated Software Vulnerability Patching

According to Google DeepMind, the company has introduced CodeMender, a new AI agent that leverages Gemini Deep Think to automatically detect and patch critical software vulnerabilities. This ...
IEEE

A Detailed Study of Vulnerability Detection using Common Vulnerabilities and Exposures from NVD using Machine Learning and Deep Learning Models

Abstract: In the recent era, usage and demand of software devices are growing rapidly. Due to cause this, chances of cyberattacks and the vulnerability is also growing at the rapid rate. Therefore, ...
Frontiers

Deep learning-based object detection for environmental monitoring using big data

The combination of deep learning-based object detection and big data has enabled a wide range of applications in environmental monitoring, addressing critical issues such as climate change, ...
Dark Reading

Vulnerability Detection Tops Agentic AI at RSAC's Startup Competition

Vulnerability startup Project Discovery won Innovation Sandbox 2025, the RSAC Conference's Shark Tank-like competition. Though perhaps the bigger story was agentic artificial intelligence (AI). This ...
Scientific Research Publishing

Chen, Y.Z., Ding, Z.J., Alowain, L., Chen, X.Y. and Wagner, D. (2023) DiverseVul: A New Vulnerable Source Code Dataset for Deep Learning-Based Vulnerability Detection.

ABSTRACT: Security vulnerabilities are a widespread and costly aspect of software engineering. Although tools exist to detect these vulnerabilities, non-machine learning techniques are often rigid and ...