Hackaday

Microsoft Uses Plagiarized AI Slop Flowchart To Explain How Git Works

It’s becoming somewhat of a theme that machine-generated content – whether it’s code, text or graphics – keeps pushing people ...
IEEE

Adversarial Machine Learning for Robust and Secure UAV Detection in Consumer Applications

Abstract: This research evaluates a cognitive AI model for unmanned aerial vehicles (UAV) detection using adversarial machine learning (AML) techniques. We test the model using the VisDrone dataset ...

These 4 critical AI vulnerabilities are being exploited faster than defenders can respond

From prompt injection to deepfake fraud, security researchers say several flaws have no known fix. Here's what to know about them.
usace.army.mil

Army establishes new AI, machine learning career path for officers

WASHINGTON – The U.S. Army has established a new career pathway for officers to specialize in artificial intelligence and machine learning (AI/ML), formally designating the 49B AI/ML Officer as an ...
Morningstar

Machine Learning Can Forecast Which Stock Factors Will Outperform

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
The Conversation

AI poses risks to national security, elections and healthcare. Here’s how to reduce them

Member of the ICMAT, AXA-ICMAT Chair in Adversarial Risk Analysis and Member of the Spanish Royal Academy of Sciences, Instituto de Ciencias Matemáticas (ICMAT-CSIC) David Rios Insua has received ...
Scientific Research Publishing

Standen, M., Kim, J. and Szabo, C. (2025) Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning. ACM Computing Surveys, 57, 1-35.

ABSTRACT: To provide quantitative analysis of strategic confrontation game such as cross-border trades like tariff disputes and competitive scenarios like auction bidding, we propose an alternating ...