detection

Fraud detection remains a significant challenge in the financial industry, requiring advanced machine learning (ML) techniques to detect fraudulent patterns while maintaining compliance with strict privacy regulations. Traditional ML models often rely on centralized data aggregation, which raises concerns about data security and regulatory constraints. Fraud cost businesses over $485.6Continue Reading

The global fashion industry is estimated to be valued at $1.84 trillion in 2025, accounting for approximately 1.63% of the world’s GDP (Statista, 2025). With such massive amounts of generated capital, so too comes the enormous potential for toxic content and misuse. In the fashion industry, teams are frequently innovatingContinue Reading

This post is co-written with Qing Chen and Mark Sinclair from Radial. Radial is the largest 3PL fulfillment provider, also offering integrated payment, fraud detection, and omnichannel solutions to mid-market and enterprise brands. With over 30 years of industry expertise, Radial tailors its services and solutions to align strategically withContinue Reading

NASA’s James Webb Space Telescope (JWST) utilizes mid-infrared spectroscopy to precisely analyze molecular components such as water vapor and sulfur dioxide in exoplanet atmospheres. The key to this analysis, where each molecule exhibits a unique spectral “fingerprint,” lies in highly sensitive photodetector technology capable of measuring extremely weak light intensities.Continue Reading

Every second counts when it comes to detecting and treating heart attacks. That’s where a new technology from the University of Mississippi comes in to identify heart attacks faster and more accurately than traditional methods. In a study published in Intelligent Systems, Blockchain and Communication Technologies, electrical and computer engineeringContinue Reading

Time series data is a distinct category that incorporates time as a fundamental element in its structure. In a time series, data points are collected sequentially, often at regular intervals, and they typically exhibit certain patterns, such as trends, seasonal variations, or cyclical behaviors. Common examples of time series dataContinue Reading