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
Diamonds with certain optically active defects can be used as highly sensitive sensors or qubits for quantum computers, where the quantum information is stored in the electron spin state of these colour centres. However, the spin states have to be read out optically, which is often experimentally complex. Now, aContinue 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
A research team at Tohoku University’s Advanced Institute for Materials Research (WPI-AIMR) has developed a new technique to rapidly and accurately determine the charge state of electrons confined in semiconductor quantum dots — fundamental components of quantum computing systems. The method is based on Bayesian inference, a statistical framework thatContinue Reading
A team of physicists at the University of Cambridge has unveiled a breakthrough in quantum sensing by demonstrating the use of spin defects in Hexagonal Boron Nitride (hBN) as powerful, room-temperature sensors capable of detecting vectorial magnetic field at the nanoscale. The findings, published in Nature Communications, mark a significantContinue Reading
In this post, we walk you through the process to build an automated mechanism using Amazon SageMaker to process your log data, run training iterations over it to obtain the best-performing anomaly detection model, and register it with the Amazon SageMaker Model Registry for your customers to use it. Log-basedContinue 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
Implementing hardware resiliency in your training infrastructure is crucial to mitigating risks and enabling uninterrupted model training. By implementing features such as proactive health monitoring and automated recovery mechanisms, organizations can create a fault-tolerant environment capable of handling hardware failures or other issues without compromising the integrity of the trainingContinue Reading
As digital commerce expands, fraud detection has become critical in protecting businesses and consumers engaging in online transactions. Implementing machine learning (ML) algorithms enables real-time analysis of high-volume transactional data to rapidly identify fraudulent activity. This advanced capability helps mitigate financial risks and safeguard customer privacy within expanding digital markets.Continue Reading
