AI framework fuses data and literature to speed high-entropy alloy discovery

High-entropy alloys are promising advanced materials for demanding applications, but discovering useful compositions is difficult and expensive due to the vast number of possible element combinations.
Duke Pratt School of Engineering

Mapping Behavior with Machine Learning

By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.

2026 Data Science Course Created by FAANG+ Data Scientists Focused on Production-Ready Skills in AI and Machine Learning

SANTA CLARA, CA - February 12, 2026 - - Interview Kickstart has launched a new Data Science course designed for working ...
North Penn Now

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
Scientific Research Publishing

A Foundational Protocol for Reproducible Visualization in Multivariate Quantum Data ()

Cristani, C. and Tessera, D. (2026) A Foundational Protocol for Reproducible Visualization in Multivariate Quantum Data. Open Access Library Journal, 13, 1-13. doi: 10.4236/oalib.1114704 .

Sophelio Launches Data Fusion Labeler (dFL) to Accelerate Sensor Data Preparation for Machine Learning

Sophelio Introduces the Data Fusion Labeler (dFL) for Multimodal Time-Series Data - The only labeling and harmonization ...
InfoWorld

AI-augmented data quality engineering

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
EurekAlert!

How can computing for AI and other demands be more energy efficient?

The growth and impact of artificial intelligence are limited by the power and energy that it takes to train machine learning models. So how are researchers working to improve computing efficiency to ...
Open Heart

Bridging machine learning and clinical practice: a multicentre nomogram for 90-day graft failure risk stratification in heart transplantation

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...
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 ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.