The Prompt Engineering Cheat Sheet: How to Write Better AI Prompts

Learn prompt engineering with this practical cheat sheet that covers frameworks, techniques, and tips for producing more ...

Machine learning offers faster, more reliable analysis of Fermi surfaces in search of spintronic materials

The search for next-generation electronic materials often starts with studying the Fermi surface, which serves as a map of a ...

Machine learning predicts asthma risk in children with early-life atopic dermatitis

Machine learning models can predict the risk for developing moderate-to-severe persistent asthma and allergic rhinitis in ...

How indirect prompt injection attacks on AI work - and 6 ways to shut them down

Cybercriminals are tricking AI into leaking your data, executing code, and sending you to malicious sites. Here's how.
eLife

Revealing global stoichiometry conservation architecture in cells from Raman spectral patterns

Conservation levels of gene expression abundance ratios are globally coordinated in cells, and cellular state changes under such biologically relevant stoichiometric constraints are readable as ...
Santa Clara University

HPC Machine Learning Tutorial

This tutorial is an adaptation of the NumPy Tutorial from Tensorflow.org. To run this tutorial, I assume you already have access to the WAVE HPC with a user account and the ability to open a terminal ...
Automation World

AI-Driven Motion Control: How Machine Learning Optimizes Motors, Reduces Downtime and Cuts Energy Costs

AI can be added to legacy motion control systems in three phases with minimal disruption: data collection via edge gateways, non-interfering anomaly detection and supervisory control integration.
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
IEEE

Machine-Learning-Based Urban Path Loss Prediction at 900 MHz: Principal Component Analysis, Clustering, Feature Importance and Regression

Abstract: In this work, the possibility of applying machine learning (ML) techniques to analyze and predict radio wave propagation losses in urban environments is explored. Thus, from a measurement ...
IEEE

A Comparative Study of Machine Learning Models for Cardiovascular Risk Prediction Using PCA-Transformed Framingham Data

Abstract: Cardiovascular disease (CVD) remains the leading cause of mortality globally, highlighting the urgent need for effective early detection systems. Supervised machine learning algorithms, such ...
Law

Training Alone Is Not Enough: Lessons From 'Recentive' and USPTO AI Examples on Patent Eligible Machine-Learning Claims

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...