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Tech & Engineering

Updates every hour. Last Updated: 30-Oct-2026 08:17 ET (30-Oct-2026 12:17 GMT/UTC)

AI content moderation takes a lesson from economics #ASA190

Acoustical Society of America
Reports and Proceedings

Large language models may be able to make moderation of social media and online communities more effective, but they are expensive to run at scale, especially when asked to provide explanations for each piece of content they flag. Yuan Zhao will present research on creating an interpretable and low-cost method for evaluating LLMs’ hate speech classification as part of 190th ASA Meeting. His framework relies on the Rational Inattention model, an economic idea developed to explain human behavior.

Meeting: 190th Meeting of the Acoustical Society of America

Consumers willing to pay more for lobster harvested with ropeless technology, UMaine study finds

University of Maine
Peer-Reviewed Publication

A study led by Qiujie “Angie” Zheng from the University of Maine found that consumers are willing to pay an average of $3.42 more for a lobster roll made with lobster harvested using ropeless fishing technology designed to reduce whale entanglement risks when presented with information on animal welfare. Researchers tested how information about whale conservation, animal welfare and Maine’s lobster industry shaped consumer willingness to pay more for lobster harvested using ropeless technology. Messaging focused on whale welfare and entanglement impacts proved most effective at increasing support for ropeless technology, with consumers willing to pay more.

Journal: Marine Resource Economics

AI’s eyes to help with component inspections

DOE/Sandia National Laboratories
Business Announcement

Sandia National Laboratories is incorporating artificial intelligence to help with inspections of ceramic components used in nuclear deterrence applications.

AI models comb patient data to predict cardiac-arrest risk

University of Washington School of Medicine/UW Medicine
Peer-Reviewed Publication

Researchers have developed artificial intelligence (AI) models that can scrutinize electronic health records (EHR) and electrocardiograms to identify individuals in the general population at elevated risk for sudden cardiac arrest — a condition that causes more than 400,000 U.S. deaths annually and has a survival rate of only 10%.

The finding represents a significant advance in predicting a largely unpredictable medical emergency that often strikes people with no known heart disease.

"Using artificial intelligence applications and health records data, the prediction of cardiac arrest in the general population is feasible,” said Dr. Neal Chatterjee, the study’s lead investigator and a cardiologist at the University of Washington School of Medicine.

JACC: Advances, a journal of the American College of Cardiology, published the paper today. Other co-senior authors are from Massachusetts General Hospital and the Broad Institute of MIT and Harvard.

Funder: American Heart Association, European Union, Foundation Leducq

How to build a discovery machine

Washington University in St. Louis
Peer-Reviewed Publication

A new study points to a better way to build discovery machines, thanks to recent research from Shantanu Chakrabartty, the Clifford W. Murphy Professor and vice dean for research in the McKelvey School of Engineering at Washington University in St. Louis.

Aston University and STFC Hartree Center announce strategic partnership to advance neuromorphic computing in the UK

Aston University
Business Announcement

Aston University and the Science and Technology Facilities Council’s (STFC) Hartree Centre are joining forces to accelerate the development, deployment, and industrial adoption of neuromorphic computing across the UK. They have signed an agreement to set up the Aston-Hartree Neuromorphic Centre of Competence at Aston University which will bring together academia, industry, and public sector stakeholders. It will act as a focal point for joint activities, shared expertise, and coordinated engagement across the UK and internationally.

Chang studying predictive resilient chain intelligence

George Mason University
Grant and Award Announcement

Kuo-Chu Chang, Professor, Systems Engineering and Operations Research (SEOR), College of Engineering and Computing (CEC), received funding for the project: “PRECISION: Predictive Resilient Chain Intelligence with Secure Integrated Optimization Networks.”

Funder: AI Fusion, Inc.

Yao to receive NSF CAREER Award

George Mason University
Grant and Award Announcement

Ningshi Yao, Assistant Professor, Electrical and Computer Engineering, College of Engineering and Computing (CEC), is set to receive funding for: “CAREER: A Unified Event-triggered Real-Time Scheduling and Control Co-Design Framework for Networked Safety-critical Control Systems.”

Pathak studying 5G-native batteryless tags for tracking & communication

George Mason University
Grant and Award Announcement

Parth Pathak, Associate Professor, Computer Science, College of Engineering and Computing (CEC), received funding for the project: “From RFIDs to mmIDs: 5G-native Batteryless Tags for Tracking and Communication.”

Funder: Virginia Innovation Partnership Authority