Researchers isolate memorization from problem-solving in AI neural networks

The researchers discovered that this separation proves remarkably clean. In a preprint paper released in late October, they ...
AHA/ASA Journals

Pragmatic Approaches to the Evaluation and Monitoring of Artificial Intelligence in Health Care: A Science Advisory From the American Heart Association

The rapid development and integration of artificial intelligence (AI), including predictive, generative, and emerging agentic ...
Wastewater Digest

Innovative approaches to sludge management: The role of AI, machine learning, and emerging technologies

Explore how artificial intelligence and digital innovations are transforming sludge dewatering in wastewater systems, ...
Neurology Advisor

Machine Learning Differentiates AD and Behavioral Variant Frontotemporal Dementia

Machine learning models using initial neuropsychological and neuropsychiatric clinical data accurately distinguished AD from bvFTD.
IEEE

MPDA: A Massively Parallel Learning and Dependency-Aware Scheduling Algorithm for Data Processing Clusters

Abstract: In the era of large-scale machine learning, large-scale clusters are extensively used for data processing jobs. However, the state-of-the-art heuristic-based and Deep Reinforcement Learning ...
IEEE

Prediction of Asthma Using Machine Learning Algorithms

Abstract: Asthma, a prevalent chronic respiratory condition, poses significant challenges to public health worldwide. Accurate and early prediction of asthma risk can greatly aid healthcare ...
Frontiers

Predicting food prices in Kenya using machine learning: a hybrid model approach with XGBoost and gradient boosting

Introduction: Food price volatility continues to be a significant concern in Kenya's economic development, posing challenges to the country's economic stability. Methodology: This study examines the ...
Nature

AI discovers learning algorithm that outperforms those designed by humans

An artificial-intelligence algorithm that discovers its own way to learn achieves state-of-the-art performance, including on some tasks it had never encountered before. Joel Lehman is at Lila Sciences ...
Quanta Magazine

The Game Theory of How Algorithms Can Drive Up Prices

Imagine a town with two widget merchants. Customers prefer cheaper widgets, so the merchants must compete to set the lowest price. Unhappy with their meager profits, they meet one night in a ...
The New York Times

Google’s Quantum Computer Makes a Big Technical Leap

Designed to accelerate advances in medicine and other fields, the tech giant’s quantum algorithm runs 13,000 times as fast as software written for a traditional supercomputer. A quantum computer at ...
marktechpost

Weak-for-Strong (W4S): A Novel Reinforcement Learning Algorithm that Trains a weak Meta Agent to Design Agentic Workflows with Stronger LLMs

W4S operates in turns. The state contains task instructions, the current workflow program, and feedback from prior executions. An action has 2 components, an analysis of what to change, and new Python ...