From Concept to Cathode: Nuton’s Partner-First Model to Close the Copper Gap

Nuton’s CEO Adam Burley lays out a partner-first, modular path to closing the copper supply gap for the energy transition—combining award-winning bioleaching with a scalable delivery model that cuts ...

Autism-friendly baseball team sparks overwhelming community support

Community support has been overwhelming. Local high schools, parents, and volunteers have rallied around the project, with ...

The MLB playoffs put managers in the spotlight. Should they rely on data or intuition?

Analytics in baseball presents an easy debate during the MLB playoffs: data vs. gut feel. But the two aren't at odds with ...

Regional ocean dynamics can be better emulated with AI models

The Gulf of Mexico, a regional ocean, is hugged by the southeastern United States and a large stretch of the Mexican coast, ...
Medical Xpress

Deep learning model estimates cancer risk of lung nodules

An artificial intelligence (AI) deep learning tool that estimates the malignancy risk of lung nodules achieved high cancer detection rates while significantly reducing false-positive results. Results ...
eLife

Comprehensive Neural Representations of Naturalistic Stimuli through Multimodal Deep Learning

This study presents a valuable application of a video-text alignment deep neural network model to improve neural encoding of naturalistic stimuli in fMRI. The authors found that models based on ...
Frontiers

Construction of a deep - learning - based rehabilitation prediction model for lower-limb motor dysfunction after stroke using synchronous EEG-EMG and fMRI

Objective: Construct a predictive model for rehabilitation outcomes in ischemic stroke patients 3 months post-stroke using resting state functional magnetic resonance imaging (fMRI) images, as well as ...
IEEE

An Optimal Scheduling Framework for Integrated Energy Systems Using Deep Reinforcement Learning and Deep Learning Prediction Models

Abstract: Model-free deep reinforcement learning has emerged as a promising method for addressing the scheduling challenges in integrated energy systems. However, uncertainty in system states ...
IEEE

Deep-BrownConrady: Prediction of Camera Calibration and Distortion Parameters Using Deep Learning and Synthetic Data

Abstract: This research addresses the challenge of camera calibration and distortion parameter prediction from a single image using deep learning models. The main contributions of this work are: (1) ...
Phys.org

Using geometry and physics to explain feature learning in deep neural networks

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...
TechCrunch

Google rolls out Gemini Deep Think AI, a reasoning model that tests multiple ideas in parallel

Google DeepMind is rolling out Gemini 2.5 Deep Think, which, the company says, is its most advanced AI reasoning model, able to answer questions by exploring and considering multiple ideas ...