EurekAlert!

AI boosts understanding of ocean dynamics and marine structure safety

Fluid–structure interaction (FSI) governs how flowing water and air interact with marine structures—from wind turbines to ...
IEEE

Leveraging Machine Learning Approaches to Decode Hive Sounds for Stress Prediction

Abstract: Beekeeping plays a vital role in preserving ecosystems through pollination and increasing biodiversity. Effective monitoring of honeybee health and hive conditions is essential to balance ...

Google Real-Time Translator: More Than Word-for-Word Translations

Google's real-time translator looks ahead and anticipates what is being said, explains Niklas Blum, Director Product ...
KXAN

Ampace and DG Matrix Announce Strategic Partnership to Deliver First UL-Certified Grid-Active BESS Integrated with Multi-Port Solid-State Transformer Architecture for AI Data ...

RALEIGH, N.C., Dec. 16, 2025 /PRNewswire/ -- Ampace, a global leader in advanced lithium-ion energy storage, today announced a strategic collaboration with DG Matrix to deliver the industry's first UL ...
IEEE

Encoder-Decoder Based Deep Reinforcement Learning for Multi-AUV Assisted Data Collection in UWSNs

Abstract: Reliable and timely data collection poses a significant challenge for underwater wireless sensor networks (UWSNs), primarily due to the extremely low data rate of underwater communication ...

Bolmo’s architecture unlocks efficient byte‑level LM training without sacrificing quality

Ai2 releases Bolmo, a new byte-level language model the company hopes would encourage more enterprises to use byte level ...
VentureBeat

Nvidia debuts Nemotron 3 with hybrid MoE and Mamba-Transformer to drive efficient agentic AI

Nvidia launched the new version of its frontier models, Nemotron 3, by leaning in on a model architecture that the world’s most valuable company said offers more accuracy and reliability for agents.
Frontiers

Robust automated preclinical fMRI preprocessing via a multi-stage dilated convolutional Swin Transformer affine registration

Introduction: Accurate preprocessing of functional magnetic resonance imaging (fMRI) data is crucial for effective analysis in preclinical studies. Key steps such as denoising, skull-stripping, and ...
GitHub

Variational Autoencoder (VAE) for Image Generation

This project implements a Variational Autoencoder (VAE) for image generation. Unlike standard autoencoders, VAE learns a probabilistic latent space by encoding images to a distribution and sampling ...