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New AI system helps scientists understand complex systems that change over time

Duke University engineers are using artificial intelligence to do something scientists have chased for centuries; turn messy, ...
United States Army

Army establishes new AI, machine learning career path for officers

The U.S. Army has established a new career pathway for officers to specialize in artificial intelligence and machine learning (AI/ML), ...

The Human Engine Behind Artificial Intelligence: How Crowdsourcing Is Powering The Next AI Revolution

The rise of the AI gig workforce has driven an important shift from commodity task execution to first-tier crowd contribution ...
PR Newswire

MicroCloud Hologram Inc. Releases Next-Generation Quantum Convolutional Neural Network Multi-Class Classification Technology, Driving Quantum Machine Learning Towards ...

SHENZHEN, China, Nov. 15, 2025 /PRNewswire/ -- MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, has launched a groundbreaking technological ...
Optics

Light-based chip boosts power efficiency of AI tasks 100-fold

Florida researchers develop optoelectronic silicon chip to perform convolution operations for artificial intelligence. Turning light-encoded data into instant convolution results. Artificial ...
EurekAlert!

New light-based chip boosts power efficiency of AI tasks 100 fold

Artificial intelligence (AI) systems are increasingly central to technology, powering everything from facial recognition to language translation. But as AI models grow more complex, they consume vast ...
Scientific Research Publishing

Tan, M. and Le, Q. (2019) EfficientNET: Rethinking Model Scaling for Convolution-al Neural Networks. International Conference on Machine Learning, Long Beach, 9-15 June 2019 ...

ABSTRACT: AI techniques are proving unbeatable in the fight for supremacy in methods of evaluation, optimization, control, object recognition, sensor monitoring, image interpretation, machine learning ...
Frontiers

A novel end-to-end learning framework for inferring lncRNA-disease associations based on convolution neural network

Introduction: In recent years, lots of computational models have been proposed to infer potential lncRNA-disease associations. Methods: In this manuscript, we introduced a novel end-to-end learning ...
IEEE

Reviving Legacy Seismic Data via Machine Learning Technique—Part 1: Expanding 3-D Seismic Survey Coverage With Gated Convolution GAN

Abstract: We propose a novel machine learning-based seismic volume reconstruction method that gradually extrapolates a seed volume by referring to line data external to the seed volume. The proposed ...