The Manila Times

MicroCloud Hologram Inc. Proposes Quantum AI Simulator Adopting Hybrid CPU-FPGA Method, Achieving Efficient Image Classification Simulation Through Heterogeneous Computing

MicroCloud Hologram Inc. (NASDAQ: HOLO), ('HOLO” or the 'Company'), a technology service provider, proposed a quantum AI simulator that adopts a hybrid CPU-FPGA method. This system performs ...
Unite.AI

Why Data Labeling Is Critical to Building Accurate Machine Learning Models

Machine learning models are usually complimented for their intelligence. However, their success mostly hinges on one fundamental aspect: data labeling for machine learning. A model has to get familiar ...
Devdiscourse

AI-driven air quality system promises faster, more reliable urban health warnings

Read more about AI-driven air quality system promises faster, more reliable urban health warnings on Devdiscourse ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
AZoSensors on MSN

Low-power sensor node brings machine learning to the edge of environmental monitoring

A new low-power sensor node framework combines sensing and machine learning, with the potential to enhance real-time environmental monitoring while optimizing energy efficiency.
Rome Sentinel

SRC gets AFRL contract for next-gen AI, machine learning

ROME — SRC, a not-for-profit defense research and development company headquartered in Syracuse with an office in Rome on the Griffiss Business and Technology Park, has been awarded a $24M contract by ...
Hacker

I-Machine Learning for the Birds: Ukwakha I-Our Own Bird Vocalization Classifier

I-Machine Learning for the Birds: Ukwakha I-Our Own Bird Vocalization Classifier nge Picture in the Noise 20 imiz read 2025/06/08 XH ...
IEEE

Hybrid Makes Better: Hybrid Differential Privacy Medical Image Classification Based on Federated Learning

Abstract: Machine learning has the potential to revolutionize medical image classification. However, machine learning requires large medical datasets to improve accuracy, which will compromise patient ...