An efficient neural screening approach rapidly identifies circuit modules governing distinct behavioral transitions in response to pathogen exposure.

The research, titled AI-Driven Hybrid Deep Learning and Swarm Intelligence for Predictive Maintenance of Smart Manufacturing Robots in Industry 4.0 and published in Electronics, introduces an AI ...

As sensor data overwhelms the cloud, Innatera’s neuromorphic chips bring always-on, ultra-low-power AI directly to the edge. But how?

Innovations addressing some of the world’s most pressing challenges took centre stage at the Innovator Meet Tech Exhibition ...

A new study published in Translational Psychiatry has found that post-traumatic stress disorder is associated with ...

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

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

During his more than two decades with Nvidia, Rev Lebaredian has had a ringside seat to the show that has been the evolution of modern AI, from the ...

South Korean researchers have developed a guided-learning framework that accurately predicts PV power without requiring irradiance sensors during operation, using routine meteorological data instead.

A 3D sensor tracks people and objects in large spaces. See how AI compute changes real-time analytics and smart ...

Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...

But this breakthrough doesn't stand alone; recent developments in plastic science and recycling include pyrolysis research to ...