Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

Google also developed its own generative AI model called Gemini, which is capable of writing emails in Gmail, summarizing ...

As we approach the AI Impact Summit 2026, global AI exosystems are undergoing a brutal yet necessary recalibration. Those calibrations are driven by t.

Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...

In 2025 Artprice successfully integrated all the key tools of its proprietary AI (Intuitive Artmarket®) into its internal ...

No gradients. No GPUs. Discover how Hamiltonian neural networks use logic and low-precision computing to challenge deep learning’s dominance.

Microgrids play a growing role in modern power systems, supporting renewable integration, local resilience, and decentralized ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

Examine the AI and computer science courses offered by Tsinghua University in 2026. Learn why Tsinghua is the top university ...

Abstract: Mobile network traffic prediction is critical for efficient network management in 5G and future 6G systems. Federated Learning (FL) enables multiple base stations (BSs) to collaboratively ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...