"The thing that’s really important to recognize," Nvidia (NVDA) CEO Jensen Huang recently said, "is that this is the largest infrastructure buildout in human history." His remark about artificial ...

You will be redirected to our submission process. Multi-omics studies now span genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, and spatial and single-cell modalities, ...

This study presents a deep learning model for breast cancer detection, achieving 99.24% accuracy and improving clinical ...

The research introduces a novel memory architecture called MSA (Memory Sparse Attention). Through a combination of the Memory Sparse Attention mechanism, Document-wise RoPE for extreme context ...

A new study reports a ViT-YOLOv8 framework for smoke and fire detection, achieving 98.5% precision and improving early ...

The spatio-temporal evolution of wall-bounded turbulence is characterized by high nonlinearity, multi-scale dynamics, and chaotic nature, making its accurate prediction a significant challenge for ...

Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory costs and time-to-first-token by up to 8x for multi-turn AI applications.

This release is good for developers building long-context applications, real-time reasoning agents, or those seeking to reduce GPU costs in high-volume production environments.

Urban congestion is a big problem in our cities. It leads to commuter delays and economic inefficiency. More tragically, though, it leads to a million deaths annually worldwide. Research appearing in ...

Universal Robots and Scale AI launch the UR AI Trainer at GTC 2026, a leader-follower system that captures force and visual ...

An international research team developed CyberSentry, a software framework using advanced deep learning and optimization techniques to enhance cybersecurity in SCADA systems for power plants and ...