The quiet professionalization of retail trading

The image of the lone, intuitive trader chasing quick profits is gradually giving way to something more disciplined. A ...

Nvidia shrinks LLM memory 20x without changing model weights

Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory ...
InfoQ

QCon London 2026: Ontology‐Driven Observability: Building the E2E Knowledge Graph at Netflix Scale

Silva, both Engineers at Netflix, presented “Ontology‐Driven Observability: Building the E2E Knowledge Graph at Netflix Scale ...

AI model improves flood forecasting with higher accuracy than current methods

New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of ...
Tech Xplore

Hybrid AI model combines graphs and transformers for real-time traffic forecasts

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 ...
IEEE

A Knowledge-Guided Pre-Training Temporal Data Analysis Foundation Model for Urban Computing

Abstract: Temporal data analysis plays a pivotal role in applications such as weather forecasting, traffic flow management, energy consumption monitoring, and other areas of urban computing. In recent ...
IEEE

Leveraging Knowledge Graph and Large Language Model Synergies for Intelligent Fault Analysis in Urban Rail Transit Signaling Systems

Abstract: To address the challenges of insufficient text data utilization and low manual diagnosis efficiency in urban rail transit signaling system fault analysis, particularly the difficulty in ...