How To Prepare For AI’s Unprecedented Network Demands

Before jumping into the AI deep end, it’s vital to take the time to understand how your infrastructure really fits together.
Open Knowledge Repository - World Bank

Maldives: Decision Support for Coral Reef and Climate Resilience Using Bayesian Networks

The coral reef ecosystems of the Maldives are critical to the nation’s ecological integrity, economic development, and ...
Unite.AI

Why AI Inference, Not Training, is the Next Great Engineering Challenge

For the past decade, the spotlight in artificial intelligence has been monopolized by training. The breakthroughs have largely come from massive compute clusters, trillion-parameter models, and the ...
IEEE

High-Confidence Classification of Partial Discharge Acoustic Signals Using Bayesian Networks for Uncertainty Quantification

Abstract: Acoustic emission (AE) detection is a nonintrusive technique for monitoring transformer conditions by capturing emissions from partial discharges (PDs), hotspots, and noise. Machine learning ...
IEEE

Deep Neural Network Inference Partitioning in Embedded Hybrid Analog-Digital Systems

Abstract: Deep Neural Networks (DNNs) deployed in resource-constrained embedded systems, like automotive platforms, often face severe “memory wall” problems and energy-consuming data movements. To ...
Frontiers

AI Applications for Causal Inference in Microbiome Research: Moving Beyond Correlation.

Recent advances in microbiome science have revealed extensive associations between microbial communities and host health; however, the causal mechanisms ...