The Feb. 26 discussion was held at Steinberg-Dietrich Hall and highlighted AI-related energy and water consumption issues.

The rapid growth of Large Language Models (LLMs) and deep learning has led to rising data center energy demands, expected to top 1,000 TWh by 2026. This paper introduces Eco-Orchestrator, a ...

Researchers in Italy have recently developed a new smart chip that could greatly reduce energy consumption while accelerating computation in high-performance computing systems and data centers.

Smart city systems are increasingly powered by AI operating across networks of Internet of Things (IoT) devices. These systems process vast amounts of data in real time to support applications such as ...

The growth of energy efficiency in traditional computer chips is slowing due to physical limitations, coinciding with a rapid increase in energy demands from the tech sector, especially artificial ...

TL;DR: Research in both biocomputing and neuromorphic computing may hold the key to better computer energy efficiency. By drawing inspiration from nature's own efficient systems, such as the human ...

The AI boom is driving an explosive surge in computational demands and reshaping the landscape of technology, infrastructure, and innovation. One of the biggest barriers to widespread AI deployment ...