EVENT POSTPONED — New date to be announced
Energy Efficiency in Artificial Intelligence
EVENT POSTPONED — New date to be announced
Energy Efficiency in Artificial Intelligence
As we use more and more AI, the demand for energy is rising fast, too. Training and running AI models requires enormous computing power — and that means huge amounts of electricity for the datacenters behind them. Reporter Mauro Mereu…
The Netherlands is taking a major step toward energy-efficient computing with a €9 million grant from the NWO Knowledge and Innovation Covenant (KIC) Long-Term Programme, awarded to the ”10X-Factor(y): Towards a Dutch ecosystem for neuromorphic technologies“ project. The project is managed…
Artificial intelligence is undergoing a massive expansion that threatens to overwhelm global energy grids. As large language models grow in size, their thirst for electricity creates a critical tension between technological progress and climate goals. Europe has emerged as a…
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a breakthrough tool called EnergAIzer. This framework predicts the power consumption of AI workloads on processors and accelerators in seconds, replacing traditional simulations that often take hours or days.…
Artificial intelligence is facing an energy crisis. As models grow larger, the electricity required to power data centers is reaching unsustainable levels. Current computing architectures suffer from the ‘Von Neumann bottleneck,’ where the constant movement of data between the processor…
Christian Bachmann from imec emphasizes that energy efficiency is the common thread across AI—from massive data centers to tiny sensors. The goal is the same: do more with less power.
The edge AI market is booming, but deployments stall in "pilot purgatory." Axelera AI's CEO Fabrizio Del Maffeo explains how purpose-built Digital In-Memory Computing architecture eliminates the data bottleneck, making AI deployments at the edge economically viable.
The University of Groningen professor and IMChip founder is developing neuromorphic chips inspired by the human brain that are up to 200 times more energy-efficient than conventional processors. Her message: interdisciplinary collaboration isn't optional—it's essential.
At the launch of TU/e's Casimir Institute, ASML's Head of Research warned that AI's soaring compute demand could soon outpace global energy supply. Innovation and collaboration across chip design, manufacturing, and academia are the only way forward.
Big Tech's promises of "green AI" mask an uncomfortable reality: massive energy demands, growing carbon emissions, and a shifting narrative that sidelines sustainability. Dr. Rianne Riemens unpacks how Silicon Valley is shaping our environmental futures.
As AI drives an explosion in chip demand and data center power use, Professor Hans Hilgenkamp points to neuromorphic computing as part of the solution. The brain runs on just 20 watts - can we build chips that do the same?
With its new Neuromorphic Computing Roadmap, the Netherlands positions itself as a global frontrunner in brain-inspired computing. The roadmap calls for €30 million investment to build shared facilities and accelerate innovation.