the Sustainability of AI
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
Position: Neglecting the Sustainability of AI is Fuelling a Global AI Arms Race
arXiv:2502.20016v2 Announce Type: replace Abstract: Sustainability encompasses three key facets: economic, environmental, and social. However, the nascent discourse on sustainable artificial intelligence (AI) predominantly focuses on the environmental sustainability of AI, neglecting the economic and social aspects. Achieving truly sustainable AI necessitates addressing the tension between its environmental sustainability, which emphasises mitigating AI's climate impact, and its social...
Brussels to Big Tech: Embrace sustainable AI or go away
BRUSSELS — The European Union’s energy chief says companies that want to profit off the artificial intelligence boom are welcome in Europe — but only if they demonstrate they are committed to the bloc’s energy, climate and environmental goals. That means supporting renewable and nuclear power sources rather than fossil fuels, and recycling the amounts of excess heat from data centers to heat Europeans’ homes and businesses, EU Energy Commissioner Dan Jørgensen told POLITICO in an...
TSMC’s Monthly Sales Rise 30% Thanks to Sustained AI Chip Demand
The Taiwan Semiconductor Manufacturing Co. (TSMC) factory in the Nanzih district in Kaohsiung, Taiwan. Photographer: An Rong Xu/Bloomberg
How Hyper-Datafication Impacts the Sustainability Costs in Frontier AI
arXiv:2602.00056v4 Announce Type: replace Abstract: Large-scale data has fuelled the success of frontier artificial intelligence (AI) models over the past decade. This expansion has relied on sustained efforts by large technology corporations to aggregate and curate internet-scale datasets. In this work, we examine the environmental, social, and economic costs of large-scale data in AI through a sustainability lens.
Position: Sustainable Open-Source AI Requires Tracking the Cumulative Footprint of Derivatives
arXiv:2601.21632v4 Announce Type: replace Abstract: Open-source AI is scaling rapidly, and model hubs now host millions of artifacts. Each foundation model can spawn large numbers of fine-tunes, adapters, quantizations, merges, and forks. We take the position that compute efficiency alone is insufficient for sustainability in open-source AI.
Beyond Nvidia: how US export curbs are forcing China to redesign its AI chip industry
Under the weight of sustained US export controls on advanced semiconductors, China’s AI chipmakers are battling to forge a self-reliant silicon ecosystem capable of breaking Nvidia’s stranglehold on the market. At the centre of this rivalry is a fundamental design debate: Should the country rely on the versatile graphics processing unit (GPU) or pivot to the highly specialised application-specific integrated circuit (ASIC)? The fight is no longer about finding a single Nvidia clone; it is...
Sustainability and Artificial Intelligence: Necessary, Challenging, and Promising Intersections
Announce Type: new Abstract: Both digital economy and digital technology researchers increasingly recognize the need to better address the role that artificial intelligence (AI) plays in shaping the evolution of the environmental, social and governance aspects of development. It appears that sustainability and AI research converge on the features of wicked problems that are complex, interconnected and dynamic. Building off such convergence, this article aims to map out the necessary,...
Plateau That Never Comes: When Efficiency Claims in Datacenters and AI Become Greenwashing
Announce Type: new Abstract: Datacenter expansion under generative AI is increasingly framed as compatible with sustainability because of efficiency gains, cleaner electricity procurement, and improved facility design. Yet these claims often do not show that absolute electricity, water, material, waste, and community-facing burdens are falling. This Perspective addresses that evidentiary gap.
BeGREEN Intelligent Plane for AI-driven Energy Efficient O-RAN management
Announce Type: new Abstract: Cellular networks are undergoing a revolutionary transform with the advent of O-RAN architectures and AI/ML solutions. O-RAN's Non-Real-Time and Near-Real Time RAN Intelligent Controllers open the door to the implementation of automated control-loops that can provide RAN optimisations in numerous scenarios and use cases, and which can be further empowered by AI-driven approaches. Energetic sustainability has raised as one of the main optimisations targets due to...