Articles on cloud carbon emissions, AI sustainability, and green software.
Every company is racing to add AI to its products. Very few can say what it costs the planet. AI inference is the fastest-growing slice of the world's computing footprint, and the worst measured. That gap is becoming a business risk.
UK data centres reportedly consume 10 billion+ litres of water a year, and 84% of proposed sites are in water-stressed areas. The industry has every reason not to count.
Cloud computing powers over 90% of enterprises, but its impact on carbon remains a black box. While standards exist for manufacturing and logistics emissions, methods for calculating the carbon costs of the cloud are so inconsistent that the two most common approaches produce results differing by 50x. With regulators closing in, that ambiguity is becoming a liability.
Global demand for cloud computing, driven in large part by the expansion of AI, is on an ever-increasing upward trajectory. Attempting to mitigate this expansion is the pursuit of the sustainable data center: facilities that can meet the world’s need for on-demand digital services whilst also being highly energy and water efficient, compatible with local environments, and emitting zero carbon.
An overview of the Green Software Foundation's SCI-AI specification and how it standardises carbon measurement for AI and LLM workloads.
Camera Forensics, a digital imaging platform used by crime investigators, wanted to know the carbon impact of the cloud-intensive services. Read their blog to find out how we did it, and what we found.
Data centers are as integral to modern life as running water or electric lights, but we are only just coming to terms with their enormous environmental impacts. If we cannot stop using data centers, how do we mitigate their impacts on the world we have to live in?
Tailpipe has built software for measuring the power draw of GPUs in cloud servers and is delighted to now make that software open source.
By 2030, datacenters are expected to consume 3% of global electricity consumption, driven by the exponential growth in AI usage. As the internet becomes increasingly over-saturated with AI content, we must consider: is the environmental cost worth the output?
How carbon-aware computing shifts workloads to times and places where the electricity grid is cleanest, reducing the carbon footprint of cloud infrastructure.
