More information available at the EU Code of Conduct on Data Centres webpage. CompanyN. Data CentresData CentresYear RegisteredAddressA1 Telekom Austria AG1Wien 1Wien 22012Lassallestrasse 9A1020 -

L’agence Whodunit a contribué à l’automne 2023 à la consultation publique portant sur la nouvelle version du RGESN (référentiel général d’éco-conception

L’Arcep publie son enquête annuelle « Pour un numérique soutenable ». Elle intègre désormais des données sur l’empreinte environnementale des fabricants de terminaux et centres de données ainsi que sur la consommation électrique des box et décodeurs.

Choisir un hébergeur web écologique, c’est à minima, un hébergeur qui assure la réduction de ses besoins en électricité, en espace et en climatisation. Mais ce n’est pas tout. Découvrez les clés pour choisir votre hébergeur web.

What is iPhone throttling? Is it happening to you? What can you do about it? These important questions are answered in brief, right here.

Écoconception Date de mise à jour : 13/02/2024 En lançant le projet de refonte de son site https://www.sentinelles-climat.org/ en 2023, […]

We have more than 80 corporate websites in our network; each one has a digital carbon footprint. Find out what we’re doing to reduce the impact of our websites.

L’objectif de cet article est de clarifier comment vous pouvez utiliser les outils que le collectif Green IT met gratuitement à votre disposition.

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As the world becomes increasingly digitalised, data centres and data transmission networks are emerging as an important source of energy demand.

ecoCode est un projet collectif visant à réduire l'impact environnemental des solutions numériques : baisse de la consommation énergétique, inclusivité, accessibilité...

Ecoconception des services numériques

The adventure begins

Overall SaaS spending fell year over year, but shadow IT overspend and app redundancies persisted, Zylo research found.

Si les problèmes publics qui entourent le développement de l’Intelligence Artificielle (IA) font souvent les gros titres (discriminations raciales, surveillance de masse, automatisation des emplois, etc), la conjonction du mouvement critique contre la tech et des activistes du climat pointe, depuis quelques années, de manière plus discrète, les effets néfastes de l’IA sur l'environnement.

In this post, I want to continue building out an incremental model, but rather than focusing on emissions calculations I want to create a model to estimate energy use.

More than 272 million new laptops are manufactured every year, making the IT industry responsible for as much greenhouse gas pollution as the entire airline industry. This equates to the IT industry contributing 2% of global carbon dioxide (CO2) emissions.  Internet usage continues to rise, with more people using mobiles and tablets in their everyday … What Is The Carbon Footprint Of A Laptop? Read More »

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Generative AI (Gen-AI) represents a major growth potential for the digital industry, a new stage in digital transformation through its many applications. Unfortunately, by accelerating the growth of digital technology, Gen-AI is contributing to the significant and multiple environmental damage caused by its sector. The question of the sustainability of IT must include this new technology and its applications, by measuring its environmental impact. To best respond to this challenge, we propose various ways of improving the measurement of Gen-AI's environmental impact. Whether using life-cycle analysis methods or direct measurement experiments, we illustrate our methods by studying Stable Diffusion a Gen-AI image generation available as a service. By calculating the full environmental costs of this Gen-AI service from end to end, we broaden our view of the impact of these technologies. We show that Gen-AI, as a service, generates an impact through the use of numerous user terminals and networks. We also show that decarbonizing the sources of electricity for these services will not be enough to solve the problem of their sustainability, due to their consumption of energy and rare metals. This consumption will inevitably raise the question of feasibility in a world of finite resources. We therefore propose our methodology as a means of measuring the impact of Gen-AI in advance. Such estimates will provide valuable data for discussing the sustainability or otherwise of Gen-AI solutions in a more transparent and comprehensive way. We intend to help this discussion by differentiating in our approach between the embodied and operational impacts of Gen-AI. In this way, we can consider the sustainability of models, as we already do for equipment.

Using Umbraco Delivery API, NextJS's Static Site Generation, and uSync, to create an ultra-low energy Umbraco website