In case anyone wants to improve/change/use it:
SUSTAINABILITY
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WordPress categories covering AI topics
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Web designers after reading this: https://t.co/yONuEtjT8L pic.twitter.com/p3y16ldruL
— Charly Wargnier (@DataChaz) 27 mai 2026Web designers after reading this:
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Jancovici criticized for his call to limit AI
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« Si on développe trop l'IA, on n'aura pas assez d'électricité pour le reste. Il faut limiter fortement le développement des data centers », affirme Jean-Marc Jancovici sur RTL. Ahurissant !
— Rafik Smati (@RafikSmati) 26 mai 2026
Cette sortie résume à elle seule le mal qui condamne la France : face à un défi, notre… pic.twitter.com/gRLi6ut3q9“If we develop AI too much, we won’t have enough electricity for the rest. We must strongly limit the development of data centers,” says Jean-Marc Jancovici on RTL. Astounding! This statement alone sums up the ailment that condemns France: faced with a challenge, our —
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Request for publication of GPT-4 architecture to clarify water estimates
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Given the scale of water estimates for the "bottle of water per generated email" that come from assumptions about GPT-4's architecture, it would be greatly in the interest of @OpenAI to publish the architecture of this now-retired, three-year-old model.
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AI hype compared to sustainability hype, ways to fix it
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Companies are hyping #AI the same way they talked up #Sustainability, but there are ways to fix that
by Suvrat Dhanorkar @ConversationUS Learn more: https://
buff.ly/gPLsvZR #ArtificialIntelligence #MachineLearning #ML -
AI to solve environmental challenges for children’s future
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This is the way AI to solve environmental challenges and ensure a safe and prosperous future for our children. Congratulations and thanks @cusp_ai team
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RDUs deliver high tokens per kilowatt-hour for AI inference
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AI infrastructure doesn’t have to mean massive power draw.
— SambaNova (@SambaNovaAI) 22 mai 2026
Our RDUs deliver the highest tokens per kilowatt-hour, helping reduce deployments with ~10kW average power consumption.
More inference. Less energy. 🦾
Learn more: https://t.co/v6jPztJPFp pic.twitter.com/dUM5bB3T5kAI infrastructure doesn’t have to mean massive power draw. Our RDUs deliver the highest tokens per kilowatt-hour, helping reduce deployments with ~10kW average power consumption. More inference. Less energy. Learn more: https://
sambanova.ai/products/rdu-a
i-chips?utm_source=x&utm_medium=organic
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AI promises: cure all diseases, automate research, eliminate boring work, personal doctor
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1.Cure all diseases 2.Automate scientific research, helping us solve challenges such as energy scarcity and discover new materials 3.Eliminate boring, repetitive work by letting AI handle those tasks 4.Give everyone access to a personal AI doctor that can monitor all of their
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Qwen 3.6 2.5x Faster on Atomic Chat with MTP
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Qwen 3.6 models are now 2.5x times faster on Atomic Chat with new MTP speedups.
— 🚨 AI News | TestingCatalog (@testingcatalog) 21 mai 2026
> MTP drafts several tokens ahead and verifies them in one pass. The speedup depends on the memory moved per pass.
Users can run Qwen 3.6 models locally via the open-source Atomic Chat to test… https://t.co/ML74IS2mHE pic.twitter.com/VPzSdcWqkWQwen 3.6 models are now 2.5x faster on Atomic Chat with new MTP speedups. > MTP drafts several tokens ahead and verifies them in one pass. The speedup depends on the memory moved per pass. Users can run Qwen 3.6 models locally via the open-source Atomic Chat to test
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AI’s potential electricity and water footprint by 2030
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Individual use is small, but at aggregate scale, resource usage is higher. By 2030, AI may use as much electricity as Japan. Water use will remain less than 1% of total US water use in 2030, but that can still strain local utilities. (and this problem alone took many runs)