Brief Author Note

Guess what?! I created my first course and hosted it on Udemy! 🫠 This took me two months on and off to complete which was a long haul.

The Environmental Impacts of Data Centers course touches on a subject that I do not see enough of when it comes to the entire AI and data center narrative that is pervasive today.

Data center development carries a large number of environmental impacts that go beyond energy and water consumption. We are talking about land use deals, global supply chain issues of rare earth minerals (REM), AI policy, and environmental justice concerns for communities.

At the end of the day, I wanted to contribute to folks learning about these issues using a life cycle assessment (LCA) perspective. There are so many communities struggling with this right now, either in the U.S. or internationally.

Hopefully, this spreads more awareness and education about these issues! Feel free to take the course (it’s free, lol) and leave me a review so I can add more modules if there is enough demand for it.

Watt you later! ⚡️ 

Nate

Quick Links!

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• Fellowships Corner

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David Kirtley and the Direction of Helion Energy (AI & Energy): David Kirtley of Helion Energy discusses nuclear fusion, plasma physics, and the company’s plan to build the first commercial fusion power plant by 2028, including how AI may accelerate progress toward clean energy.

Dr. Li, The Godmother of AI on AI Models (AI & Data Centers/Hardware): Dr. Fei-Fei Li traces the evolution of modern AI from ImageNet to today’s world-model breakthroughs and explains how rapid hardware and data center advances are shaping the next frontier of robotics and AI research.

Solving the Climate Crisis with AI (AI & Environment): Professor Gina Neff examines whether AI can meaningfully support climate action, highlighting the environmental costs of rapid AI expansion, the role of data centers, and the urgent need for transparency and democratic accountability.

A Critical Re-framing of the AI(s) and Sustainability Regulation Debate through the Lens of Law and Technology (AI & Policy/ESG): This paper argues that debates on “sustainable AI” are constrained by a misleading binary, AI as environmental harm vs. ecological solution, leading to shallow, energy-focused regulation, and calls for reframing governance around the socio-economic forces and power dynamics driving AI development.

GreenMix: Energy-Efficient Serverless Computing via Randomized Sketching on Asymmetric Multi-Cores (AI & Data Centers/Hardware/Models): GreenMix introduces a serverless scheduling system that exploits asymmetric multicore processors to cut energy use and keep-alive costs while meeting QoS, using randomized sketching to achieve near-optimal performance and outperform state-of-the-art schedulers.

AutoClimDS: Climate Data Science Agentic AI — A Knowledge Graph is All You Need (AI & Climate Science): This paper presents a knowledge-graph-driven system paired with AI agents that simplifies climate data science by enabling natural-language dataset discovery, automated data access, and cloud-native workflows, lowering technical barriers and improving reproducibility.

GridStrategies: Power Demand Forecasts Revised Up for Third Year Running, Led by Data Centers (AI & Energy): This report shows that U.S. electricity demand forecasts have been revised upward for the third consecutive year, driven largely by the explosive growth of data centers and AI infrastructure, highlighting mounting pressure on grid capacity and long-term energy planning.

AI in the Street: Lessons from Everyday Encounters with AI Innovation (AI & Resources): This report examines how people interact with AI in day-to-day public environments, revealing disparities in visibility, access, and trust, and offering insights into how AI innovation is shaped by real-world social, cultural, and material conditions.

Technology Sector Engagement on the GHG Protocol: An InfluenceMap Report (AI & Sustainability): InfluenceMap analyzes how major tech companies are lobbying during the GHG Protocol’s Scope 2 revision process, finding substantial efforts to shape emissions accounting rules in ways that could benefit the sector while raising concerns about transparency and global climate integrity.

WeatherNext 2: Our Most Advanced Weather Forecasting Model (AI & Multiple Applications): WeatherNext 2, developed by Google DeepMind and Google Research, is an AI weather model that delivers forecasts up to 8× faster with 1-hour resolution, using a new Functional Generative Network to generate thousands of possible outcomes in under a minute on a single TPU.

How Data Centers Manage Intense Heat: Cooling Systems Explained (AI & Digital & Cloud Sustainability): This video breaks down how Equinix data centers handle extreme server heat, offering an inside look at the cooling systems and engineering solutions that keep digital infrastructure stable, efficient, and sustainable.

GREEN.DAT AI (AI & Data Centers/Hardware): GREEN.DAT.AI supports the goals of the European Green Deal by developing energy-efficient, large-scale data analytics services designed to reduce the environmental footprint of industrial AI systems and data management processes.

Extropic (AI & Data Centers/Hardware): Based in North America, Extropic is building thermodynamic computing hardware that dramatically improves energy efficiency compared to traditional GPUs, aiming to reshape the future of AI infrastructure.

LIFEPOWR (AI & Energy): Based in Europe, LIFEPOWR optimizes energy flows across decentralized energy assets, enabling real-time grid balancing and unlocking new flexibility for Europe’s evolving clean energy system.

WeatherNext 2 (AI & Climate & Extreme Weather): WeatherNext 2 is Google DeepMind and Google Research’s state-of-the-art family of AI weather forecasting models, delivering faster, high-resolution predictions across a wide range of climate and extreme weather variables.

Azure Planetary Computer Client Library for Python (AI & Geospatial Analysis): This Python client library provides programmatic access to Microsoft’s Planetary Computer Pro, enabling users to ingest, manage, search, and distribute large-scale geospatial datasets through the STAC open specification.

Developer’s Dilemma: An Interactive China AI Decision Tree (AI & Policy): This interactive experience places users in the role of a Chinese AI developer navigating trade-offs across the tech stack balancing performance, cost, political constraints, and commercial opportunity within China’s AI ecosystem.

CoMotion Labs Climate Tech Incubator (AI & Energy): This six-month cohort-based incubator at the Seattle Climate Innovation Hub supports pre-seed and seed-stage climate tech startups working across energy, AI/data infrastructure, mobility, and the built environment. Startups gain mentorship, workspace, commercialization training, and access to UW’s innovation ecosystem. Applications close December 7, 2025.

ANH Academy Science-Policy Fellowships – Round 2 (AI & Policy): This one-year full-time fellowship places early-career researchers into policy organizations across Sub-Saharan Africa and South Asia to advance evidence-informed decisions on diets, food systems, and planetary health. Fellows receive ~£52,600 in support, mentorship, and structured training in science-policy engagement. Applications close February 28, 2026.

AI for Sustainability (AI4S) Visiting Professorship (AI & Sustainability): Cornell’s AI4S Visiting Professorship invites global faculty to collaborate on high-impact AI-and-sustainability research, offer seminars or short courses, and engage with the CAISI network. Appointments last two years, with flexible visit durations from weeks to months. Applications close January 15, 2026.

If you have resources that you wish to submit to the AI & Environment Resource Hub, fill out the Google Form! Thank you for suggesting resources to add to the Resource Hub. 🙃 

That’s it for this week.

Thanks for reading the 27th issue of The Climate Code! It means a lot to me and we have more coming in the future, so definitely stick around! 💚 

Nate

P.S.

New here? Check out the AI & Environment Resource Hub if you have no idea what it is. 😆