I got back from the DCD Connect Conference recently and it was all about one thing: data centers! The conference was full of data center operators, it was such a trip learning about the challenges that they face along with their perception of where the biggest challenges lie with all this infrastructure that represents trillions of dollars (projected in the future, of course). There were eight themes that signalled a lot of what the conference was all about including: interconnection delays to the grid, workforce shortages, community opposition efforts, utility bottlenecks, greenwashing perceptions, measurement chaos, energy architecture mismatches, and geographic constraints. Feel free to explore my notes to learn more here.

Some interesting articles of the week:

Caio! 👋

Nate

Can AI Save Nature, or Will It Cause More Harm? (AI & Ecology/Biodiversity): In this episode of EY Sustainability Matters, David Rae, EY Global Lead for Technology, AI and Innovation at EY Climate Change and Sustainability Services, explores the complex intersection of artificial intelligence (AI) and nature. The host poses the question: Can technology solve the nature loss crisis, or will its resource-heavy footprint only accelerate the problem?

Nature Speaks. Can AI Help Us Listen? (AI & Ecology/Biodiversity): More than 8 million species share our planet. Until now, we have only understood the language of one. In this keynote, Aza Raskin, Co-founder of Earth Species Project, explores how AI is being used to decode the languages of other species, revealing complex, learned communication across the animal kingdom. For the first time in history, we can truly listen.

Your Cloud Has a Dirty Secret: The Hidden Carbon Footprint of Your Company's Tech with Tim Prosser (AI & Data Centers/Hardware): What is the real environmental footprint of your organisation's IT infrastructure and is your cloud provider telling you the full story? In this episode, we welcome back Tim Prosser for part one of a two-part deep dive into digital sustainability.

Reviewing the Socio-Technical Dynamics of AI, Data Centers, and Digitalization on Energy and the Environment (AI & Environment): This paper uses a sociotechnical systems approach to conduct a systematic literature search and screened 364 articles published from 2000 to 2025 to analyze impacts and opportunities across four critical dimensions of AI, data centers, and digitalization provisioning: natural resources, facilities and components, applications, and users and institutions.

Transfer Learning and Explainable AI for Heating Load Forecasting: A Large-Scale Benchmark with SHAP-Based Static Features (AI & Energy): Accurate short-term heating load forecasts are crucial for flexible, low-carbon buildings and district heating systems, but many buildings have only limited historical data. This paper benchmarked seven time series forecasting models across 18 mostly real heating load datasets and show how transfer learning can help close this data gap.

The Marginal Energy and Water Cost of AI Inference (AI & Environment): Public debate frequently portrays artificial intelligence inference as highly energy- and water-intensive, often based on opaque or inconsistent assumptions. Using explicit computational, hardware, and infrastructure parameters, this paper finds that a single query typically consumes around 1.3 Wh of electricity and 4.3 milliliters of water.

AI Data Center Moratorium Act (AI Policy & Governance): Senator Bernie Sanders and Representative Alexandria Ocasio-Cortez introduce legislation to impose a moratorium on AI data center construction.

Strengthening Supply Chains Can Improve Resilience and Reduce Economic Security Risks for Key Energy Technologies (AI & Multiple Resources): The International Energy Agency examines how strengthening supply chains can improve resilience and reduce economic security risks for key energy technologies.

DATA Act of 2026 (AI & Energy): Senator Tom Cotton introduces legislation addressing data and technology accountability in the energy sector.

How AI Factories Maximize Tokens, Power, and Profit With NVIDIA DSX (AI & Multiple Applications): As global demand for AI infrastructure accelerates, NVIDIA Omniverse DSX provides a digital twin blueprint for designing, simulating, and operating AI factories at maximum efficiency. DSX helps developers optimize token throughput, resilience, and energy use across physical, electrical, thermal, and network systems.

Why People Are Throwing AI Data Centers in the Ocean (AI & Multiple Applications): Every time you type a request into ChatGPT, the servers processing it guzzle water and electricity. Engineers are trying to fix this by building data centers underwater and are even trying to shoot them into space. But does that work?

How Can Google Data Centers Support Reliable Electricity? (AI & Energy): Data center demand response is a smart solution to make the electricity system more affordable and reliable, enabling our AI data centers to bring new benefits to communities where we operate. Grand River Dam Authority explains how our data center demand response pilot during Winter Storm Fern supported grid reliability and cost savings for Oklahomans.

Everstar Inc. (AI & Energy): Engineering energy abundance through AI-accelerated nuclear licensing, compliance, and supply chain development.

GoCodeGreen (AI & Environment): A ClimateTech company focused on measuring and identifying actions to reduce the carbon impact of digital.

Eurofiber (AI & Data Centers/Hardware): Eurofiber has been a provider of industry-leading open digital infrastructure since 2000. Utilizing our own fiberoptic network and datacenters, we provide smart, open, future-proof cloud infrastructure and connectivity solutions to companies, government bodies and non-profit organizations.

Data Center Siting Tool (AI & Infrastructure): Hover over a country to see parameters. Pick a data center size, turn on add mode and click on a country to place up to 5 data centers. Map created by Pawel Czyzak.

Civic Analytics Skills for Claude (AI & Workforce Development): A framework for evidence-based city policy analysis. Built on world-class methodologies from the Bloomberg Centers at JHU and HKS, J-PAL at MIT, and The GovLab at NYU and Northeastern, connecting Claude AI to live open data from Boston, Pittsburgh, and San Jose.

Geospatial Analysis (AI & Geospatial Analysis): Geospatial Atlas is a tool that provides interactive visualizations for large point datasets. It allows you to visualize, cross-filter, and search the data and its metadata.

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Thanks for reading the 34th 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.

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