Brief Author Note

👋 Welcome back! We have 62 subscribers which is awesome considering its only been a week since I launched The Climate Code. I received a lot of positive feedback on the first issue which is great to read.

In case you missed it, I finished up my AI x Energy deep dive recently and did a LinkedIn Live last Saturday. 👀 

This presentation explores real world applications of AI in the energy sector, showcasing how AI and machine learning are driving climate solutions across the grid, renewables, storage, and beyond.

There’s also a cool mindmap I did to visualize the 40+ companies that I covered in the presentation.

Check it out these resources! Here is the webinar, slide deck, and mindmap. Let me know if any of the links don’t work and I can fix them.

👋 Chau!

Quick Links!

• Podcast Episodes

• Scientific Papers

• Policy Documents

• Multimedia

• Organizations

• Tools

• Submit Resources

The Real Costs of Climate Action (AI & Policy): How economically grounded is the UK’s net zero commitment? Listen to Jason Mitchell discuss with Professor Sir Dieter Helm, University of Oxford, about what new forces and factors are reshaping net zero ambitions; how the UK should think about optimal climate policy; and why a realist approach is critical for navigating the political economy factors of climate action. There is also discussion around the environmental costs of being an AI superpower.

AI's Growing Appetite: Can Data Centers Keep Up? (AI & Data Centers/Hardware): In this episode of The AI Forecast, Scott Jarnagin, CEO of Caddis Cloud Solutions, joins the podcast to discuss the evolving landscape of data centers in the age of AI. He touches on the significant increase in energy consumption associated with AI workloads, the historical shifts in data center strategies, and the challenges faced in designing and planning for future data center needs.

Building a Data-Centric Digital Grid (AI & Data Centers/Hardware): Alexina Jackson brings system thinking and a willingness to test assumptions to the task of grid modernization and data center developments.

Large Language Models in Climate and Sustainability Policy: Limits and Opportunities (AI & Policy): This study evaluates how large language models (LLMs) can support climate and sustainability policy by classifying and analyzing text data across two case studies, while also identifying key limitations like interpretability and usability that must be addressed to ensure reliable decision-making.

ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change (AI & Climate Science): This paper presents ClimateGPT, a family of open-source large language models trained on interdisciplinary climate science data, featuring multilingual support, retrieval-augmented generation, and strong performance on climate-specific benchmarks, all developed using renewable energy.

Does Artificial Intelligence Bias Perceptions of Environmental Challenges? (AI & Social/Economic Impacts): This study analyzes over 1500 chatbot responses and reveals that AI systems often exhibit bias by promoting incremental solutions to environmental issues, downplaying systemic change, and avoiding discussions of accountability or social justice.

The Hidden Emissions of Tech (AI & Infrastructure): This guide reveals the hidden emissions of the tech industry and offers actionable strategies for businesses to decarbonize and become climate-friendly.

Harnessing AI for the Earth (AI & Sustainability): This report explores how the Fourth Industrial Revolution and specifically artificial intelligence can be harnessed to address environmental challenges, while also warning of new risks that require proactive governance and cross-sector collaboration.

Landscape Assessment of AI for Climate and Nature (AI & Biodiversity): This report, commissioned by the Bezos Earth Fund and led by Columbia University, explores how AI can accelerate climate and nature solutions while emphasizing the need for ethical, equitable, and collaborative approaches across sectors to maximize impact and mitigate risks.

I Live 400 Yards From Mark Zuckerberg’s Massive Data Center (AI & Environmental Impact): What's the true cost of the AI revolution and who should be paying for it? We went to Georgia to find out and do a deep dive with a homeowner’s situation.

Can You Run a Grid Entirely on Renewables? (AI & Energy): Can an electrical grid be run entirely on renewables, without facing black outs or wide spread power cuts? "Yes," says Anders Lindberg, President of Energy and Executive VP at Wärtsilä, on this week's episode of Cleaning Up. It'll just cost $65 trillion extra by 2050.

Flexibility: The Key to Unlocking More Data Center Power (AI & Energy): Are regional power grids actually constrained? Or could dozens of gigawatts of power be unlocked by new approaches to grid management and data center power contracts? That’s the intriguing question posed by new research from an energy analyst, and it could have large implications for the data center industry.

ClimAIr Project (AI & Social/Economic Impacts): Harnessing AI to combat climate change and improve respiratory health across Europe.

Smart Parks (AI & Conservation Science): Smart Parks is using innovative techniques for the protection of endangered species, humans, and the environment. Through the use of sensor technology and other cutting-edge technology Smart Parks continues to enhance its methods to help people, animals, and the environment.

Venato (AI & Policy): Venato helps identify, monitor, and understand regulations in a streamlined fashion. This is achieved through a combination of targeted web scraping and a citation based AI model, to ensure trustworthy sources of information.

SkyTruth Cerulean (AI & Ocean Conservation): This AI-powered tool uses AI to detect ocean oil pollution and link it to their most likely source. It can find oil slicks in satellite imagery using machine learning models and identify nearby vessels and offshore oil platforms that may be responsible for those slicks.

Green Software Landscape (AI & Policy) : This landscape database contains measurement and optimization tools for achieving green software goals.

Carbon-Aware SDK Tool (AI & Energy): This release consolidates the ElectricityMaps sources, introduces new CO₂-intensity signal support in WattTime, and rounds out the release with documentation improvements and critical bug fixes.

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 2nd 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. 😆