Brief Author Note

Did you hear the news? The Alberta Machine Intelligence Institute (Amii) in Canada is launching the AI Pathways: Energizing Canada’s Low-Carbon Workforce program with support from the Government of Canada’s Sustainable Jobs Training Fund.

Why should you care? 🙄 

It’s the first program that I have seen that shows how a country is preparing their energy workers to become an AI-literate workforce.

I wonder if this framework is going to be deployed around the world to embrace the future of AI, energy, and workforces?

Cya later, alligator! 🐊 ,

Nate

Quick Links!

• Podcast Episodes

• Scientific Papers

• Policy Documents

• Multimedia

• Organizations

• Tools

• Fellowships Corner

• Submit Resources

India's Climate Crossroads: Growth, Energy, & Resilience (AI & Energy): Avanti Bhati and Nandan Sharalaya explore India’s climate and energy future, discussing the intersection of rapid economic growth, resilience planning, and the potential role of AI in supporting sustainable energy solutions.

AI & Energy Efficiency: Just Follow The Money! (AI & Energy): Anne Currie dives into how AI model selection and deployment impact energy use, offering practical guidance for developers on reducing energy consumption while aligning with the financial incentives driving AI efficiency.

Backstage: The Green Software Movement Platform (AI & Workforce Development): Chris Skipper and Gosia Fricze introduce the new Green Software Movement Platform, a collaborative hub connecting practitioners, tools, and resources to accelerate adoption of sustainable software practices worldwide.

When Machine Learning Models Retire, Decay, or Become Obsolete: A Review on Algorithms, Software, and Hardware (AI & Data Centers/Hardware/Models): This paper presents a systematic review of AI systems’ lifecycle energy consumption and a six-part framework for improving sustainability through scheduling, architecture, algorithms, metrics, optimization, and adaptive computation.

SFR-DeepResearch: Towards Effective Reinforcement Learning for Autonomously Reasoning Single Agents (AI & Data Centers/Hardware/Models): This paper presents a reinforcement learning approach to enhance single-agent LLMs for Deep Research, achieving strong performance on the Humanity’s Last Exam benchmark and offering analysis of model training with synthetic data.

Optimizing Microgrid Composition for Sustainable Data Centers (AI & Data Centers/Hardware/Models): This paper presents an optimization framework that integrates Vessim with NREL SAM to simulate and optimize data center microgrids, accounting for operational and embodied emissions to support sustainable energy planning.

The People Say No: Resisting Data Centers in the South (AI & Environmental Justice): This report presents community-led research documenting opposition to data center development across the U.S. South, highlighting environmental, social, and economic concerns driving grassroots resistance.

Generative AI for Geospatial Challenge — A Taylor Geospatial Institute Report (AI & Geospatial Analysis): This report presents insights from the Generative AI for Geospatial Challenge, exploring how large models can be applied to geospatial data and outlining opportunities for research and industry collaboration.

AI-Enabled Policy Project (AIPP) Convening: Bringing Together Technology and Policy Experts on Using AI to Improve Policymaking (AI Policy & Governance): This report presents proceedings from RAND’s AIPP convening, summarizing discussions on how AI tools can support evidence-based policymaking and identifying future research priorities.

Bristow Data Center Vote Sparks Outcry: Residents Demand Delay (AI & Sustainable Development): This video presents community protests against the Bristow Data Center Campus, capturing local voices calling for a delay in government approval due to environmental and community concerns.

Rewiring Systems for Climate Actions (AI & Climate Policy): This video presents Isabell Steidel’s TEDx talk on breaking cycles of inaction in the climate crisis, emphasizing systemic barriers and the need for policy change to enable socio-ecological transformation.

Sustainably Scaling AI Adoption (AI & Multiple Applications): This video presents an HPE discussion on building sustainable AI infrastructure, exploring solutions to manage the energy, cooling, and compute demands of next-generation AI workloads.

Nuclearn (AI & Energy): This company applies AI to modernize nuclear energy operations, providing advanced tools that improve efficiency and safety for over 60 reactors worldwide.

CuspAI (AI & Circular Economy): This company harnesses AI to accelerate materials discovery, aiming to unlock trillion-dollar breakthroughs in chemistry and engineering for a faster, more sustainable materials economy.

Aurora Solar (AI & Energy): This company offers cloud-based AI-powered software that streamlines solar design, sales, and delivery, helping scale solar adoption and make clean energy more accessible.

Aqcat25 (AI & Materials Chemistry): This tool provides a large-scale dataset of DFT calculation trajectories for heterogeneous catalysis, enabling machine learning research on adsorption energies, forces, and catalyst design for sustainable chemical processes.

Apertus LLM (AI & Workforce Development): This tool presents an open-source multilingual large language model (70B and 8B parameters) designed to support over 1,000 languages with transparent training data, advancing open and equitable AI research.

MapYourGrid (AI & Energy): This tool enables global volunteers to map power grid infrastructure, improving data for electrification planning, decarbonization efforts, and energy access in underserved regions.

AI Pathways: Energizing Canada’s Low-Carbon Workforce (Canada) (Open to Canadian energy sector applicants): This program presents training for nearly 5,000 Canadian energy workers, engineers, technologists, project managers, scientists, technicians, and operators to build AI and machine learning literacy via online courses, a MOOC, and in-person sessions as part of the transition toward a low-carbon energy sector. Deadline: Applications reviewed on a rolling basis.

2026 Tech Policy Press Fellowship Program (Open to global applicants): This year-long, part-time fellowship supports journalists, researchers, and public policy professionals to pursue independent reporting or analysis on tech & democracy issues; fellows receive a US $10,000 stipend, editorial mentorship, and cohort-based learning and work remotely. Deadline: October 15, 2025

CITP Technology Fellows Program (U.S.) (Open to U.S. technologists with public interest / government experience): This fellowship engages technologists with 3+ years experience to lend technical expertise to state/local government bodies addressing technology policy issues (AI governance, privacy, digital equity etc.), with flexible commitment (~5-8 hours/month), virtual + Princeton-based gatherings, and opportunities for paid project work. Deadline: October 15, 2025 (rolling until then)

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 17th 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. 😆