I just found this out yesterday when I was cleaning the house! July 29/July 30 is when Q2 of the big tech financial disclosures finally comes out for 2026. This is especially critical because we will finally get to see just how far along data center capex expenditure is going to be in the U.S.

Sometimes I do wonder if we are heading to like the “red line” of data center capex spending and what that means for the U.S. economy as a whole. In one of my favorite shows of all time, the “red line” in Battlestar Galactica refers to the maximum distance you can perform a Faster-Than-Light (FTL) jump. If you go beyond said point, you essentially run the risk of being lost forever. That is quite the metaphorical analogy to the U.S. economy and what that means if the bubble ever pops.

We may be closer than you think with Google reporting its first negative cash flow quarter in a long time due to their AI spending. To be clear, they are still way profitable, it’s just that their spending on everything AI related is getting out of control. I can hear the skeptics yelling at me and unsubscribing, “you’re not a believer!” already LOL.

Chau 👋,

Nate

AI, Sustainability, and Banking: A Conversation with Natalie Sinha (AI & Policy/ESG): In this episode, host Nina Benoit interviews Nathalie Sinha, a sustainable finance leader, writer, and public speaker to explore the intersection of AI, data centers, and sustainability.

The Dirty Data Centre Era with Chris Adams (Green Web Foundation) (AI & Data Centers/Hardware): Chris Adams, Director of Technology and Policy at the Green Web Foundation, returns to Architect Tomorrow to unpack the first State of the Fossil-Free Internet report, subtitled The Dirty Data Centre Edition.

Hunting Lions with Drones (To Protect Them) (AI & Ecology/Biodiversity): What happens when ancient tradition meets cutting-edge technology? In this episode of Possible Worlds, Malaika Vaz travels to the Amboseli ecosystem in East Africa to embed with the Lion Guardians, a group of Maasai warriors who are completely redefining wildlife conservation.

Energy Calculus: A Compositional Algebra of Energy in Computational Systems (AI & Energy): Energy is a binding constraint for AI scaling, yet it lacks the formal treatment that computation, communication, and learning have long enjoyed. We propose energy calculus, a compositional algebra that treats energy as a first-class primitive in this paper. Authors: Chowdhury et al. Journal: arXiv.

Beyond Carbon: A Call for Research on the Impacts of Computing Systems on Human Health (AI & Social/Economic Impacts): Sustainability research for large-scale computing has converged on carbon as the primary accounting unit, and much work has gone into reducing it. However, carbon emissions are only one possible indicator of computing's impact. We call for systems research into minimizing the human health impacts incurred by large-scale computing. Authors: Kopczyk and Chandra. Journal: HotCarbon.

Counting Own Goals: High-Level Assessment of the Economic Relationship Between the ICT and the Oil and Gas Sectors and Its Environmental Implications (AI & Environment): The ICT sector has been one of the most successful and fastest-growing industries in history. While the environmental issue in this sector has mainly been addressed by assessing its footprint and, to a lesser extent, its avoided emissions or net impacts, the additional emissions from the digitalization of carbon-intensive activities, such as the Oil and Gas (O&G) sector, have rarely been discussed. Authors: Roussilhe et al. Journal: arXiv.

NVTC's 6th Biennial 2026 Data Center Report (AI & Infrastructure): The Northern Virginia Technology Council's biennial assessment of the data center industry in the world's largest data center market. Authoring Body: Northern Virginia Technology Council.

Data Centres as Demand Anchors: Reducing Dispatch Down and Strengthening Northern Ireland's Grid (AI & Energy): A report on how data centers can act as demand anchors to reduce dispatch down and strengthen Northern Ireland's grid. Authoring Body: GreenScale.

Estimating GHG Emissions from AI Use (AI & Sustainability): A methodology paper on estimating the greenhouse gas emissions associated with AI use. Authoring Body: Watershed.

Addressing Water Challenges for AI and Data Centres (AI & Water/Ocean Resources): Artificial Intelligence (AI) has the potential to transform how water is managed. Yet, these emerging opportunities raise critical considerations around issues such as data governance, energy use, and the environmental footprint of digital infrastructure. To explore these challenges and opportunities, IWRA is launching a new webinar series: "The Promises and Challenges of AI, Data Centres & Freshwater Futures". Bringing together experts from around the world, the series examines the intersection of emerging technologies and water sustainability.

Data Centers: Site Selection to Approval (AI & Environmental Impact): In this episode of The Market Edge, Diana O'Lare sits down with Flypower CEO Navdeep Martin to discuss how AI-powered site selection and community risk intelligence are helping teams answer two critical questions: Should we build here? And what is our path to approval?

How Elon Musk's AI Empire In Memphis Became A Cautionary Tale (AI & Environmental Impact): Elon Musk's xAI has made the Memphis, Tennessee area the center of its AI ambitions, building three data centers and a power plant in Southaven, Mississippi. Its Colossus infrastructure was built with breakneck speed, but the buildout has been chaotic, and xAI now faces multiple lawsuits accusing it of using loud, pollution-emitting gas turbines, some without the required Clean Air Act permits. CNBC traveled to Memphis and Southaven to learn why the data centers are such a flashpoint, why backlash is spreading nationwide, and what hyperscalers can do to win support as they race to build AI infrastructure.

ML.Energy (AI & Data Centers/Hardware): We build computer systems that measure, understand, expose, and optimize the modern ML energy and power consumption. Location: North America.

Hivenet (AI & Infrastructure): The unmatched price-performance cloud for serious AI and HPC workloads. Location: Europe.

Aleterra (AI & Water Resources): Building water resilience with cutting-edge climate-tech. 70%+ water savings, verified. Powering Net Water Positive projects & communities. Location: North America.

Grid Resources Directory (AI & Energy): Every data source and model for the US electric grid, on one board. Price: FREE.

Encode: AI for Science Challengescape (AI & Workforce Development): A living directory of open problems in science, each one submitted by a UK-based researcher at the frontier: a lab with the expertise, the data, and a question that AI could move. Starting with the UK, it's the same tool we use internally to match our Fellows to projects and collaborators. Now it's open to everyone. Price: FREE.

AI 2040 (AI & Policy): A continuation of the AI 2027 report and where AI development can go in the future. Price: FREE.

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. 🙃

RE100 booting out Meta because they went all in on their natural gas obsessions with AI data centers! I wonder if we are going to see other Big Tech companies getting booted out of renewable energy-type groups?

Thanks for reading the 51st issue of The Climate Code! It means a lot to me and we have more coming in the future, so definitely stick around! 💚

Nate

PS 😁

New here? I would recommend checking out Data Center Battlegrounds (our YouTube channel focusing on the environmental impacts of data centers) and also the AI & Environment Resource Hub itself.

PPS 😆

If you’re feeling EXTRA GUTSY, connect with me here on LinkedIn! Say hey 👋.