The hottest Energy Use Substack posts right now

Water use by datacenters is often overstated when reported without context; cooling architecture, power source, location, and whether you count direct vs. embedded water all hugely change the footprint.
A concrete comparison shows a 400 MW datacenter can use ~346 million gallons/year while an average In-N-Out store uses ~147 million gallons/year, so that datacenter is roughly equivalent to 2.5 burger joints and can produce billions of tokens per burger of water footprint.
Mitigations and accounting matter: hybrid dry/adiabatic cooling, power choices, chip-manufacturing impacts, and onsite water recycling can greatly reduce net blue-water use, and standardized water accounting is needed for fair comparisons.

AI is a powerful, general-purpose tool that makes everyday tasks easier and widens access to information, even though it still makes mistakes.
Public fear of AI—especially in the U.S.—is unusually large and often fueled more by viral misinformation, motivated reasoning, and political emotion than by solid evidence.
Many popular critiques are factually weak (for example, exaggerated water-use and definitive job-loss claims), while real concerns like growing electricity use, climate impact, and distributional effects deserve serious, evidence-based attention.

Modern combat — from fighter jets and rockets to detonations — releases huge amounts of greenhouse gases and other pollutants during the fighting.
Rebuilding and cleanup after wars add large, long‑lasting emissions and pollution, sometimes rivaling the annual output of whole countries.
Multiple current conflicts together are a significant, often overlooked driver of the climate crisis, so cutting fossil fuel use in military operations could reduce that harm.

During the late 1500s, people in England started using coal instead of wood for heating. This change was not just about using a cheaper fuel; it actually transformed how land was used, allowing more space for crops.
The rise of coal in households was influenced by advances in technology like chimneys and coal grates, which made it possible to burn coal more efficiently and with less smoke. These innovations helped shift people's preferences towards coal.
Coal became popular in brewing and other industries because it was cheaper than wood. This increased demand for coal, eventually leading to a significant rise in its use in homes and cities.

The AI boom was driven by exaggerated promises and speculation, but the big societal breakthroughs haven’t materialized and many AI projects are unprofitable while causing real harms like higher energy bills and unsafe outputs.
Tech giants are pivoting from grand future visions to selling AI as an everyday utility and entertainment tool, trying to grow user bases to justify sky-high valuations.
Because the industry is concentrated among the very rich, there’s a real risk they’ll push for taxpayer-funded bailouts if the bubble bursts, and rising inequality means ordinary people would suffer most from the fallout.

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Vertical farming can grow greens indoors, but it won't solve global food issues soon. It's too energy-intensive and often expensive.
Growing leafy greens like lettuce can work if electricity costs are low. However, for staple crops like wheat, vertical farming is not a practical option right now.
While vertical farms might use less land, they can have a bigger carbon footprint than traditional farming, depending on the energy source used.

AI and data centers raise real energy and water concerns: electricity demand is the bigger issue, water worries are emotionally charged, and cooling or water-use choices can change the impact.
A patchwork of state regulations is making it harder for smaller AI companies to compete and could stifle useful innovation, while policymakers often focus on narrow problems like deepfakes instead of bigger issues like energy and grid planning.
Nobody really knows how AI will transform the world, so there’s a lot of uncertainty, and near-term risks from malicious humans using AI deserve more attention than hypothetical superintelligent scenarios.

When it comes to climate policy, some people view costs as benefits, creating different perspectives on energy use and global warming solutions.
Alternatives like nuclear power, natural gas, and geoengineering can help reduce global warming without reducing energy use, but not all advocates support these options.
Using a crisis like global warming as an excuse for political agendas or personal beliefs is a common pattern across different contexts and political ideologies.

Three proposed blended scenarios for addressing climate change: drift, embrace localization (Gardenworld), embrace high tech (world)
Use of technology like AI and chatbots to manage Gardenworld projects for feeding, sheltering, and aesthetics
Local efforts to maintain Internet connectivity as a common project in the face of grid failures