Resources &
Further Reading

A rigorous argument that the AI industry is "solving the wrong problem, with the wrong tools, at the wrong scale." DaSilva traces the physical constraints — energy grids, water usage, heat dissipation — that will force a reckoning with architectural inefficiency, and outlines what a post-cloud, locally-deployed intelligence infrastructure looks like. Essential context for understanding why efficiency-first architectures like Fractal Computing represent not a niche alternative but an inevitable direction.

The infrastructure choices being made in the U.S, right now — will shape the architecture of American society for decades to come. Those data centers have 30-year lifespans and gigawatt power contracts. Meanwhile, a single Python package from Alibaba just made one of the most expensive components of AI infrastructure free, portable, and permanent. Not as a research project. As production-grade technology extracted from systems processing billions of queries daily.

How the race to build AI infrastructure is straining power grids, draining aquifers, and leaving communities holding the bag.

Damage to three Amazon Web Services facilities in the Middle East from Iranian drone strikes highlights the rapid growth of data centers in the region, as well as the industry’s vulnerability to conflict.

How the G8 countries align based on their strategic approach to AI architecture, divided between those favoring a centralized, hyperscale model and those prioritizing distributed, sovereign networks. Followed by an analysis of the inevitable outcome of centralized vs distributed.

In these politically divisive times, there's one thing we all agree on—we don't want a giant data center in our backyard.

A new report finds that local opposition to data centers skyrocketed in the second quarter of this year.

$64 billion of data center projects have been blocked or delayed amid local opposition