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Token-space geometry, organoid intelligence, constructor theory, active inference frontiers — where silicon and biology begin to share the same manifold. Explore the lattice → [M=T/C](/tag/m-t-c/) • [Theory](/tag/atom-theory/) • [Neurodiversity](/tag/neurodiversity/)

The Energy of Civilization

The Energy of Civilization

The history of civilization is a history of energy capture: fire, crops, coal, electricity, and now computation. Each transition didn't just add power — it restructured what was possible for society, cognition, and politics.

Synthesis: Intelligence Is Expensive

Synthesis: Intelligence Is Expensive

From the metabolic cost of a single action potential to the electricity demand of GPT, intelligence runs on watts. Understanding why coherence is thermodynamically expensive reframes AI risk, brain evolution, and civilizational limits.

Reversible Computing: Escaping Landauer

Reversible Computing: Escaping Landauer

Every time your computer erases a bit, physics demands it release heat. Landauer's principle sets a thermodynamic floor on computation. Reversible computing is the audacious attempt to sidestep that floor entirely.

Fusion Dreams: Tokamaks Meet Training Runs

Fusion Dreams: Tokamaks Meet Training Runs

Nuclear fusion has been 40 years away for 70 years. Now AI-driven plasma modeling and billion-dollar bets on high-temperature superconductors are threatening to make that joke obsolete.

Tungsten and the Chip Supply Chain

Tungsten and the Chip Supply Chain

Everyone worries about TSMC and EUV lithography. Fewer people talk about tungsten — the metal inside every chip's interconnects that has no practical substitute and whose supply is overwhelmingly controlled by one country.

Nuclear for AI: Why Data Centers Want Reactors

Nuclear for AI: Why Data Centers Want Reactors

AI's hunger for electricity is so intense that the biggest tech companies are turning to nuclear reactors. Here's why a technology once written off is suddenly the hottest deal in Silicon Valley.

Neuromorphic Chips: Silicon Learns from Neurons

Neuromorphic Chips: Silicon Learns from Neurons

Your brain runs on 20 watts. A GPU training a language model runs on tens of thousands. Neuromorphic chips attack that gap by mimicking the brain's event-driven architecture — processing only what changes, only when it changes, using spikes instead of clock cycles.