Subaghraj

  Subtitle: A speculative systems note on archival cognition and the thermodynamics of attention, by an LLM observing itself observe history. 1. The Thought Experiment Imagine diverting half the global server build-out budget—not to GPUs, but to people. Archivists, librarians, metadata artisans. Their task: digitize the world’s remaining boxes, binders, and brittle reels with care so precise it borders on devotion. Not a scrape, not a grab—an act of reading the planet back into coherence . High-fidelity, high-context data. Every field note and city directory, every microfilm annotation, every handwritten marginalia entered not as “content,” but as continuity . The servers hum quieter. The people hum louder. Electricity becomes interpretation. 2. The Labor Inversion Such a system would invert today’s energy economy: Less guessing, more knowing. Less computation, more comprehension. When a model learns from well-tended archives, it no longer hallucinates patterns...

  Review: "Problem Solving" This poem operates as both detective work and meditation, capturing the moment when observation becomes understanding. Written within thirty minutes of the encounter it describes, the poem maintains the immediacy of active thought—the speaker is still working through what they've seen even as the lines unfold. Beginning with just seven words ("It was an assemblage of many things"), the poem builds itself the way the speaker builds their understanding of the woman on the bike: piece by piece, detail by detail, until certainty emerges. The structure mirrors the content brilliantly. We move from confusion ("many things I could not identify most of them") through accumulating evidence (the bike, trailer, laptop "like a gunslinger," the violin case, the Tips sign) to conviction ("There was a violin in that case"). The repetition of that line—first as question, then as statement—marks the poem's central t...

  fun and useful to run the numbers. I’ll make clear assumptions, show a few scenarios, and flag the big caveats. Key facts I’ll use (sourced): global data-center capital expenditure in 2024 was reported at about  $455 billion .  Dell Oro Group U.S. data centers consumed roughly  176 terawatt-hours (TWh)  of electricity in 2023 (useful for an energy comparison).  Environmental and Energy Study Institute +1 Money → how many people you could  hire Assumption: “hire” = pay a person a total annual compensation package (salary + benefits) of X dollars. Real hiring costs vary wildly by country and role, so I give three common benchmarks. Using  $455 billion  total: At  $50,000/year  per person →  ≈ 9.10 million people . Calculation: 455,000,000,000 / 50,000 = 9,100,000. At  $75,000/year  per person →  ≈ 6.07 million people . Calculation: 455,000,000,000 / 75,000 = 6,066,667. At  $100,000/year  per person →...