Sand to Sentence — the machine-intelligence stack

A self-guided descent through 27 strata

Every AI answer
begins as sand.

Between a quartz seam in North Carolina and a sentence on your screen sit roughly 27 layers of civilisation — crucibles and crystal pullers, tin-plasma light sources, copper damascene, stacked memory, cold plates, gas turbines, all-reduce collectives, preference data, attention heads, and finally a person deciding whether the answer was worth anything. This is the whole chain, one layer at a time, with the companies that own each link.

01 · lithosphere 27 · return & residue
How to read this

Each stratum is a layer of the stack; each station inside it is a distinct technology, process or market with its own physics and its own incumbents. The coloured pips on a card are a criticality read — how concentrated and how substitutable that link is. Three magenta pips means a genuine single point of failure for the whole industry.

Figures reflect public reporting through mid-2026 and move fast — treat capacities, valuations and roadmap dates as of that vintage, not as live data. Company lists are illustrative of who matters at each link, not exhaustive or ranked, and nothing here is investment advice. Built as a map for understanding, not a database of record.

The dependency web

Every station, stacked by depth. Hover a node to light its supply cone; click to open it. Drag to pan, scroll to zoom.

what it needs (upstream) what it feeds (downstream) zoom in to read names

Seventeen orders of magnitude, drawn to scale

Feel a nanometre.

Everything here is drawn at its true relative size. Scroll, drag or use ← → to travel from the silicon lattice to the Earth. Click anything to centre it.

across the view
How to read this

The horizontal axis is logarithmic: every 300 pixels is one power of ten. Objects are drawn at true relative size — if something looks a hundred times bigger than its neighbour, it is a hundred times bigger. That is why most of the ruler looks empty. Seventeen orders of magnitude do not fit on a screen, and pretending otherwise is the usual lie in diagrams like this.

Shapes are schematic; proportions are not. Each object carries a precision flag — exact for defined or measured quantities, typical for a representative production value that varies by vendor and node, approx for the right order of magnitude and not much more. Sources and reasoning are on the Method page.

Sand to sentence, actually quantified

What does one answer
really cost?

Follow 1,000 output tokens — roughly one substantial answer — backwards through the whole stack, converting units at every step, until it arrives at rock. Every factor below is sourced or derived in the open; press how on any step to see the working. Change the assumptions and the whole chain recomputes.

How to argue with this

Each step is a single multiplication, and each multiplier is either cited or derived from first principles in the panel behind its how button. The ranges are not error bars in the statistical sense — they are the span between defensible low and high parameter choices, propagated through the chain. Where they are wide, the honest answer is wide.

The largest single uncertainty by far is energy per output token, which varies by two orders of magnitude between a distilled model answering directly and a frontier model reasoning at length. Nothing else in the chain comes close. Figures last reviewed .

Sources, assumptions and limits

How this site
knows what it claims.

What the words mean

Where each kind of claim comes from

Grouped by how much you should trust it, weakest first. Judgement calls are listed before cited figures on purpose — they are the ones that shape the site most and defend themselves least.

Against the grain

Findings that contradict what most people assume, collected in one place. Each is load-bearing: it changes how the rest of the stack reads.

The assumption ledger

Every parameter behind the Cascade, generated directly from data/static/cascade.json — the same file the calculation reads. If a number changes there, it changes here, and the build fails if it loses its source or falls outside its own range.

Switchable assumptionOptionsWhat it means
ParameterCentralRangeDerivationSource

Where this is most likely wrong

Written by the person who built it, which makes it incomplete by construction. Additions welcome.

Corrections

Figures reflect public reporting through and move fast. Company lists are illustrative of who matters at each link, not exhaustive or ranked. Nothing here is investment advice. Built as a map for understanding, not a database of record. This page last reviewed .

CompanyWhat it does here StationBase