Four layers and their chokepoints

Follow the chip down

The history module told you a frontier model is something perhaps a dozen organisations can build. This lesson is about why the number is that small, and it comes from following one chip from the model back down to the sand.

Layer one: the machines that make the chips

The transistors on a modern AI chip are a few nanometres across, and drawing them requires a lithography machine that uses extreme ultraviolet light. One company in the Netherlands makes those machines. Nobody else does; nobody else has come close after two decades of trying. Each costs on the order of two hundred million euros, the newest generation nearer four hundred million, and the company ships a few dozen a year. That single firm is the narrowest point in the entire industry, and since 2019 its government has, under pressure from the United States, forbidden it to sell the machines to China.

Layer two: the factories

Owning the machine is not enough; running a fabrication plant at the leading edge is a skill held by very few. One company in Taiwan makes roughly ninety per cent of the world’s most advanced chips, including every AI accelerator that matters. A South Korean firm is a distant second. The United States, having lost this capability over thirty years, is spending tens of billions to rebuild a fraction of it, and India, which has none, is building its first plant at a technology level two decades behind the frontier. That most of the world’s AI compute passes through one island is a fact that shapes foreign policy.

Layer three: the designs

The chips themselves are designed by a handful of firms and, for AI, overwhelmingly by one. The company from the graphics-chip lesson holds, by most estimates, four fifths or more of the market for AI accelerators, and its programming platform from 2007 is the reason: fifteen years of tools, libraries and trained engineers are built on it, and switching is expensive. Google designs its own chips and uses them internally; Amazon and Microsoft have followed; a US rival designs competitive hardware with a smaller software base. The high-bandwidth memory stacked beside every one of these chips comes from three firms, two of them Korean.

Layer four: the buildings and the labs

The chips are bought in tens of thousands and installed in data centres owned mostly by three American cloud companies and a few specialists, drawing power from grids the chip-makers did not plan for. On top of the buildings sit the labs: perhaps a dozen organisations, in the United States and China with one or two in Europe and the Gulf, that can pay for a frontier training run. Above those, the data (the web, the licensing deals, the human labour from the previous module) and above that, everything you use.

How the chokepoints get used

A chokepoint that exists will be used, and the first use came in October 2022. The United States banned the export of its most advanced AI chips to China, then tightened the rules a year later, then in early 2025 proposed a system of tiers for every country on earth (with India in a middle tier subject to caps) and then withdrew it four months later. In 2025 the rules for the chips sold to China changed several times in a year. A Chinese lab’s efficient model of early 2025 was, in part, a response to being restricted to a deliberately weakened chip.

The point is not the particular rule. It is that the physical structure of the industry lets two or three governments decide who may compute, and they have started deciding.

Where India stands

At every layer above the sand, India is a buyer. It has no leading-edge fabrication and no chip design at the frontier. It has a national programme, funded in 2024 at around ten thousand crore rupees, to buy tens of thousands of accelerators and make them available to researchers and start-ups as shared compute, and it has a large share of the world’s data-labelling and software labour. Its own language models are built on open weights from American and Chinese labs, adapted with Indian text. That is a reasonable position for a country to take and it is also a dependent one, and the open-weights lesson in the history module is the reason it is possible at all.

What this means for the rest of the module

Regulation, copyright, energy and safety are all shaped by the fact that the makers are few. A law can reach a dozen labs more easily than a million users. A copyright settlement is negotiated with a handful of firms. An electricity grid is strained by the same handful of buildings. And a safety commitment is only as broad as the labs that sign it. Keep the four layers in mind; every lesson that follows is about who sits on one of them.