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READER GUIDE · PLAIN ENGLISH

Understand the system — at your own pace

A guided learning path for readers who want to understand the system before diving into the live research.

This section is optional.Prefer the answer without the lesson? See the 60-second system view → or go straight to what changed →
LEARN THE SYSTEM · BEGINNER → TECHNICAL

From individual chips to a national AI infrastructure system.

Use this only if you want the guided version. You can read the thesis, news flow and company research without completing any lessons. Here, the same ideas are unpacked step by step.

By the end, you should be able to:read the architecture map · understand the main bottlenecks · follow the national coordination thesis · distinguish evidence from inference · interrogate company claims
GUIDED PATH

Build the system in seven steps

Read in order if this is new to you. If you already know a layer, jump directly to it.

01
COMPUTE ARCHITECTURE

How do thousands of AI processors work together?

Start with the basic scaling problem, then learn what Huawei means by a SuperPoD and why interconnect can determine useful performance.

Learn SuperPoD →
02
MEMORY

Why can a fast AI chip still spend time waiting?

Learn how HBM, memory bandwidth and KV cache feed accelerators — and why compute performance is more than FLOPS.

Learn memory & HBM →
03
PHYSICAL INFRASTRUCTURE

What does AI change inside a data centre?

Connect the compute system to power density, cooling, fibre and usable MW. This is the physical AIDC layer.

Learn AIDC →
04
GEOGRAPHY & POLICY

Why is China building compute in different places?

Learn 东数西算 — East Data, West Computing: the geography of demand, land, energy and workloads that can tolerate distance.

Learn East Data–West Computing →
05
NATIONAL ARCHITECTURE

How could separate compute resources become a more coordinated network?

Move from data-centre geography to 全国一体化算力网: visibility, interconnection, scheduling, settlement and the limits to true fungibility.

Learn the national compute network →
06
POWER & ENERGY

Can computing workloads respond to where electricity is available?

Learn how portable workloads, schedulers, data centres, grids, storage and renewable generation can potentially interact.

Learn compute–energy coordination →
07
SOFTWARE & ORCHESTRATION

What decides which computing resource does which job?

Finish with the control plane: the software problem of discovering, allocating and coordinating heterogeneous compute.

Learn orchestration →
PUT IT TOGETHER

You now have the pieces. See the complete system.

The research thesis asks whether these layers can be coordinated well enough that China competes more effectively at the level of useful system output — despite important component constraints. The architecture page shows our current answer; the research page shows the evidence that changes it.

HOW EVERY LESSON WORKS

Learn first.
Interrogate second.

1. Understand the problem. We begin with the real-world constraint rather than jargon.

2. Learn the mechanism. Technical terminology is introduced once you have a mental model for it.

3. Examine the evidence. Policy documents, company disclosures and observed implementation are kept distinct from our inference.

4. Know the limits. Every lesson states what the evidence does not yet prove and points you toward the next concept.

APPLY WHAT YOU LEARNED

Now interrogate a company announcement.

Practise separating reservations from delivered capacity, compatibility from orchestration, and policy connections from operating national coordination.