Analysis
Long-form essays on AI, engineering, and where technology is actually heading, with a running perspective on what Africa and China can learn from each other.
Filter by domain
Showing all 39 essays
China's education ministry revoked or suspended 12,200 undergraduate programme slots in five years and added 10,200. The number everyone repeated is real. What it means has been reported wrong.
Generic reasoning costs $0.05 per million tokens. The premium moved to what nobody wrote down: how one mould behaves, what a Lagos trader really charges, what a supplier means by 差不多.
Token prices are set in dollars while African revenue is set in naira, and tokenizers charge some African languages nine times more tokens for the same sentence. That maths decides viability, not mode
An engineer who stays in Lagos and works for a foreign employer is present but economically absent. The country keeps the person and loses the tax base, the mentorship and the firm never built.
Hyperscaler capex reached roughly $745bn for 2026 while the two largest labs run at about $105bn combined. The bubble is real. The compute will outlive it. An engineer's read from Shenzhen.
The weights are real and the licences are real, and they say different things. Read the Chinese announcement next to the English one and the gift starts to look like a distribution strategy.
The wrapper layer is gone. What survives is proprietary data, workflow depth, regulatory position and distribution, and the proof sits in Harvey's post-training run and a 180 million euro EU tender.
The label used to mean cheap and derivative. In batteries, solar, drones, robots and open-weight models it now marks the frontier. The perception lag is worth money to anyone testing on evidence.
An ageing workforce and an explicit industrial policy point the same direction. Beneath the humanoid demos sits a component supply chain that quietly changed hands: reducers, sensors, actuators.
Two randomized trials of AI-assisted developers reached opposite results. The difference was not the tool. It was how much of the task depended on context nobody had written down.
Chinese labs release open weights because a 2017 State Council plan told them to export standards rather than products, and because downloaded weights cannot be switched off by anyone.
Chinese firms built much of Africa's power and telecom. Now the AI models are Chinese and free, and free is a more durable form of influence than any loan.
AI writing detectors measure how predictable your prose is, which is a proxy for native fluency rather than for cheating. A watermark can prove a model was involved, never who wrote what.
Producing a function was never the scarce skill. Deciding what should exist, what breaks it and what the system costs in three years is the work, and none of that got cheaper when generation did.
Most organisations are staffed entirely at level one and are surprised when level three does not happen by itself. The four levels of AI fluency are separated by what you own when it breaks.
Four regimes, four instruments: a product safety file in Brussels, a court docket in Washington, a filing number in Beijing and a review date in Addis. The artefacts converge. The triggers do not.
Content Credentials prove a file's chain of custody. They do not prove a person made the decisions. Two very different products are being sold under one promise, at $10 and at $9,195.
Which AI models you may use is settled by export licences, regulatory filings, data residency rules and licence territory clauses. Capability is not a gate anywhere in that chain.
Judgment is manufactured in the boring ninety percent of junior work. Shut the intake now and the shortage lands in the mid-2030s, when nothing can fix it quickly.
Frontier models resolve about 95 percent of SWE-bench Verified and 20.6 percent of OSWorld 2.0. The gap is not noise. Step count, not task difficulty, is what still breaks agents in production.
The AI risks that dominate the global conversation are the ones that bite hardest in rich countries. From Lagos and Shenzhen the salient questions are language, price, labour and state capacity.
Robot governance is settled in ISO committees, insurer-funded biomechanics labs and tender documents, years before any parliament votes. In July 2026 the EU moved its own deadline to wait for the stan
Influence is rarely won by broadcasting. It is won by becoming infrastructure: the handset default, the network the engineers trained on, the standards seat, the freely licensed model weights.
China's mass AI adoption was manufactured by firms owning payments, delivery and a super-app, not by consumer curiosity. Subsidy bought usage. Whether it bought habit is a separate question.
Wheels are cheap per metre. Legs handle discontinuity. The hybrid tries to buy both and pays in actuators, distal mass and a switching problem. An engineer's account of when that trade is worth it.
The AI wins for a small business are boring: quoting, document extraction, translation for China trade. The waste is predictable: platforms bought before anyone defined the process.
Shenzhen stopped being cheap years ago. What it still sells is density: an iteration loop that runs in four days because the mould shop, the fab and the assembler are all inside an hour's drive.
Model collapse needs a replacement loop to happen. Keep a slice of real data and it stops. That caveat, not the doom headline, is what turned verifiable pre-2022 text into a priced asset.
Digitisation, digitalisation and digital transformation describe three different amounts of work. Most plants claim the third while doing the first, and that gap explains the disappointment.
Tencent QClaw's real move is distribution, not intelligence: an MIT-licensed runtime Tencent did not write, wrapped into a three-minute consumer install that executes on the user's own machine.
Seven inflection points, from the 2008 Beijing-Tianjin line to DeepSeek R1, read for what each revealed about how decisions get made in China and who paid the bill. Triumph and dismissal both miss.
Every general purpose technology took decades to show up in the productivity statistics, because the technology was never the bottleneck. Reorganising the work around it was.
AI efficiency has become a euphemism for cutting staff. That is the least imaginative use and the one with the worst evidence behind it. What the trials actually show, including the negative ones.
The argument about AI in education is being run as a cheating story. That is the least interesting version of it. Assessment was always measuring a proxy, and the proxy is what broke.
A 500Hz sensor in a football is a timestamping instrument, not a measuring one. What fusion actually buys you, and why clock alignment across devices breaks more systems than sampling rate ever does.
Forecasting gets the budget and moves the least. The gains that hold up in cross-border sourcing are duller: reading documents, watching lead times drift and shrinking the exception queue.
America's AI advantage was never producing the most talent, it was being the place talent had to go. DeepSeek showed that gravity can shift, and a downloadable model does not hand Africa a cluster.
How Artificial Intelligence Restructures Development Theory for Emerging Economies
Informal trade, smallholder yields and African-language speech mostly never become records. That missing measurement, not missing engineers, is what limits what can be built.
No articles found
Try a different filter.