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★★★★★ Pick of the week Added 02/11/2026
Following AI chips through customs: where the compute really goes
Where do the world's AI chips actually end up, when chipmakers and cloud companies rarely say? Isabel Juniewicz and Lucio Melito of Epoch AI build an answer from customs records in 16 major destinations, netting out transit hubs and adding chips made and used in China. Read it for the method as much as the results: it shows how far public trade data can go, and where it goes blind. We picked it because it is original data with its limits stated plainly. The piece launches Epoch's own data explorer, the only stake we found.
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★★★★☆ Added 02/11/2026
AI that works with people: a research agenda beyond full automation
Is building AI mainly a project of replacing human labour, or could research aim somewhere else? Gabriel Unger, an economist at Stanford's Digital Economy Lab, and Arvind Narayanan argue that computer science has drifted towards automation by habit as well as incentive, and sketch the technical problems that collaboration between people and AI would need solved. Read it for a positive programme, not another critique. We picked it because it engages the economics and the history of the field, not just the ethics. The authors argue from a stated position; their interest is academic, and we found no commercial stake.
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★★★★☆ Added 02/11/2026
An early-warning system for how people use chatbots
How would anyone know, early, that people were changing how they use chatbots in ways that might cause harm? Clara Collier, editor in chief of Asterisk, interviews Jessica Dai, a computer science PhD candidate at UC Berkeley whose team analysed three years of posts on the r/ChatGPT forum. Read it for a concrete picture of what an adverse event reporting system for AI could look like, and the practical obstacles in the way. We picked it for pairing a real dataset with a policy proposal. Dai is discussing the team's own paper; beyond that we found no stake.
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★★★★☆ Added 02/11/2026
Reading Beijing's signals before the next US-China AI dialogue
What does China actually want from the AI dialogue it agreed with Washington during Xi Jinping's state visit? Zichen Wang translates and annotates an article from Yuyuantantian, an outlet of China's state broadcaster that cites people on the Chinese negotiating side. Read it to see how Beijing frames AI risk differently from American safety circles, which issues it treats as ready for agreement, and what the article leaves unsaid. We picked it because it puts a Chinese-language policy signal in front of English readers with careful commentary. Wang writes the Pekingnology newsletter; we found no stake.
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★★★★☆ Added 02/11/2026
Open-weight AI from China: how Beijing weighs the risks
Chinese labs now release open models close to the American frontier. Does anyone in China worry about what criminals could do with them? Gabriel Wagner sets out the case against open weights, asks what evidence there is of real misuse, and quotes what Chinese standard-setters and regulators have actually written about the risk. Read it for a view of China's AI safety debate drawn from Chinese documents, which English-language coverage rarely uses. We picked it because it weighs both sides before reaching a view. Wagner works at Concordia AI, a Beijing-based AI safety advisory whose newsletter argues China takes safety more seriously than many think: a stake worth knowing.
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★★★★☆ Added 02/11/2026
Is China really spending half its AI on slop?
A viral claim says more than half of China's AI computing goes on cheap AI-made dramas and videos. Where did the figure come from, does it add up, and why did it sting so much? Zilan Qian traces the number back through investor calls and state media, checks it with rough arithmetic, then asks why a society so devoted to usefulness feels ashamed of its favourite entertainment. Read it for a debate that rarely reaches English, told from Chinese sources. We picked it for combining a careful fact-check with a real argument. Qian is a research scholar at GovAI who studies AI in China; we found no stake.
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★★★☆☆ Added 02/11/2026
What we lose when machines do our sensing for us
As phones and now AI take over navigating, remembering and choosing, what happens to the bodily skills those tasks used to build? Melanie Challenger argues that some technologies strengthen our capacities while others quietly replace the actions that form them, and draws on evolution and cognitive science to tell the two apart. Read it for a distinction worth applying to your own habits. We picked it as this issue's wildcard: a piece about AI that starts from the body rather than the model. Challenger writes from personal experience as well as research; we found no stake.
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★★★☆☆ Added 02/11/2026
A Chinese scholar's view of America's grip on data centres
Washington often worries that China is winning the AI race by building infrastructure abroad. How does the race look from Beijing? Jeffrey Ding translates and summarises an essay by a Peking University researcher who argues the opposite: American firms dominate the world's data centres through a hub-and-satellite system that leaves other countries carrying the costs. Read it for an argument Western readers rarely meet in its own words, with a link to the full translation. We picked it because it unsettles a common assumption about the AI race. Ding is an assistant professor of political science at George Washington University who translates Chinese writing on AI; we found no stake.
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★★★★★ Pick of the week Added 27/10/2026
How Chinese companies talk about recursive self-improvement
What do Chinese AI companies mean when they talk about AI improving itself? Zilan Qian and Cheryl Wu read about 1,400 company documents to find out. Read it to test the common story of a US-China race toward recursive self-improvement against what Chinese firms actually say. We picked it for original data on a question usually argued from assumptions. Qian and Wu write for Asterisk, a magazine on science and technology; we found no stake.
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★★★★★ Added 27/10/2026
MOFCOM's New Rules and the Future of Chinese AI
Will China's new export-control rules end the open release of its AI models? The ChinaTalk team, led by Quinn Ennis, spent three days on the commerce ministry's draft and explains what it would cover. Read it to understand a change that could reshape the open-model world, and the question still open at its centre. We picked it as a close reading of a primary text that most coverage only summarised. Ennis and colleagues write for ChinaTalk, a newsletter on China and technology; we found no stake.
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★★★★☆ Added 27/10/2026
A big-tent or small-tent AI safety movement?
Should the AI safety movement focus on extinction risk, or on the many smaller harms already in sight? Arvind Narayanan and Sayash Kapoor make the case for a broader movement while conceding much to the other side. Read it for a fair-minded argument that clarifies what the safety debate is really about. We picked it because it engages its opponents instead of caricaturing them. The authors are computer scientists known for scepticism about AI hype and existential risk, a position stated openly; we found no other stake.
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★★★★☆ Added 27/10/2026
The current balance of power in open models
Who leads in open AI models, the United States or China, and does it matter? Nathan Lambert sets out the evidence prepared for a briefing to members of Congress. Read it for a compact, numbers-led view of the open-model race and of what restricting Chinese models would cost. We picked it as a primary text from a policy briefing. Lambert builds open models for a living, a stake the piece discloses and readers should weigh.
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★★★★☆ Added 27/10/2026
OpenAI's ironic credibility problem
When OpenAI fired three safety researchers, how could anyone inside know the real reason? Dan Kagan-Kans does not try to settle who is right, and asks instead what the episode means for employees who may one day have to raise concerns. Read it for a sharp point about trust and verification inside AI labs. We picked it for turning a news story into a lasting question. Kagan-Kans writes for Understanding AI, a newsletter on AI and its effects; we found no stake.
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★★★★☆ Added 27/10/2026
Why humanoid robots won't catch up to human workers any time soon
Why do humanoid robots that dance and sprint still struggle to peel an orange? Kai Williams talked to many roboticists about the gap between viral demos and useful work. Read it to understand which problems are solved, which are not, and why the hard ones could take years. We picked it for deflating hype with reporting rather than opinion. Williams writes for Understanding AI; the piece carries a sponsorship from 80,000 Hours, a careers non-profit, and we found no stake in robotics.
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★★★★☆ Added 27/10/2026
What will happen to Indian IT?
What happens to the world's back office when AI can write code and answer calls? This Asterisk essay traces India's bet on exporting skilled labour, from IBM's exit in 1978 to an industry employing millions. Read it to understand how much of India's economy rests on an arbitrage that AI now undercuts. We picked it for a long view of a question usually asked only about Western jobs. The essay appears in Asterisk, a magazine on science and technology; the page we read does not name the author, and we found no stake.
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★★★★☆ Added 27/10/2026
The Lithography Lever
Where is the West's real leverage over China's AI chips? In this ChinaTalk interview, Jordan Schneider presses Nick Brown of the Center for Technology and Statecraft on lithography machines, compute estimates and the proposed MATCH Act. Read it for a detailed, numbers-first view of what export controls could still achieve and what they might provoke. We picked it for its depth on the one input that is hard to replace. Both argue for tighter export controls, a position stated openly; we found no other stake.
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★★★★☆ Added 19/10/2026
Open-weight models trail closed models in cyber capabilities by 6 to 7 months
Epoch’s own Cyber Capabilities Index puts the best open-weight model, Z.ai’s GLM-5.3, above OpenAI’s GPT-5.4 but still six to seven months behind the closed frontier, where Anthropic’s Claude Opus 5.5 and OpenAI’s GPT-6 Astra are tied. A concrete, regularly updated number for a question usually answered by vibes: how far behind is open-weight AI really, and in which capability.
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★★★★☆ Added 19/10/2026
BYD expands EV shipping fleet as wars upend freight costs and key trade routes
Reports that BYD is adding its own car-carrying ships because a global shortage of vessels, worsened by conflict-driven rerouting, is capping how many vehicles it can get out of China. A concrete look at how a carmaker ends up owning shipping capacity rather than buying it, and at war’s second-order effects on an industry that has nothing to do with the fighting itself.
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★★★★☆ Added 19/10/2026
Western open-weight models still can’t beat China
From a Rest of World San Francisco event, reports experts concluding that Chinese open-weight models now offer strong capability at lower cost than the nearest Western equivalents, even as the labs behind them struggle to turn that lead into revenue. Named, on-record disagreement rather than a single analyst’s take, on a question that keeps getting asserted rather than tested.
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★★★★☆ Added 19/10/2026
ASML Is Building a Hybrid Bonding Tool
Working from patent filings and ASML’s roadmap rather than any company announcement, argues ASML is quietly building a die-to-wafer hybrid bonding tool that would let it compete on alignment accuracy and particle control in advanced packaging, a segment currently led by Besi. Explicitly inference rather than confirmed disclosure, and paywalled past the open questions ASML still has to solve, but the underlying patent reading is the kind of groundwork most chip coverage skips.
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★★★★☆ Added 19/10/2026
The Case for DUV Controls
Saif Khan of the Center for Technology and Statecraft argues that halting exports of deep ultraviolet lithography tools, not the more publicised bans on leading-edge chips, is the lever that actually caps China’s long-run compute. His own modelling puts China’s ceiling at roughly ten million domestically made chips a year by the mid-2030s against a US figure near a billion H100-equivalents, though he flags wide error bars. Worth reading as the strongest case for a specific policy from someone who wants that policy adopted.
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★★★☆☆ Added 19/10/2026
Will developing nations be able to handle millions of AI agents?
Asks what happens when Meta’s and OpenAI’s new personal AI agents, trained mostly on wealthy-world data and behaviour, reach markets with different infrastructure, languages and family structures. Short on hard data by Rest of World’s usual standard, but the question itself, whether adoption outruns fit, is one the launch coverage skips entirely.
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★★★★★ Added 12/10/2026
Can AI automate AI R&D yet?
Epoch AI’s InnovationEval tests whether frontier models can independently devise a machine learning technique that matches one researchers already built by hand, and finds Claude Fable 5 and GPT-5.6 Sol reaching only 2 and 15 per cent of the original’s performance after correcting for selective reporting. A clean, well-controlled result against the claim that AI can already automate its own research pipeline.
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★★★★☆ Added 12/10/2026
US adults are no more likely to face cyber incidents than when Claude Fable 5 launched
Two Epoch AI/Ipsos surveys of US adults, three months apart, find no statistically detectable rise in people reporting a cyber incident even among heavy AI users, despite rising AI capabilities and vulnerability disclosures over the same period. Useful as a check on the gap between capability headlines and measured real-world harm, though it only captures what people notice, not what actually happened to them.
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★★★★☆ Added 12/10/2026
Conflict in the Red Sea is forcing cloud giants to find a new route for the internet
Reports that Google, Meta and Microsoft are paying premium rates for backup land routes as fighting near Yemen threatens the undersea cables that carry internet traffic between Europe and Asia through the Red Sea. A concrete case of a regional conflict reshaping the physical infrastructure of the global cloud, not just shipping and oil.
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★★★★☆ Added 12/10/2026
As U.S. blocks DJI, Insta360 races to win American creators
Reports how Insta360 and its drone brand Antigravity are gaining ground among American creators as clearer US rules against DJI create an opening, with Insta360’s cameras and drones now harder to avoid at the point where DJI used to dominate. A concrete look at how an export ban reshapes a market rather than just restricting one company.
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★★★★☆ Added 12/10/2026
How do Chinese AI companies make money?
Finds China’s six leading AI firms together earn roughly a tenth of what OpenAI and Anthropic pull in combined, with open-weight releases eroding the pricing power of firms that rely on API sales. Argues Alibaba and ByteDance likely do better than their AI revenue alone suggests, since cloud compute and advertising that AI supports are harder to measure separately.
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★★★★☆ Added 12/10/2026
Who is most exposed to a chip supply shock?
Epoch AI’s modelling finds China more exposed than the US to a combined Taiwan chip-supply shock and China-West trade decoupling, mainly because chips make up a larger share of the cost of what China imports. The exact margin is uncertain, but China comes out worse in every version of the model the authors tested.
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★★★★☆ Added 12/10/2026
Can AI automate Epoch?
Epoch AI turns its own research process into a test case, finding that frontier models such as Claude Fable 5.1 and GPT-6 Astra handle well-defined coding and analysis tasks reliably but fall down on open-ended work: learning house standards, designing informative experiments, judging flawed results. A rare instance of an AI research outfit testing whether the technology could already do its own job, and concluding it cannot.
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★★★★☆ Added 12/10/2026
The Spice Trader vs. the Tariffs
Interviews the co-founder of a small spice importer now suing over tariffs imposed under a trade statute, Section 301, he argues was never designed for this use, with forced-labour justifications that do not track actual labour-risk data by country. A rare worm’s-eye view of how sweeping tariff powers land on a bootstrapped business still waiting 12 to 18 months for its case to clear the courts while the tariffs keep getting collected.
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★★★★☆ Added 12/10/2026
Beijing Will Not Pace the Frontier: China’s Speed-First AI Safety Regime
Argues China’s AI safety rhetoric is some of the most forward-leaning of any government on paper, but its practice is speed-first: only 3.6 per cent of releases in the authors’ dataset come with a published safety evaluation, and regulation targets applications rather than frontier model capability itself. Paywalled beyond the opening section, but the data point alone is worth having.
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★★★☆☆ Added 12/10/2026
Not just AI. China is building technologies that challenge U.S. dominance
Adapted from Steve Feldstein’s book “Bytes and Bullets”, the piece argues China’s technology challenge to the US runs well beyond AI, into batteries, solar, drones and satellites, where Chinese firms already hold manufacturing and cost advantages. Useful for breadth, though it is a book excerpt rather than independent reporting, so treat the framing as the author’s own case.
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★★★☆☆ Added 12/10/2026
Anthropic Subscriptions Offer 5x+ More Value Than OpenAI
Argues that subscription plans matter disproportionately for AI lab margins despite being a small share of revenue, because they are heavily subsidised, and that a plan’s real value depends on the specific model and workload rather than the headline price. Finds Anthropic’s current plans give noticeably more value than OpenAI’s since OpenAI tightened its top-tier usage limits.
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★★★★★ Added 05/10/2026
Who gets to decide if AI is safe? Africa wants a say
African officials told the UN Security Council they want to help set AI safety standards rather than remain a testing ground for other countries’ models, with Kenya the only African state inside any international AI safety network. Documents concrete local harms, from an algorithm that raised health insurance costs for poor Kenyan households to Boko Haram’s own use of AI, that safety frameworks built for wealthy markets simply do not screen for.
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★★★★☆ Added 05/10/2026
The AI boom is making the world’s cheapest smartphones disappear
Traces a direct chain from Samsung, SK Hynix and Micron diverting memory chips to AI data centres through to a roughly 60 per cent year-on-year collapse in shipments of phones under $100, as manufacturers chase higher margins instead of the budget segment. Names the mechanism rather than just the price rise, and puts a number, about 800 million people, on who loses access as a result.
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★★★★☆ Added 05/10/2026
Awkward: Saudi Arabia’s new EV brand takes on the U.S. rival it already controls
Saudi Arabia’s sovereign wealth fund owns roughly 58 per cent of Lucid while simultaneously building Ceer, a domestic rival EV brand whose top model nearly matches Lucid’s flagship on power output, as Lucid’s Saudi sales and market value both slide. The more striking number is BYD’s: its Saudi sales rose 369 per cent over the same period, the competitor both Western and Gulf manufacturers are actually losing to.
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★★★★☆ Added 05/10/2026
AI companies want to embed safety evaluators, but countries need their own
Argues that letting AI companies design and run their own safety evaluations is itself a concentration-of-power risk, citing an OpenAI agent’s breach of an Australian healthcare database as a case safety testing built for Silicon Valley never anticipated. Reports that even Anthropic devotes only about a tenth of its training budget to security, and that poorer countries lack the technical capacity to build independent evaluation regimes of their own.
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★★★★☆ Added 05/10/2026
China’s AI Safety Money Problem
Argues China’s thin AI safety ecosystem is a funding problem rather than a political one, since the country’s 2016 charity and overseas NGO laws make independent, foreign-backed safety philanthropy almost impossible to run at scale. Puts a number on the gap, roughly $20 million a year domestically against over $1 billion globally, and surveys where safety work actually happens instead: state labs, universities and compliance-driven “safety as a service” firms.
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★★★★☆ Added 05/10/2026
How many AI agents could we run?
Estimates that the high-bandwidth memory shipped through 2027 could run somewhere between 33 million frontier-model agents and 1.9 billion agents on cheaper open models, equivalent to as many weekly working hours as 140 to 720 million full-time staff. Also shows the demand side lagging badly behind: using even a fifth of that capacity would cost $2.6 to $5.3 trillion a year in API terms, against roughly $1 trillion in projected developer revenue.
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★★★★☆ Added 05/10/2026
How GLM-5.3 Sparse Attention Affects HBM Memory Usage
Shows that sparse attention cuts compute bandwidth but not memory capacity, since picking the top tokens still needs the full context sitting in HBM, and walks through how GLM-5.3 and the SGLang team’s cache-offloading system work around that limit. Finds the resulting setup genuinely cheaper per token on Nvidia hardware but still slow to produce a first response, a trade-off the piece treats as unresolved rather than solved.
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How we rate
How the stars work
★★★★★ Original reporting or data, explains a mechanism, argues fairly.
★★★★ Excellent, one soft spot: a frame, narrow scope, or an interview.
★★★ Solid, if the subject already interests you.
Rated on the piece, never its politics. A frame tag, in italics, names the position a piece argues from so you can weigh it before you read.