The publishing industry doesn’t mind disgracing itself; and authors far downstream of the churn of philistine mass-market books can only be grateful for the subsidy we receive from bestsellers. There is no general or common reader in the sense that Virginia Woolf referred to; we have consumerist readers who must pick from brightly-colored, similar IRL-clickbait-bookish items. This is the general law of publishing in this decade and, largely, this century.

The unholy alliance, announced this week — and covered breathlessly by the New York Times — between YouTuber Mr Beast (otherwise known as Jimmy Donaldson) and author James Patterson is not only a vivid reminder of how stupid books have to be to sell. It’s also a reminder of the larger move by the Big Five publishers to recapture the attention of male readers, who have stopped buying books, ironically, in favor of video content like Mr Beast’s.

What Mr Beast and James Patterson share, even more tellingly, is a preoccupation with understanding the cognitive mechanics of attention, and the storytelling algorithms which capture attention. Patterson is to thrillers what Mr Beast is to YouTube: they are masters of mental meth, of the dopamine hit. It is not surprising that, according to the New York Times, Patterson is one of Donaldson’s favorite writers (where Chaucer does land in the Beast literary canon?).

The Beast click-machine will pay editors’ salaries, even if his fee is rumored to be around the eight-figure mark. And yet those resources will be funneled into giant swings and misses on advances for other mega-sellers as the industry gambles with its house money. The Beast-Patterson windfall will not, I suspect, encourage HarperCollins editors and their corporate publisher overlords to invest in young or overlooked writers, in translations of difficult international masters — let alone the under-published genres of poetry, drama or philosophy.

Mr Beast could do more for literature if he told his online audience to read difficult, serious books, old and new. The honorable thing would be to spend the attention-capital he’s accrued by developing a science of attention-hacking and spend it on what’s left of intelligent culture. Like a land developer who has razed a row of old houses in a dying town, Mr Beast could offer to save those that remain. So could Patterson. But, of course, that’s not how things work.

The degree to which Mr Beast’s young click-addict audience will transfer to books is, as the NYT notes, unclear; but if even a fraction of his 500 million followers buy his book, it will be a major windfall for a large corporate publisher like HarperCollins. The Leviathan works best at scale.

For adults who still idealize the possibilities of the book, who still live on a dying star in the Gutenberg Galaxy, who still imagine that a book might edify, inform, imbue with wisdom, hone the mind’s wit, the only possible — and dignified — response is scorn. Spiritual rebellion against slop and attention-hacking is in order. If you’re reading this, if you’ve read other press about the Unholy Alliance, buy a different book, from a different kind of publisher, for the sake both of your cultural soul and the culture itself.

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Matthew Gasda is a playwright, author, and columnist for UnHerd, based in New York City.

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China is trying to catch up with America on artificial intelligence. The Wall Street Journal has reported that Zhipu AI — one of China’s six “AI tiger” LLMs — has released a new model that can rival leading US systems, including Anthropic’s Mythos, in cybersecurity tasks such as pinpointing security bugs. While this marks a milestone in China’s drive to catch up with Western AI capabilities, strong performance on a single benchmark does not mean it has taken the lead. Chinese models still lag behind their Western counterparts in broader capabilities, such as autonomous operation. Skepticism is therefore warranted before resorting to hysterical conclusions, but complacency about the geopolitical implications of China’s AI advances would be an even greater mistake.

On the infrastructure side, Chinese AI is still constrained by access to advanced chips, with American labs way ahead in computing capacity as well as investment. Analysis from earlier this year suggests that Chinese models are likely to be at least a few months behind those in the US. But they are still continuing to make progress, or that the geopolitical importance of AI will be decided only by whose LLM has ventured deeper into the technological frontier. The practical applications of AI, countries’ to capture foreign markets, and the application of AI into the real economy will matter just as much.

Here, China may hold an advantage. As with its dominance across many critical supply chains, Beijing may not need to produce the most advanced AI systems — only those that are affordable and widely deployable. In doing so, it could consolidate global influence by supplying functional, low-cost AI at scale.

Beijing seems to be pursuing exactly that path, developing an AI “open-source” strategy that offers affordable, widely available AI models for companies and individuals to use and modify as they wish. The production of the DeepSeek AI model, which matched the performance of Silicon Valley tools such as ChatGPT at a fraction of the cost for users, created goodwill among Chinese models with developers.

The four most popular models on OpenRouter, an AI hardware platform for developers, are now all Chinese. The goal for China is not only to win the frontier-model race, but to make its systems the default layer of AI adoption across industries and global markets. For most economies, the choice is increasingly between an affordable tool they can deploy now and a more robust one that may be out of reach.

And while the countries adopting Chinese models may be exposed to political pressure and cyber threats from Beijing, safer and more capable alternatives matter little if they are unaffordable. American AI companies are already under pressure to monetize products whose operating costs are rising. If Chinese open-source models become the cheap default for startups, universities, governments and businesses across the developing world, then America’s AI lead will be eroded from below.

Perhaps more concerning for America in the long run is how AI can give Chinese manufacturing even more strength, through the ongoing integration of AI as a general-purpose technology. China’s new Five-Year Plan mentioned AI more than 50 times and includes an “AI+” action plan aimed at spreading AI across the economy.

Beijing has been pioneering automation of its critical infrastructure for years, with promising recent results in increasing warplane production capacity. In that regard, China’s open-model strategy and manufacturing dominance will reinforce each other. Cheap, adaptable models accelerate deployment across the real economy while those deployments generate real-world data and use cases that can feed back into further model improvement.

The United States should not dismiss the importance of its lead in the AI race. That lead worries Beijing, not least because a more automated Chinese economy would also become more vulnerable to AI-generated cyber threats. But nor should Washington assume that China cannot catch up with American capabilities over time.

This AI competition represents part of a broader struggle over tech supply chains and geopolitical influence. Decisions over whether to adopt US or Chinese models could produce a more fragmented global reality, with different regions relying on different cloud providers, chips and security structures. The result will likely be a global economy which is divided into competing spheres, rather than one which produces a single winner.

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Miquel Vila is a political and geopolitical risk consultant focusing on industrial strategy, critical infrastructure and global supply chains.

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