This week, the National Gallery made an eye-popping announcement that it has secured £375 million of philanthropic funding to launch a hugely ambitious expansion of its site on Trafalgar Square. But “Project Domani” is not just an architectural expansion. Breaking a previously unwritten rule established in the Nineties, the new wing will host art created after 1900 in a move that steps on the Tate’s toes.

The National Gallery’s director, Gabriele Finaldi, wants the institution to tell the story of modern art. “The story of painting is a continuum,” the gallery announcement declares, “and that is why it is necessary for the National Gallery to continue to evolve and extend the story it tells.” The National Gallery and the Tate, we’re told, have established a historic new partnership which will see the two galleries “working together to build and further develop the UK’s world-leading national collection for the benefit of everyone”.

Senior cultural establishment figures tend not to have arguments in public about each others’ institutions, of course. Speaking on the BBC’s Today program earlier this week, Finaldi was at pains to emphasize that, really, there’s overlap between the two collections, that the 1900 cut-off isn’t so hard-and-fast. But the National Gallery’s new project is inevitably a power play over who is going to lead the way in the national collections of visual art, at a moment when the institutions are grappling with the public’s changing relationship to art in the digital age.

The Tate’s recent visitor number troubles are much argued over — it’s really Brexit and Covid’s fault, says the institution. But in terms of raw visitor numbers the National Gallery, even with its classical and Renaissance and painting-only remit, mostly matched Tate Modern year-on-year until the pandemic. People like the old stuff as much as the new. Meanwhile, Tate Britain has seen a long-term decline in visitors to its Millbank site, its take on the story of British art having become a downbeat lecture on decolonization.

So, for all the back-patting and talk of collaboration, the National Gallery’s move is significant and, undeniably, self-interested. But it also raises sincere questions that modern Britain hasn’t had an explicit conversation about. How should our collections and taxpayer funds be used to keep them be divided between historical and contemporary art? What is the difference between “British” and “foreign” art, and which ought we to prefer?

Unlike the National Gallery’s more coherent map of European painting to 1900, the Tate’s collection is the mixed-up outcome of a hundred years of trying to platform modern British art as a thing distinct from “modern art” as a whole. At first the “National Gallery of British Art”, in 1926 the Tate became the place to show the “modern foreign art” embodied by the French Impressionists. Postwar, the Tate — by then independent of the National Gallery, which had previously run it — collected a lot of modern British art, the foreign stuff less so, continuing this insular outlook until Nicholas Serota, ardent advocate of European and American contemporary art, started to backfill the gaps during his long tenure.

Trying to sort out this bolted-together, confused remit, Serota split the collection between the new Tate Modern and the renamed Tate Britain at Millbank. But the split never quite worked. During the years of ever-increasing globalization from around the turn of the century to Brexit, the global contemporary art-friendly Tate Modern was a raging success, while Tate Britain languished as the underdog, its curators increasingly embarrassed by the old stuff. Hip British artists were not always too keen to be labeled as boring old “British”. The question that has haunted Tate Britain since is: what is so important about British art anymore? In a Left-leaning art world filled with the guilt of Empire, that answer has usually been: “nothing much”.

And now that the 20th century is ancient history, the National Gallery clearly no longer sees the Tate’s claim to “modern” as exclusive. Behind the cordial words of collaboration, one institution is making a play to be the home of all art in Britain. The one with £375 million in the bank is always likely to prevail over the one running a deficit.

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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