Andy Burnham has decisively won the Makerfield by-election, and will return to the Commons after almost a decade away. Barring an upset on the scale of the 2017 Tory campaign, he looks set to be Britain’s next prime minister — at least until the next general election. Although he is touted by hopeful Labour MPs as the only man who can restore Labour’s fortunes, his star was already dimming before he even secured his seat: the more the public see of Burnham, the less they seem to like him.

While the next general election is still Nigel Farage’s to lose, Reform UK activists in Makerfield had been worried by a new spectre haunting the Right: Rupert Lowe and his Restore Britain party. Both outfits sit to the Right of the Conservatives, and their differences are rooted more in personalities and egos than fundamental policies. Restore is more hardline on immigration and more free-market on economics, but both parties are pulling in the same direction.

The logic seemed simple: by outbidding Reform, Restore would poach Right-wing voters, splitting the vote and allowing other parties to come through the middle. Lowe’s party has little realistic chance of winning any seats, so all it is doing is holding back the Right more broadly.

Ultimately, talk of Restore Britain splitting the Right-wing vote proved overblown: Burnham won with 55%, to Reform’s 35% and Restore’s 7%. While the result is no doubt a disappointment for Farage, there is a silver lining: Lowe is not the serious threat to Reform’s Right flank that many feared. Restore’s result in Makerfield shows the limits of its appeal. The party threw everything at this by-election, being the first to announce a candidate and reportedly having hundreds of activists in the seat on polling day, only to win 7% of the vote. As tactical voting becomes ever more important, Reform will use this result as a clear signal to voters: it is pointless voting for a minor party.

Although polling covering Restore is scant, some does exist. National polling carried out in April by Find Out Now — albeit commissioned by Restore Britain — put the new party on 9%, picking up support from 27% of 2024 Reform voters. Constituency polling, with smaller samples and bigger margins of error, found that around 40-50% of 2024 Makerfield Reform voters would back Restore. If this is accurate, the split could make the difference between first and second place in a handful of seats, handing victories to Left-wing parties.

Things are not quite as bad as they seem for Farage, however. First, in polls not commissioned by Restore, the party tends to get around 2-4%, meaning its absolute impact is likely to be negligible. Second, the losses Reform faces to Restore are more than made up for by the fact that Farage’s party is winning over those who did not vote in 2024, as well as a solid chunk of 2024 Conservative voters.

Besides, Makerfield was a by-election. Fighting a single seat is fundamentally different to fighting 650 separate contests, alongside the logistical organisation that goes with it. It is telling, for instance, that Restore did not stand a candidate in either of the two Scottish by-elections which took place yesterday, but Reform did.

Restore still poses some threat to Farage, and if the new party survives to the next general election it could cost Reform a few seats across the country. But Lowe’s party remains a primarily online phenomenon, and Makerfield has shown that Restore’s bark is worse than its bite.

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David Jeffery is a lecturer in British Politics at the University of Liverpool.

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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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