What’s better than artificial intelligence? Why, Personal Superintelligence, of course. Meaning, technology that’s more intelligent than a human, but also serving humans. That’s what Meta (the company behind Facebook, Instagram, and WhatsApp) has announced it’s working on.

Mark Zuckerberg is serious about Meta Superintelligence Labs (MSL). In recent months, he has hired some of the biggest AI guns, poaching top talent from most of his rival AI giants with huge salary offers. He also has the advantage of vast troves of data that Meta already has on individuals, collected whenever we interact with their services, or even with apparently unrelated online activities. The files of data it holds on most of the world’s population — even those without Facebook accounts — underlie the personalised advertising which is Meta’s main source of income. And this is key to the “personal” bit of Personal Superintelligence.

Mark Zuckerberg’s vision is of “everyone having a personal superintelligence that helps you achieve your goals, create what you want to see in the world, experience any adventure, be a better friend to those you care about, and grow to become the person you aspire to be”.

This sounds suspiciously like the kind of AI chatbot assistant that Meta — along with other technology companies — is already rolling out on your laptop or smartphone.  But it is also a canny business move, distinguishing Meta’s project from centralised AI models. Zuckerberg’s announcement letter invokes the dystopian vision of a world where AI has taken everyone’s jobs, and we “live on a dole of its output,” in his words. Instead, he promises, each of us will have a personal superintelligence “that knows us deeply, understands our goals, and can help us achieve them”.

Whether a machine can ever know a person, or understand human goals, is very doubtful, but Meta’s AI will have a great deal of data to help. Interacting with an AI personal assistant will not only add to the in-depth information Meta holds, but also create a feeling of trust, potentially laying the user open to influence on what to buy, how to behave, or even what to believe.

The goal of AI that can out-think humans has haunted and driven technologists for many years. Alongside the heady promise of a human-created being that outstrips its creators run the fears of such a powerful technology escaping human control. Given our limited understanding of our own minds, it is hubristic to imagine we can create Artificial General Intelligence — a machine that matches and surpasses human thinking — but in many specific areas AI already out-performs humans. You don’t need to believe in a synthetic mind superior to our own, to see the potential power of AI.

One of Meta’s new hires to lead the Superintelligence Lab, Alexandr Wang, with ex-Google CEO Eric Schmidt and Dan Hendrycks of the Centre for AI Safety, recently published a paper comparing superintelligence to nuclear weapons. Governments already recognise its importance, strategically as well as economically. The race for ever-faster, ever-smarter AI is global.

To this competition, Meta brings intellectual firepower, the physical infrastructure of computing power, and the resource of massive banks of data on which to train AI models. It could soon be launching its Personal Superintelligence in a device near you. But in spite of the massive investment in people, computing power, and data processing, it’s still not clear what makes it qualitatively different from existing AI assistants. Faster, less prone to hallucinations and stupid mistakes, and equipped with astonishingly intimate details of your life, yes. Smarter than a human? No.

Mark Zuckerberg calls it “a tool for personal empowerment”, an AI that will help you instead of taking your place. But, like so many of Meta’s activities, it’s not clear whether we, the users, are intended to be the customers, or merely the audience for an advertising platform more personalised, and more all-pervading, than ever before. If you thought Facebook knew too much about your habits, friends, and innermost thoughts before, just wait till your entire digital life is being lived through a personal AI assistant, “superintelligent” or not.

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Timandra Harkness presents the BBC Radio 4 series, FutureProofing and How To Disagree. Her book, Technology is Not the Problem, is published by Harper Collins.

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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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