This week’s news reports highlighting the discovery of the “strongest evidence yet” of life on a distant planet, K2-18b, raise a number of pertinent questions. If life is confirmed there, what would be the next step? Should humans try to establish some sort of contact with these extraterrestrials once we know where they are?

The reports stem from a new paper based on the James Webb Space Telescope (JWST)’s detection of the spectral fingerprint of a single molecule, dimethyl sulfide, in the atmosphere of the exoplanet — that is, a planet which exists outside our solar system. This molecule is not a reliable biomarker according to another paper from earlier this year, which shows that it is found in the interstellar medium without the presence of life. On Earth, this molecule is produced by microorganisms in the oceans.

Inferences based on the detection of molecular biomarkers in the atmospheres of exoplanets are indirect. However, the detection of molecules associated with industrial pollution, such as chlorofluorocarbons (CFCs), will be far more indicative of intelligent life.

If we ever conclusively discover life on an exoplanet, we should definitely listen to any technological signals it transmits. But a dialogue would be challenging. K2-18b is 124 light years away: if we send a communication signal towards it right now, the earliest time we would receive a response at the speed of light would be in the year 2273. Humans, of course, are not that patient, and would love to learn more about the exoplanet through observation over the next two and half centuries.

The K2-18b reports coincide with another arresting bit of news, this time involving Michael Kratsios, the new director of the Office of Science and Technology Policy (OSTP) in the White House. On Monday Kratsios gave his first public talk in the role, remarking that “our technologies permit us to manipulate time and space.” This statement was part of a broader discussion on how regulatory frameworks since the Seventies have potentially hindered technological advancements, in which Kratsios suggested a wider reevaluation to enhance American productivity and innovation. Does this point to the US government possessing secret knowledge about how to manipulate spacetime, garnered from years of reverse engineering of alien spacecraft recovered on Earth?

The field equations formulated by Albert Einstein in 1915 may provide some answers to this troubling question. These equations relate the curvature of spacetime on their left-hand side to the mass or energy density of matter or radiation on their right-hand side. The distortions of time or space are minuscule unless one concentrates a huge amount of mass within a small volume. For example, the Sun distorts spacetime at a minuscule level of one part in 10^8 at the position of Earth. The resulting tiny curvature is sufficient to make the Earth move in a circle around the Sun.

When black holes with tens of solar masses collide at cosmological distances, they produce small ripples in spacetime near Earth, as first detected by the Laser Interferometer Gravitational-Wave Observatory (Ligo) in 2015. The immediate vicinity of black holes is characterised by large spacetime distortions, but the US government does not have access to such environments. We use Einstein’s equations to acquire precise navigation with GPS systems; if these equations were wrong, we would get lost.

What’s more, any experimentation by the US government does not reach the energy densities accessible at the European Organization for Nuclear Research (Cern)’s Large Hadron Collider by many orders of magnitude. This implies that if there is any new physics regarding the manipulation of spacetime, it would have been noticed in unclassified data shared by the international community of physicists at Cern. Secrets were leaked out of the Manhattan Project, and physicists worldwide would have known of any major advance in the theory of gravity.

If we ever learn how to bottle the “dark energy” which causes the accelerated expansion of the universe, we might have access to repulsive — as opposed to attractive — gravity that could propel a craft without fuel. Discovering a more advanced civilisation with this knowledge would unleash a new wave of American innovation, in line with Kratsios’s ambitions. But we have to find these alien technologies first. For that to happen, Nasa needs to allocate billions of dollars to the search for extraterrestrial technosignatures, rather than just investing in biosignatures. Hopefully, someone out there is listening.

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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