Kian Sadeghi was 25 years old when he decided to monetize human evolution. His company, Nucleus Genomics, charges parents $5,999 to rank their IVF embryos across 900 different traits: everything from projected IQ and height to cancer risk and probable lifespan. The Wall Street Journal reported on it this week and the company has been trending on X as a result, with tech bros and longevity enthusiasts celebrating what some see as the next frontier in human optimization.

The pitch is straightforward enough. Upload your embryos’ genetic data, and Nucleus will score each one like a used car listing. Want a tall child with low Alzheimer’s risk? That’s embryo number three. Prefer high IQ with good cardiovascular odds? Try number seven. As Sadeghi puts it, parents can now “select the future of your bloodline with a dashboard.”

This isn’t some distant sci-fi scenario. Nucleus has already analyzed 120,000 embryos through its partnership with Genomic Prediction. The technology seems to work, the market exists, and Peter Thiel’s Founders Fund has written some of the checks. While 23andMe collapses under the weight of its own data-privacy scandals, modest data output, and overall unprofitable business model, this next-generation genetic company is selling something far more consequential than ancestry reports and basic medical information.

Sadeghi speaks fluently in Silicon Valley’s language of disruption and optimization. At longevity conferences, he frames embryo selection as “debugging genetic code” and “taking medicine back and putting it in people’s hands”. This rhetoric transforms profound ethical questions into technical problems, as if selecting human traits were no different from choosing iPhone features.

What strikes me about Sadeghi’s venture isn’t the technology itself, given that embryo screening for Down syndrome and Tay-Sachs has been standard practice for years (albeit controversial in some circles). It’s the brazen expansion into polygenic traits like intelligence and longevity, coupled with Silicon Valley’s trademark certainty that disrupting natural selection is just another optimization problem. The company provides “probability assessments” for IQ, though they admit these predictions have limited accuracy.

Limited or not, some rich family will buy it anyway. After all, if you could reduce your child’s cancer risk by 20%, why wouldn’t you? If one embryo projects to live five years longer than another, what kind of parent would choose the shorter-lived option? Each individual decision makes perfect sense. Yet collectively, we’re engineering something unprecedented: a society where genetic advantages could compound across generations like interest in a trust fund.

Unlike previous aristocracies based on land or titles, genetic advantages can’t be redistributed through revolution or reform. The Romanovs’ hemophilia and the Habsburgs’ innumerable ailments reminds us that even royal bloodlines were subject to genetic bad luck. But when intelligence, health and longevity become purchasable commodities, class mobility shifts from difficult to biologically impossible. Two generations from now, the children of parents who could afford comprehensive embryo selection might form a literally different breed of human — systematically taller, smarter, healthier and longer-lived than the rest.

There’s a deeper irony here that the longevity crowd seems to miss. Natural genetic diversity is a feature, not a bug. Random variation serves as insurance against unforeseen challenges, whether new diseases, environmental changes or other selective pressures we haven’t imagined. When wealthy families all select for similar “optimal” traits, they’re creating genetic monocultures. We’ve seen what happens to specialized dog breeds. There, the very traits that win pageants often create health vulnerabilities.

Besides, Darwinian survival isn’t about living longest. It’s about producing the most offspring who themselves reproduce successfully. The couple who uses Nucleus to select their perfect embryo might get three genetically optimized children from multiple rounds of IVF, although it bears noting that this is an invasive procedure requiring significant egg harvesting. Meanwhile, their less affluent neighbors might have five kids the old-fashioned way. Which family wins the evolutionary game?

The regulatory landscape here in the US is essentially non-existent. While the EU has wisely set strict limits on genetic selection in its Charter of Fundamental Rights, America treats embryo ranking like any other consumer choice.

Unless this proves to be another startup failure like 23andMe and Theranos, it could represent the quiet birth of humanity’s first permanent caste system, where class lines get encoded directly into DNA. The train is already leaving the station, and it only goes in one direction. Those who can afford a ticket will board. The rest, unable to avail themselves of the sort of “Intelligent Design” previously reserved to an omnipotent creator, will watch their children fall further behind with each passing generation.

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Oliver Bateman is a historian and journalist based in Pittsburgh. He blogs, vlogs, and podcasts at his Substack, Oliver Bateman Does the Work

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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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