Stay Ahead, Stay ONMINE

The race to make the perfect baby is creating an ethical mess

Consider, if you will, the translucent blob in the eye of a microscope: a human blastocyst, the biological specimen that emerges just five days or so after a fateful encounter between egg and sperm. This bundle of cells, about the size of a grain of sand pulled from a powdery white Caribbean beach, contains the coiled potential of a future life: 46 chromosomes, thousands of genes, and roughly six billion base pairs of DNA—an instruction manual to assemble a one-of-a-kind human. Now imagine a laser pulse snipping a hole in the blastocyst’s outermost shell so a handful of cells can be suctioned up by a microscopic pipette. This is the moment, thanks to advances in genetic sequencing technology, when it becomes possible to read virtually that entire instruction manual. An emerging field of science seeks to use the analysis pulled from that procedure to predict what kind of a person that embryo might become. Some parents turn to these tests to avoid passing on devastating genetic disorders that run in their families. A much smaller group, driven by dreams of Ivy League diplomas or attractive, well-behaved offspring, are willing to pay tens of thousands of dollars to optimize for intelligence, appearance, and personality. Some of the most eager early boosters of this technology are members of the Silicon Valley elite, including tech billionaires like Elon Musk, Peter Thiel, and Coinbase CEO Brian Armstrong.  Embryo selection is less like a build-a-baby workshop and more akin to a store where parents can shop for their future children from several available models—complete with stat cards. But customers of the companies emerging to provide it to the public may not be getting what they’re paying for. Genetics experts have been highlighting the potential deficiencies of this testing for years. A 2021 paper by members of the European Society of Human Genetics said, “No clinical research has been performed to assess its diagnostic effectiveness in embryos. Patients need to be properly informed on the limitations of this use.” And a paper published this May in the Journal of Clinical Medicine echoed this concern and expressed particular reservations about screening for psychiatric disorders and non-­disease-related traits: “Unfortunately, no clinical research has to date been published comprehensively evaluating the effectiveness of this strategy [of predictive testing]. Patient awareness regarding the limitations of this procedure is paramount.”     Moreover, the assumptions underlying some of this work—that how a person turns out is the product not of privilege or circumstance but of innate biology—have made these companies a political lightning rod.  SELMAN DESIGN As this niche technology begins to make its way toward the mainstream, scientists and ethicists are racing to confront the implications—for our social contract, for future generations, and for our very understanding of what it means to be human. Preimplantation genetic testing (PGT), while still relatively rare, is not new. Since the 1990s, parents undergoing in vitro fertilization have been able to access a number of genetic tests before choosing which embryo to use. A type known as PGT-M can detect single-gene disorders like cystic fibrosis, sickle cell anemia, and Huntington’s disease. PGT-A can ascertain the sex of an embryo and identify chromosomal abnormalities that can lead to conditions like Down syndrome or reduce the chances that an embryo will implant successfully in the uterus. PGT-SR helps parents avoid embryos with issues such as duplicated or missing segments of the chromosome. Those tests all identify clear-cut genetic problems that are relatively easy to detect, but most of the genetic instruction manual included in an embryo is written in far more nuanced code. In recent years, a fledgling market has sprung up around a new, more advanced version of the testing process called PGT-P: preimplantation genetic testing for polygenic disorders (and, some claim, traits)—that is, outcomes determined by the elaborate interaction of hundreds or thousands of genetic variants. In 2020, the first baby selected using PGT-P was born. While the exact figure is unknown, estimates put the number of children who have now been born with the aid of this technology in the hundreds. As the technology is commercialized, that number is likely to grow. Embryo selection is less like a build-a-baby workshop and more akin to a store where parents can shop for their future children from several available models—complete with stat cards indicating their predispositions. A handful of startups, armed with tens of millions of dollars of Silicon Valley cash, have developed proprietary algorithms to compute these stats—analyzing vast numbers of genetic variants and producing a “polygenic risk score” that shows the probability of an embryo developing a variety of complex traits.   For the last five years or so, two companies—Genomic Prediction and Orchid—have dominated this small landscape, focusing their efforts on disease prevention. But more recently, two splashy new competitors have emerged: Nucleus Genomics and Herasight, which have rejected the more cautious approach of their predecessors and waded into the controversial territory of genetic testing for intelligence. (Nucleus also offers tests for a wide variety of other behavioral and appearance-related traits.)  The practical limitations of polygenic risk scores are substantial. For starters, there is still a lot we don’t understand about the complex gene interactions driving polygenic traits and disorders. And the biobank data sets they are based on tend to overwhelmingly represent individuals with Western European ancestry, making it more difficult to generate reliable scores for patients from other backgrounds. These scores also lack the full context of environment, lifestyle, and the myriad other factors that can influence a person’s characteristics. And while polygenic risk scores can be effective at detecting large, population-level trends, their predictive abilities drop significantly when the sample size is as tiny as a single batch of embryos that share much of the same DNA. The medical community—including organizations like the American Society of Human Genetics, the American College of Medical Genetics and Genomics, and the American Society for Reproductive Medicine—is generally wary of using polygenic risk scores for embryo selection. “The practice has moved too fast with too little evidence,” the American College of Medical Genetics and Genomics wrote in an official statement in 2024. But beyond questions of whether evidence supports the technology’s effectiveness, critics of the companies selling it accuse them of reviving a disturbing ideology: eugenics, or the belief that selective breeding can be used to improve humanity. Indeed, some of the voices who have been most confident that these methods can successfully predict nondisease traits have made startling claims about natural genetic hierarchies and innate racial differences. What everyone can agree on, though, is that this new wave of technology is helping to inflame a centuries-old debate over nature versus nurture. The term “eugenics” was coined in 1883 by a British anthropologist and statistician named Sir Francis Galton, inspired in part by the work of his cousin Charles Darwin. He derived it from a Greek word meaning “good in stock, hereditarily endowed with noble qualities.” Some of modern history’s darkest chapters have been built on Galton’s legacy, from the Holocaust to the forced sterilization laws that affected certain groups in the United States well into the 20th century. Modern science has demonstrated the many logical and empirical problems with Galton’s methodology. (For starters, he counted vague concepts like “eminence”—as well as infections like syphilis and tuberculosis—as heritable phenotypes, meaning characteristics that result from the interaction of genes and environment.) Yet even today, Galton’s influence lives on in the field of behavioral genetics, which investigates the genetic roots of psychological traits. Starting in the 1960s, researchers in the US began to revisit one of Galton’s favorite methods: twin studies. Many of these studies, which analyzed pairs of identical and fraternal twins to try to determine which traits were heritable and which resulted from socialization, were funded by the US government. The most well-known of these, the Minnesota Twin Study, also accepted grants from the Pioneer Fund, a now defunct nonprofit that had promoted eugenics and “race betterment” since its founding in 1937.  The nature-versus-nurture debate hit a major inflection point in 2003, when the Human Genome Project was declared complete. After 13 years and at a cost of nearly $3 billion, an international consortium of thousands of researchers had sequenced 92% of the human genome for the first time. Today, the cost of sequencing a genome can be as low as $600, and one company says it will soon drop even further. This dramatic reduction has made it possible to build massive DNA databases like the UK Biobank and the National Institutes of Health’s All of Us, each containing genetic data from more than half a million volunteers. Resources like these have enabled researchers to conduct genome-wide association studies, or GWASs, which identify correlations between genetic variants and human traits by analyzing single-nucleotide polymorphisms (SNPs)—the most common form of genetic variation between individuals. The findings from these studies serve as a reference point for developing polygenic risk scores. Most GWASs have focused on disease prevention and personalized medicine. But in 2011, a group of medical researchers, social scientists, and economists launched the Social Science Genetic Association Consortium (SSGAC) to investigate the genetic basis of complex social and behavioral outcomes. One of the phenotypes they focused on was the level of education people reached. “It was a bit of a phenotype of convenience,” explains Patrick Turley, an economist and member of the steering committee at SSGAC, given that educational attainment is routinely recorded in surveys when genetic data is collected. Still, it was “clear that genes play some role,” he says. “And trying to understand what that role is, I think, is really interesting.” He adds that social scientists can also use genetic data to try to better “understand the role that is due to nongenetic pathways.” Many on the left are generally willing to allow that any number of traits, from addiction to obesity, are genetically influenced. Yet heritable cognitive ability seems to be “beyond the pale for us to integrate as a source of difference.” The work immediately stirred feelings of discomfort—not least among the consortium’s own members, who feared that they might unintentionally help reinforce racism, inequality, and genetic determinism.  It’s also created quite a bit of discomfort in some political circles, says Kathryn Paige Harden, a psychologist and behavioral geneticist at the University of Texas in Austin, who says she has spent much of her career making the unpopular argument to fellow liberals that genes are relevant predictors of social outcomes.  Harden thinks a strength of those on the left is their ability to recognize “that bodies are different from each other in a way that matters.” Many are generally willing to allow that any number of traits, from addiction to obesity, are genetically influenced. Yet, she says, heritable cognitive ability seems to be “beyond the pale for us to integrate as a source of difference that impacts our life.”  Harden believes that genes matter for our understanding of traits like intelligence, and that this should help shape progressive policymaking. She gives the example of an education department seeking policy interventions to improve math scores in a given school district. If a polygenic risk score is “as strongly correlated with their school grades” as family income is, she says of the students in such a district, then “does deliberately not collecting that [genetic] information, or not knowing about it, make your research harder [and] your inferences worse?” To Harden, persisting with this strategy of avoidance for fear of encouraging eugenicists is a mistake. If “insisting that IQ is a myth and genes have nothing to do with it was going to be successful at neutralizing eugenics,” she says, “it would’ve won by now.” Part of the reason these ideas are so taboo in many circles is that today’s debate around genetic determinism is still deeply infused with Galton’s ideas—and has become a particular fixation among the online right.  SELMAN DESIGN After Elon Musk took over Twitter (now X) in 2022 and loosened its restrictions on hate speech, a flood of accounts started sharing racist posts, some speculating about the genetic origins of inequality while arguing against immigration and racial integration. Musk himself frequently reposts and engages with accounts like Crémieux Recueil, the pen name of independent researcher Jordan Lasker, who has written about the “Black-White IQ gap,” and i/o, an anonymous account that once praised Musk for “acknowledging data on race and crime,” saying it “has done more to raise awareness of the disproportionalities observed in these data than anything I can remember.” (In response to allegations that his research encourages eugenics, Lasker wrote to MIT Technology Review, “The popular understanding of eugenics is about coercion and cutting people cast as ‘undesirable’ out of the breeding pool. This is nothing like that, so it doesn’t qualify as eugenics by that popular understanding of the term.” After going to print, i/o wrote in an email, “Just because differences in intelligence at the individual level are largely heritable, it does not mean that group differences in measured intelligence … are due to genetic differences between groups,” but that the latter is not “scientifically settled” and “an extremely important (and necessary) research area that should be funded rather than made taboo.” He added, “I’ve never made any argument against racial integration or intermarriage or whatever.” X and Musk did not respond to requests for comment.) Harden, though, warns against discounting the work of an entire field because of a few noisy neoreactionaries. “I think there can be this idea that technology is giving rise to the terrible racism,” she says. The truth, she believes, is that “the racism has preexisted any of this technology.” In 2019, a company called Genomic Prediction began to offer the first preimplantation polygenic testing that had ever been made commercially available. With its LifeView Embryo Health Score, prospective parents are able to assess their embryos’ predisposition to genetically complex health problems like cancer, diabetes, and heart disease. Pricing for the service starts at $3,500. Genomic Prediction uses a technique called an SNP array, which targets specific sites in the genome where common variants occur. The results are then cross-checked against GWASs that show correlations between genetic variants and certain diseases. Four years later, a company named Orchid began offering a competing test. Orchid’s Whole Genome Embryo Report distinguished itself by claiming to sequence more than 99% of an embryo’s genome, allowing it to detect novel mutations and, the company says, diagnose rare diseases more accurately. For $2,500 per embryo, parents can access polygenic risk scores for 12 disorders, including schizophrenia, breast cancer, and hypothyroidism.  Orchid was founded by a woman named Noor Siddiqui. Before getting undergraduate and graduate degrees from Stanford, she was awarded the Thiel fellowship—a $200,000 grant given to young entrepreneurs willing to work on their ideas instead of going to college—back when she was a teenager, in 2012. This set her up to attract attention from members of the tech elite as both customers and financial backers. Her company has raised $16.5 million to date from investors like Ethereum founder Vitalik Buterin, former Coinbase CTO Balaji Srinivasan, and Armstrong, the Coinbase CEO. In August Siddiqui made the controversial suggestion that parents who choose not to use genetic testing might be considered irresponsible. “Just be honest: you’re okay with your kid potentially suffering for life so you can feel morally superior …” she wrote on X. Americans have varied opinions on the emerging technology. In 2024, a group of bioethicists surveyed 1,627 US adults to determine attitudes toward a variety of polygenic testing criteria. A large majority approved of testing for physical health conditions like cancer, heart disease, and diabetes. Screening for mental health disorders, like depression, OCD, and ADHD, drew a more mixed—but still positive—response. Appearance-related traits, like skin color, baldness, and height, received less approval as something to test for. Intelligence was among the most contentious traits—unsurprising given the way it has been weaponized throughout history and the lack of cultural consensus on how it should even be defined. (In many countries, intelligence testing for embryos is heavily regulated; in the UK, the practice is banned outright.) In the 2024 survey, 36.9% of respondents approved of preimplantation genetic testing for intelligence, 40.5% disapproved, and 22.6% said they were uncertain. Despite the disagreement, intelligence has been among the traits most talked about as targets for testing. From early on, Genomic Prediction says, it began receiving inquiries “from all over the world” about testing for intelligence, according to Diego Marin, the company’s head of global business development and scientific affairs. At one time, the company offered a predictor for what it called “intellectual disability.” After some backlash questioning both the predictive capacity and the ethics of these scores, the company discontinued the feature. “Our mission and vision of this company is not to improve [a baby], but to reduce risk for disease,” Marin told me. “When it comes to traits about IQ or skin color or height or something that’s cosmetic and doesn’t really have a connotation of a disease, then we just don’t invest in it.” Orchid, on the other hand, does test for genetic markers associated with intellectual disability and developmental delay. But that may not be all. According to one employee of the company, who spoke on the condition of anonymity, intelligence testing is also offered to “high-roller” clients. According to this employee, another source close to the company, and reporting in the Washington Post, Musk used Orchid’s services in the conception of at least one of the children he shares with the tech executive Shivon Zilis. (Orchid, Musk, and Zilis did not respond to requests for comment.) I met Kian Sadeghi, the 25-year-old founder of New York–based Nucleus Genomics, on a sweltering July afternoon in his SoHo office. Slight and kinetic, Sadeghi spoke at a machine-gun pace, pausing only occasionally to ask if I was keeping up.  Sadeghi had modified his first organism—a sample of brewer’s yeast—at the age of 16. As a high schooler in 2016, he was taking a course on CRISPR-Cas9 at a Brooklyn laboratory when he fell in love with the “beautiful depth” of genetics. Just a few years later, he dropped out of college to build “a better 23andMe.”  His company targets what you might call the application layer of PGT-P, accepting data from IVF clinics—and even from the competitors mentioned in this story—and running its own computational analysis. “Unlike a lot of the other testing companies, we’re software first, and we’re consumer first,” Sadeghi told me. “It’s not enough to give someone a polygenic score. What does that mean? How do you compare them? There’s so many really hard design problems.” Like its competitors, Nucleus calculates its polygenic risk scores by comparing an individual’s genetic data with trait-associated variants identified in large GWASs, providing statistically informed predictions.  Nucleus provides two displays of a patient’s results: a Z-score, plotted from –4 to 4, which explains the risk of a certain trait relative to a population with similar genetic ancestry (for example, if Embryo #3 has a 2.1 Z-score for breast cancer, its risk is higher than average), and an absolute risk score, which includes relevant clinical factors (Embryo #3 has a minuscule actual risk of breast cancer, given that it is male). The real difference between Nucleus and its competitors lies in the breadth of what it claims to offer clients. On its sleek website, prospective parents can sort through more than 2,000 possible diseases, as well as traits from eye color to IQ. Access to the Nucleus Embryo platform costs $8,999, while the company’s new IVF+ offering—which includes one IVF cycle with a partner clinic, embryo screening for up to 20 embryos, and concierge services throughout the process—starts at $24,999. “Maybe you want your baby to have blue eyes versus green eyes,” Nucleus founder Kian Sadeghi said at a June event. “That is up to the liberty of the parents.” Its promises are remarkably bold. The company claims to be able to forecast a propensity for anxiety, ADHD, insomnia, and other mental issues. It says you can see which of your embryos are more likely to have alcohol dependence, which are more likely to be left-handed, and which might end up with severe acne or seasonal allergies. (Nevertheless, at the time of writing, the embryo-screening platform provided this disclaimer: “DNA is not destiny. Genetics can be a helpful tool for choosing an embryo, but it’s not a guarantee. Genetic research is still in it’s [sic] infancy, and there’s still a lot we don’t know about how DNA shapes who we are.”) To people accustomed to sleep trackers, biohacking supplements, and glucose monitoring, taking advantage of Nucleus’s options might seem like a no-brainer. To anyone who welcomes a bit of serendipity in their life, this level of perceived control may be disconcerting to say the least. Sadeghi likes to frame his arguments in terms of personal choice. “Maybe you want your baby to have blue eyes versus green eyes,” he told a small audience at Nucleus Embryo’s June launch event. “That is up to the liberty of the parents.” On the official launch day, Sadeghi spent hours gleefully sparring with X users who accused him of practicing eugenics. He rejects the term, favoring instead “genetic optimization”—though it seems he wasn’t too upset about the free viral marketing. “This week we got five million impressions on Twitter,” he told a crowd at the launch event, to a smattering of applause. (In an email to MIT Technology Review, Sadeghi wrote, “The history of eugenics is one of coercion and discrimination by states and institutions; what Nucleus does is the opposite—genetic forecasting that empowers individuals to make informed decisions.”) Nucleus has raised more than $36 million from investors like Srinivasan, Alexis Ohanian’s venture capital firm Seven Seven Six, and Thiel’s Founders Fund. (Like Siddiqui, Sadeghi was a recipient of a Thiel fellowship when he dropped out of college; a representative for Thiel did not respond to a request for comment for this story.) Sadeghi has even poached Genomic Prediction’s cofounder Nathan Treff, who is now Nucleus’s chief clinical officer. Sadeghi’s real goal is to build a one-stop shop for every possible application of genetic sequencing technology, from genealogy to precision medicine to genetic engineering. He names a handful of companies providing these services, with a combined market cap in the billions. “Nucleus is collapsing all five of these companies into one,” he says. “We are not an IVF testing company. We are a genetic stack.” This spring, I elbowed my way into a packed hotel bar in the Flatiron district, where over a hundred people had gathered to hear a talk called “How to create SUPERBABIES.” The event was part of New York’s Deep Tech Week, so I expected to meet a smattering of biotech professionals and investors. Instead, I was surprised to encounter a diverse and curious group of creatives, software engineers, students, and prospective parents—many of whom had come with no previous knowledge of the subject. The speaker that evening was Jonathan Anomaly, a soft-spoken political philosopher whose didactic tone betrays his years as a university professor. Some of Anomaly’s academic work has focused on developing theories of rational behavior. At Duke and the University of Pennsylvania, he led introductory courses on game theory, ethics, and collective action problems as well as bioethics, digging into thorny questions about abortion, vaccines, and euthanasia. But perhaps no topic has interested him so much as the emerging field of genetic enhancement.  In 2018, in a bioethics journal, Anomaly published a paper with the intentionally provocative title “Defending Eugenics.” He sought to distinguish what he called “positive eugenics”—noncoercive methods aimed at increasing traits that “promote individual and social welfare”—from the so-called “negative eugenics” we know from our history books. Anomaly likes to argue that embryo selection isn’t all that different from practices we already take for granted. Don’t believe two cousins should be allowed to have children? Perhaps you’re a eugenicist, he contends. Your friend who picked out a six-foot-two Harvard grad from a binder of potential sperm donors? Same logic. His hiring at the University of Pennsylvania in 2019 caused outrage among some students, who accused him of “racial essentialism.” In 2020, Anomaly left academia, lamenting that “American universities had become an intellectual prison.” A few years later, Anomaly joined a nascent PGT-P company named Herasight, which was promising to screen for IQ. At the end of July, the company officially emerged from stealth mode. A representative told me that most of the money raised so far is from angel investors, including Srinivasan, who also invested in Orchid and Nucleus. According to the launch announcement on X, Herasight has screened “hundreds of embryos” for private customers and is beginning to offer its first publicly available consumer product, a polygenic assessment that claims to detect an embryo’s likelihood of developing 17 diseases. Their marketing materials boast predictive abilities 122% better than Orchid’s and 193% better than Genomic Prediction’s for this set of diseases. (“Herasight is comparing their current predictor to models we published over five years ago,” Genomic Prediction responded in a statement. “Our team is confident our predictors are world-class and are not exceeded in quality by any other lab.”)  The company did not include comparisons with Nucleus, pointing to the “absence of published performance validations” by that company and claiming it represented a case where “marketing outpaces science.” (“Nucleus is known for world-class science and marketing, and we understand why that’s frustrating to our competitors,” a representative from the company responded in a comment.)  Herasight also emphasized new advances in “within-family validation” (making sure that the scores are not merely picking up shared environmental factors by comparing their performance between unrelated people to their performance between siblings) and “cross-­ancestry accuracy” (improving the accuracy of scores for people outside the European ancestry groups where most of the biobank data is concentrated). The representative explained that pricing varies by customer and the number of embryos tested, but it can reach $50,000. When it comes to traits that Jonathan Anomaly believes are genetically encoded, intelligence is just the tip of the iceberg. He has also spoken about the heritability of empathy, violence, religiosity, and political leanings. Herasight tests for just one non-disease-related trait: intelligence. For a couple who produce 10 embryos, it claims it can detect an IQ spread of about 15 points, from the lowest-scoring embryo to the highest. The representative says the company plans to release a detailed white paper on its IQ predictor in the future. The day of Herasight’s launch, Musk responded to the company announcement: “Cool.” Meanwhile, a Danish researcher named Emil Kirkegaard, whose research has largely focused on IQ differences between racial groups, boosted the company to his nearly 45,000 followers on X (as well as in a Substack blog), writing, “Proper embryo selection just landed.” Kirkegaard has in fact supported Anomaly’s work for years; he’s posted about him on X and recommended his 2020 book Creating Future People, which he called a “biotech eugenics advocacy book,” adding: “Naturally, I agree with this stuff!” When it comes to traits that Anomaly believes are genetically encoded, intelligence—which he claimed in his talk is about 75% heritable—is just the tip of the iceberg. He has also spoken about the heritability of empathy, impulse control, violence, passivity, religiosity, and political leanings. Anomaly concedes there are limitations to the kinds of relative predictions that can be made from a small batch of embryos. But he believes we’re only at the dawn of what he likes to call the “reproductive revolution.” At his talk, he pointed to a technology currently in development at a handful of startups: in vitro gametogenesis. IVG aims to create sperm or egg cells in a laboratory using adult stem cells, genetically reprogrammed from cells found in a sample of skin or blood. In theory, this process could allow a couple to quickly produce a practically unlimited number of embryos to analyze for preferred traits. Anomaly predicted this technology could be ready to use on humans within eight years. SELMAN DESIGN “I doubt the FDA will allow it immediately. That’s what places like Próspera are for,” he said, referring to the so-called “startup city” in Honduras, where scientists and entrepreneurs can conduct medical experiments free from the kinds of regulatory oversight they’d encounter in the US. “You might have a moral intuition that this is wrong,” said Anomaly, “but when it’s discovered that elites are doing it privately … the dominoes are going to fall very, very quickly.” The coming “evolutionary arms race,” he claimed, will “change the moral landscape.” He added that some of those elites are his own customers: “I could already name names, but I won’t do it.” After Anomaly’s talk was over, I spoke with a young photographer who told me he was hoping to pursue a master’s degree in theology. He came to the event, he told me, to reckon with the ethical implications of playing God. “Technology is sending us toward an Old-to-New-Testament transition moment, where we have to decide what parts of religion still serve us,” he said soberly. Criticisms of polygenic testing tend to fall into two camps: skepticism about the tests’ effectiveness and concerns about their ethics. “On one hand,” says Turley from the Social Science Genetic Association Consortium, “you have arguments saying ‘This isn’t going to work anyway, and the reason it’s bad is because we’re tricking parents, which would be a problem.’ And on the other hand, they say, ‘Oh, this is going to work so well that it’s going to lead to enormous inequalities in society.’ It’s just funny to see. Sometimes these arguments are being made by the same people.” One of those people is Sasha Gusev, who runs a quantitative genetics lab at the Dana-Farber Cancer Institute. A vocal critic of PGT-P for embryo selection, he also often engages in online debates with the far-right accounts promoting race science on X. Gusev is one of many professionals in his field who believe that because of numerous confounding socioeconomic factors—for example, childhood nutrition, geography, personal networks, and parenting styles—there isn’t much point in trying to trace outcomes like educational attainment back to genetics, particularly not as a way to prove that there’s a genetic basis for IQ. He adds, “I think there’s a real risk in moving toward a society where you see genetics and ‘genetic endowments’ as the drivers of people’s behavior and as a ceiling on their outcomes and their capabilities.” Gusev thinks there is real promise for this technology in clinical settings among specific adult populations. For adults identified as having high polygenic risk scores for cancer and cardiovascular disease, he argues, a combination of early screening and intervention could be lifesaving. But when it comes to the preimplantation testing currently on the market, he thinks there are significant limitations—and few regulatory measures or long-term validation methods to check the promises companies are making. He fears that giving these services too much attention could backfire. “These reckless, overpromised, and oftentimes just straight-up manipulative embryo selection applications are a risk for the credibility and the utility of these clinical tools,” he says. Many IVF patients have also had strong reactions to publicity around PGT-P. When the New York Times published an opinion piece about Orchid in the spring, angry parents took to Reddit to rant. One user posted, “For people who dont [sic] know why other types of testing are necessary or needed this just makes IVF people sound like we want to create ‘perfect’ babies, while we just want (our) healthy babies.” Still, others defended the need for a conversation. “When could technologies like this change the mission from helping infertile people have healthy babies to eugenics?” one Redditor posted. “It’s a fine line to walk and an important discussion to have.” Some PGT-P proponents, like Kirkegaard and Anomaly, have argued that policy decisions should more explicitly account for genetic differences. In a series of blog posts following the 2024 presidential election, under the header “Make science great again,” Kirkegaard called for ending affirmative action laws, legalizing race-based hiring discrimination, and removing restrictions on data sets like the NIH’s All of Us biobank that prevent researchers like him from using the data for race science. Anomaly has criticized social welfare policies for putting a finger on the scale to “punish the high-IQ people.” Indeed, the notion of genetic determinism has gained some traction among loyalists to President Donald Trump.  In October 2024, Trump himself made a campaign stop on the conservative radio program The Hugh Hewitt Show. He began a rambling answer about immigration and homicide statistics. “A murderer, I believe this, it’s in their genes. And we got a lot of bad genes in our country right now,” he told the host. Gusev believes that while embryo selection won’t have much impact on individual outcomes, the intellectual framework endorsed by many PGT-P advocates could have dire social consequences. “If you just think of the differences that we observe in society as being cultural, then you help people out. You give them better schooling, you give them better nutrition and education, and they’re able to excel,” he says. “If you think of these differences as being strongly innate, then you can fool yourself into thinking that there’s nothing that can be done and people just are what they are at birth.” For the time being, there are no plans for longitudinal studies to track actual outcomes for the humans these companies have helped bring into the world. Harden, the behavioral geneticist from UT Austin, suspects that 25 years down the line, adults who were once embryos selected on the basis of polygenic risk scores are “going to end up with the same question that we all have.” They will look at their life and wonder, “What would’ve had to change for it to be different?” Julia Black is a Brooklyn-based features writer and a reporter in residence at Omidyar Network. She has previously worked for Business Insider, Vox, The Information, and Esquire.

Consider, if you will, the translucent blob in the eye of a microscope: a human blastocyst, the biological specimen that emerges just five days or so after a fateful encounter between egg and sperm. This bundle of cells, about the size of a grain of sand pulled from a powdery white Caribbean beach, contains the coiled potential of a future life: 46 chromosomes, thousands of genes, and roughly six billion base pairs of DNA—an instruction manual to assemble a one-of-a-kind human.

Now imagine a laser pulse snipping a hole in the blastocyst’s outermost shell so a handful of cells can be suctioned up by a microscopic pipette. This is the moment, thanks to advances in genetic sequencing technology, when it becomes possible to read virtually that entire instruction manual.

An emerging field of science seeks to use the analysis pulled from that procedure to predict what kind of a person that embryo might become. Some parents turn to these tests to avoid passing on devastating genetic disorders that run in their families. A much smaller group, driven by dreams of Ivy League diplomas or attractive, well-behaved offspring, are willing to pay tens of thousands of dollars to optimize for intelligence, appearance, and personality. Some of the most eager early boosters of this technology are members of the Silicon Valley elite, including tech billionaires like Elon Musk, Peter Thiel, and Coinbase CEO Brian Armstrong. 

Embryo selection is less like a build-a-baby workshop and more akin to a store where parents can shop for their future children from several available models—complete with stat cards.

But customers of the companies emerging to provide it to the public may not be getting what they’re paying for. Genetics experts have been highlighting the potential deficiencies of this testing for years. A 2021 paper by members of the European Society of Human Genetics said, “No clinical research has been performed to assess its diagnostic effectiveness in embryos. Patients need to be properly informed on the limitations of this use.” And a paper published this May in the Journal of Clinical Medicine echoed this concern and expressed particular reservations about screening for psychiatric disorders and non-­disease-related traits: “Unfortunately, no clinical research has to date been published comprehensively evaluating the effectiveness of this strategy [of predictive testing]. Patient awareness regarding the limitations of this procedure is paramount.”    

Moreover, the assumptions underlying some of this work—that how a person turns out is the product not of privilege or circumstance but of innate biology—have made these companies a political lightning rod. 

SELMAN DESIGN

As this niche technology begins to make its way toward the mainstream, scientists and ethicists are racing to confront the implications—for our social contract, for future generations, and for our very understanding of what it means to be human.


Preimplantation genetic testing (PGT), while still relatively rare, is not new. Since the 1990s, parents undergoing in vitro fertilization have been able to access a number of genetic tests before choosing which embryo to use. A type known as PGT-M can detect single-gene disorders like cystic fibrosis, sickle cell anemia, and Huntington’s disease. PGT-A can ascertain the sex of an embryo and identify chromosomal abnormalities that can lead to conditions like Down syndrome or reduce the chances that an embryo will implant successfully in the uterus. PGT-SR helps parents avoid embryos with issues such as duplicated or missing segments of the chromosome.

Those tests all identify clear-cut genetic problems that are relatively easy to detect, but most of the genetic instruction manual included in an embryo is written in far more nuanced code. In recent years, a fledgling market has sprung up around a new, more advanced version of the testing process called PGT-P: preimplantation genetic testing for polygenic disorders (and, some claim, traits)—that is, outcomes determined by the elaborate interaction of hundreds or thousands of genetic variants.

In 2020, the first baby selected using PGT-P was born. While the exact figure is unknown, estimates put the number of children who have now been born with the aid of this technology in the hundreds. As the technology is commercialized, that number is likely to grow.

Embryo selection is less like a build-a-baby workshop and more akin to a store where parents can shop for their future children from several available models—complete with stat cards indicating their predispositions.

A handful of startups, armed with tens of millions of dollars of Silicon Valley cash, have developed proprietary algorithms to compute these stats—analyzing vast numbers of genetic variants and producing a “polygenic risk score” that shows the probability of an embryo developing a variety of complex traits.  

For the last five years or so, two companies—Genomic Prediction and Orchid—have dominated this small landscape, focusing their efforts on disease prevention. But more recently, two splashy new competitors have emerged: Nucleus Genomics and Herasight, which have rejected the more cautious approach of their predecessors and waded into the controversial territory of genetic testing for intelligence. (Nucleus also offers tests for a wide variety of other behavioral and appearance-related traits.) 

The practical limitations of polygenic risk scores are substantial. For starters, there is still a lot we don’t understand about the complex gene interactions driving polygenic traits and disorders. And the biobank data sets they are based on tend to overwhelmingly represent individuals with Western European ancestry, making it more difficult to generate reliable scores for patients from other backgrounds. These scores also lack the full context of environment, lifestyle, and the myriad other factors that can influence a person’s characteristics. And while polygenic risk scores can be effective at detecting large, population-level trends, their predictive abilities drop significantly when the sample size is as tiny as a single batch of embryos that share much of the same DNA.

The medical community—including organizations like the American Society of Human Genetics, the American College of Medical Genetics and Genomics, and the American Society for Reproductive Medicine—is generally wary of using polygenic risk scores for embryo selection. “The practice has moved too fast with too little evidence,” the American College of Medical Genetics and Genomics wrote in an official statement in 2024.

But beyond questions of whether evidence supports the technology’s effectiveness, critics of the companies selling it accuse them of reviving a disturbing ideology: eugenics, or the belief that selective breeding can be used to improve humanity. Indeed, some of the voices who have been most confident that these methods can successfully predict nondisease traits have made startling claims about natural genetic hierarchies and innate racial differences.

What everyone can agree on, though, is that this new wave of technology is helping to inflame a centuries-old debate over nature versus nurture.


The term “eugenics” was coined in 1883 by a British anthropologist and statistician named Sir Francis Galton, inspired in part by the work of his cousin Charles Darwin. He derived it from a Greek word meaning “good in stock, hereditarily endowed with noble qualities.”

Some of modern history’s darkest chapters have been built on Galton’s legacy, from the Holocaust to the forced sterilization laws that affected certain groups in the United States well into the 20th century. Modern science has demonstrated the many logical and empirical problems with Galton’s methodology. (For starters, he counted vague concepts like “eminence”—as well as infections like syphilis and tuberculosis—as heritable phenotypes, meaning characteristics that result from the interaction of genes and environment.)

Yet even today, Galton’s influence lives on in the field of behavioral genetics, which investigates the genetic roots of psychological traits. Starting in the 1960s, researchers in the US began to revisit one of Galton’s favorite methods: twin studies. Many of these studies, which analyzed pairs of identical and fraternal twins to try to determine which traits were heritable and which resulted from socialization, were funded by the US government. The most well-known of these, the Minnesota Twin Study, also accepted grants from the Pioneer Fund, a now defunct nonprofit that had promoted eugenics and “race betterment” since its founding in 1937. 

The nature-versus-nurture debate hit a major inflection point in 2003, when the Human Genome Project was declared complete. After 13 years and at a cost of nearly $3 billion, an international consortium of thousands of researchers had sequenced 92% of the human genome for the first time.

Today, the cost of sequencing a genome can be as low as $600, and one company says it will soon drop even further. This dramatic reduction has made it possible to build massive DNA databases like the UK Biobank and the National Institutes of Health’s All of Us, each containing genetic data from more than half a million volunteers. Resources like these have enabled researchers to conduct genome-wide association studies, or GWASs, which identify correlations between genetic variants and human traits by analyzing single-nucleotide polymorphisms (SNPs)—the most common form of genetic variation between individuals. The findings from these studies serve as a reference point for developing polygenic risk scores.

Most GWASs have focused on disease prevention and personalized medicine. But in 2011, a group of medical researchers, social scientists, and economists launched the Social Science Genetic Association Consortium (SSGAC) to investigate the genetic basis of complex social and behavioral outcomes. One of the phenotypes they focused on was the level of education people reached.

“It was a bit of a phenotype of convenience,” explains Patrick Turley, an economist and member of the steering committee at SSGAC, given that educational attainment is routinely recorded in surveys when genetic data is collected. Still, it was “clear that genes play some role,” he says. “And trying to understand what that role is, I think, is really interesting.” He adds that social scientists can also use genetic data to try to better “understand the role that is due to nongenetic pathways.”

Many on the left are generally willing to allow that any number of traits, from addiction to obesity, are genetically influenced. Yet heritable cognitive ability seems to be “beyond the pale for us to integrate as a source of difference.”

The work immediately stirred feelings of discomfort—not least among the consortium’s own members, who feared that they might unintentionally help reinforce racism, inequality, and genetic determinism. 

It’s also created quite a bit of discomfort in some political circles, says Kathryn Paige Harden, a psychologist and behavioral geneticist at the University of Texas in Austin, who says she has spent much of her career making the unpopular argument to fellow liberals that genes are relevant predictors of social outcomes. 

Harden thinks a strength of those on the left is their ability to recognize “that bodies are different from each other in a way that matters.” Many are generally willing to allow that any number of traits, from addiction to obesity, are genetically influenced. Yet, she says, heritable cognitive ability seems to be “beyond the pale for us to integrate as a source of difference that impacts our life.” 

Harden believes that genes matter for our understanding of traits like intelligence, and that this should help shape progressive policymaking. She gives the example of an education department seeking policy interventions to improve math scores in a given school district. If a polygenic risk score is “as strongly correlated with their school grades” as family income is, she says of the students in such a district, then “does deliberately not collecting that [genetic] information, or not knowing about it, make your research harder [and] your inferences worse?”

To Harden, persisting with this strategy of avoidance for fear of encouraging eugenicists is a mistake. If “insisting that IQ is a myth and genes have nothing to do with it was going to be successful at neutralizing eugenics,” she says, “it would’ve won by now.”

Part of the reason these ideas are so taboo in many circles is that today’s debate around genetic determinism is still deeply infused with Galton’s ideas—and has become a particular fixation among the online right. 

SELMAN DESIGN

After Elon Musk took over Twitter (now X) in 2022 and loosened its restrictions on hate speech, a flood of accounts started sharing racist posts, some speculating about the genetic origins of inequality while arguing against immigration and racial integration. Musk himself frequently reposts and engages with accounts like Crémieux Recueil, the pen name of independent researcher Jordan Lasker, who has written about the “Black-White IQ gap,” and i/o, an anonymous account that once praised Musk for “acknowledging data on race and crime,” saying it “has done more to raise awareness of the disproportionalities observed in these data than anything I can remember.” (In response to allegations that his research encourages eugenics, Lasker wrote to MIT Technology Review, “The popular understanding of eugenics is about coercion and cutting people cast as ‘undesirable’ out of the breeding pool. This is nothing like that, so it doesn’t qualify as eugenics by that popular understanding of the term.” After going to print, i/o wrote in an email, “Just because differences in intelligence at the individual level are largely heritable, it does not mean that group differences in measured intelligence … are due to genetic differences between groups,” but that the latter is not “scientifically settled” and “an extremely important (and necessary) research area that should be funded rather than made taboo.” He added, “I’ve never made any argument against racial integration or intermarriage or whatever.” X and Musk did not respond to requests for comment.)

Harden, though, warns against discounting the work of an entire field because of a few noisy neoreactionaries. “I think there can be this idea that technology is giving rise to the terrible racism,” she says. The truth, she believes, is that “the racism has preexisted any of this technology.”


In 2019, a company called Genomic Prediction began to offer the first preimplantation polygenic testing that had ever been made commercially available. With its LifeView Embryo Health Score, prospective parents are able to assess their embryos’ predisposition to genetically complex health problems like cancer, diabetes, and heart disease. Pricing for the service starts at $3,500. Genomic Prediction uses a technique called an SNP array, which targets specific sites in the genome where common variants occur. The results are then cross-checked against GWASs that show correlations between genetic variants and certain diseases.

Four years later, a company named Orchid began offering a competing test. Orchid’s Whole Genome Embryo Report distinguished itself by claiming to sequence more than 99% of an embryo’s genome, allowing it to detect novel mutations and, the company says, diagnose rare diseases more accurately. For $2,500 per embryo, parents can access polygenic risk scores for 12 disorders, including schizophrenia, breast cancer, and hypothyroidism. 

Orchid was founded by a woman named Noor Siddiqui. Before getting undergraduate and graduate degrees from Stanford, she was awarded the Thiel fellowship—a $200,000 grant given to young entrepreneurs willing to work on their ideas instead of going to college—back when she was a teenager, in 2012. This set her up to attract attention from members of the tech elite as both customers and financial backers. Her company has raised $16.5 million to date from investors like Ethereum founder Vitalik Buterin, former Coinbase CTO Balaji Srinivasan, and Armstrong, the Coinbase CEO.

In August Siddiqui made the controversial suggestion that parents who choose not to use genetic testing might be considered irresponsible. “Just be honest: you’re okay with your kid potentially suffering for life so you can feel morally superior …” she wrote on X.

Americans have varied opinions on the emerging technology. In 2024, a group of bioethicists surveyed 1,627 US adults to determine attitudes toward a variety of polygenic testing criteria. A large majority approved of testing for physical health conditions like cancer, heart disease, and diabetes. Screening for mental health disorders, like depression, OCD, and ADHD, drew a more mixed—but still positive—response. Appearance-related traits, like skin color, baldness, and height, received less approval as something to test for.

Intelligence was among the most contentious traits—unsurprising given the way it has been weaponized throughout history and the lack of cultural consensus on how it should even be defined. (In many countries, intelligence testing for embryos is heavily regulated; in the UK, the practice is banned outright.) In the 2024 survey, 36.9% of respondents approved of preimplantation genetic testing for intelligence, 40.5% disapproved, and 22.6% said they were uncertain.

Despite the disagreement, intelligence has been among the traits most talked about as targets for testing. From early on, Genomic Prediction says, it began receiving inquiries “from all over the world” about testing for intelligence, according to Diego Marin, the company’s head of global business development and scientific affairs.

At one time, the company offered a predictor for what it called “intellectual disability.” After some backlash questioning both the predictive capacity and the ethics of these scores, the company discontinued the feature. “Our mission and vision of this company is not to improve [a baby], but to reduce risk for disease,” Marin told me. “When it comes to traits about IQ or skin color or height or something that’s cosmetic and doesn’t really have a connotation of a disease, then we just don’t invest in it.”

Orchid, on the other hand, does test for genetic markers associated with intellectual disability and developmental delay. But that may not be all. According to one employee of the company, who spoke on the condition of anonymity, intelligence testing is also offered to “high-roller” clients. According to this employee, another source close to the company, and reporting in the Washington Post, Musk used Orchid’s services in the conception of at least one of the children he shares with the tech executive Shivon Zilis. (Orchid, Musk, and Zilis did not respond to requests for comment.)


I met Kian Sadeghi, the 25-year-old founder of New York–based Nucleus Genomics, on a sweltering July afternoon in his SoHo office. Slight and kinetic, Sadeghi spoke at a machine-gun pace, pausing only occasionally to ask if I was keeping up. 

Sadeghi had modified his first organism—a sample of brewer’s yeast—at the age of 16. As a high schooler in 2016, he was taking a course on CRISPR-Cas9 at a Brooklyn laboratory when he fell in love with the “beautiful depth” of genetics. Just a few years later, he dropped out of college to build “a better 23andMe.” 

His company targets what you might call the application layer of PGT-P, accepting data from IVF clinics—and even from the competitors mentioned in this story—and running its own computational analysis.

“Unlike a lot of the other testing companies, we’re software first, and we’re consumer first,” Sadeghi told me. “It’s not enough to give someone a polygenic score. What does that mean? How do you compare them? There’s so many really hard design problems.”

Like its competitors, Nucleus calculates its polygenic risk scores by comparing an individual’s genetic data with trait-associated variants identified in large GWASs, providing statistically informed predictions. 

Nucleus provides two displays of a patient’s results: a Z-score, plotted from –4 to 4, which explains the risk of a certain trait relative to a population with similar genetic ancestry (for example, if Embryo #3 has a 2.1 Z-score for breast cancer, its risk is higher than average), and an absolute risk score, which includes relevant clinical factors (Embryo #3 has a minuscule actual risk of breast cancer, given that it is male).

The real difference between Nucleus and its competitors lies in the breadth of what it claims to offer clients. On its sleek website, prospective parents can sort through more than 2,000 possible diseases, as well as traits from eye color to IQ. Access to the Nucleus Embryo platform costs $8,999, while the company’s new IVF+ offering—which includes one IVF cycle with a partner clinic, embryo screening for up to 20 embryos, and concierge services throughout the process—starts at $24,999.

“Maybe you want your baby to have blue eyes versus green eyes,” Nucleus founder Kian Sadeghi said at a June event. “That is up to the liberty of the parents.”

Its promises are remarkably bold. The company claims to be able to forecast a propensity for anxiety, ADHD, insomnia, and other mental issues. It says you can see which of your embryos are more likely to have alcohol dependence, which are more likely to be left-handed, and which might end up with severe acne or seasonal allergies. (Nevertheless, at the time of writing, the embryo-screening platform provided this disclaimer: “DNA is not destiny. Genetics can be a helpful tool for choosing an embryo, but it’s not a guarantee. Genetic research is still in it’s [sic] infancy, and there’s still a lot we don’t know about how DNA shapes who we are.”)

To people accustomed to sleep trackers, biohacking supplements, and glucose monitoring, taking advantage of Nucleus’s options might seem like a no-brainer. To anyone who welcomes a bit of serendipity in their life, this level of perceived control may be disconcerting to say the least.

Sadeghi likes to frame his arguments in terms of personal choice. “Maybe you want your baby to have blue eyes versus green eyes,” he told a small audience at Nucleus Embryo’s June launch event. “That is up to the liberty of the parents.”

On the official launch day, Sadeghi spent hours gleefully sparring with X users who accused him of practicing eugenics. He rejects the term, favoring instead “genetic optimization”—though it seems he wasn’t too upset about the free viral marketing. “This week we got five million impressions on Twitter,” he told a crowd at the launch event, to a smattering of applause. (In an email to MIT Technology Review, Sadeghi wrote, “The history of eugenics is one of coercion and discrimination by states and institutions; what Nucleus does is the opposite—genetic forecasting that empowers individuals to make informed decisions.”)

Nucleus has raised more than $36 million from investors like Srinivasan, Alexis Ohanian’s venture capital firm Seven Seven Six, and Thiel’s Founders Fund. (Like Siddiqui, Sadeghi was a recipient of a Thiel fellowship when he dropped out of college; a representative for Thiel did not respond to a request for comment for this story.) Sadeghi has even poached Genomic Prediction’s cofounder Nathan Treff, who is now Nucleus’s chief clinical officer.

Sadeghi’s real goal is to build a one-stop shop for every possible application of genetic sequencing technology, from genealogy to precision medicine to genetic engineering. He names a handful of companies providing these services, with a combined market cap in the billions. “Nucleus is collapsing all five of these companies into one,” he says. “We are not an IVF testing company. We are a genetic stack.”


This spring, I elbowed my way into a packed hotel bar in the Flatiron district, where over a hundred people had gathered to hear a talk called “How to create SUPERBABIES.” The event was part of New York’s Deep Tech Week, so I expected to meet a smattering of biotech professionals and investors. Instead, I was surprised to encounter a diverse and curious group of creatives, software engineers, students, and prospective parents—many of whom had come with no previous knowledge of the subject.

The speaker that evening was Jonathan Anomaly, a soft-spoken political philosopher whose didactic tone betrays his years as a university professor.

Some of Anomaly’s academic work has focused on developing theories of rational behavior. At Duke and the University of Pennsylvania, he led introductory courses on game theory, ethics, and collective action problems as well as bioethics, digging into thorny questions about abortion, vaccines, and euthanasia. But perhaps no topic has interested him so much as the emerging field of genetic enhancement. 

In 2018, in a bioethics journal, Anomaly published a paper with the intentionally provocative title “Defending Eugenics.” He sought to distinguish what he called “positive eugenics”—noncoercive methods aimed at increasing traits that “promote individual and social welfare”—from the so-called “negative eugenics” we know from our history books.

Anomaly likes to argue that embryo selection isn’t all that different from practices we already take for granted. Don’t believe two cousins should be allowed to have children? Perhaps you’re a eugenicist, he contends. Your friend who picked out a six-foot-two Harvard grad from a binder of potential sperm donors? Same logic.

His hiring at the University of Pennsylvania in 2019 caused outrage among some students, who accused him of “racial essentialism.” In 2020, Anomaly left academia, lamenting that “American universities had become an intellectual prison.”

A few years later, Anomaly joined a nascent PGT-P company named Herasight, which was promising to screen for IQ.

At the end of July, the company officially emerged from stealth mode. A representative told me that most of the money raised so far is from angel investors, including Srinivasan, who also invested in Orchid and Nucleus. According to the launch announcement on X, Herasight has screened “hundreds of embryos” for private customers and is beginning to offer its first publicly available consumer product, a polygenic assessment that claims to detect an embryo’s likelihood of developing 17 diseases.

Their marketing materials boast predictive abilities 122% better than Orchid’s and 193% better than Genomic Prediction’s for this set of diseases. (“Herasight is comparing their current predictor to models we published over five years ago,” Genomic Prediction responded in a statement. “Our team is confident our predictors are world-class and are not exceeded in quality by any other lab.”) 

The company did not include comparisons with Nucleus, pointing to the “absence of published performance validations” by that company and claiming it represented a case where “marketing outpaces science.” (“Nucleus is known for world-class science and marketing, and we understand why that’s frustrating to our competitors,” a representative from the company responded in a comment.) 

Herasight also emphasized new advances in “within-family validation” (making sure that the scores are not merely picking up shared environmental factors by comparing their performance between unrelated people to their performance between siblings) and “cross-­ancestry accuracy” (improving the accuracy of scores for people outside the European ancestry groups where most of the biobank data is concentrated). The representative explained that pricing varies by customer and the number of embryos tested, but it can reach $50,000.

When it comes to traits that Jonathan Anomaly believes are genetically encoded, intelligence is just the tip of the iceberg. He has also spoken about the heritability of empathy, violence, religiosity, and political leanings.

Herasight tests for just one non-disease-related trait: intelligence. For a couple who produce 10 embryos, it claims it can detect an IQ spread of about 15 points, from the lowest-scoring embryo to the highest. The representative says the company plans to release a detailed white paper on its IQ predictor in the future.

The day of Herasight’s launch, Musk responded to the company announcement: “Cool.” Meanwhile, a Danish researcher named Emil Kirkegaard, whose research has largely focused on IQ differences between racial groups, boosted the company to his nearly 45,000 followers on X (as well as in a Substack blog), writing, “Proper embryo selection just landed.” Kirkegaard has in fact supported Anomaly’s work for years; he’s posted about him on X and recommended his 2020 book Creating Future People, which he called a “biotech eugenics advocacy book,” adding: “Naturally, I agree with this stuff!”

When it comes to traits that Anomaly believes are genetically encoded, intelligence—which he claimed in his talk is about 75% heritable—is just the tip of the iceberg. He has also spoken about the heritability of empathy, impulse control, violence, passivity, religiosity, and political leanings.

Anomaly concedes there are limitations to the kinds of relative predictions that can be made from a small batch of embryos. But he believes we’re only at the dawn of what he likes to call the “reproductive revolution.” At his talk, he pointed to a technology currently in development at a handful of startups: in vitro gametogenesis. IVG aims to create sperm or egg cells in a laboratory using adult stem cells, genetically reprogrammed from cells found in a sample of skin or blood. In theory, this process could allow a couple to quickly produce a practically unlimited number of embryos to analyze for preferred traits. Anomaly predicted this technology could be ready to use on humans within eight years.

SELMAN DESIGN

“I doubt the FDA will allow it immediately. That’s what places like Próspera are for,” he said, referring to the so-called “startup city” in Honduras, where scientists and entrepreneurs can conduct medical experiments free from the kinds of regulatory oversight they’d encounter in the US.

“You might have a moral intuition that this is wrong,” said Anomaly, “but when it’s discovered that elites are doing it privately … the dominoes are going to fall very, very quickly.” The coming “evolutionary arms race,” he claimed, will “change the moral landscape.”

He added that some of those elites are his own customers: “I could already name names, but I won’t do it.”

After Anomaly’s talk was over, I spoke with a young photographer who told me he was hoping to pursue a master’s degree in theology. He came to the event, he told me, to reckon with the ethical implications of playing God. “Technology is sending us toward an Old-to-New-Testament transition moment, where we have to decide what parts of religion still serve us,” he said soberly.


Criticisms of polygenic testing tend to fall into two camps: skepticism about the tests’ effectiveness and concerns about their ethics. “On one hand,” says Turley from the Social Science Genetic Association Consortium, “you have arguments saying ‘This isn’t going to work anyway, and the reason it’s bad is because we’re tricking parents, which would be a problem.’ And on the other hand, they say, ‘Oh, this is going to work so well that it’s going to lead to enormous inequalities in society.’ It’s just funny to see. Sometimes these arguments are being made by the same people.”

One of those people is Sasha Gusev, who runs a quantitative genetics lab at the Dana-Farber Cancer Institute. A vocal critic of PGT-P for embryo selection, he also often engages in online debates with the far-right accounts promoting race science on X.

Gusev is one of many professionals in his field who believe that because of numerous confounding socioeconomic factors—for example, childhood nutrition, geography, personal networks, and parenting styles—there isn’t much point in trying to trace outcomes like educational attainment back to genetics, particularly not as a way to prove that there’s a genetic basis for IQ.

He adds, “I think there’s a real risk in moving toward a society where you see genetics and ‘genetic endowments’ as the drivers of people’s behavior and as a ceiling on their outcomes and their capabilities.”

Gusev thinks there is real promise for this technology in clinical settings among specific adult populations. For adults identified as having high polygenic risk scores for cancer and cardiovascular disease, he argues, a combination of early screening and intervention could be lifesaving. But when it comes to the preimplantation testing currently on the market, he thinks there are significant limitations—and few regulatory measures or long-term validation methods to check the promises companies are making. He fears that giving these services too much attention could backfire.

“These reckless, overpromised, and oftentimes just straight-up manipulative embryo selection applications are a risk for the credibility and the utility of these clinical tools,” he says.

Many IVF patients have also had strong reactions to publicity around PGT-P. When the New York Times published an opinion piece about Orchid in the spring, angry parents took to Reddit to rant. One user posted, “For people who dont [sic] know why other types of testing are necessary or needed this just makes IVF people sound like we want to create ‘perfect’ babies, while we just want (our) healthy babies.”

Still, others defended the need for a conversation. “When could technologies like this change the mission from helping infertile people have healthy babies to eugenics?” one Redditor posted. “It’s a fine line to walk and an important discussion to have.”

Some PGT-P proponents, like Kirkegaard and Anomaly, have argued that policy decisions should more explicitly account for genetic differences. In a series of blog posts following the 2024 presidential election, under the header “Make science great again,” Kirkegaard called for ending affirmative action laws, legalizing race-based hiring discrimination, and removing restrictions on data sets like the NIH’s All of Us biobank that prevent researchers like him from using the data for race science. Anomaly has criticized social welfare policies for putting a finger on the scale to “punish the high-IQ people.”

Indeed, the notion of genetic determinism has gained some traction among loyalists to President Donald Trump. 

In October 2024, Trump himself made a campaign stop on the conservative radio program The Hugh Hewitt Show. He began a rambling answer about immigration and homicide statistics. “A murderer, I believe this, it’s in their genes. And we got a lot of bad genes in our country right now,” he told the host.

Gusev believes that while embryo selection won’t have much impact on individual outcomes, the intellectual framework endorsed by many PGT-P advocates could have dire social consequences.

“If you just think of the differences that we observe in society as being cultural, then you help people out. You give them better schooling, you give them better nutrition and education, and they’re able to excel,” he says. “If you think of these differences as being strongly innate, then you can fool yourself into thinking that there’s nothing that can be done and people just are what they are at birth.”

For the time being, there are no plans for longitudinal studies to track actual outcomes for the humans these companies have helped bring into the world. Harden, the behavioral geneticist from UT Austin, suspects that 25 years down the line, adults who were once embryos selected on the basis of polygenic risk scores are “going to end up with the same question that we all have.” They will look at their life and wonder, “What would’ve had to change for it to be different?”

Julia Black is a Brooklyn-based features writer and a reporter in residence at Omidyar Network. She has previously worked for Business Insider, Vox, The Information, and Esquire.

Shape
Shape
Stay Ahead

Explore More Insights

Stay ahead with more perspectives on cutting-edge power, infrastructure, energy,  bitcoin and AI solutions. Explore these articles to uncover strategies and insights shaping the future of industries.

Shape

Three options for wireless power in the enterprise

Sensors such as these can be attached to pallets to track its location, says Srivastava. “People in Europe are very conscious about where their food is coming from and, to comply with regulations, companies need to have sensors on the pallets,” he says. “Or they might need to know that

Read More »

IBM unveils advanced quantum computer in Spain

IBM executives and officials from the Basque Government and regional councils in front of Europe’s first IBM Quantum System Two, located at the IBM-Euskadi Quantum Computational Center in San Sebastián, Spain. The Basque Government and IBM unveil the first IBM Quantum System Two in Europe at the IBM-Euskadi Quantum Computational

Read More »

Oracle Taps VoltaGrid for Data Center Power Infrastructure

VoltaGrid LLC said Wednesday it has secured an agreement with Oracle Corp to deliver technology to enable the supply of natural gas-derived electricity to the information technology major’s data centers. The Houston, Texas-based gas power solutions provider will deploy 2.3 gigawatts (GW) of “cutting-edge, ultra-low-emissions infrastructure, supplied by Energy Transfer’s pipeline network, to support the energy demands of Oracle Cloud Infrastructure’s (OCI) next-generation artificial intelligence (AI) data centers”, it said in a press release. “The VoltaGrid power infrastructure will be delivered through the proprietary VoltaGrid platform – a modular, high-transient-response system developed by VoltaGrid with key suppliers, including INNIO Jenbacher and ABB”. “This power plant deployment is being supplied with firm natural gas from Energy Transfer’s expansive pipeline and storage systems”, VoltaGrid added. OCI executive vice president Mahesh Thiagarajan said, “AI workloads are uniquely power-intensive and highly variable, often creating swings in demand. By collaborating with VoltaGrid, we’re engineering innovations that dampen these swings, making AI’s power usage more stable, predictable and grid-friendly”. “VoltaGrid’s platform joins OCI’s broad energy portfolio to bolster our leading-edge AI infrastructure with dependable power that can be effortlessly scaled”, Thiagarajan added. Earlier this year VoltaGrid and Vantage Data Centers signed an agreement to deploy over one GW of power generation capacity across the latter’s North American portfolio using VoltaGrid’s gas microgrid technology. “This collaboration will set a new benchmark for speed, reliability and energy access, meeting the growing demand for data center energy solutions driven by hyperscalers and large cloud providers without putting additional cost or strain on grid systems”, a joint statement said February 11. Vantage Data Centers operates campuses in the United States and Canada that electrify and connect cloud providers and large enterprises, according to the company. “Cloud and AI technologies require the rapid development of additional data center infrastructure”, commented Dana Adams,

Read More »

Ukraine Claims Russia Refinery Strike

Ukraine’s General Staff claimed a strike on Rosneft PJSC’s Saratov refinery as NATO allies ramp up pressure on Russia’s energy industry to bring President Vladimir Putin to the negotiating table. Ukrainian military forces attacked the facility in Russia’s Volga region overnight, the General Staff said in a statement on Telegram, without providing details on the extent of any damage. Bloomberg couldn’t independently verify the claim and Rosneft didn’t immediately respond to a request for a comment. In recent weeks, Ukraine has stepped up strikes on Russia’s energy infrastructure, from refineries to crude pipelines and sea terminals. The attacks come as the Kremlin has intensified its own assaults on Ukraine and shown little intention of negotiating an agreement to end the war. A number of countries are exerting pressure on Moscow to stop military actions and resume peace talks. The UK on Wednesday imposed sanctions on Russia’s two largest oil producers — Rosneft and Lukoil PJSC — as well as Chinese energy firms importing Russian crude and liquefied gas. Meanwhile US President Donald Trump said Indian Prime Minister Narendra Modi had vowed to halt purchases of Russian oil, even though the government in New Delhi later said consumer interests remain its top priority in shaping energy-import policy. The Saratov refinery is able to process about 140,000 barrels of crude a day. It’s a key supplier of gasoline and diesel to Russia’s European regions, where most of the country’s population lives. The facility has been a target of Ukrainian drones several times this year, most recently on Sept. 20. Since the start of August, Kiyv has carried out at least 30 attacks on Russian refineries, compared with 21 from January to July, according to data compiled by Bloomberg. It will continue such strikes, Defense Minister Denys Shmyhal told reporters in Brussels on Wednesday. WHAT DO YOU THINK? Generated

Read More »

SEB Expects OPEC to Cut Production Soon

In a report sent to Rigzone by the Skandinaviska Enskilda Banken AB (SEB) team on Tuesday, SEB Chief Commodities Analyst Bjarne Schieldrop outlined that SEB expects the OPEC group to cut production soon. “We … expect OPEC to implement cuts to avoid a large increase in inventories in Q1-26,” Schieldrop said in the report. “The group will probably revert to cuts either at its early December meeting when they discuss production for January or in early January when they discuss production for February,” he added. “The oil price will likely head yet lower until the group reverts to cuts,” Schieldrop warned. In the report, Schieldrop highlighted that, in its recently released monthly report, the International Energy Agency (IEA) “estimates that the need for crude oil from OPEC in 2026 will be 25.4 million barrels per day versus production by the group in September of 29.1 million barrels per day”. “The group thus needs to do some serious cutting at the end of 2025 if it wants to keep the market balanced and avoid inventories from skyrocketing – given that IEA is correct that is,” he added. “We do however expect OPEC to implement cuts,” Schieldrop highlighted in the SEB report. “We think OPEC(+) will trim/cut production as needed into 2026 to prevent a huge build-up in global oil stocks and a crash in prices but for now we are still heading lower. Into the $50ies per barrel,” he added. In a separate SEB report sent to Rigzone on October 7, Schieldrop said “the message from OPEC+ over the [October 4-5] weekend was we are still on a weakening path with rising supply from the group”. He added, however, that “there is nothing we have seen from the group so far which indicates that they will close their eyes, let the world drown

Read More »

GB Energy Launches Aberdeen Energy Taskforce

In a statement posted on its website recently, Great British Energy (GBE) announced that it has launched the “Aberdeen Energy Taskforce”. The taskforce is defined in the statement as “a new leadership group designed to ensure that the energy transition delivers for the Northeast of Scotland – securing good local jobs, investment, and opportunity as Britain moves to clean power”. In the statement, GBE said the taskforce will act as a bridge between national ambition and local opportunity. “It will advise the company’s board and executive team on how to ensure GBE’s investment reflects the strengths, needs, and aspirations of Aberdeen and the wider region,” the statement noted. “The move supports the Government’s Clean Power Mission to secure home-grown energy and achieve clean power by 2030, while ensuring that communities are not left behind in the transition,” it added. GBE highlighted in the statement that Aberdeen has been the energy capital of Europe for decades but said job losses and market volatility in oil and gas have hit the region hard. “The taskforce will help ensure the wealth of skills and experience developed in oil and gas fuels Britain’s next generation of clean energy industries – from offshore wind and green hydrogen to carbon capture and storage (CCUS),” the statement noted. According to the GBE statement, the taskforce’s core objectives include; “championing Aberdeen’s global role in the clean energy transition across offshore wind, hydrogen, CCUS, and workforce reskilling”; “securing a fair transition, ensuring that GBE investment delivers secure, well-paid, low-carbon jobs and skills for oil and gas workers, young people, and underrepresented groups”; maximizing regional value by helping shape capital and procurement decisions that unlock local supply chains, innovation, and manufacturing”; “embedding community benefit at the heart of GBE delivery, through engagement with local authorities, anchor institutions, and residents”; and

Read More »

UK Sanctions Major Russian Oil Producers

The UK slapped sanctions on Russia’s biggest oil producers and two Chinese energy firms that deal with Moscow as London seeks to intensify pressure on the Kremlin over the war in Ukraine. Britain blacklisted state-run oil giant Rosneft PJSC and Lukoil PJSC on Wednesday, the Office of Financial Sanctions Implementation said in a statement. It also targeted Chinese firms that handle Russian energy for the first time: a terminal handling Russian liquefied gas and an oil refiner. Western nations are turning the screws on Russia’s energy sector in a bid to curb the flow of petrodollars to the Kremlin and limit President Vladimir Putin’s ability to finance the war. Taxes from the oil and gas industries account for about a quarter of the federal budget. “As Putin’s aggression intensifies, we are stepping up our response,” UK Chancellor Rachel Reeves said in a separate statement.  The UK sanctioned China’s Beihai liquefied natural gas terminal, which has become the key offloading point for cargoes from Russia’s Arctic LNG 2 project, as well as Chinese oil processor Shandong Yulong. While the UK previously imposed wide-ranging sanctions on tankers transporting Russian oil and gas, the targeting of two big oil producers – as well as Chinese firms – marks an escalation.  Rosneft and Lukoil account for more than half of all oil produced in Russia and undertake business of “strategic significance” to the government, the UK government said. The UK also sanctioned a liquefied natural gas import facility and a company that processes Russian oil. Of the three major sanctioning authorities targeting Russia – the others being the US and EU – the UK’s measures have had the least impact on Russia’s oil tankers, so it’s not clear how effective these measures will be. A greater concern for Moscow might be if Washington and Brussels followed suit. The sanctioning of

Read More »

Sable Says Court Ruling Won’t Affect Santa Ynez Operations

Sable Offshore Corp said Wednesday the Santa Barbara Superior Court had issued a tentative ruling indicating the court would deny the company’s claims against the California Coastal Commission (CCC), in a permitting dispute over repairs on the Santa Ynez Unit (SYU) pipeline system. However, Houston, Texas-based Sable insisted even if the court decision becomes final, “the ruling would have no impact on the resumption of petroleum transportation through the Las Flores Pipeline System”. “Additionally, oil and gas production from the federal Santa Ynez Unit and the flow of petroleum from the Santa Ynez Unit to the Las Flores Canyon processing facilities or to a potential offshore storage and treating vessel (OS&T) would be unaffected by rulings in the Coastal Commission litigation”, it said in a statement on its website. SYU is Sable’s sole operation. SYU ceased flows 2015 after an oil spill that, according to the CCC, released 123,000 gallons of oil and caused environmental damage to 150 miles of coastline. SYU was then owned by Plains Pipeline LP, which sold it to Exxon Mobil Corp 2022. Sable acquired SYU from ExxonMobil February 2024. Nonetheless Sable plans to escalate such a final judgment by the Superior Court to the California Court of Appeal. “Sable is suing the Coastal Commission for the damages it has caused Sable by erroneously issuing cease and desist orders during Sable’s anomaly repair program on the Las Flores Pipeline System”, the statement said. “The anomaly repair program and hydrotesting of the Las Flores Pipeline System was [sic] completed in May 2025 in accordance with the Federal Consent Decree. “Sable intends to continue its pursuit of the writ of mandate in the Court of Appeal as well as declaratory relief and inverse condemnation claims in excess of approximately $347 million”. Sable added it “continues to work diligently with the

Read More »

Oracle’s big bet for AI: Zettascale10

“OCI Zettascale10 was designed with the goal of integrating large-scale generative AI use cases, including training and running large language models,” said Info-Tech’s Palanichamy. Oracle also introduced new capabilities in Oracle Acceleron, its OCI networking stack, that it said helps customers run workloads more quickly and cost-effectively. They include dedicated network fabrics, converged NICs, and host-level zero-trust packet routing that Oracle says can double network and storage throughput while cutting latency and cost. Oracle’s zettascale supercomputer is built on the Acceleron RoCE (RDMA over Converged Ethernet) architecture and Nvidia AI infrastructure. This allows it to deliver what Oracle calls “breakthrough” scale, “extremely low” GPU-to-GPU latency, and improved price/performance, cluster use, and overall reliability. The new architecture has a “wide, shallow, resilient” fabric, according to Oracle, and takes advantage of switching capabilities built into modern GPU network interface cards (NICs). This means it can connect to multiple switches at the same time, but each switch stays on its own isolated network plane. Customers can thus deploy larger clusters, faster, while running into fewer stalls and checkpoint restarts, because traffic can be shifted to different network planes and re-routed when the system encounters unstable or contested paths. The architecture also features power-efficient optics and is “hyper-optimized” for density, as its clusters are located in large data center campuses within a two-kilometer radius, Oracle said.

Read More »

Q&A: IBM’s Mikel Díez on hybridizing quantum and classical computing

And, one clarification. Back in 2019, when we launched our first quantum computer, with between 5 and 7 qubits, what we could attempt to do with that capacity could be perfectly simulated on an ordinary laptop. After the advances of these years, being able to simulate problems requiring more than 60 or 70 qubits with classical technology is not possible even on the largest classical computer in the world. That’s why what we do on our current computers, with 156 qubits, is run real quantum circuits. They’re not simulated: they run real circuits to help with artificial intelligence problems, optimization of simulation of materials, emergence of models… all that kind of thing. The Basque Government’s BasQ program includes three types of initiatives or projects. The first are related to the evolution of quantum technology itself: how to continue improving error correction, how to identify components of quantum computers, and how to optimize both these and the performance of these devices. From a more scientific perspective, we are working on how to represent the behavior of materials so that we can improve the resistance of polymers, for example. This is useful in aeronautics to improve aircraft suspension. We are also working on time crystals, which, from a scientific perspective, seek to improve precision, sensor control, and metrology. Finally, a third line relates to the application of this technology in industry; for example, we are exploring how to improve the investment portfolio for the banking sector, how to optimize the energy grid , and how to explore logistics problems. What were the major challenges in launching the machine you’re inaugurating today? Why did you choose the Basque Country to implement your second Quantum System Two? Before implementing a facility of this type in a geographic area, we assess whether it makes sense based on

Read More »

Preparing for 800 VDC Data Centers: ABB, Eaton Support NVIDIA’s AI Infrastructure Evolution

Vendors and operators are already preparing for AI campuses measured in gigawatts. ABB’s announcement underscores the scale of this transition—not incremental retrofits, but entirely new development models for multi-GW AI infrastructure. How ABB Is Supporting the Move to 800-V DC Data Centers ABB says its joint work with NVIDIA will focus on advanced power solutions to enable 800-V DC architectures supporting 1-MW racks. Expect DC-rated breakers, protection relays, busways, and power shelves engineered for higher DC voltages, along with interfaces for liquid-cooled rack busbars. In parallel with the NVIDIA partnership, ABB has introduced an AI-ready refresh of its MNS® low-voltage switchgear, integrating SACE Emax 3 breakers with enhanced sensing and analytics to reduce footprint while improving selectivity and uptime. These components form the foundational building blocks of the higher-density electrical rooms and prefabricated skids that will define next-generation data centers. ABB’s MegaFlex UPS line already targets hyperscale and colocation environments with megawatt-class modules (UL 415/480-V variants), delivering high double-conversion efficiency and seamless integration with ABB’s Ability™ Data Center Automation platform—unifying BMS, EPMS, and DCIM functions. As racks transition to 800-V DC and liquid-cooled buses, continuous thermal-electrical co-optimization becomes essential. In this new paradigm, telemetry and controls will matter as much as copper and coolant. NVIDIA’s technical brief positions 800-V DC as the remedy for today’s inefficiencies—reducing space, cable mass, and conversion losses that accompany rising rack densities of 200 to 600 kW and beyond. The company’s 800-V rollout is targeted for 2027, with ecosystem partners spanning the entire electrical stack. Early signals from the OCP Global Summit 2025 confirm that vendors are moving rapidly to align their products and architectures with this vision. The Demands of Next-Generation GPUs NVIDIA’s Vera Rubin NVL144 rack design previews what the next phase of AI infrastructure will require: 45 °C liquid cooling, liquid-cooled busbars,

Read More »

Nvidia’s DGX Spark desktop supercomputer is on sale now, but hard to find

Industrial demand Nvidia’s DGX chips are in high demand in industry, though, and it’s more likely that Micro Center’s one-Spark limit is to prevent businesses scooping them up by the rack-load to run AI applications in their data centers. The DGX Spark contains an Nvidia GB10 Grace Blackwell chip, 128GB of unified system memory, a ConnectX-7 smart NIC for connecting two Spark’s in parallel, and up to 4TB of storage in a package just 150mm (about 6 inches) square. It consumes 240W of electrical power and delivers 1 petaflop of performance at FP4 precision — that’s one million billion floating point operations with four-bit precision per second. In comparison, Nvidia said, its original DGX-1 supercomputer based on its Pascal chip architecture and launched in 2016 delivered 170 teraflops (170,000 billion operations per second) at FP16 precision, but cost $129,000 and consumed 3,200W. It also weighed 60kg, compared to the Spark’s 1.2kg or 2.65 pounds. Nvidia won’t be the only company selling compact systems based on the DGX Spark design: It said that partner systems will be available from Acer, Asus, Dell Technologies, Gigabyte, HP, Lenovo, and MSI. This article originally appeared on Computerworld.

Read More »

Florida’s Data Center Moment: Power, Policy, and Potential

Florida is rapidly positioning itself as one of the next major frontiers for data center development. With extended tax incentives, proactive utilities, and a strategic geographic advantage, the state is aligning power, policy, and economic development in ways that echo the early playbook of Northern Virginia. In the latest episode of The Data Center Frontier Show, Buddy Rizer, Executive Director of Loudoun County Economic Development, and Lila Jaber, Founder of the Florida’s Women in Energy Leadership Forum and former Chair of the Florida Public Service Commission, join DCF to explore the opportunities and lessons shaping Florida’s emergence as a data center powerhouse. Energy and Infrastructure: A Strong Starting Position Unlike regions grappling with grid strain, Florida begins its data center growth story with energy abundance. While Loudoun County, Virginia—home to the world’s largest concentration of data centers—faced a 600 MW power deficit last year and could reach 12 GW of demand by 2030, Florida maintains excess generation capacity and robust renewable energy integration. Utilities like Florida Power & Light (FPL) and Duke Energy are already preparing for hyperscale and AI-driven loads, filing new large-load tariff structures to balance growth with ratepayer protection. Over the past decade, Florida utilities have also invested billions to harden their grids against hurricanes and extreme weather, resulting in some of the most resilient energy infrastructure in the country. Florida’s 10-year generation planning requirement, which ensures a diverse portfolio including nuclear, solar, and battery storage, further positions the state to meet growing digital infrastructure needs through hybrid on-site generation and demand-response capabilities. Economic and Workforce Advantages The state’s renewed sales tax exemptions for data centers through 2037—and the raised 100 MW IT load threshold—signal a strong bid to attract hyperscale operators and large-scale AI campuses. Florida also offers a competitive electricity rate structure comparable to Virginia’s

Read More »

Inside Blackstone’s Electrification Push: From Shermco to the Power Backbone of AI Data Centers

According to the National Electrical Manufacturers Association (NEMA), U.S. energy demand is projected to grow 50% by 2050. Electrical manufacturers have invested more than $10 billion since 2021 in new technologies to expand grid and manufacturing capacity, also reducing reliance on materials from China by 32% since 2018. Power access, sustainable infrastructure, and land acquisition have become critical factors shaping where and how data center facilities are built. As we previously reported in Data Center Frontier, investors realized this years ago, viewing these facilities both as technology assets and a unique convergence of real estate, utility infrastructure, and mission-critical systems that can also generate revenue. One of those investors is global asset manager Blackstone, which through its Energy Transition Partners private equity arm, recently acquired Shermco Industries for $1.6 billion. Announced August 21, the deal is part of Blackstone’s strategy to invest in companies that support the growing demand for electrification and a more reliable power grid. The goal is to strengthen data center infrastructure reliability and expand critical electrical services. Founded in 1974, Texas-based Shermco is one of the largest electrical testing organizations accredited by the InterNational Electrical Testing Association (NETA). The company operates in a niche yet important space: providing lifecycle electrical services, including maintenance, testing, commissioning, repair, and design, in support of data centers, utilities, and industrial clients. It has more than 40 service centers in the U.S. and Canada. In addition to helping Blackstone support its electrification and power grid reliability goals, the Shermco purchase is also part of Blackstone’s strategy to increase scale and resources—revenue increases without a substantial increase in resources—thus expanding its footprint and capabilities within the essential energy services sector.  As data centers expand globally, become more energy intensive, and are pressured to incorporate renewables and modernize grids, Blackstone’s leaders plan to leverage Shermco’s

Read More »

Microsoft will invest $80B in AI data centers in fiscal 2025

And Microsoft isn’t the only one that is ramping up its investments into AI-enabled data centers. Rival cloud service providers are all investing in either upgrading or opening new data centers to capture a larger chunk of business from developers and users of large language models (LLMs).  In a report published in October 2024, Bloomberg Intelligence estimated that demand for generative AI would push Microsoft, AWS, Google, Oracle, Meta, and Apple would between them devote $200 billion to capex in 2025, up from $110 billion in 2023. Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025. Both figures, though, are way higher than Microsoft’s 2020 capital expenditure of “just” $17.6 billion. The majority of the increased spending is tied to cloud services and the expansion of AI infrastructure needed to provide compute capacity for OpenAI workloads. Separately, last October Amazon CEO Andy Jassy said his company planned total capex spend of $75 billion in 2024 and even more in 2025, with much of it going to AWS, its cloud computing division.

Read More »

John Deere unveils more autonomous farm machines to address skill labor shortage

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

Read More »

2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

Read More »

OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

Read More »