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Yahoo
a day ago
- Health
- Yahoo
'World's Oldest Baby' Born From 30-Year-Old Frozen Embryo
An adopted embryo that was frozen for 30 and a half years has given rise to what some claim is the 'oldest baby' in the world. According to an exclusive scoop from MIT Technology Review's Jessica Hamzelou, the newborn baby boy was conceived in the United States in May 1994 to one set of parents and born on 26 July 2025 to another set of parents. For decades, the embryo remained frozen in time, both young and old all at once. Related: The biological mother, Linda Archerd, and her then-husband froze the embryo while undergoing in vitro fertilization (IVF) in the 1990s. After having a baby girl, the couple was left with three embryos in the bank. Decades later, Archerd decided it was time to donate them. Lindsey and Tim Pierce are the happy recipients of her generosity. "We didn't go into it thinking we would break any records," Lindsey told Hamzelou at MIT Tech Review. "We just wanted to have a baby." Previously, the longest-frozen embryos to result in the birth of a child were cryopreserved in the US for just over 30 years. The double embryo transfer resulted in twins in 2022. The latest record-breaking adoption was completed by a fertility clinic in Tennessee, run by reproductive endocrinologist John Gordon, who believes every embryo has a chance at life because of his religion. US fertility clinics like his are pushing the limits of IVF technology, even if the frozen embryos they transfer wouldn't be accepted elsewhere in the world. In Australia, for instance, embryos can only be frozen for up to five years, while in the United Kingdom they can be stored for up to 55 years. In the US, however, embryos can be frozen indefinitely. What's more, many go unclaimed, which raises ethical concerns, and which legally means they cannot be donated for reproductive use or research. By some estimates, there are currently as many as 1.5 million embryos frozen in the US. "These are formidable numbers that keep growing every year with currently no clear ethical or legal means to reach a practical solution," computational biochemist Shina Caroline Lynn Kamerlin wrote in a paper from 2024. In recent years, clinics have been thawing and transferring older and older frozen embryos for 'adoption'. The result is that some of the newborn children have siblings who are decades older than them. The Pierce family's son, for instance, was conceived at around the same time as Archerd's daughter in the 1990s, meaning his sister is around 30 years older than him. The Pierce family adopted the embryo from Archerd through the Snowflakes program, which is run by the Nightlight Christian Adoptions agency. Beth Button, executive director of the program, told Hamzelou at MIT Tech Review that she thinks "over 90 percent of clinics in the US would not have accepted these embryos." IVF technologies have changed a lot over the years, and older embryos are stored in ways that can be trickier to thaw using modern methods. There are also concerns over viability. In 2022, a large retrospective study in China found that prolonged storage time can negatively affect the survival rate of embryos, although it did not seem to have a significant influence on neonatal health. Still, the research is mixed. Other studies have found that the length of cryopreservation does not influence embryo survival after thawing. Most studies on the topic are based on embryos that have been frozen for much less than 30 years. Fertility clinics in the US are putting this life-giving technology to the test. They have not yet found the limit. Related News This Potent Psychedelic Mysteriously Echoes Near-Death Experiences Mysterious 2,500-Year-Old 'Gift to The Gods' Finally Identified 4,000-Year-Old Handprint Discovered on Ancient Egyptian Artifact Solve the daily Crossword
Indian Express
12-07-2025
- Business
- Indian Express
Karen Hao's Empire of AI brings nuance and much-needed scepticism to the study of AI
Most conversations that we have around Artificial Intelligence (AI) today share one commonality: the technology's society-altering capacity, its ability to leap us towards the next breakthrough, a better world, a future that we rarely imagined would be possible. The founding mission of Open AI, the company that made AI a household name through ChatGPT in 2022, is 'to ensure that artificial general intelligence — AI systems that are generally smarter than humans — benefits all of humanity'. Behind this seemingly optimistic idea, tech reporter Karen Hao argues, is the stench of empires of old — a civilising mission that promises modernity and progress while accumulating power and money through the exploitation of labour and resources. Hao has spent seven years covering AI — at the MIT Tech Review, The Washington Post and The Atlantic. She was the first to profile OpenAI and extensively document the AI supply chain — taking the conversation beyond the promise of Silicon Valley's innovation through reportage around people behind the black boxes that are AI models. And it is these stories that find centre-stage in 'Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI', her debut book. It is a company book and, like all good business books, gives an intimate picture of the rise of an idea, the people, strategy and money behind it. But the book stands out as it provides us one way of framing the dizzying AI boom and conversation around us. In doing so, the book joins the list of non-fiction on AI that brings nuance and much-needed scepticism of the subject while being acutely aware of its potential. In 2024, Arvind Narayanan and Sayash Kapoor from the Computer Science department of Princeton University wrote 'AI Snake Oil: What Artificial Intelligence Can Do, What It Can't, and How to Tell the Difference'. The book lays out the basics of AI research, helping distinguish hype from reality. The same year, tech journalist Parmy Olson wrote Supremacy: AI, ChatGPT, and the Race that Will Change the World about the unprecedented monopoly that Open AI and Google's AI research wing Deepmind currently have in the world. This approach needs a lot of computing capacity. The physical manifestation of it are the massive data centres that are mushrooming everywhere. These data centres, in turn, consume a lot of energy. Open AI cracked this technique and doubled down on it: more data, more high-functioning and expensive Graphic Processing Units (GPUs) that make the computation happen, and more data centers to house them. This more-is-more approach, Hao writes, has 'choked' alternative forms to AI research, which has been a subject many have been trying to crack and expand since the 1950s. 'There was research before that explored minimising data for training models while achieving similar gains. Then Large Language Models and ChatGPT entered the picture. Research suddenly stopped. Two things happened: money flowed into transformers (a type of highly-effective neural network) and generative AI, diverting funding from other explorations,' Hao says. With the 'enormous externalities' of environmental costs, data privacy issues and labour exploitation of AI today, it is important to 'redirect some funds to explore new scientific frontiers that offer the same benefits of advanced AI without extraordinary costs,' Hao argues. But it might be harder than said. In her book, Hao traces how researchers, who were working outside major AI companies, are now financially affiliated with them. Funding, too, primarily, comes from tech companies or academic labs associated with them. 'There's a misconception among the public and policymakers that AI research remains guided by a pure scientific drive,' Hao says, adding that 'the foundations of AI knowledge have been overtaken by profit motives.'
