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A brief history of “three-parent babies”

This week we heard that eight babies have been born in the UK following an experimental form of IVF that involves DNA from three people. The approach was used to prevent women with genetic mutations from passing mitochondrial diseases to their children. You can read all about the results, and the reception to them, here.  But these eight babies aren’t the first “three-parent” children out there. Over the last decade, several teams have been using variations of this approach to help people have babies. This week, let’s consider the other babies born from three-person IVF. I can’t go any further without talking about the term we use to describe these children. Journalists, myself included, have called them “three-parent babies” because they are created using DNA from three people. Briefly, the approach typically involves using the DNA from the nuclei of the intended parents’ egg and sperm cells. That’s where most of the DNA in a cell is found. But it also makes use of mitochondrial DNA (mtDNA)—the DNA found in the energy-producing organelles of a cell—from a third person. The idea is to avoid using the mtDNA from the intended mother, perhaps because it is carrying genetic mutations. Other teams have done this in the hope of treating infertility. mtDNA, which is usually inherited from a person’s mother, makes up a tiny fraction of total inherited DNA. It includes only 37 genes, all of which are thought to play a role in how mitochondria work (as opposed to, say, eye color or height). That’s why some scientists despise the term “three-parent baby.” Yes, the baby has DNA from three people, but those three can’t all be considered parents, critics argue. For the sake of argument, this time around I’ll use the term “three-person IVF” from here on out. So, about these babies. The first were reported back in the 1990s. Jacques Cohen, then at Saint Barnabas Medical Center in Livingston, New Jersey, and his colleagues thought they might be able to treat some cases of infertility by injecting the mitochondria-containing cytoplasm of healthy eggs into eggs from the intended mother. Seventeen babies were ultimately born this way, according to the team. (Side note: In their paper, the authors describe potential resulting children as “three-parental individuals.”) But two fetuses appeared to have genetic abnormalities. And one of the children started to show signs of a developmental disorder. In 2002, the US Food and Drug Administration put a stop to the research. The babies born during that study are in their 20s now. But scientists still don’t know why they saw those abnormalities. Some think that mixing mtDNA from two people might be problematic. Newer approaches to three-person IVF aim to include mtDNA from just the donor, completely bypassing the intended mother’s mtDNA. John Zhang at the New Hope Fertility Center in New York City tried this approach for a Jordanian couple in 2016. The woman carried genes for a fatal mitochondrial disease and had already lost two children to it. She wanted to avoid passing it on to another child. Zhang took the nucleus of the woman’s egg and inserted it into a donor egg that had had its own nucleus removed—but still had its mitochondria-containing cytoplasm. That egg was then fertilized with the woman’s husband’s sperm. Because it was still illegal in the US, Zhang controversially did the procedure in Mexico, where, as he told me at the time, “there are no rules.” The couple eventually welcomed a healthy baby boy. Less than 1% of the boy’s mitochondria carried his mother’s mutation, so the procedure was deemed a success. There was a fair bit of outrage from the scientific community, though. Mitochondrial donation had been made legal in the UK the previous year, but no clinic had yet been given a license to do it. Zhang’s experiment seemed to have been conducted with no oversight. Many questioned how ethical it was, although Sian Harding, who reviewed the ethics of the UK procedure, then told me it was “as good as or better than what we’ll do in the UK.” The scandal had barely died down by the time the next “three-person IVF” babies were announced. In 2017, a team at the Nadiya Clinic in Ukraine announced the birth of a little girl to parents who’d had the treatment for infertility. The news brought more outrage from some quarters, as scientists argued that the experimental procedure should only be used to prevent severe mitochondrial diseases. It wasn’t until later that year that the UK’s fertility authority granted a team in Newcastle a license to perform mitochondrial donation. That team launched a trial in 2017. It was big news—the first “official” trial to test whether the approach could safely prevent mitochondrial disease. But it was slow going. And meanwhile, other teams were making progress. The Nadiya Clinic continued to trial the procedure in couples with infertility. Pavlo Mazur, a former embryologist who worked at that clinic, tells me that 10 babies were born there as a result of mitochondrial donation. Mazur then moved to another clinic in Ukraine, where he says he used a different type of mitochondrial donation to achieve another five healthy births for people with infertility. “In total, it’s 15 kids made by me,” he says. But he adds that other clinics in Ukraine are also using mitochondrial donation, without sharing their results. “We don’t know the actual number of those kids in Ukraine,” says Mazur. “But there are dozens of them.” In 2020, Nuno Costa-Borges of Embryotools in Barcelona, Spain, and his colleagues described another trial of mitochondrial donation. This trial, performed in Greece, was also designed to test the procedure for people with infertility. It involved 25 patients. So far, seven children have been born. “I think it’s a bit strange that they aren’t getting more credit,” says Heidi Mertes, a medical ethicist at Ghent University in Belgium. The newly announced UK births are only the latest “three-person IVF” babies. And while their births are being heralded as a success story for mitochondrial donation, the story isn’t quite so simple. Three of the eight babies were born with a non-insignificant proportion of mutated mitochondria, ranging between 5% and 20%, depending on the baby and the sample. Dagan Wells of the University of Oxford, who is involved in the Greece trial, says that two of the seven babies in their study also appear to have inherited mtDNA from their intended mothers. Mazur says he has seen several cases of this “reversal” too. This isn’t a problem for babies whose mothers don’t carry genes for mitochondrial disease. But it might be for those whose mothers do. I don’t want to pour cold water over the new UK results. It was great to finally see the results of a trial that’s been running for eight years. And the births of healthy babies are something to celebrate. But it’s not a simple success story. Mitochondrial donation doesn’t guarantee a healthy baby. We still have more to learn, not only from these babies, but from the others that have already been born. This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here.

This week we heard that eight babies have been born in the UK following an experimental form of IVF that involves DNA from three people. The approach was used to prevent women with genetic mutations from passing mitochondrial diseases to their children. You can read all about the results, and the reception to them, here

But these eight babies aren’t the first “three-parent” children out there. Over the last decade, several teams have been using variations of this approach to help people have babies. This week, let’s consider the other babies born from three-person IVF.

I can’t go any further without talking about the term we use to describe these children. Journalists, myself included, have called them “three-parent babies” because they are created using DNA from three people. Briefly, the approach typically involves using the DNA from the nuclei of the intended parents’ egg and sperm cells. That’s where most of the DNA in a cell is found.

But it also makes use of mitochondrial DNA (mtDNA)—the DNA found in the energy-producing organelles of a cell—from a third person. The idea is to avoid using the mtDNA from the intended mother, perhaps because it is carrying genetic mutations. Other teams have done this in the hope of treating infertility.

mtDNA, which is usually inherited from a person’s mother, makes up a tiny fraction of total inherited DNA. It includes only 37 genes, all of which are thought to play a role in how mitochondria work (as opposed to, say, eye color or height).

That’s why some scientists despise the term “three-parent baby.” Yes, the baby has DNA from three people, but those three can’t all be considered parents, critics argue. For the sake of argument, this time around I’ll use the term “three-person IVF” from here on out.

So, about these babies. The first were reported back in the 1990s. Jacques Cohen, then at Saint Barnabas Medical Center in Livingston, New Jersey, and his colleagues thought they might be able to treat some cases of infertility by injecting the mitochondria-containing cytoplasm of healthy eggs into eggs from the intended mother. Seventeen babies were ultimately born this way, according to the team. (Side note: In their paper, the authors describe potential resulting children as “three-parental individuals.”)

But two fetuses appeared to have genetic abnormalities. And one of the children started to show signs of a developmental disorder. In 2002, the US Food and Drug Administration put a stop to the research.

The babies born during that study are in their 20s now. But scientists still don’t know why they saw those abnormalities. Some think that mixing mtDNA from two people might be problematic.

Newer approaches to three-person IVF aim to include mtDNA from just the donor, completely bypassing the intended mother’s mtDNA. John Zhang at the New Hope Fertility Center in New York City tried this approach for a Jordanian couple in 2016. The woman carried genes for a fatal mitochondrial disease and had already lost two children to it. She wanted to avoid passing it on to another child.

Zhang took the nucleus of the woman’s egg and inserted it into a donor egg that had had its own nucleus removed—but still had its mitochondria-containing cytoplasm. That egg was then fertilized with the woman’s husband’s sperm.

Because it was still illegal in the US, Zhang controversially did the procedure in Mexico, where, as he told me at the time, “there are no rules.” The couple eventually welcomed a healthy baby boy. Less than 1% of the boy’s mitochondria carried his mother’s mutation, so the procedure was deemed a success.

There was a fair bit of outrage from the scientific community, though. Mitochondrial donation had been made legal in the UK the previous year, but no clinic had yet been given a license to do it. Zhang’s experiment seemed to have been conducted with no oversight. Many questioned how ethical it was, although Sian Harding, who reviewed the ethics of the UK procedure, then told me it was “as good as or better than what we’ll do in the UK.”

The scandal had barely died down by the time the next “three-person IVF” babies were announced. In 2017, a team at the Nadiya Clinic in Ukraine announced the birth of a little girl to parents who’d had the treatment for infertility. The news brought more outrage from some quarters, as scientists argued that the experimental procedure should only be used to prevent severe mitochondrial diseases.

It wasn’t until later that year that the UK’s fertility authority granted a team in Newcastle a license to perform mitochondrial donation. That team launched a trial in 2017. It was big news—the first “official” trial to test whether the approach could safely prevent mitochondrial disease.

But it was slow going. And meanwhile, other teams were making progress. The Nadiya Clinic continued to trial the procedure in couples with infertility. Pavlo Mazur, a former embryologist who worked at that clinic, tells me that 10 babies were born there as a result of mitochondrial donation.

Mazur then moved to another clinic in Ukraine, where he says he used a different type of mitochondrial donation to achieve another five healthy births for people with infertility. “In total, it’s 15 kids made by me,” he says.

But he adds that other clinics in Ukraine are also using mitochondrial donation, without sharing their results. “We don’t know the actual number of those kids in Ukraine,” says Mazur. “But there are dozens of them.”

In 2020, Nuno Costa-Borges of Embryotools in Barcelona, Spain, and his colleagues described another trial of mitochondrial donation. This trial, performed in Greece, was also designed to test the procedure for people with infertility. It involved 25 patients. So far, seven children have been born. “I think it’s a bit strange that they aren’t getting more credit,” says Heidi Mertes, a medical ethicist at Ghent University in Belgium.

The newly announced UK births are only the latest “three-person IVF” babies. And while their births are being heralded as a success story for mitochondrial donation, the story isn’t quite so simple. Three of the eight babies were born with a non-insignificant proportion of mutated mitochondria, ranging between 5% and 20%, depending on the baby and the sample.

Dagan Wells of the University of Oxford, who is involved in the Greece trial, says that two of the seven babies in their study also appear to have inherited mtDNA from their intended mothers. Mazur says he has seen several cases of this “reversal” too.

This isn’t a problem for babies whose mothers don’t carry genes for mitochondrial disease. But it might be for those whose mothers do.

I don’t want to pour cold water over the new UK results. It was great to finally see the results of a trial that’s been running for eight years. And the births of healthy babies are something to celebrate. But it’s not a simple success story. Mitochondrial donation doesn’t guarantee a healthy baby. We still have more to learn, not only from these babies, but from the others that have already been born.

This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here.

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The Q&A session came on the heels of layoffs across the company. Tan was hired in March, and almost immediately he began to promise to divest and reduce non-core assets. Gelsinger had also begun divesting the company of losers, but they were nibbles around the edge. Tan is promising to take an axe to the place. In addition to discontinuing products, the company has outsourced marketing and media relations — for the first time in more than 25 years of covering this company, I have no internal contacts at Intel. Many more workers are going to lose their jobs in coming weeks. So far about 500 have been cut in Oregon and California but many more is expected — as much as 20% of the overall company staff may go, and Intel has over 100,000 employees, according to published reports. Tan believes the company is bloated and too bogged down with layers of management to be reactive and responsive in the same way that AMD and Nvidia are. “The whole process of that (deciding) is so slow and eventually nobody makes a decision,” he is quoted as saying. Something he has decided on is AI, and he seems to have decided to give up. “On training, I think it is too late for us,” Tan said, adding that Nvidia’s position in that market is simply “too strong.” So there goes what sales Gaudi3 could muster. Instead, Tan said Intel will focus on “edge” artificial intelligence, where AI capabilities Are brought to PCs and other remote devices rather than big AI processors in data centers like Nvidia and AMD are doing. “That’s an area that I think is emerging, coming up very big and we want to make sure that we capture,” Tan said.

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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.

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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

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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

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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

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