An ancient man’s remains were hacked apart and kept in a garage

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An ancient man’s remains were hacked apart and kept in a garage

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 I’ve been working on a story about a brain of glass. About five years ago, archaeologists found shiny black glass fragments inside the skull of a man who died in the Mount Vesuvius eruption of 79 CE. It seems they are pieces of brain, turned to glass. Scientists have found ancient brains before—some are thought to be at least 10,000 years old. But this is the only time they’ve seen a brain turn to glass. They’ve even been able to spot neurons inside it. The man’s remains were found at Herculaneum, an ancient city that was buried under meters of volcanic ash following the eruption. We don’t know if there are any other vitrified brains on the site. None have been found so far, but only about a quarter of the city has been excavated. Some archaeologists want to continue excavating the site. But others argue that we need to protect it. Further digging will expose it to the elements, putting the artifacts and remains at risk of damage. You can only excavate a site once, so perhaps it’s worth waiting until we have the technology to do so in the least destructive way. After all, there are some pretty recent horror stories of excavations involving angle grinders, and of ancient body parts ending up in garages. Future technologies might eventually make our current approaches look similarly barbaric. The inescapable fact of fields like archaeology or paleontology is this: When you study ancient remains, you’ll probably end up damaging them in some way. Take, for example, DNA analysis. Scientists have made a huge amount of progress in this field. Today, geneticists can crack the genetic code of extinct animals and analyze DNA in soil samples to piece together the history of an environment. But this kind of analysis essentially destroys the sample. To perform DNA analysis on human remains, scientists typically cut out a piece of bone and grind it up. They might use a tooth. But once it has been studied, that sample is gone for good. Archaeological excavations have been performed for hundreds of years, and as recently as the 1950s, it was common for archaeologists to completely excavate a site they discovered. But those digs cause damage too. Nowadays, when a site is discovered, archaeologists tend to focus on specific research questions they might want to answer, and excavate only enough to answer those questions, says Karl Harrison, a forensic archaeologist at the University of Exeter in the UK. “We will cross our fingers, excavate the minimal amount, and hope that the next generation of archaeologists will have new, better tools and finer abilities to work on stuff like this,” he says. In general, scientists have also become more careful with human remains. Matteo Borrini, a forensic anthropologist at Liverpool John Moores University in the UK, curates his university’s collection of skeletal remains, which he says includes around 1,000 skeletons of medieval and Victorian Britons. The skeletons are extremely valuable for research, says Borrini, who himself has investigated the remains of one person who died from exposure to phosphorus in a match factory and another who was murdered. When researchers ask to study the skeletons, Borrini will find out whether the research will somehow alter them. “If there is destructive sampling, we need to guarantee that the destruction will be minimal, and that there will be enough material [left] for further study,” he says. “Otherwise we don’t authorize the study.” If only previous generations of archaeologists had taken a similar approach. Harrison told me the story of the discovery of “St Bees man,” a medieval man found in a lead coffin in Cumbria, UK, in 1981. The man, thought to have died in the 1300s, was found to be extraordinarily well preserved—his skin was intact, his organs were present, and he even still had his body hair. Normally, archaeologists would dig up such ancient specimens with care, using tools made of natural substances like stone or brick, says Harrison. Not so for St Bees man. “His coffin was opened with an angle grinder,” says Harrison. The man’s body was removed and “stuck in a truck,” where he underwent a standard modern forensic postmortem, he adds. “His thorax would have been opened up, his organs [removed and] weighed, [and] the top of his head would have been cut off,” says Harrison. Samples of the man’s organs “were kept in [the pathologist’s] garage for 40 years.” If St Bees man were discovered today, the story would be completely different. The coffin itself would be recognized as a precious ancient artifact that should be handled with care, and the man’s remains would be scanned and imaged in the least destructive way possible, says Harrison. Even Lindow man, who was discovered a mere three years later in nearby Manchester, got better treatment. His remains were found in a peat bog, and he is thought to have died over 2,000 years ago. Unlike poor St Bees man, he underwent careful scientific investigation, and his remains took pride of place in the British Museum. Harrison remembers going to see the exhibit when he was 10 years old. Harrison says he’s dreaming of minimally destructive DNA technologies—tools that might help us understand the lives of long-dead people without damaging their remains. I’m looking forward to covering those in the future. (In the meantime, I’m personally dreaming of a trip to—respectfully and carefully—visit Herculaneum.) Now read the rest of The Checkup Read more from MIT Technology Review’s archive Some believe an “ancient-DNA revolution” is underway, as scientists use modern technologies to learn about human, animal, and environmental remains from the past. My colleague Antonio Regalado has the details in his recent feature. The piece was published in the latest edition of our magazine, which focuses on relationships. Ancient DNA analysis made it to MIT Technology Review’s annual list of top 10 Breakthrough Technologies in 2023. You can read our thoughts on the breakthroughs of 2025 here. DNA that was frozen for 2 million years was sequenced in 2022. The ancient DNA fragments, which were recovered from Greenland, may offer insight into the environment of the polar desert at the time. Environmental DNA, also known as eDNA, can help scientists assemble a snapshot of all the organisms in a given place. Some are studying samples collected from Angkor Wat in Cambodia, which is believed to have been built in the 12th century. Others are hoping that ancient DNA can be used to “de-extinct” animals that once lived on Earth. Colossal Biosciences is hoping to resurrect the dodo and the woolly mammoth. From around the web Next-generation obesity drugs might be too effective. One trial participant lost 22% of her body weight in nine months. Another lost 30% of his weight in just eight months. (STAT) A US court upheld the conviction of Elizabeth Holmes, the disgraced founder of the biotechnology company Theranos, who was sentenced to over 11 years for defrauding investors out of hundreds of millions of dollars. Her sentence has since been reduced by two years for good behavior. (The Guardian) An unvaccinated child died of measles in Texas. The death is the first reported as a result of the outbreak that is spreading in Texas and New Mexico, and the first measles death reported in the US in a decade. Health and Human Services Secretary Robert F. Kennedy Jr. appears to be downplaying the outbreak. (NBC News) A mysterious disease with Ebola-like symptoms has emerged in the Democratic Republic of Congo. Hundreds of people have been infected in the last five weeks, and more than 50 people have died. (Wired) Towana Looney has been discharged from the hospital three months after receiving a gene-edited pig kidney. “I’m so grateful to be alive and thankful to have received this incredible gift,” she said. (NYU Langone)

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 I’ve been working on a story about a brain of glass. About five years ago, archaeologists found shiny black glass fragments inside the skull of a man who died in the Mount Vesuvius eruption of 79 CE. It seems they are pieces of brain, turned to glass.

Scientists have found ancient brains before—some are thought to be at least 10,000 years old. But this is the only time they’ve seen a brain turn to glass. They’ve even been able to spot neurons inside it.

The man’s remains were found at Herculaneum, an ancient city that was buried under meters of volcanic ash following the eruption. We don’t know if there are any other vitrified brains on the site. None have been found so far, but only about a quarter of the city has been excavated.

Some archaeologists want to continue excavating the site. But others argue that we need to protect it. Further digging will expose it to the elements, putting the artifacts and remains at risk of damage. You can only excavate a site once, so perhaps it’s worth waiting until we have the technology to do so in the least destructive way.

After all, there are some pretty recent horror stories of excavations involving angle grinders, and of ancient body parts ending up in garages. Future technologies might eventually make our current approaches look similarly barbaric.

The inescapable fact of fields like archaeology or paleontology is this: When you study ancient remains, you’ll probably end up damaging them in some way. Take, for example, DNA analysis. Scientists have made a huge amount of progress in this field. Today, geneticists can crack the genetic code of extinct animals and analyze DNA in soil samples to piece together the history of an environment.

But this kind of analysis essentially destroys the sample. To perform DNA analysis on human remains, scientists typically cut out a piece of bone and grind it up. They might use a tooth. But once it has been studied, that sample is gone for good.

Archaeological excavations have been performed for hundreds of years, and as recently as the 1950s, it was common for archaeologists to completely excavate a site they discovered. But those digs cause damage too.

Nowadays, when a site is discovered, archaeologists tend to focus on specific research questions they might want to answer, and excavate only enough to answer those questions, says Karl Harrison, a forensic archaeologist at the University of Exeter in the UK. “We will cross our fingers, excavate the minimal amount, and hope that the next generation of archaeologists will have new, better tools and finer abilities to work on stuff like this,” he says.

In general, scientists have also become more careful with human remains. Matteo Borrini, a forensic anthropologist at Liverpool John Moores University in the UK, curates his university’s collection of skeletal remains, which he says includes around 1,000 skeletons of medieval and Victorian Britons. The skeletons are extremely valuable for research, says Borrini, who himself has investigated the remains of one person who died from exposure to phosphorus in a match factory and another who was murdered.

When researchers ask to study the skeletons, Borrini will find out whether the research will somehow alter them. “If there is destructive sampling, we need to guarantee that the destruction will be minimal, and that there will be enough material [left] for further study,” he says. “Otherwise we don’t authorize the study.”

If only previous generations of archaeologists had taken a similar approach. Harrison told me the story of the discovery of “St Bees man,” a medieval man found in a lead coffin in Cumbria, UK, in 1981. The man, thought to have died in the 1300s, was found to be extraordinarily well preserved—his skin was intact, his organs were present, and he even still had his body hair.

Normally, archaeologists would dig up such ancient specimens with care, using tools made of natural substances like stone or brick, says Harrison. Not so for St Bees man. “His coffin was opened with an angle grinder,” says Harrison. The man’s body was removed and “stuck in a truck,” where he underwent a standard modern forensic postmortem, he adds.

“His thorax would have been opened up, his organs [removed and] weighed, [and] the top of his head would have been cut off,” says Harrison. Samples of the man’s organs “were kept in [the pathologist’s] garage for 40 years.”

If St Bees man were discovered today, the story would be completely different. The coffin itself would be recognized as a precious ancient artifact that should be handled with care, and the man’s remains would be scanned and imaged in the least destructive way possible, says Harrison.

Even Lindow man, who was discovered a mere three years later in nearby Manchester, got better treatment. His remains were found in a peat bog, and he is thought to have died over 2,000 years ago. Unlike poor St Bees man, he underwent careful scientific investigation, and his remains took pride of place in the British Museum. Harrison remembers going to see the exhibit when he was 10 years old.

Harrison says he’s dreaming of minimally destructive DNA technologies—tools that might help us understand the lives of long-dead people without damaging their remains. I’m looking forward to covering those in the future. (In the meantime, I’m personally dreaming of a trip to—respectfully and carefully—visit Herculaneum.)

Now read the rest of The Checkup

From around the web

Next-generation obesity drugs might be too effective. One trial participant lost 22% of her body weight in nine months. Another lost 30% of his weight in just eight months. (STAT)

A US court upheld the conviction of Elizabeth Holmes, the disgraced founder of the biotechnology company Theranos, who was sentenced to over 11 years for defrauding investors out of hundreds of millions of dollars. Her sentence has since been reduced by two years for good behavior. (The Guardian)

An unvaccinated child died of measles in Texas. The death is the first reported as a result of the outbreak that is spreading in Texas and New Mexico, and the first measles death reported in the US in a decade. Health and Human Services Secretary Robert F. Kennedy Jr. appears to be downplaying the outbreak. (NBC News)

A mysterious disease with Ebola-like symptoms has emerged in the Democratic Republic of Congo. Hundreds of people have been infected in the last five weeks, and more than 50 people have died. (Wired)

Towana Looney has been discharged from the hospital three months after receiving a gene-edited pig kidney. “I’m so grateful to be alive and thankful to have received this incredible gift,” she said. (NYU Langone)

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Q2 Executive Roundtable Recap

Matt Vincent is Editor in Chief of Data Center Frontier, where he leads editorial strategy and coverage focused on the infrastructure powering cloud computing, artificial intelligence, and the digital economy. A veteran B2B technology journalist with more than two decades of experience, Vincent specializes in the intersection of data centers, power, cooling, and emerging AI-era infrastructure. Since assuming the EIC role in 2023, he has helped guide Data Center Frontier’s coverage of the industry’s transition into the gigawatt-scale AI era, with a focus on hyperscale development, behind-the-meter power strategies, liquid cooling architectures, and the evolving energy demands of high-density compute, while working closely with the Digital Infrastructure Group at Endeavor Business Media to expand the brand’s analytical and multimedia footprint. Vincent also hosts The Data Center Frontier Show podcast, where he interviews industry leaders across hyperscale, colocation, utilities, and the data center supply chain to examine the technologies and business models reshaping digital infrastructure. Since its inception he serves as Head of Content for the Data Center Frontier Trends Summit. Before becoming Editor in Chief, he served in multiple senior editorial roles across Endeavor Business Media’s digital infrastructure portfolio, with coverage spanning data centers and hyperscale infrastructure, structured cabling and networking, telecom and datacom, IP physical security, and wireless and Pro AV markets. He began his career in 2005 within PennWell’s Advanced Technology Division and later held senior editorial positions supporting brands such as Cabling Installation & Maintenance, Lightwave Online, Broadband Technology Report, and Smart Buildings Technology. Vincent is a frequent moderator, interviewer, and keynote speaker at industry events including the HPC Forum, where he delivers forward-looking analysis on how AI and high-performance computing are reshaping digital infrastructure. He graduated with honors from Indiana University Bloomington with a B.A. in English Literature and Creative Writing and lives in southern New Hampshire with

Emergence Water and Nimbus: Water Joins Power as AI Infrastructure’s Next Critical Constraint

For much of the past decade, the conversation surrounding AI infrastructure has been dominated by one resource above all others: power. Utilities have become strategic partners. Natural gas generation, small modular reactors, microgrids and behind-the-meter power have become central themes across virtually every major data center conference. Developers increasingly speak about securing megawatts years before they discuss servers. But another infrastructure constraint is quietly following the same trajectory: Water. According to executives from Emergence Water and Nimbus Advanced Process Cooling Systems, water is rapidly evolving beyond its traditional role as a sustainability metric and becoming one of the primary determinants of where AI campuses can be built, how they are cooled, and how efficiently they will operate over the coming decade. Speaking with Data Center Frontier Editor in Chief Matt Vincent on the latest DCF Show podcast, Emergence Water Chief Product Officer Leif Percifield and Nimbus Technical Director Vamsi Mokkapati described an industry where water has effectively joined power and fiber as foundational infrastructure for AI development. “From a community perspective, water is absolutely the number one priority about where and why a data center gets built,” Percifield said. “From the developer, it’s pretty binary. They either have water available to them—or they don’t.” Water Is Becoming a Site Selection Constraint The shift reflects the changing realities of AI infrastructure. Traditional enterprise data centers often viewed water primarily through sustainability reporting or Power Usage Effectiveness (PUE) discussions. AI facilities operating at unprecedented rack densities have fundamentally altered that equation. Liquid cooling, hybrid cooling architectures and increasingly sophisticated thermal management strategies all place new emphasis on reliable long-term water availability. Equally important, communities are beginning to scrutinize water usage with the same intensity previously reserved for electrical demand. Percifield says those conversations are increasingly determining whether projects move forward at all.

U.S. Open powers up AI-ready network in challenging environment

Environmental conditions add another layer of complexity. Anthony Santora, managing director of IT for the USGA, describes the championship network as a data center without the usual comforts. There’s dust, rain, wind, and wide temperature swings instead of clean, controlled air. Hardware resides in trailers and weatherproof enclosures, not in racks behind raised floor tiles. For network engineers who spend most of their time on office campuses and in colos, that’s an important reminder: Critical infrastructure increasingly sits in places that look nothing like a traditional wiring closet. User behavior is just as hostile. The U.S. Open has its own term — the “Tiger effect” (though one could argue it’s now the Scottie effect) — for what happens when tens of thousands of fans follow a single golfer. The hot spot moves with the group, and the RF design must cope with a dense, moving cluster of devices. That pattern should sound familiar to anyone who supports large conferences or festivals; it’s the same phenomenon, just under a different name. Building an AI‑ready, fault‑tolerant course network Cisco’s answer to this environment is a fully redundant, mobile core design. Instead of a single large core in a building, the network collapses into dual trailers that serve as cores on the go, typically anchored at the NBC broadcast compound and another central location. Each core hosts Cisco Secure Firewall appliances, FMCs, core Catalyst switches, DHCP, UPS, and generators, all in pairs. Rodriguez was matter-of-fact about the philosophy: “We do everything in pairs as much as we can.” If one fails, its twin picks up the load.

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.

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

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

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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