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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

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)

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TotalEnergies farms out 40% participating interest in certain licenses offshore Nigeria to Chevron

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South Sudan Oil Exports at Risk

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Exxon CFO to Retire

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Phase 1 of Varco’s Sizing John BESS in Liverpool Reaches Full Operation

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Kinder Morgan Expects to Ride on LNG, Power Demand Growth

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Arista goes big with campus wireless tech

In a white paper describing how VESPA works, Arista wrote: The first component of VESPA involves Arista access points creating VXLAN tunnels to Arista switches serving as WLAN Gateways…. Second, as device packets arrive via the AP, it dynamically creates an Ethernet Segment Identifier (Type 6 ESI) based on the AP’s VTEP IP address. These dynamically created tunnels can scale to 30K ESI’s spread across paired switches in the cluster which provide active/active load sharing (performance+HA) to the APs. Third, the gateway switches use Type 2 EVPN NLRI (Network Layer Reachability Information) to learn and exchange end point MAC addresses across the cluster. … With this architecture, adding more EVPN WLAN gateways scales both AP and user connections, to tens of thousands of end points. To manage the forwarding information for hundreds of thousands of clients (e.g: FIB next hop and rewrite) would prove very complex and expensive if using conventional networking solutions. Arista’s innovation is to distribute this function across the WiFi access points with a unique MAC Rewrite Offload feature (MRO). With MRO, the access point is responsible for servicing mobile client ARP requests (using its own mac address), building a localized MAC-IP binding table, and forwarding client IP addresses to the WLAN gateways with the APs MAC address. The WLAN Gateways therefore only learns one (MAC) address for all the clients associated with the AP. This improves the gateway’s scaling from 10X to 100X, allowing these cost effective gateways to support hundreds of thousands of clients attached to the APs. AVA system gets a boost In addition to the new wireless technology, Arista is also bolstering the capabilities of its natural-language, generative AI-based Autonomous Virtual Assist (AVA) system for delivering network insights and AIOps.  AVA is aimed at providing an intelligent assistant that’s not there to replace

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Most significant networking acquisitions of 2025

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Aviz Networks launches enterprise-grade community SONiC distribution

First, the company enabled FRR (Free Range Routing) features that exist in the community code but aren’t consistently implemented across different ASICs. VRRP (Virtual Router Redudancy Protocol) provides router redundancy for high availability. Spanning tree variants prevent network loops in layer 2 topologies. MLAG allows two switches to act as a single logical device for link aggregation. EVPN enhancements support layer 2 and layer 3 VPN services over VXLAN overlays. These protocols work differently depending on the underlying silicon, so Aviz normalized their implementation across Broadcom, Nvidia, Cisco and Marvell chips. Second, Aviz fixed bugs discovered in production deployments. One customer deployed community SONiC with OpenStack and started migrating virtual machines between hosts. The network fabric couldn’t handle the workload and broke. Aviz identified the failure modes and patched them.  Third, Aviz built a software component that normalizes monitoring data across vendors. Broadcom’s Tomahawk ASIC generates different telemetry formats than Nvidia’s Spectrum or Cisco’s Silicon One. Network operators need consistent data for troubleshooting and capacity planning. The software collects ASIC-specific logs and network operating system telemetry, then translates them into a standardized format that works the same way regardless of which silicon vendor’s chips are running in the switches. Validated for enterprise deployment scenarios The distribution supports common enterprise network architectures.  IP CLOS provides the leaf-spine topology used in modern data centers for predictable latency and scalability. EVPN/VXLAN creates layer 2 and layer 3 overlay networks that span physical network boundaries. MLAG configurations provide link redundancy without spanning tree limitations. Aviz provides validated runbooks for these deployments across data center, edge and AI fabric use cases. 

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US approves Nvidia H200 exports to China, raising questions about enterprise GPU supply

Shifting demand scenarios What remains unclear is how much demand Chinese firms will actually generate, given Beijing’s recent efforts to steer its tech companies away from US chips. Charlie Dai, VP and principal analyst at Forrester, said renewed H200 access is likely to have only a modest impact on global supply, as China is prioritizing domestic AI chips and the H200 remains below Nvidia’s latest Blackwell-class systems in performance and appeal. “While some allocation pressure may emerge, most enterprise customers outside China will see minimal disruption in pricing or lead times over the next few quarters,” Dai added. Neil Shah, VP for research and partner at Counterpoint Research, agreed that demand may not surge, citing structural shifts in China’s AI ecosystem. “The Chinese ecosystem is catching up fast, from semi to stack, with models optimized on the silicon and software,” Shah said. Chinese enterprises might think twice before adopting a US AI server stack, he said. Others caution that even selective demand from China could tighten global allocation at a time when supply of high-end accelerators remains stretched, and data center deployments continue to rise.

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What does Arm need to do to gain enterprise acceptance?

But in 2017, AMD released the Zen architecture, which was equal if not superior to the Intel architecture. Zen made AMD competitive, and it fueled an explosive rebirth for a company that was near death a few years prior. AMD now has about 30% market share, while Intel suffers from a loss of technology as well as corporate leadership. Now, customers have a choice of Intel or AMD, and they don’t have to worry about porting their applications to a new platform like they would have to do if they switched to Arm. Analysts weigh in on Arm Tim Crawford sees no demand for Arm in the data center. Crawford is president of AVOA, a CIO consultancy. In his role, he talks to IT professionals all the time, but he’s not hearing much interest in Arm. “I don’t see Arm really making a dent, ever, into the general-purpose processor space,” Crawford said. “I think the opportunity for Arm is special applications and special silicon. If you look at the major cloud providers, their custom silicon is specifically built to do training or optimized to do inference. Arm is kind of in the same situation in the sense that it has to be optimized.” “The problem [for Arm] is that there’s not necessarily a need to fulfill at this point in time,” said Rob Enderle, principal analyst with The Enderle Group. “Obviously, there’s always room for other solutions, but Arm is still going to face the challenge of software compatibility.” And therein lies what may be Arm’s greatest challenge: software compatibility. Software doesn’t care (usually) if it’s on Intel or AMD, because both use the x86 architecture, with some differences in extensions. But Arm is a whole new platform, and that requires porting and testing. Enterprises generally don’t like disruption —

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Intel decides to keep networking business after all

That doesn’t explain why Intel made the decision to pursue spin-off in the first place. In July, NEX chief Sachin Katti issued a memo that outlined plans to establish key elements of the Networking and Communications business as a stand-alone company. It looked like a done deal, experts said. Jim Hines, research director for enabling technologies and semiconductors at IDC, declined to speculate on whether Intel could get a decent offer but noted NEX is losing ground. IDC estimates Intel’s market share in overall semiconductors at 6.8% in Q3 2025, which is down from 7.4% for the full year 2024 and 9.2% for the full year 2023. Intel’s course reversal “is a positive for Intel in the long term, and recent improvements in its financial situation may have contributed to the decision to keep NEX in house,” he said. When Tan took over as CEO earlier this year, prioritized strengthening the balance sheet and bringing a greater focus on execution. Divest NEX was aligned with these priorities, but since then, Intel has secured investments from the US Government, Nvidia and SoftBank that have reduced the need to raise cash through other means, Hines notes. “The NEX business will prove to be a strategic asset for Intel as it looks to protect and expand its position in the AI datacenter market. Success in this market now requires processor suppliers to offer a full-stack solution, not just silicon. Scale-up and scale-out networking solutions are a key piece of the package, and Intel will be able to leverage its NEX technologies and software, including silicon photonics, to develop differentiated product offerings in this space,” Hines 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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