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Mitigating emissions from air freight: Unlocking the potential of SAF with book and claim

In association withAvelia Emissions from air freight have increased by 25% since 2019, according to a 2024 analysis by environmental advocacy organization Stand.Earth. The researchers found that the expansion of cargo-only fleets to transport goods during the pandemic — as air travel halted, slower freight modes faced disruption, but demand for rapid delivery soared — has led to a yearly increase of almost 20 million tons of carbon dioxide, making up 93.8m tonnes from air freight overall. [embedded content] And though fleet modernization and operational improvements by freight operators have contributed to ongoing decarbonization efforts, sustainable aviation fuel (SAF) looks set to be instrumental in helping the sector achieve its ambitions to reduce environmental footprint in the long-term. When used neat, or pure and unblended, SAF can help reduce the life cycle of greenhouse gas emissions from aviation by as much as 80% relative to conventional fuel. It’s why the International Air Transport Association (IATA) estimates that SAF could account for as much as 65% of total reduction of emissions. For Christoph Wolff, CEO of the Smart Freight Centre, “SAF is the main pathway” to decarbonization across both freight and the wider aviation ecosystem. “The great thing about SAF is it’s chemically identical to Jet A fuel,” he says. “You can blend it [which means] you have a pathway to ramp it up. You can start small and you can scale it. By scaling it there is the promise or the hope that the price comes down.” At at least twice the price of conventional jet fuel, cost is a significant barrier hindering broader adoption. And it isn’t the only one standing between SAF and wider penetration. Bridging the gap between a concentrated supply of SAF and global demand also remains a major hurdle. Though the number of verified SAF outlets has increased from fewer than 20 locations in 2021 to 114 as of April 2025, according to sustainability solutions framework 4Air, that accounts for only 92 airports worldwide out of more than 40,000. “SAF is central to the decarbonization of the aviation sector,” believes Raman Ojha, president of Shell Aviation. “Having said that, adoption and penetration of SAF hasn’t really picked up massively. It’s not due to lack of production capacity, but there are lots of things that are at play. And book and claim in that context helps to bridge that gap.” Bridging the gap with book and claim Book and claim is a chain of custody model, where the flow of administrative records is not necessarily connected to the physical product through the supply chain (source: ISO 22095:2020). Book and claim potentially enables airlines and corporations to access the life cycle GHG emissions reduction benefits of SAF relative to conventional jet fuel even when SAF is not physically available at their location; this model helps bridge the gap between that concentrated supply and global demand, until SAF’s availability improves. “To be bold, without book and claim, no short-term science-based target will be achieved,” says Bettina Paschke, vice president of ESG accounting, reporting and controlling at DHL Express. “Book and claim is essential to achieving science-based targets.” “SAF production facilities are not everywhere,” she reiterates. “They’re very focused on one location, and if a customer wants to fulfil a mass balance obligation, SAF would need to be shipped around the world just to be at that airport for that customer. That would be very complicated, and very unrealistic.” It would also, counterintuitively, increase total emissions. By using book and claim instead, air freight operators can unlock the life cycle greenhouse gas emissions reduction benefits of SAF relative to conventional jet fuel now, without waiting for supply to broaden. “It might no longer be needed when we have SAF product facilities at each airport in the future,” she points out. “But at the moment, that’s not the case.” At DHL itself, the mechanism has become central to achieving its own three interconnected sustainability pillars, which focus on decarbonizing logistics supply chains, supporting customers toward their decarbonization goals, and ensuring credible emission claims can be shared along the value chain. Demonstrating the importance of a credible and viable framework for book and claim systems is also what inspired the 2022 launch of Shell’s Avelia, one of the first blockchain-powered digital SAF book and claim solutions for aviation, which expanded in 2024 to encompass air freight in addition to business travel. Depending on the offering, Avelia offers freight forwarders the opportunity to share the life cycle greenhouse gas emissions reduction benefits of SAF relative to conventional jet fuel across the value chain with shippers using their services. “It’s also backed by a physical supply chain, which gives our customers — whether those be corporates or freight forwarders or even airlines — a peace of mind that the SAF has been injected at a certain airport, it’s been used and environmental attributes, with the help of blockchain, have been tracked to where they’re getting retired,” says Ojha. He adds: “The most important or critical part is the transparency that it’s providing to our customers to be sure that they’re not saying something which they can’t confidently stand behind.” Moving beyond early adoption To scale up SAF via book and claim and help make it a more commercially viable lower-carbon solution, its adoption will need to be a coordinated “ecosystem play,” says Wolff. That includes early adopters, such as DHL, inspiring action from peers, solution providers such as Shell, working with various stakeholders to drive joint advocacy, and industry associations, like the Smart Freight Centre creating the required frameworks, educational resources, and industry alignment. An active book and claim community made up of many forward-thinking advocates is already driving much of this work forward with a common goal to develop greater standardization and consensus, Wolff points out. “It helps to make sure all definitions on the system are compatible and they can talk to one another, provide educational support, and [also that] there’s a repository of transactions so that it can be documented in a way that people can see and think, ‘oh this is how we do it.’ There are some early adopters that are very experienced, but it needs a lot more people for it to get comfortable.” In early 2024, discussions were held with a diverse group of expert book and claim stakeholders to develop and refine 11 key principles and best practices book and claim models. These represent an aligned set of principles informed by practical successes and challenges faced by practitioners working to decarbonize the heavy transport sector. Adherence to such a framework is crucial given that book and claim is not yet accepted by the Greenhouse Gas (GHG) Protocol nor the Science Based Targets Initiative (SBTi) as a recognized model for reducing greenhouse gas emissions — though there are hopes that might change. “The industrialization of book and claim delivery systems is key to credibility and recognition,” says Wolff. “The Greenhouse Gas Protocol and the Science Based Targets Initiative are making steps in recognizing that. There’s a pathway that the Smart Freight Centre is very closely involved in the technical working groups for [looking]to build such a system where, in addition to physical inventory, you also pursue market-based inventories.” Paschke urges companies not to sit back and wait for policy to change before taking action, though. “The solution is there,” she says. “There are companies like DHL that are making huge upfront investments, and every single contribution helps to scale the industry and give a strong signal to the eco-space.” As pressure to accelerate decarbonization gains pace, it’s critical that air freight operators consider this now, agrees Ojha. “Don’t wait for perfection in guidelines, regulations, or platforms — act now,” he says. “That’s very, very critical. Second, learn by doing and join hands with others. Don’t try to do everything independently or in-house. “Third, make use of registries and platforms, such as Avelia, that can give credibility. Join them, utilize them, and leverage them so that you won’t have to establish auditability from scratch. “And fourth, don’t look at scope book and claim as a means for acquiring a certificate for environmental attributes. Think in terms of your decarbonisation commitment and think of this as a tool for exposure management. Think in terms of the bigger picture.” That bigger picture being a significant sector-wide push toward faster decarbonization — and turning the tide on emissions’ steep upward ascent. Watch the full webcast. This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review. This content is produced by MIT Technology Review Insights in association with Avelia. Avelia is a Shell owned solution and brand that was developed with support from Amex GBT, Accenture and Energy Web Foundation. The views from individuals not affiliated with Shell are their own and not those of Shell PLC or its affiliates. Cautionary note | Shell Global

In association withAvelia

Emissions from air freight have increased by 25% since 2019, according to a 2024 analysis by environmental advocacy organization Stand.Earth.

The researchers found that the expansion of cargo-only fleets to transport goods during the pandemic — as air travel halted, slower freight modes faced disruption, but demand for rapid delivery soared — has led to a yearly increase of almost 20 million tons of carbon dioxide, making up 93.8m tonnes from air freight overall.

[embedded content]

And though fleet modernization and operational improvements by freight operators have contributed to ongoing decarbonization efforts, sustainable aviation fuel (SAF) looks set to be instrumental in helping the sector achieve its ambitions to reduce environmental footprint in the long-term.

When used neat, or pure and unblended, SAF can help reduce the life cycle of greenhouse gas emissions from aviation by as much as 80% relative to conventional fuel. It’s why the International Air Transport Association (IATA) estimates that SAF could account for as much as 65% of total reduction of emissions.

For Christoph Wolff, CEO of the Smart Freight Centre, “SAF is the main pathway” to decarbonization across both freight and the wider aviation ecosystem.

“The great thing about SAF is it’s chemically identical to Jet A fuel,” he says. “You can blend it [which means] you have a pathway to ramp it up. You can start small and you can scale it. By scaling it there is the promise or the hope that the price comes down.”

At at least twice the price of conventional jet fuel, cost is a significant barrier hindering broader adoption.

And it isn’t the only one standing between SAF and wider penetration.

Bridging the gap between a concentrated supply of SAF and global demand also remains a major hurdle.

Though the number of verified SAF outlets has increased from fewer than 20 locations in 2021 to 114 as of April 2025, according to sustainability solutions framework 4Air, that accounts for only 92 airports worldwide out of more than 40,000.

“SAF is central to the decarbonization of the aviation sector,” believes Raman Ojha, president of Shell Aviation. “Having said that, adoption and penetration of SAF hasn’t really picked up massively. It’s not due to lack of production capacity, but there are lots of things that are at play. And book and claim in that context helps to bridge that gap.”

Bridging the gap with book and claim

Book and claim is a chain of custody model, where the flow of administrative records is not necessarily connected to the physical product through the supply chain (source: ISO 22095:2020).

Book and claim potentially enables airlines and corporations to access the life cycle GHG emissions reduction benefits of SAF relative to conventional jet fuel even when SAF is not physically available at their location; this model helps bridge the gap between that concentrated supply and global demand, until SAF’s availability improves.

“To be bold, without book and claim, no short-term science-based target will be achieved,” says Bettina Paschke, vice president of ESG accounting, reporting and controlling at DHL Express. “Book and claim is essential to achieving science-based targets.”

“SAF production facilities are not everywhere,” she reiterates. “They’re very focused on one location, and if a customer wants to fulfil a mass balance obligation, SAF would need to be shipped around the world just to be at that airport for that customer. That would be very complicated, and very unrealistic.” It would also, counterintuitively, increase total emissions. By using book and claim instead, air freight operators can unlock the life cycle greenhouse gas emissions reduction benefits of SAF relative to conventional jet fuel now, without waiting for supply to broaden. “It might no longer be needed when we have SAF product facilities at each airport in the future,” she points out. “But at the moment, that’s not the case.”

At DHL itself, the mechanism has become central to achieving its own three interconnected sustainability pillars, which focus on decarbonizing logistics supply chains, supporting customers toward their decarbonization goals, and ensuring credible emission claims can be shared along the value chain.

Demonstrating the importance of a credible and viable framework for book and claim systems is also what inspired the 2022 launch of Shell’s Avelia, one of the first blockchain-powered digital SAF book and claim solutions for aviation, which expanded in 2024 to encompass air freight in addition to business travel. Depending on the offering, Avelia offers freight forwarders the opportunity to share the life cycle greenhouse gas emissions reduction benefits of SAF relative to conventional jet fuel across the value chain with shippers using their services.

“It’s also backed by a physical supply chain, which gives our customers — whether those be corporates or freight forwarders or even airlines — a peace of mind that the SAF has been injected at a certain airport, it’s been used and environmental attributes, with the help of blockchain, have been tracked to where they’re getting retired,” says Ojha.

He adds: “The most important or critical part is the transparency that it’s providing to our customers to be sure that they’re not saying something which they can’t confidently stand behind.”

Moving beyond early adoption

To scale up SAF via book and claim and help make it a more commercially viable lower-carbon solution, its adoption will need to be a coordinated “ecosystem play,” says Wolff. That includes early adopters, such as DHL, inspiring action from peers, solution providers such as Shell, working with various stakeholders to drive joint advocacy, and industry associations, like the Smart Freight Centre creating the required frameworks, educational resources, and industry alignment.

An active book and claim community made up of many forward-thinking advocates is already driving much of this work forward with a common goal to develop greater standardization and consensus, Wolff points out. “It helps to make sure all definitions on the system are compatible and they can talk to one another, provide educational support, and [also that] there’s a repository of transactions so that it can be documented in a way that people can see and think, ‘oh this is how we do it.’ There are some early adopters that are very experienced, but it needs a lot more people for it to get comfortable.”

In early 2024, discussions were held with a diverse group of expert book and claim stakeholders to develop and refine 11 key principles and best practices book and claim models. These represent an aligned set of principles informed by practical successes and challenges faced by practitioners working to decarbonize the heavy transport sector.

Adherence to such a framework is crucial given that book and claim is not yet accepted by the Greenhouse Gas (GHG) Protocol nor the Science Based Targets Initiative (SBTi) as a recognized model for reducing greenhouse gas emissions — though there are hopes that might change.

“The industrialization of book and claim delivery systems is key to credibility and recognition,” says Wolff. “The Greenhouse Gas Protocol and the Science Based Targets Initiative are making steps in recognizing that. There’s a pathway that the Smart Freight Centre is very closely involved in the technical working groups for [looking]to build such a system where, in addition to physical inventory, you also pursue market-based inventories.”

Paschke urges companies not to sit back and wait for policy to change before taking action, though. “The solution is there,” she says. “There are companies like DHL that are making huge upfront investments, and every single contribution helps to scale the industry and give a strong signal to the eco-space.”

As pressure to accelerate decarbonization gains pace, it’s critical that air freight operators consider this now, agrees Ojha. “Don’t wait for perfection in guidelines, regulations, or platforms — act now,” he says. “That’s very, very critical. Second, learn by doing and join hands with others. Don’t try to do everything independently or in-house.

“Third, make use of registries and platforms, such as Avelia, that can give credibility. Join them, utilize them, and leverage them so that you won’t have to establish auditability from scratch.

“And fourth, don’t look at scope book and claim as a means for acquiring a certificate for environmental attributes. Think in terms of your decarbonisation commitment and think of this as a tool for exposure management. Think in terms of the bigger picture.”

That bigger picture being a significant sector-wide push toward faster decarbonization — and turning the tide on emissions’ steep upward ascent.

Watch the full webcast.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.

This content is produced by MIT Technology Review Insights in association with Avelia. Avelia is a Shell owned solution and brand that was developed with support from Amex GBT, Accenture and Energy Web Foundation. The views from individuals not affiliated with Shell are their own and not those of Shell PLC or its affiliates. Cautionary note | Shell Global

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Cooling Consolidation Hits AI Scale: LiquidStack, Submer, and the Future of Data Center Thermal Strategy

As AI infrastructure scales toward ever-higher rack densities and gigawatt-class campuses, cooling has moved from a technical subsystem to a defining strategic issue for the data center industry. A trio of announcements in early February highlights how rapidly the cooling and AI infrastructure stack is consolidating and evolving: Trane Technologies’ acquisition of LiquidStack; Submer’s acquisition of Radian Arc, extending its reach from core data centers into telco edge environments; and Submer’s partnership with Anant Raj to accelerate sovereign AI infrastructure deployment across India. Layered atop these developments is fresh guidance from Oracle Cloud Infrastructure explaining why closed-loop, direct-to-chip cooling is becoming central to next-generation facility design, particularly in regions where water use has become a flashpoint in community discussions around data center growth. Taken together, these developments show how the industry is moving beyond point solutions toward integrated, scalable AI infrastructure ecosystems, where cooling, compute, and deployment models must work together across hyperscale campuses and distributed edge environments alike. Trane Moves to Own the Cooling Stack The most consequential development comes from Trane Technologies, which on February 10 announced it has entered into a definitive agreement to acquire LiquidStack, one of the pioneers and leading innovators in data center liquid cooling. The acquisition significantly strengthens Trane’s ambition to become a full-service thermal partner for data center operators, extending its reach from plant-level systems all the way down to the chip itself. LiquidStack, headquartered in Carrollton, Texas, built its reputation on immersion cooling and advanced direct-to-chip liquid solutions supporting high-density deployments across hyperscale, enterprise, colocation, edge, and blockchain environments. Under Trane, those technologies will now be scaled globally and integrated into a broader thermal portfolio. In practical terms, Trane is positioning itself to deliver cooling across the full thermal chain, including: • Central plant equipment and chillers.• Heat rejection and controls

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Infrastructure Maturity Defines the Next Phase of AI Deployment

The State of Data Infrastructure Global Report 2025 from Hitachi Vantara arrives at a moment when the data center industry is undergoing one of the most profound structural shifts in its history. The transition from enterprise IT to AI-first infrastructure has moved from aspiration to inevitability, forcing operators, developers, and investors to confront uncomfortable truths about readiness, resilience, and risk. Although framed around “AI readiness,” the report ultimately tells an infrastructure story: one that maps directly onto how data centers are designed, operated, secured, and justified economically. Drawing on a global survey of more than 1,200 IT leaders, the report introduces a proprietary maturity model that evaluates organizations across six dimensions: scalability, reliability, security, governance, sovereignty, and sustainability. Respondents are then grouped into three categories—Emerging, Defined, and Optimized—revealing a stark conclusion: most organizations are not constrained by access to AI models or capital, but by the fragility of the infrastructure supporting their data pipelines. For the data center industry, the implications are immediate, shaping everything from availability design and automation strategies to sustainability planning and evolving customer expectations. In short, extracting value from AI now depends less on experimentation and more on the strength and resilience of the underlying infrastructure. The Focus of the Survey: Infrastructure, Not Algorithms Although the report is positioned as a study of AI readiness, its primary focus is not models, training approaches, or application development, but rather the infrastructure foundations required to operate AI reliably at scale. Drawing on responses from more than 1,200 organizations, Hitachi Vantara evaluates how enterprises are positioned to support production AI workloads across six dimensions as stated above: scalability, reliability, security, governance, sovereignty, and sustainability. These factors closely reflect the operational realities shaping modern data center design and management. The survey’s central argument is that AI success is no longer

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AI’s New Land Grab: Meta’s Indiana Megaproject and the Rise of Europe’s Neocloud Challengers

While Meta’s Indiana campus anchors hyperscale expansion in the United States, Europe recorded its own major infrastructure milestone this week as Amsterdam-based AI infrastructure provider Nebius unveiled plans for a 240-megawatt data center campus in Béthune, France, near Lille in the country’s northern industrial corridor. When completed, the campus will rank among Europe’s largest AI-focused data center facilities and positions northern France as a growing node in the continent’s expanding AI infrastructure map. The development repurposes a former Bridgestone tire manufacturing site, reflecting a broader trend across Europe in which legacy industrial properties, already equipped with heavy power access, transport links, and industrial zoning, are being converted into large-scale digital infrastructure hubs. Located within reach of connectivity and enterprise corridors linking Paris, Brussels, London, and Amsterdam, the site allows Nebius to serve major European markets while avoiding the congestion and power constraints increasingly shaping Tier 1 data center hubs. Industrial Infrastructure Becomes Digital Infrastructure Developers increasingly view former industrial sites as ideal for AI campuses because they often provide: • Existing grid interconnection capacity built for heavy industry• Transport and logistics infrastructure already in place• Industrial zoning that reduces permitting friction• Large contiguous parcels suited to phased campus expansion For regions like Hauts-de-France, redevelopment projects also offer economic transition opportunities, replacing legacy manufacturing capacity with next-generation digital infrastructure investment. Local officials have positioned the project as part of broader efforts to reposition northern France as a logistics and technology hub within Europe. The Neocloud Model Gains Ground Beyond the site itself, Nebius’ expansion illustrates the rapid emergence of neocloud infrastructure providers, companies building GPU-intensive AI capacity without operating full hyperscale cloud ecosystems. These firms increasingly occupy a strategic middle ground: supplying AI compute capacity to enterprises, startups, and even hyperscalers facing short-term infrastructure constraints. Nebius’ rise over the past year

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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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