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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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JLL’s 2026 Global Data Center Outlook: Navigating the AI Supercycle, Power Scarcity and Structural Market Transformation

Sovereign AI and National Infrastructure Policy JLL frames artificial intelligence infrastructure as an emerging national strategic asset, with sovereign AI initiatives representing an estimated $8 billion in cumulative capital expenditure by 2030. While modest relative to hyperscale investment totals, this segment carries outsized strategic importance. Data localization mandates, evolving AI regulation, and national security considerations are increasingly driving governments to prioritize domestic compute capacity, often with pricing premiums reaching as high as 60%. Examples cited across Europe, the Middle East, North America, and Asia underscore a consistent pattern: digital sovereignty is no longer an abstract policy goal, but a concrete driver of data center siting, ownership structures, and financing models. In practice, sovereign AI initiatives are accelerating demand for locally controlled infrastructure, influencing where capital is deployed and how assets are underwritten. For developers and investors, this shift introduces a distinct set of considerations. Sovereign projects tend to favor jurisdictional alignment, long-term tenancy, and enhanced security requirements, while also benefiting from regulatory tailwinds and, in some cases, direct state involvement. As AI capabilities become more tightly linked to economic competitiveness and national resilience, policy-driven demand is likely to remain a durable (if specialized) component of global data center growth. Energy and Sustainability as the Central Constraint Energy availability emerges as the report’s dominant structural constraint. In many major markets, average grid interconnection timelines now extend beyond four years, effectively decoupling data center development schedules from traditional utility planning cycles. As a result, operators are increasingly pursuing alternative energy strategies to maintain project momentum, including: Behind-the-meter generation Expanded use of natural gas, particularly in the United States Private-wire renewable energy projects Battery energy storage systems (BESS) JLL points to declining battery costs, seen falling below $90 per kilowatt-hour in select deployments, as a meaningful enabler of grid flexibility, renewable firming, and

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SoftBank, DigitalBridge, and Stargate: The Next Phase of OpenAI’s Infrastructure Strategy

OpenAI framed Stargate as an AI infrastructure platform; a mechanism to secure long-duration, frontier-scale compute across both training and inference by coordinating capital, land, power, and supply chain with major partners. When OpenAI announced Stargate in January 2025, the headline commitment was explicit: an intention to invest up to $500 billion over four to five years to build new AI infrastructure in the U.S., with $100 billion targeted for near-term deployment. The strategic backdrop in 2025 was straightforward. OpenAI’s model roadmap—larger models, more agents, expanded multimodality, and rising enterprise workloads—was driving a compute curve increasingly difficult to satisfy through conventional cloud procurement alone. Stargate emerged as a form of “control plane” for: Capacity ownership and priority access, rather than simply renting GPUs. Power-first site selection, encompassing grid interconnects, generation, water access, and permitting. A broader partner ecosystem beyond Microsoft, while still maintaining a working relationship with Microsoft for cloud capacity where appropriate. 2025 Progress: From Launch to Portfolio Buildout January 2025: Stargate Launches as a National-Scale Initiative OpenAI publicly launched Project Stargate on Jan. 21, 2025, positioning it as a national-scale AI infrastructure initiative. At this early stage, the work was less about construction and more about establishing governance, aligning partners, and shaping a public narrative in which compute was framed as “industrial policy meets real estate meets energy,” rather than simply an exercise in buying more GPUs. July 2025: Oracle Partnership Anchors a 4.5-GW Capacity Step On July 22, 2025, OpenAI announced that Stargate had advanced through a partnership with Oracle to develop 4.5 gigawatts of additional U.S. data center capacity. The scale of the commitment marked a clear transition from conceptual ambition to site- and megawatt-level planning. A figure of this magnitude reshaped the narrative. At 4.5 GW, Stargate forced alignment across transformers, transmission upgrades, switchgear, long-lead cooling

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Lenovo unveils purpose-built AI inferencing servers

There is also the Lenovo ThinkSystem SR650i, which offers high-density GPU computing power for faster AI inference and is intended for easy installation in existing data centers to work with existing systems. Finally, there is the Lenovo ThinkEdge SE455i for smaller, edge locations such as retail outlets, telecom sites, and industrial facilities. Its compact design allows for low-latency AI inference close to where data is generated and is rugged enough to operate in temperatures ranging from -5°C to 55°C. All of the servers include Lenovo’s Neptune air- and liquid-cooling technology and are available through the TruScale pay-as-you-go pricing model. In addition to the new hardware, Lenovo introduced new AI Advisory Services with AI Factory Integration. This service gives access to professionals for identifying, deploying, and managing best-fit AI Inferencing servers. It also launched Premier Support Plus, a service that gives professional assistance in data center management, freeing up IT resources for more important projects.

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Samsung warns of memory shortages driving industry-wide price surge in 2026

SK Hynix reported during its October earnings call that its HBM, DRAM, and NAND capacity is “essentially sold out” for 2026, while Micron recently exited the consumer memory market entirely to focus on enterprise and AI customers. Enterprise hardware costs surge The supply constraints have translated directly into sharp price increases across enterprise hardware. Samsung raised prices for 32GB DDR5 modules to $239 from $149 in September, a 60% increase, while contract pricing for DDR5 has surged more than 100%, reaching $19.50 per unit compared to around $7 earlier in 2025. DRAM prices have already risen approximately 50% year to date and are expected to climb another 30% in Q4 2025, followed by an additional 20% in early 2026, according to Counterpoint Research. The firm projected that DDR5 64GB RDIMM modules, widely used in enterprise data centers, could cost twice as much by the end of 2026 as they did in early 2025. Gartner forecast DRAM prices to increase by 47% in 2026 due to significant undersupply in both traditional and legacy DRAM markets, Chauhan said. Procurement leverage shifts to hyperscalers The pricing pressures and supply constraints are reshaping the power dynamics in enterprise procurement. For enterprise procurement, supplier size no longer guarantees stability. “As supply becomes more contested in 2026, procurement leverage will hinge less on volume and more on strategic alignment,” Rawat said. Hyperscale cloud providers secure supply through long-term commitments, capacity reservations, and direct fab investments, obtaining lower costs and assured availability. Mid-market firms rely on shorter contracts and spot sourcing, competing for residual capacity after large buyers claim priority supply.

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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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