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Nigerian Oil Pipeline Sabotage Threatens Crude Output Revival

Nigeria’s push to revive oil production and encourage investment has been put at risk by sabotage at the heart of its crude pipeline system. Better security has been key to a recovery in the nation’s output, which rose 40% over the past few years after slumping to little more than half its historic peak. In […]

Nigeria’s push to revive oil production and encourage investment has been put at risk by sabotage at the heart of its crude pipeline system.

Better security has been key to a recovery in the nation’s output, which rose 40% over the past few years after slumping to little more than half its historic peak. In January, Africa’s biggest producer even breached its once-distant OPEC quota. 

The vandalism on a segment of the Trans-Niger Pipeline — which handles about 15% of the nation’s exports — is a setback for a government that had already taken measures to increase security in the area. President Bola Tinubu responded by imposing a state of emergency in Rivers State on Tuesday, citing an 18-month political standoff between local officials who he said failed to stop acts of sabotage by militants. 

“This is a blow to the Tinubu government’s recent successes on oil output, gains driven in part by improved security measures,” said Clementine Wallop, director for sub-Saharan Africa at political-risk consultant Horizon Engage. “It is also a very difficult investment signal during a period where the government seemed to be turning a corner on energy.”

Renaissance Africa Energy, a local consortium that only last week took control of assets including the TNP that it bought from Shell Plc, said it has no plans to issue a force majeure over exports of Bonny Light crude. Two tankers are waiting to load from the Bonny terminal, according to ship tracking data compiled by Bloomberg.

In 2022, when Nigeria nearly dipped below a million barrels a day, security on the TNP had deteriorated to such an extent that the pipeline system had been illegally tapped in about 150 places. That meant producers only received a small fraction of the volumes they pumped through.

Tightening security on oil pipelines has recently pushed thieves to target gas conduits instead. Still, the broader revival of vandalism and sabotage raises critical challenges for Nigeria, which relies on oil and gas revenue to fund about half of its budget. 

The political instability that led to Tinubu imposing a state of emergency adds to the uncertainty. That started when Rivers State Governor Siminalayi Fubara and his predecessor Nyesom Wike — a Tinubu ally and the only opposition member in the president’s cabinet — fell out after elections in 2023, creating local factions that threatened to turn violent.

“Against that backdrop, we see scope for further near-term unrest,” Wallop said.

Last month, Nigeria’s highest court ruled that Fubara had acted illegally when he governed the state without the majority of legislators loyal to his rival. It directed the central bank to withhold revenues — mostly its share of crude oil and gas sales — further raising tensions.

Tinubu ordered the suspension of Fubara and his deputy for six months, alongside local legislators elected in 2023. The president appointed a retired military administrator to govern the state.

Renaissance has begun a joint investigation into the vandalism, according to a company spokesman. While avoiding a force majeure — a legal clause allowing companies to skip their contractual obligations — the infrastructure damage presents a first major challenge to the local group.

“The approach Renaissance takes will be crucial in setting the tone around how the above ground challenges in Nigeria’s oil and gas sector will be resolved by the indigenous operators,” said Mansur Mohammed, head of West Africa upstream research for Wood Mackenzie Ltd.



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Google Cloud partners with mLogica to offer mainframe modernization

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Power Moves: Viaro’s head of transition to operatorship and more

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Judge Rules Against Sale of Gulf of Mexico Oil Drilling Rights

A federal district judge on Thursday ruled against a Biden administration sale of oil and gas drilling rights in the Gulf of Mexico, faulting the government with failing to sufficiently analyze its possible effects on the climate and endangered whales.  However, US District Judge Amit P. Mehta in Washington left open the question of what to do about the two-year-old sale, instead directing additional arguments on the best remedy. Options could include invalidating leases sold in the auction or ordering those contracts be revised to include more limitations. The sale, which Congress mandated as part of the Inflation Reduction Act, made 13,600 blocks spanning approximately 73.3 million acres available. Ultimately, 32 companies, including Chevron USA, Inc., participated in that March 29, 2023 auction, paying the government $250.6 million for 299 leases.   But Mehta said the Interior Department violated the National Environmental Policy Act by insufficiently analyzing the auction. Among the problems, Mehta found, was that Interior’s Bureau of Ocean Energy Management didn’t fully consider potential energy market changes in its analysis of the potential greenhouse gas emissions that would result from activity on new oil and gas leases.  Mehta also said the bureau had made a “glaring omission” in not incorporating another agency’s assessment about the habitat and location of the endangered Rice’s whale. The bureau focused its impact analysis on the species’ core habitat, even though there was “credible evidence” it could be persistently found outside the area, the judge said.  Although the Inflation Reduction Act required the sale, Mehta emphasized that the Interior Department still retained discretion to set terms and impose limits on available acreage.  The challenge was brought by six environmental organizations. George Torgun, an a lawyer with Earthjustice, called the ruling “a welcome moment of justice for the Gulf ecosystem and frontline communities who have

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GM Energy joins PG&E bidirectional EV charging pilot in California

GM Energy has joined Pacific Gas & Electric Co.’s vehicle-to-everything bidirectional charging pilot program for electric vehicles in Northern and Central California, the utility provider announced March 13. Eligible residential customers enrolled in PG&E’s vehicle-to-everything (V2X) pilot will receive discounts of up to $4,500 off the price of a GM Energy home charging bundle and vehicle-to-home enablement kit, which is usually priced at $7,299. The base incentive is $2,500 for installing the equipment, with up to $2,000 of additional incentives available for residents of disadvantaged communities and early adopters. Vehicle-to-home charging technology is intended to serve as a backup source of power that can, for example, supply energy to homes during power outages. But according to the companies involved in the pilot project, it can do much more. “For utilities, legislators, customers and others, this pilot is an opportunity to see the full value of our V2H technology beyond just providing power to a home during power outages,” GM Energy Vice President Wade Sheffer said in a statement. “This can be a tool that helps overall grid resiliency and showcases the unique advantages of EVs while, in the future, may even reduce the overall total cost of EV ownership.” The partnership highlights how utilities are increasingly working with automakers to determine strategies to reduce demand on the energy grid and help accelerate the shift to EVs. PG&E is also working with Ford in a similar partnership, and has partnered with BMW since 2015 to study smart charging. GM EVs currently eligible for the program include the 2024 Chevrolet Silverado, Equinox, Blazer and GMC Sierra Denali, as well as the 2024-2025 Cadillac Lyriq. However, GM Energy soon plans to add all of the automaker’s EVs to the pilot. Residents participating in the pilot must also enroll in PG&E’s Emergency Load Reduction Program, which offers incentives for customers

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TotalEnergies Invests $172 Million in 6 German Battery Storage Projects

TotalEnergies SE has announced an investment outlay of EUR 160 million ($172.34 million) for 6 battery energy storage system projects under construction in Germany. The projects have a combined capacity of 221 megawatts (MW). They are being developed by Kyon Energy, acquired by the French energy major last year. Construction started at the end of 2024 and commissioning is planned for early 2026, according to TotalEnergies. “The launch of these projects marks a major milestone in TotalEnergies’ development of battery energy storage capacity in Germany, where the Company has operations in the production, trading, aggregation and commercialization of clean firm power”, TotalEnergies said in a press release. “This storage capacity will allow TotalEnergies to contribute to the resilience of the German power system, by reducing congestion and adding flexibility in order to quickly boost the country’s renewables sector”. TotalEnergies said it has 2 gigawatts of storage capacity under development and 321 MW under construction in Germany. “The implementation and integration of all these battery projects will allow us to supply our customers with clean firm power, contributing directly to our targeted 12 percent profitability in this activity”, commented chair and chief executive Patrick Pouyanné. In Germany, TotalEnergies expects to have 7 GW of onshore wind and solar in development and 200 MW of installed or under construction after the completion of its acquisition of VSB Group. Announcing the EUR 1.57 billion purchase from Swiss asset manager Partners Group on December 4, 2024, TotalEnergies noted, “VSB has over 475 MW of renewable capacity in operation or under construction mainly in Germany and France, and a pipeline of 18 GW of wind, solar and battery storage technologies mainly across Germany, Poland and France”. “This transaction will strengthen TotalEnergies Integrated Power value chain in Germany, which represents half of VSB’s portfolio”, TotalEnergies said then.

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Reservoir Group’s smarter, more cost effective approach to well data collection

Leading services company Reservoir Group has found an innovative solution during coil tubing operations that promises to save operators time and money. For decades, gathering critical data during coil tubing deployment involved separate logging runs, adding time and cost to well monitoring. That’s because traditional methods required wireline or slickline deployment of gauges, forcing operators to interrupt operations to retrieve vital information. Recognising the inefficiencies of this approach, Reservoir Group developed a system of gauges mounted directly on coil tubing. This breakthrough technology allows operators to collect pressure and temperature data, assess wellbore integrity, and detect leaks during the drilling process itself. An early deployment of the system saved one company $65,000. How groundbreaking technology works Reservoir Group’s flow-through gauge carrier is a non-magnetic, 718 nickel alloy tool that seamlessly integrates with coil tubing operations. The carrier can be equipped with a range of memory tools, including: Dual pressure and temperature gauges Acoustic logging tools Gamma ray/CCL (casing collar locator) Electromagnetic logging tools By deploying these gauges on coil tubing, operators can simultaneously conduct standard well interventions, such as jetting cleanouts, while collecting essential well data. This eliminates the downtime typically associated with logging runs and ensures that valuable insights are gathered without disrupting the workflow. Key benefits of Reservoir Group’s solution Compared to traditional logging methods, Reservoir Group’s coil tubing solution offers several distinct advantages: Efficiency Gains: Since the gauges are deployed on coil tubing during existing operations, there’s no need for an additional logging run, significantly reducing rig time. Cost Savings: Eliminating separate wireline or slickline runs results in substantial cost reductions. A recent case study demonstrated savings of $65,000 for a single well intervention. Versatility: The technology supports a wide range of well environments, from pressures of 150 psi to 30,000 psi and temperatures between -20°C and

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E&Ps Flag ‘Uncertainty’ in Latest Dallas Fed Energy Survey

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Airtel connects India with 100Tbps submarine cable

“Businesses are becoming increasingly global and digital-first, with industries such as financial services, data centers, and social media platforms relying heavily on real-time, uninterrupted data flow,” Sinha added. The 2Africa Pearls submarine cable system spans 45,000 kilometers, involving a consortium of global telecommunications leaders including Bayobab, China Mobile International, Meta, Orange, Telecom Egypt, Vodafone Group, and WIOCC. Alcatel Submarine Networks is responsible for the cable’s manufacturing and installation, the statement added. This cable system is part of a broader global effort to enhance international digital connectivity. Unlike traditional telecommunications infrastructure, the 2Africa Pearls project represents a collaborative approach to solving complex global communication challenges. “The 100 Tbps capacity of the 2Africa Pearls cable significantly surpasses most existing submarine cable systems, positioning India as a key hub for high-speed connectivity between Africa, Europe, and Asia,” said Prabhu Ram, VP for Industry Research Group at CyberMedia Research. According to Sinha, Airtel’s infrastructure now spans “over 400,000 route kilometers across 34+ cables, connecting 50 countries across five continents. This expansive infrastructure ensures businesses and individuals stay seamlessly connected, wherever they are.” Gogia further emphasizes the broader implications, noting, “What also stands out is the partnership behind this — Airtel working with Meta and center3 signals a broader shift. India is no longer just a consumer of global connectivity. We’re finally shaping the routes, not just using them.”

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Former Arista COO launches NextHop AI for customized networking infrastructure

Sadana argued that unlike traditional networking where an IT person can just plug a cable into a port and it works, AI networking requires intricate, custom solutions. The core challenge is creating highly optimized, efficient networking infrastructure that can support massive AI compute clusters with minimal inefficiencies. How NextHop is looking to change the game for hyperscale networking NextHop AI is working directly alongside its hyperscaler customers to develop and build customized networking solutions. “We are here to build the most efficient AI networking solutions that are out there,” Sadana said. More specifically, Sadana said that NextHop is looking to help hyperscalers in several ways including: Compressing product development cycles: “Companies that are doing things on their own can compress their product development cycle by six to 12 months when they partner with us,” he said. Exploring multiple technological alternatives: Sadana noted that hyperscalers might try and build on their own and will often only be able to explore one or two alternative approaches. With NextHop, Sadana said his company will enable them to explore four to six different alternatives. Achieving incremental efficiency gains: At the massive cloud scale that hyperscalers operate, even an incremental one percent improvement can have an oversized outcome. “You have to make AI clusters as efficient as possible for the world to use all the AI applications at the right cost structure, at the right economics, for this to be successful,” Sadana said. “So we are participating by making that infrastructure layer a lot more efficient for cloud customers, or the hyperscalers, which, in turn, of course, gives the benefits to all of these software companies trying to run AI applications in these cloud companies.” Technical innovations: Beyond traditional networking In terms of what the company is actually building now, NextHop is developing specialized network switches

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Microsoft abandons data center projects as OpenAI considers its own, hinting at a market shift

A potential ‘oversupply position’ In a new research note, TD Cowan analysts reportedly said that Microsoft has walked away from new data center projects in the US and Europe, purportedly due to an oversupply of compute clusters that power AI. This follows reports from TD Cowen in February that Microsoft had “cancelled leases in the US totaling a couple of hundred megawatts” of data center capacity. The researchers noted that the company’s pullback was a sign of it “potentially being in an oversupply position,” with demand forecasts lowered. OpenAI, for its part, has reportedly discussed purchasing billions of dollars’ worth of data storage hardware and software to increase its computing power and decrease its reliance on hyperscalers. This fits with its planned Stargate Project, a $500 billion, US President Donald Trump-endorsed initiative to build out its AI infrastructure in the US over the next four years. Based on the easing of exclusivity between the two companies, analysts say these moves aren’t surprising. “When looking at storage in the cloud — especially as it relates to use in AI — it is incredibly expensive,” said Matt Kimball, VP and principal analyst for data center compute and storage at Moor Insights & Strategy. “Those expenses climb even higher as the volume of storage and movement of data grows,” he pointed out. “It is only smart for any business to perform a cost analysis of whether storage is better managed in the cloud or on-prem, and moving forward in a direction that delivers the best performance, best security, and best operational efficiency at the lowest cost.”

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PEAK:AIO adds power, density to AI storage server

There is also the fact that many people working with AI are not IT professionals, such as professors, biochemists, scientists, doctors, clinicians, and they don’t have a traditional enterprise department or a data center. “It’s run by people that wouldn’t really know, nor want to know, what storage is,” he said. While the new AI Data Server is a Dell design, PEAK:AIO has worked with Lenovo, Supermicro, and HPE as well as Dell over the past four years, offering to convert their off the shelf storage servers into hyper fast, very AI-specific, cheap, specific storage servers that work with all the protocols at Nvidia, like NVLink, along with NFS and NVMe over Fabric. It also greatly increased storage capacity by going with 61TB drives from Solidigm. SSDs from the major server vendors typically maxed out at 15TB, according to the vendor. PEAK:AIO competes with VAST, WekaIO, NetApp, Pure Storage and many others in the growing AI workload storage arena. PEAK:AIO’s AI Data Server is available now.

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SoftBank to buy Ampere for $6.5B, fueling Arm-based server market competition

SoftBank’s announcement suggests Ampere will collaborate with other SBG companies, potentially creating a powerful ecosystem of Arm-based computing solutions. This collaboration could extend to SoftBank’s numerous portfolio companies, including Korean/Japanese web giant LY Corp, ByteDance (TikTok’s parent company), and various AI startups. If SoftBank successfully steers its portfolio companies toward Ampere processors, it could accelerate the shift away from x86 architecture in data centers worldwide. Questions remain about Arm’s server strategy The acquisition, however, raises questions about how SoftBank will balance its investments in both Arm and Ampere, given their potentially competing server CPU strategies. Arm’s recent move to design and sell its own server processors to Meta signaled a major strategic shift that already put it in direct competition with its own customers, including Qualcomm and Nvidia. “In technology licensing where an entity is both provider and competitor, boundaries are typically well-defined without special preferences beyond potential first-mover advantages,” Kawoosa explained. “Arm will likely continue making independent licensing decisions that serve its broader interests rather than favoring Ampere, as the company can’t risk alienating its established high-volume customers.” Industry analysts speculate that SoftBank might position Arm to focus on custom designs for hyperscale customers while allowing Ampere to dominate the market for more standardized server processors. Alternatively, the two companies could be merged or realigned to present a unified strategy against incumbents Intel and AMD. “While Arm currently dominates processor architecture, particularly for energy-efficient designs, the landscape isn’t static,” Kawoosa added. “The semiconductor industry is approaching a potential inflection point, and we may witness fundamental disruptions in the next 3-5 years — similar to how OpenAI transformed the AI landscape. SoftBank appears to be maximizing its Arm investments while preparing for this coming paradigm shift in processor architecture.”

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Nvidia, xAI and two energy giants join genAI infrastructure initiative

The new AIP members will “further strengthen the partnership’s technology leadership as the platform seeks to invest in new and expanded AI infrastructure. Nvidia will also continue in its role as a technical advisor to AIP, leveraging its expertise in accelerated computing and AI factories to inform the deployment of next-generation AI data center infrastructure,” the group’s statement said. “Additionally, GE Vernova and NextEra Energy have agreed to collaborate with AIP to accelerate the scaling of critical and diverse energy solutions for AI data centers. GE Vernova will also work with AIP and its partners on supply chain planning and in delivering innovative and high efficiency energy solutions.” The group claimed, without offering any specifics, that it “has attracted significant capital and partner interest since its inception in September 2024, highlighting the growing demand for AI-ready data centers and power solutions.” The statement said the group will try to raise “$30 billion in capital from investors, asset owners, and corporations, which in turn will mobilize up to $100 billion in total investment potential when including debt financing.” Forrester’s Nguyen also noted that the influence of two of the new members — xAI, owned by Elon Musk, along with Nvidia — could easily help with fundraising. Musk “with his connections, he does not make small quiet moves,” Nguyen said. “As for Nvidia, they are the face of AI. Everything they do attracts attention.” Info-Tech’s Bickley said that the astronomical dollars involved in genAI investments is mind-boggling. And yet even more investment is needed — a lot more.

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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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