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IBM pushes sovereign computing with a software stack that works across cloud platforms

When workloads move, identity management, encryption keys, and audit trails tied to the old provider don’t transfer seamlessly, forcing CIOs to rebuild governance frameworks to meet regulatory requirements in the new environment, Hinchcliffe added. In contrast, Sovereign Core is trying to offer more control to CIOs by allowing them to keep encryption keys, identity management, […]

When workloads move, identity management, encryption keys, and audit trails tied to the old provider don’t transfer seamlessly, forcing CIOs to rebuild governance frameworks to meet regulatory requirements in the new environment, Hinchcliffe added.

In contrast, Sovereign Core is trying to offer more control to CIOs by allowing them to keep encryption keys, identity management, and operational authority within their jurisdiction, which should enable them to switch providers without rebuilding governance frameworks, Hinchcliffe pointed out.

Seconding Hinchcliffe, HyperFRAME Research’s leader of AI stack Stephanie Walter noted that the frequency and stringency of regulator-driven audits were increasing, specifically the EU: Regulators are no longer satisfied with promises of compliance but are seeking more evidence, audit trails, and continuous compliance reporting.

Sovereign Core, according to Hinchcliffe, could also help CIOs tackle these demands with automated evidence collection and continuous monitoring, reducing overhead for banks, government agencies, and defense-adjacent industries.

Boost for moving sovereign AI pilots to production

Analysts say Sovereign Core could help CIOs and their enterprises push their AI pilots into production, especially the ones that require strict data residency and compliance controls.

Most enterprises and organizations are hesitant to send proprietary data to a public AI model, and at the same can’t run GPU-backed inference completely inside their own sovereign boundary, said Phil Fersht, CEO of HFS Research.

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Yea or nay: Will Nvidia H200 chips go to China?

He noted, “the broader implications and potential impacts may signal to enterprise customers of Nvidia that perhaps they don’t need the latest and greatest GPUs from [them] either to achieve acceptable results across select AI workloads. It is doubtful that Nvidia would commission additional production issues for H200 without China

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Chinese AI firm trains state-of-the-art model entirely on Huawei chips

The pricing positions GLM-Image as a cost-effective option for enterprises generating marketing materials, presentations, and other text-heavy visual content at scale. Technical approach and benchmark performance GLM-Image employs a hybrid architecture combining a 9-billion-parameter autoregressive model with a 7-billion-parameter diffusion decoder, according to Zhipu’s technical report. The autoregressive component handles

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Oil Prices Retreat After 5 Session Rebound

Oil prices retreated after a five-session rebound as concerns about the geopolitical situation in the Middle East abated to some extent. That’s what Daniel Takieddine, Co-founder and CEO of Sky Links Capital Group, said in a market analysis sent to Rigzone today, adding that “the announcement that the U.S. administration has put its latest move in the area on hold tempered immediate fears of supply disruption in an important oil producing region”. Takieddine warned, however, that geopolitical risk has not disappeared. “Tensions across major producing regions remain elevated, and developments in Eastern Europe and Latin America continue to inject uncertainty into energy supply chains,” he said in the analysis. “In parallel, U.S. crude inventory data showed a strong increase in stockpiles, reinforcing the perception that physical inventory remains plentiful and that recent gains were running ahead of underlying demand conditions,” he added. Looking ahead, Takieddine stated in the analysis that any renewed escalation in the Middle East or other producing regions would quickly push crude prices back to the upside. “However, over the long term, the concerns over an oversupplied market remain a weight on prices and could pull oil toward new lows if geopolitical risks abate more consistently,” he said. In a market comment sent to Rigzone on Thursday, Naeem Aslam, Chief Analyst at Zaye Capital Markets, noted that “crude oil prices remain volatile as markets continuously reprice the geopolitical risk premium against underlying supply-demand fundamentals”. “The latest price swings have largely been driven by shifting Middle East dynamics, including troop movements, Iran-related tension, and broader security posturing, which lifted risk premium earlier, while recent signs of de-escalation have triggered a pullback,” Aslam said in the comment. “Meanwhile, recent economic data reinforced resilient consumption and steady housing activity, supporting the view that demand remains intact but not overheating enough to

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Woodside, JERA Finalize Winter LNG Deal for Japan

JERA Co Inc and Woodside Energy Group Ltd have finalized an agreement for the Australian company to export liquefied natural gas (LNG) to the Japanese power utility in the winter months for five years. The companies already have an existing contract under which Woodside is to deliver 400,000 metric tons a year of LNG to Japan. The 10-year agreement is to fulfill its first cargo this year on a delivered basis, as announced September 18, 2024. Under the new deal, Woodside will deliver the volumes on an ex-ship basis between the months of December and February from 2027. Three cargoes totaling about 200,000 metric tons will be delivered per year, JERA said in a press release Wednesday. “Gas-fired power generation plays a critical role in meeting peak energy demand and balancing seasonal fluctuations – challenges that are becoming more pronounced as renewable energy expands”, JERA said. “Securing sufficient LNG supply during the winter months, when global gas demand surges, is essential to maintaining a stable electricity supply in Japan”. “The volumes supplied to JERA will be sourced from Woodside’s global LNG portfolio, leveraging assets such as Scarborough, North West Shelf, Pluto LNG and LALNG, once it is operational”, Woodside said in a separate online statement about the new agreement. JERA owns 15.1 percent in the Scarborough field offshore Western Australia, part of the broader Scarborough Energy Project. Scarborough Energy is on track to start exporting LNG in the second half of this year, Woodside affirmed Tuesday as it announced the arrival of the project’s floating production unit. Scarborough Energy includes the development of the Scarborough field off the coast of Karratha, the construction of a second gas processing train for Pluto LNG with a capacity of five million metric tons per annum (MMtpa) and modifications to Pluto Train 1, according to

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OEUK Highlights ‘Key to Delivering North Sea Future Plan’

Cross-sector collaboration and close consultation of industry experts will be key to delivering the North Sea Future Plan (NSFP). That’s what Mark Wilson, HSE and Operations Director at industry body Offshore Energies UK (OEUK), said in a release sent to Rigzone recently, which highlighted that OEUK will host its 2026 HSE conference on February 25, “bringing together leaders from across sectors to shape the future of the North Sea as a multi-purpose energy basin”. “Under the theme ‘Trust. Transparency. Transformation’, the conference will kick off with a pivotal session based on the UK government’s North Sea Future Plan, which will explore how co-location between offshore wind, oil and gas, and carbon capture and storage (CCUS) can deliver a safer, cleaner basin,” OEUK said in its release. The UK Department for Energy Security and Net Zero (DESNZ) announced the NSFP in a statement posted on its site back in November 2025. “We look forward to welcoming industry leaders, technical experts, regulators, and innovators to this one-day event,” Wilson said in the OEUK release. “The first session of the day is a great opportunity to hear how improved guidance, aligned standards, better data sharing, and early engagement can enable offshore energies to achieve safe and sustainable co-location across the North Sea and support the plan’s integrated vision,” he added. OEUK noted in its release that its event explores the themes of trust, transparency, and transformation across all areas of health, safety, and environment, including emissions performance. It added that the conference features full audience events as well as a series of parallel breakout sessions throughout the day. In its statement published in November last year, DESNZ announced the publication of a “landmark plan to protect existing jobs and deliver the next generation of good, new jobs”.  “The government is charting a new course for the North Sea, providing a

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BP Sees Up To $5B Impairments Tied to Low Carbon Assets

BP PLC said Wednesday it expects to book $4-5 billion in write-downs primarily related to its “transition” business for the fourth quarter of 2025. “These charges are primarily attributable to the gas and low-carbon energy segment and are excluded from underlying replacement cost profit [BP’s version of adjusted net profit]”, the British oil and gas giant said in an outlook statement ahead of results, scheduled for February 10, 2026. BP did not disclose the affected projects. BP had already recognized a net impairment charge of $881 million from natural gas and low-carbon energy for the first nine months of 2025, and $1.86 billion for 2024, in its third quarter report published November 4, 2025. BP has signed agreements to sell several energy transition-related businesses as part of a “reset” strategy that involves divesting $20 billion worth of assets by 2027 and scaling down renewables investment. On December 16, 2025 state-owned Petróleo Brasileiro SA (Petrobras) and BP solar company Lightsource BP Renewable Energy Investments Ltd said they had penned a deal under which Petrobras would acquire 49.99 percent of Lightsource BP’s subsidiaries in Brazil. Lightsource BP’s Brazilian portfolio included 1-1.5 gigawatts in different stages of development, according to a joint online statement. On August 4, 2025 Japanese power utility JERA Co Inc and BP completed the spinoff of their offshore wind portfolios into a joint venture. BP contributed its development projects in Germany and the United Kingdom and secured leases in the UK and the United States. On July 18, 2025 BP said it had agreed to divest its onshore wind business in the U.S. to LS Power Development LLC, giving up 1.3 gigawatts of net capacity from 10 projects in operation. On July 9, 2025 BP said it had penned a deal to divest its BP Pulse, convenience and mobility businesses in

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Oil Slips After Trump Signals Iran De-Escalation

Oil fell after the close, wiping out a day of gains after US President Donald Trump said he had been assured that Iran would stop killing protesters, signaling he could hold off on a threatened military response to the repression of widespread demonstrations in the nation. West Texas Intermediate was down as much as 3% after settlement on Wednesday, dropping to around $59 a barrel in a rapid reversal before paring some of those losses. Prices had settled on Wednesday at $62.02. Oil had gained in each of the last five sessions as traders awaited the US response to political upheaval in Iran, with the US moving military staff and Tehran warning neighboring countries against assisting an attack. Concerns about a disruption to Iran’s approximately 3.3 million barrel-per-day production and key shipping lanes had helped push prices to their highest since October. But prices fell sharply after US President Donald Trump told reporters in the Oval Office Wednesday, “we’ve been told that the killing in Iran is stopping – it’s stopped.” The comments lessened expectations of an immediate US military response to the demonstrations against the government of Supreme Leader Ayatollah Ali Khamenei. Trump said he would be “very upset” if the information proved untrue and the violent crackdown continued. Oil has pushed higher in the new year as turmoil in OPEC’s fourth-largest producer, along with upheaval in Venezuela, restored a premium to prices following a run of five monthly losses spurred by expectations for a glut. The bumper rally in crude over recent days had caught off guard a market that had been steeped with bearish bets, while further boosts came from bullish options wagers, where volumes soared to a record this week, and an annual commodity index rebalancing that added inflows to crude markets. On the physical front,

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Shell, Exxon Pull Planned North Sea Gas Sale To Viaro

Shell Plc and Exxon Mobil Corp. canceled a proposed deal to sell natural gas assets in the North Sea to upstart firm Viaro Energy. Shell said in a statement that the oil majors couldn’t complete the transaction to sell the strategic Bacton onshore gas terminal and 11 offshore facilities to oil tycoon Francesco Mazzagatti’s Viaro. The ending of the transaction follows a protracted regulatory review by the North Sea Transition Authority, which said it had needed further information from Viaro before any decision. “The parties have worked hard and in close alignment to try and complete this transaction over many months, but despite this being a fully funded opportunity, the completion conditions were not met as commercial and market conditions evolved and we mutually agreed not to proceed,” Mazzagatti said Wednesday. When it announced the deal in the summer of 2024, Shell said the transaction was expected to complete in 2025. The NSTA, which was recently given new powers to oversee mergers and acquisitions in the North Sea, said the regulator was “waiting to receive the additional information requested from the purchasing party to make a decision.” The deal included the Bacton terminal on the east coast of England, a site of “strategic national importance,” according to Shell. It’s the sole entry point for gas from Belgium and the Netherlands, supplying as much as one-third of the UK’s gas supply. Mazzagatti, Viaro’s founder, is facing criminal charges in Italy and civil forgery and fraud allegations in the UK. He denies all allegations made against him.  The halt to the deal has paused an acquisition streak that made Viaro the most prolific buyer of UK oil and gas assets over the past five years, according to data compiled by Bloomberg. The decision also follows a London Court of Appeal ruling over

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OpenAI turns to Cerebras in a mega deal to scale AI inference infrastructure

Analysts expect AI workloads to grow more varied and more demanding in the coming years, driving the need for architectures tuned for inference performance and putting added pressure on data center networks. “This is prompting hyperscalers to diversify their computing systems, using Nvidia GPUs for general-purpose AI workloads, in-house AI accelerators for highly optimized tasks, and systems such as Cerebras for specialized low-latency workloads,” said Neil Shah, vice president for research at Counterpoint Research. As a result, AI platforms operating at hyperscale are pushing infrastructure providers away from monolithic, general-purpose clusters toward more tiered and heterogeneous infrastructure strategies. “OpenAI’s move toward Cerebras inference capacity reflects a broader shift in how AI data centers are being designed,” said Prabhu Ram, VP of the industry research group at Cybermedia Research. “This move is less about replacing Nvidia and more about diversification as inference scales.” At this level, infrastructure begins to resemble an AI factory, where city-scale power delivery, dense east–west networking, and low-latency interconnects matter more than peak FLOPS, Ram added. “At this magnitude, conventional rack density, cooling models, and hierarchical networks become impractical,” said Manish Rawat, semiconductor analyst at TechInsights. “Inference workloads generate continuous, latency-sensitive traffic rather than episodic training bursts, pushing architectures toward flatter network topologies, higher-radix switching, and tighter integration of compute, memory, and interconnect.”

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Cisco’s 2026 agenda prioritizes AI-ready infrastructure, connectivity

While most of the demand for AI data center capacity today comes from hyperscalers and neocloud providers, that will change as enterprise customers delve more into the AI networking world. “The other ecosystem members and enterprises themselves are becoming responsible for an increasing proportion of the AI infrastructure buildout as inferencing and agentic AI, sovereign cloud, and edge AI become more mainstream,” Katz wrote. More enterprises will move to host AI on premises via the introduction of AI agents that are designed to inject intelligent insight into applications and help improve operations. That’s where the AI impact on enterprise network traffic will appear, suggests Nolle. “Enterprises need to host AI to create AI network impact. Just accessing it doesn’t do much to traffic. Having cloud agents access local data center resources (RAG etc.) creates a governance issue for most corporate data, so that won’t go too far either,” Nolle said.  “Enterprises are looking at AI agents, not the way hyperscalers tout agentic AI, but agents running on small models, often open-source, and are locally hosted. This is where real AI traffic will develop, and Cisco could be vulnerable if they don’t understand this point and at least raise it in dialogs where AI hosting comes up,” Nolle said. “I don’t expect they’d go too far, because the real market for enterprise AI networking is probably a couple years out.” Meanwhile, observers expect Cisco to continue bolstering AI networking capabilities for enterprise branch, campus and data centers as well as hyperscalers, including through optical support and other gear.

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Microsoft tells communities it will ‘pay its way’ as AI data center resource usage sparks backlash

It will work with utilities and public commissions to set the rates it pays high enough to cover data center electricity costs (including build-outs, additions, and active use). “Our goal is straightforward: To ensure that the electricity cost of serving our data centers is not passed on to residential customers,” Smith emphasized. For example, the company is supporting a new rate structure Wisconsin that would charge a class of “very large customers,” including data centers, the true cost of the electricity required to serve them. It will collaborate “early, closely, and transparently” with local utilities to add electricity and supporting infrastructure to existing grids when needed. For instance, Microsoft has contracted with the Midcontinent Independent System Operator (MISO) to add 7.9GW of new electricity generation to the grid, “more than double our current consumption,” Smith noted. It will pursue ways to make data centers more efficient. For example, it is already experimenting with AI to improve planning, extract more electricity from existing infrastructure, improve system resilience, and speed development of new infrastructure and technologies (like nuclear energy). It will advocate for state and national public policies that ensure electricity access that is affordable, reliable, and sustainable in neighboring communities. Microsoft previously established priorities for electricity policy advocacy, Smith noted, but “progress has been uneven. This needs to change.” Microsoft is similarly committed when it comes to data center water use, promising four actions: Reducing the overall amount of water its data centers use, initially improving it by 40% by 2030. The company is exploring innovations in cooling, including closed-loop systems that recirculate cooling liquids. It will collaborate with local utilities to map out water, wastewater, and pressure needs, and will “fully fund” infrastructure required for growth. For instance, in Quincy, Washington, Microsoft helped construct a water reuse utility that recirculates

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Can retired naval power plants solve the data center power crunch?

HGP’s plan includes a revenue share with the government, and the company would create a decommissioning fund, according to Bloomberg. The alternative? After a lengthy decommissioning process, the reactors are shipped to a remote storage facility in Washington state together dust along with dozens of other retired nuclear reactors. So the carrier itself isn’t going to be turned into a data center, but its power plants are being proposed for a data center on land. And even with the lengthening decommissioning process, that’s still faster than building a nuclear power plant from scratch. Don’t hold your breath, says Kristen Vosmaer, managing director, JLL Work Dynamics Data Center team. The idea of converting USS Nimitz’s nuclear reactors to power AI data centers sounds compelling but faces insurmountable obstacles, he argues. “Naval reactors use weapons-grade uranium that civilian entities cannot legally possess, and the Nuclear Regulatory Commission has no pathway to license such facilities. Even setting aside the fuel issue, these military-designed systems would require complete reconstruction to meet civilian safety standards, eliminating any cost advantages over purpose-built nuclear plants,” Vosmaer said. The maritime concept itself, however, does have some merit, said Vosmaer. “Ocean cooling can reduce energy consumption compared to land-based data centers, and floating platforms offer positioning flexibility that fixed facilities cannot match,” Vosmaer said.

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What exactly is an AI factory?

Others, however, seem to use the word to mean something smaller than a data center, referring more to the servers, software, and other systems used to run AI. For example, the AWS AI Factory is a combination of hardware and software that runs on-premises but is managed by AWS and comes with AWS services such as Bedrock, networking, storage and databases, and security.  At Lenovo, AI factories appear to be packaged servers designed to be used for AI. “We’re looking at the architecture being a fixed number of racks, all working together as one design,” said Scott Tease, vice president and general manager of AI and high-performance computing at Lenovo’s infrastructure solutions group. That number of racks? Anything from a single rack to hundreds, he told Computerworld. Each rack is a little bigger than a refrigerator, comes fully assembled, and is often fully preconfigured for the customer’s use case. “Once it arrives at the customer site, we’ll have service personnel connect power and networking,” Tease said. For others, the AI factory concept is more about the software.

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Meta establishes Meta Compute to lead AI infrastructure buildout

At that scale, infrastructure constraints are becoming a binding limit on AI expansion, influencing decisions like where new data centers can be built and how they are interconnected. The announcement follows Meta’s recent landmark agreements with Vistra, TerraPower, and Oklo aimed at supporting access to up to 6.6 gigawatts of nuclear energy to fuel its Ohio and Pennsylvania data center clusters. Implications for hyperscale networking Analysts say Meta’s approach indicates how hyperscalers are increasingly treating networking and interconnect strategy as first-order concerns in the AI race. Tulika Sheel, senior vice president at Kadence International, said that Meta’s initiative signals that hyperscale networking will need to evolve rapidly to handle massive internal data flows with high bandwidth and ultra-low latency. “As data centers grow in size and GPU density, pressure on networking and optical supply chains will intensify, driving demand for more advanced interconnects and faster fiber,” Sheel added. Others pointed to the potential architectural shifts from this. “Meta is using Disaggregated Scheduled Fabric and Non-Scheduled Fabric, along with new 51 Tbps switches and Ethernet for Scale-Up Networking, which is intensifying pressure on switch silicon, optical modules, and open rack standards,” said Biswajeet Mahapatra, principal analyst at Forrester. “This shift is forcing the ecosystem to deliver faster optical interconnects and greater fiber capacity, as Meta targets significant backbone growth and more specialized short-reach and coherent optical technologies to support cluster expansion.” The network is no longer a secondary pipe but a primary constraint. Next-generation connectivity, Sheel said, is becoming as critical as access to compute itself, as hyperscalers look to avoid network bottlenecks in large-scale AI deployments.

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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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