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IP Fabric 7.9 boosts visibility across hybrid environments

Multicloud and hybrid network viability has also been extended to include IPv6 path analysis, helping teams reason about connectivity in dual-stack and hybrid environments. This capability addresses a practical challenge for enterprises deploying IPv6 alongside existing IPv4 infrastructure. Network teams can now validate that applications can reach IPv6 endpoints and identify segments where IPv6 connectivity […]

Multicloud and hybrid network viability has also been extended to include IPv6 path analysis, helping teams reason about connectivity in dual-stack and hybrid environments. This capability addresses a practical challenge for enterprises deploying IPv6 alongside existing IPv4 infrastructure. Network teams can now validate that applications can reach IPv6 endpoints and identify segments where IPv6 connectivity breaks down. The platform models both protocols within the same digital twin, showing how traffic transitions between IPv4 and IPv6 segments.

According to Bykov, platform engineering groups will now be able to visualize complex application workloads from multiple dimensions. That includes the implications of security and advanced routing policy on applications, all the way up to the point of termination within the enterprise. 

The cloud abstraction problem

One of the reasons why hybrid visibility for networks can be an issue is because cloud providers deliberately abstract infrastructure complexity from users. Azure Firewall delivers packet filtering as a managed service without exposing the underlying compute or network resources. Private Link creates connectivity paths without requiring customers to understand the routing mechanics.

This abstraction serves a purpose. It allows teams to consume network functions without managing physical infrastructure. But it creates a visibility problem for operations teams who need to understand how these functions affect application traffic.

IP Fabric’s approach is to model the control plane behavior without exposing the underlying implementation. The platform represents what Azure Firewall does to traffic without attempting to map Microsoft’s internal infrastructure. It shows how Private Link affects connectivity without revealing the provider’s routing fabric.

“Abstraction is vital to be able to operate complex infrastructure, and it’s a major appeal that a specific network or security function can be used without having to deal with the underlying complexity,” Bykov explained. “However, that function itself makes a decision about the traffic, affecting the application and that is the control element that the customer is interested in.”

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IP Fabric 7.9 boosts visibility across hybrid environments

Multicloud and hybrid network viability has also been extended to include IPv6 path analysis, helping teams reason about connectivity in dual-stack and hybrid environments. This capability addresses a practical challenge for enterprises deploying IPv6 alongside existing IPv4 infrastructure. Network teams can now validate that applications can reach IPv6 endpoints and

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Trump Administration Calls for Emergency Power Auction to Build Big Power Plants Again

WASHINGTON—U.S. Secretary of Energy Chris Wright and Secretary of the Interior Doug Burgum, vice-chair and chair of the National Energy Dominance Council (NEDC) respectively, today joined Mid-Atlantic governors urging PJM Interconnection, L.L.C. (PJM) to temporarily overhaul its market rules to strengthen grid reliability and reduce electricity costs for American families and businesses by building more than $15 billion of reliable baseload power generation.  The initiative calls on PJM to conduct an emergency procurement auction to address escalating electricity prices and growing reliability risks across the mid-Atlantic region of the United States. The action follows a series of PJM policies over the years that have weakened the electric grid, including the premature shutdown of reliable power generation.  President Trump declared a National Energy Emergency on his first day in office, warning that the previous administrations energy subtraction agenda left the country vulnerable to blackouts and soaring electricity prices. During the Biden administration, PJM forced nearly 17 gigawatts of reliable baseload power generation offline. For the first time in history, PJM’s capacity auction failed to secure enough generation resources to meet basic reliability requirements. If not fixed, it will lead to further rising prices and blackouts.  “High electricity prices are a choice,” said Energy Secretary Chris Wright. “The Biden administration’s forceful closures of coal and natural gas plants without reliable replacements left the United States in an energy emergency. Perhaps no region in America is more at risk than in PJM. That’s why President Trump asked governors across the Mid-Atlantic to come together and call upon PJM to allow America to build big reliable power plants again. Our directives will restore affordable and reliable electricity so American families thrive and America’s manufacturing industries once again boom. President Trump promised to unleash American energy and put the American people first. This plan keeps

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Russian Oil and Gas Revenue Falls to Lowest in 5 Years

Russia’s revenues from its oil and gas industry, vital to financing its war in Ukraine, dropped to a five-year low in 2025 as crude prices slumped and gas exports declined. The nation’s budget received a total of 8.48 trillion rubles ($108 billion) in oil and gas taxes last year, Finance Ministry said on Thursday. That’s 24 percent less than in 2024 and the lowest level since the start of the decade, historic figures show.  Russia, a top-three global oil producer and home to the world’s largest gas reserves, heavily relies on tax revenues from the two industries to fill its state coffers. The decline, mainly driven by a combination of weaker global oil prices, stronger ruble and energy sanctions against Russia, comes as the Kremlin has boosted military spending significantly above what it planned to fund the war, which is about to enter a fifth year. To bridge the widening gap between revenues and spending, the government in Moscow has eaten into more than half of the country’s National Wellbeing Fund – a buffer against economic shocks – and turned to expensive borrowings that will take years to pay back.   Oil revenues dropped more than 22 percent year on year to 7.13 trillion rubles, reaching the lowest level since 2023, Bloomberg calculations show. Concerns about an oversupply in the global crude market, and discounts for Russian barrels in particular due to western sanctions, hit the flow of money into state coffers. The official data show that the average price of Urals, Russia’s main oil-export blend, for tax purposes was $57.65 a barrel in 2025, a 15 percent drop from a year earlier.   Starting from November, when the US blacklisted two major oil producers Rosneft PJSC and Lukoil PJSC, the discount of Urals to the Brent benchmark widened to about $27 a barrel at

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Hamm to Halt Drilling in Bakken Shale

(Update) January 16, 2026, 3:39 PM GMT: Article updated with context throughout. Harold Hamm, the billionaire wildcatter who helped kick off the US shale oil revolution, said he’s about to shut down his company’s drilling in North Dakota’s Bakken for the first time in decades because of low crude prices. “This will be the first time in over 30 years that Harold Hamm has not had an operation with drilling rigs in North Dakota,” Hamm, the founder of shale driller Continental Resources Inc., said in a telephone interview Thursday. “There’s no need to drill it when margins are basically gone.” It’s a significant milestone for the Bakken. The shale patch in North Dakota is where Hamm, 80, first proved that fracking and horizontal drilling techniques could be successfully applied to previously untouchable oil reserves. The fracking revolution ushered in a new growth era in US oil and the country went on to become the world’s top producer. Operators in the US shale patch, once the world’s leader in oil production growth, are now closely watching commodity prices as they hover near the level that makes drilling profitable for producers. If prices drop into the low $50-per-barrel range for several months, companies are expected to make more drastic cuts to drilling and fracking.  While each shale basin has different cost levels, the Bakken in particular is seen as a bellwether for the direction of US crude output. The average well in the Bakken requires a minimum of $58 a barrel to cover costs and generate a small profit, according to a report from BloombergNEF. That’s up almost 4% from a year earlier, largely due to rising drilling expenses. Meanwhile global oil prices have steadily declined in the past several months on expectations of a glut. West Texas Intermediate, the US benchmark, has fallen

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USA Crude Oil Stocks Rise More Than 3MM Barrels WoW

U.S. commercial crude oil inventories, excluding those in the Strategic Petroleum Reserve (SPR), increased by 3.4 million barrels from the week ending January 2 to the week ending January 9. That’s what the U.S. Energy Information Administration (EIA) highlighted in its latest weekly petroleum status report, which was released on January 14 and included data for the week ending January 9. According to this EIA report, crude oil stocks, not including the SPR, stood at 422.4 million barrels on January 9, 419.1 million barrels on January 2, and 412.7 million barrels on January 10, 2025. The report highlighted that data may not add up to totals due to independent rounding. Crude oil in the SPR stood at 413.7 million barrels on January 9, 413.5 million barrels on January 2, and 394.3 million barrels on January 10, 2025, the report showed. Total petroleum stocks – including crude oil, total motor gasoline, fuel ethanol, kerosene type jet fuel, distillate fuel oil, residual fuel oil, propane/propylene, and other oils – stood at 1.713 billion barrels on January 9, the report revealed. Total petroleum stocks were up 6.4 million barrels week on week and up 88.1 million barrels year on year, the report pointed out. “At 422.4 million barrels, U.S. crude oil inventories are about three percent below the five year average for this time of year,” the EIA said in its latest weekly petroleum status report. “Total motor gasoline inventories increased by 9.0 million barrels from last week and are about four percent above the five year average for this time of year. Finished gasoline inventories decreased, while blending components inventories increased last week,” it added. “Distillate fuel inventories slightly decreased last week and are about four percent below the five year average for this time of year. Propane/propylene inventories decreased 2.4 million barrels from

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ENGIE, Ares Add 730 MW to Joint RE Portfolio in US

Ares Management Corp and ENGIE SA have added one wind and two solar projects already operating in the ERCOT market to their renewable energy partnership in the United States. The new assets have a combined capacity of 730 megawatts, a joint statement said. “ENGIE will retain a controlling share in the portfolio and will continue to operate and manage the assets”, the partners said. “The continued growth of our relationship with Ares reflects the strength of ENGIE’s portfolio of assets and our track record of delivering, operating and financing growth in the U.S. despite challenging circumstances”, said Dave Carroll, chief executive and chief renewables officer of ENGIE North America. “This transaction supports ENGIE’s strategy of continued investment in North America by deepening its partnership with a leading infrastructure investor, recycling capital to facilitate continued expansion of renewable generation to meet strong demand for power in the U.S.”, the joint statement said. French state-backed utility ENGIE has over 16 gigawatts (GW) of renewable generation projects in operation or under construction across the U.S. and Canada. Globally it has an installed capacity of 52.7 GW of renewables and energy storage, with a goal of 95 GW by 2030, the statement said. In the U.S., ENGIE has announced two projects this year, the Knox 2A and Knox 2B community solar farms in Galesburg, Illinois. The facilities are designed to deliver a combined 8.2 kilowatt hours a year to the state grid. The capacity represents an avoidance of over 7,800 metric tons of carbon dioxide emissions annually, the same as taking off nearly 1,700 cars off the road for a year, ENGIE said in a press release January 6, 2026. Also in Illinois ENGIE and co-venturer Solstice Power Technologies LLC started up the 2.5-MW Harmony community solar project late last year. “The Harmony community

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Mitsubishi to Acquire Haynesville Shale Assets for $5.2B

Mitsubishi Corp announced Friday a deal to acquire producing shale gas positions in Louisiana and Texas from operators related to Aethon Energy Management LLC for $5.2 billion. “This transaction marks MC’s entry into the U.S. shale gas business across the value chain, from upstream ownership through domestic sales and export of produced gas”, the diversified Japanese group said in an online statement. Mitsubishi signed an agreement to buy all equity stakes in Aethon III LLC, Aethon United LP and related entities (collectively Aethon) with existing shareholders including Aethon Energy Management, Ontario Teachers’ Pension Plan and RedBird Capital Partners, the statement said. Mitsubishi said it would purchase a total of nearly 1.7 million units. The parties expect to consummate the transaction in the second quarter. “Building on MC’s established North American energy platform – which includes upstream shale gas development with Ovintiv in British Columbia, midstream marketing and logistics through CIMA Energy in Houston, LNG exports via LNG Canada and Cameron LNG, and power generation through Diamond Generating Corp – this acquisition further strengthens MC’s integrated energy and power business”, the statement said. Mitsubishi said it plans to expand its U.S. presence into data center development, chemicals production and related businesses. “Aethon’s shale gas assets are primarily located in the Haynesville Shale formation, spanning Texas and Louisiana, and currently produce approximately 2.1 Bcfd [billion cubic feet a day] of natural gas (equivalent to about 15 million tons per year of LNG)”, the company noted. “Haynesville is a major supply source of natural gas for the growing southern U.S. market and offers favorable access to multiple LNG export terminals, including Cameron LNG, where MC holds liquefaction capacity rights under a tolling agreement. “Aethon’s natural gas is currently sold in the U.S. southern market, and part of this volume is being considered for export as LNG

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Power shortages, carbon capture, and AI automation: What’s ahead for data centers in 2026

“Despite a broader use of AI tools in enterprises and by consumers, that does not mean that AI compute, AI infrastructure in general, will be more evenly spread out,” said Daniel Bizo, research director at Uptime Institute, during the webinar. “The concentration of AI compute infrastructure is only increasing in the coming years.” For enterprises, the infrastructure investment remains relatively modest, Uptime Institute found. Enterprises will limit investment to inference and only some training, and inference workloads don’t require dramatic capacity increases. “Our prediction, our observation, was that the concentration of AI compute infrastructure is only increasing in the coming years by a couple of points. By the end of this year, 2026, we are projecting that around 10 gigawatts of new IT load will have been added to the global data center world, specifically to run generative AI workloads and adjacent workloads, but definitely centered on generative AI,” Bizo said. “This means these 10 gigawatts or so load, we are talking about anywhere between 13 to 15 million GPUs and accelerators deployed globally. We are anticipating that a majority of these are and will be deployed in supercomputing style.” 2. Developers will not outrun the power shortage The most pressing challenge facing the industry, according to Uptime, is that data centers can be built in less than three years, but power generation takes much longer. “It takes three to six years to deploy a solar or wind farm, around six years for a combined-cycle gas turbine plant, and even optimistically, it probably takes more than 10 years to deploy a conventional nuclear power plant,” said Max Smolaks, research analyst at Uptime Institute. This mismatch was manageable when data centers were smaller and growth was predictable, the report notes. But with projects now measured in tens and sometimes hundreds of

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Google warns transmission delays are now the biggest threat to data center expansion

The delays stem from aging transmission infrastructure unable to handle concentrated power demands. Building regional transmission lines currently takes seven to eleven years just for permitting, Hanna told the gathering. Southwest Power Pool has projected 115 days of potential loss of load if transmission infrastructure isn’t built to match demand growth, he added. These systemic delays are forcing enterprises to reconsider fundamental assumptions about cloud capacity. Regions including Northern Virginia and Santa Clara that were prime locations for hyperscale builds are running out of power capacity. The infrastructure constraints are also reshaping cloud competition around power access rather than technical capabilities. “This is no longer about who gets to market with the most GPU instances,” Gogia said. “It’s about who gets to the grid first.” Co-location emerges as a faster alternative to grid delays Unable to wait years for traditional grid connections, hyperscalers are pursuing co-location arrangements that place data centers directly adjacent to power plants, bypassing the transmission system entirely. Pricing for these arrangements has jumped 20% in power-constrained markets as demand outstrips availability, with costs flowing through to cloud customers via regional pricing differences, Gogia said. Google is exploring such arrangements, though Hanna said the company’s “strong preference is grid-connected load.” “This is a speed to power play for us,” he said, noting Google wants facilities to remain “front of the meter” to serve the broader grid rather than operating as isolated power sources. Other hyperscalers are negotiating directly with utilities, acquiring land near power plants, and exploring ownership stakes in power infrastructure from batteries to small modular nuclear reactors, Hanna said.

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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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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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