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NetBrain boosts AI smarts to automatically diagnose, remediate network problems

Device layer (physical and virtual devices) Topology layer (Level 2 and Level 3 connections) Control plane layer (traffic flows, security policies) Intent layer (configurations, states, and designed behaviors) Tao emphasized that in his view, the key to managing a modern network is to understand intent. The 12.1 release enhances this capability with the automatic discovery […]

  1. Device layer (physical and virtual devices)
  2. Topology layer (Level 2 and Level 3 connections)
  3. Control plane layer (traffic flows, security policies)
  4. Intent layer (configurations, states, and designed behaviors)

Tao emphasized that in his view, the key to managing a modern network is to understand intent.

The 12.1 release enhances this capability with the automatic discovery of network intent. The goal is to create a distributed, intelligent network modeling system that can discover and manage network intent without heavy human intervention, using AI and automation to continuously assess and adapt network configurations.

NetBrain aims to prevent future network outages

As part of the 12.1 update, the new post-mortem analysis feature allows organizations to quickly investigate network issues across their entire infrastructure. 

The system will automatically scan an entire network for similar problems after an outage. By using intent-based network mapping, AI and automation, NetBrain will then take the initial post-mortem findings and use that information for ongoing monitoring, tracking similar potential failure points across the network and proactively identifying potential future incidents. 

Looking ahead, NetBrain is working on creating more AI-powered network automation capabilities to reduce the need for hands-on human interventions. This vision represents a significant shift in network management, with AI increasingly handling complex operational tasks that previously required human expertise, allowing network professionals to focus on more strategic initiatives.

“More and more human tasks are shifting to automation, with more automation shifting to AI,” Tao said. “I can see 50% of network operations tasks now can be AI enabled in a matter of months right now.”

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Groundcover grows funding for eBPF-based observability tech

Groundcover’s expanded eBPF approach goes beyond traditional network monitoring, Azulay said: “eBPF is no longer just about network monitoring. We use it as an x-ray into operations flowing through the kernel of the operating system.”  Groundcover uses eBPF to provide full application-level traces. Azulay explained that the system can see the

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Viking CCS pipeline wins planning consent

A pipeline that will be used to transport carbon to be buried in a depleted North Sea gas field has been awarded planning consent. An application for the Viking CCS pipeline submitted by energy firm Harbour Energy was granted official development consent by the Secretary of State for Energy Security and Net Zero. The 34-mile (55km) pipeline between Immingham and the Theddlethorpe gas terminal on the Lincolnshire coast is a key plank in the project, which is one of the UK’s so-called “track 2” CCS projects awaiting further support from government. The other is Acorn at Peterhead. Its backers have estimated the project could unlock £7 billion of investment across the Humber region by 2035, with 10,000 jobs during construction and £4bn in economic value forecast by the end of the decade. The consent marks some progress as concern grows that delays to CCS plans may risk the UK failing to meet net zero targets. Harbour had initially envisaged making a final investment on the Viking scheme decision last year. The North Sea producer has since focused on developing oil and gas production internationally following its $11.2bn acquisition of Wintershall Dea. It has also since withdrawn from another UK CCS project. The UK’s track 1 CCS projects including HyNet in the North West of England and the East Coast Cluster in Teesside were backed with £21.7 billion in government support over 10 years. The onshore, buried pipeline will transport CO₂ captured from the industrial cluster at Immingham on the first stage of its journey out to the Viking reservoirs via an existing 75-mile (120km) pipeline, the Lincolnshire offshore gas gathering system (LOGGS),  with plans for a further new 13-mile (20km) spur line. The Viking fields could store up to 300m tonnes of CO₂, with the system handling up to 10m

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Trump targets state climate laws in latest executive order

President Donald Trump issued an executive order (EO) Apr. 8 tasking Atty. Gen. Pam Bondi to ensure states and cities follow federal climate and energy laws, not their own, more aggressive energy rules and climate standards. “Burdensome and ideologically motivated state policies “threaten American energy dominance and our economic and national security,” the order reads. The EO directs Bondi to remove “illegitimate impediments” to develop, site, produce, invest in, or use US energy resources. Trump ordered states to focus on eliminating barriers related to domestic oil, natural gas, coal, hydropower, geothermal, biofuel, critical mineral, and nuclear resources. Trump told Bondi to target state laws imposing carbon taxes and fees and those mentioning terms like “environmental justice” and “greenhouse gas emissions.”  The order requires Bondi to identify and stop enforcement of state laws she determines illegal based on the EO, and to submit a report within 60 days outlining steps taken and to recommend further executive or legislative action. Trump called out 3 states: California for its “radical” cap-and-trade program, in place since 2012; and Vermont and New York’s superfund policies that Trump called climate change ‘extortion laws’ that require fossil fuel companies to pay for past contributions to greenhouse gas emissions.   “The federal government cannot unilaterally strip states’ independent constitutional authority,” said New York Gov. Kathy Hochul and New Mexico Gov. Michelle Lujan Grisham, co-chairs of the US Climate Alliance. “We are a nation of states — and laws — and we will not be deterred. We will keep advancing solutions to the climate crisis that safeguard Americans’ fundamental right to clean air and water, create good-paying jobs, grow the clean energy economy, and make our future healthier and safer.” The US Climate Alliance is a bipartisan coalition of 24 governors committed to a net-zero future through state-led, high-impact

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EIA reduces global oil demand projections on tariff uncertainties

In its April issue Short-Term Energy Outlook (STEO), the US Energy Information Administration (EIA) lowered its projections for global oil demand growth. The agency now expects global consumption to rise by 0.9 million b/d in 2025 and by 1.0 million b/d in 2026 — downward revisions of 0.4 million b/d and 0.1 million b/d, respectively, from last month’s forecast. These estimates, which are based on economic projections from Oxford Economics completed before the latest tariff actions, are clouded by heightened uncertainty around global GDP growth. Oil prices tumbled during the first week of April amid escalating trade tensions and shifts in oil production policy. On Apr. 2, President Donald J. Trump signed an Executive Order imposing 10% tariffs on imports from all countries, with even higher rates on selected nations. Just 2 days later, China retaliated with a 34% tariff on US imports. Meanwhile, OPEC+ announced on Apr. 3 that some member countries would bring forward planned production increases from July to May. The rapid series of announcements triggered significant market volatility. By Apr. 7, Brent crude oil spot prices had plummeted 14% to $66/bbl. EIA expects continued volatility in crude oil and commodity prices as global markets digest the implications of the evolving trade landscape. “Our reduction in liquid fuels demand growth compared with last STEO is concentrated in Asia as a result of US tariffs. Despite that uncertainty, we continue to see non-OECD Asia as the primary driver of global oil demand growth in the forecast. We expect India will increase its consumption of liquid fuels by 0.3 million b/d in both 2025 and 2026, compared with an increase of 0.2 million in 2024, driven by rising demand for transportation fuels. We forecast China’s liquid fuels consumption will grow by 0.2 million b/d in both 2025 and 2026,

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EVOL: Neo Next speculation, Kistos’ island plans, and HAR2 just has to be good

This week we got further updates on the Neo Energy and Repsol tie-up, Kistos’ full year results for 2024 and the results of HAR 2. Energy Voice’s Ryan Duff, Erikka Askeland and Mat Perry discuss. First up, what’s happening at Flotta? Erikka chats about the gas terminal’s hydrogen plans and what attracted Neo Energy’s private equity backers to the Spanish firm’s UK division. Ryan argues that tax incentives from Repsol’s extensive decommissioning liabilities may be the answer. Next up, Ryan discusses Kistos and its plans to expand the Greater Laggan Area off the west coast of Shetland. The firm has brought attention to the Glendronach field now that operatorship of the area is changing hands. When talking about gas, there has to be a Trump, the trio discusses how US policy is impacting global oil and gas firms. Finally, Mat chats about hydrogen and the results of HAR 2. Was it perfect? No, but maybe it doesn’t need to be. He discusses some of the talking points from a recent conference in Birmingham, which touched on getting hydrogen “good”, but it doesn’t need to be “perfect” in order to unlock investment. Price is still a sticking point for this fuel source but the government is aiming to tackle this too. Listen to Energy Voice Out Loud on your podcast platform of choice.

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The power industry must oppose Trump’s coal bailout … again

Ari Peskoe is director of Harvard Law School’s Electricity Law Initiative. President Donald Trump’s executive order on the “Reliability and Security of the U.S. Electric Grid” is his latest effort to save the shrinking fleet of inefficient coal-fired power plants from extinction. The plan outlined in the order is a throwback to his “Grid Reliability and Resilience Pricing Rule” that the power industry opposed and FERC unanimously rejected in 2018. Like the earlier proposal, the new executive order would disrupt power markets and raise energy prices for consumers in order to subsidize owners of aging coal-burning boilers. As it did during Trump’s first term, the power sector should rally against Trump’s plan because it illegally usurps the industry’s processes for deciding how to keep the lights on. First-term efforts fizzle Trump’s efforts to enrich coal plant owners date back to the earliest days of his first term. In 2017, the Department of Energy filed a proposal at FERC to exempt coal and nuclear plants from interstate markets administered by the eastern regional transmission organizations. DOE hypothesized that the markets were not adequately compensating these “fuel-secure” plants and therefore asked FERC to set special rates for coal and nuclear plants. The power industry lined up against the plan, filing comments at FERC that explained how DOE’s plan was unsupported by any evidence, would override state policies, and would increase prices. FERC quickly rejected DOE’s proposal on a bipartisan basis. Yet the administration continued to flirt with coal bailouts. By May 2018, DOE had written a lengthy memo arguing that national security concerns justified handouts to coal plant owners. Meanwhile, FirstEnergy had formally requested that DOE force PJM to pay cost-of-service rates to every coal and nuclear plant in PJM. Opposition from broad coalitions of market participants was key to the proposals’

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Natural Gas Searching for ‘Near Term Equilibrium’

In an EBW Analytics Group report sent to Rigzone by the EBW team today, Eli Rubin, an energy analyst at the company, noted that natural gas is searching for “near term equilibrium”. “After easing yesterday morning from Wednesday’s dramatic 48 cent intraday rally, the NYMEX front-month contract sold off further after another soft EIA [U.S. Energy Information Administration] storage report,” Rubin said in the EBW report. “Technically, the May contract slid below the 100-day moving average at $3.52 per million British thermal units (MMBtu) and is retesting Tuesday’s low close at $3.465,” Rubin added. “Fundamentally, while next week could see both early-season heat and late-season cold, weather-driven demand is set to retreat rapidly into the back half of April,” Rubin continued. The EBW analyst went on to state in the report that lower production and stronger LNG may offer support for gas prices but added triple-digit weekly injections could be on the near-term horizon. “The forced selling of the past week … may be over,” Rubin said in the report. “Uncertainty is elevated. After a speculator surge in late winter drove NYMEX futures up, the unwinding of speculator longs has near-term pricing closer to fair fundamental value as the longer-term strip presents more compelling valuations,” Rubin added. The EIA’s latest weekly natural gas storage report, which was released on April 10 and included data for the week ending April 4, stated that “working gas in storage was 1,830 billion cubic feet as of Friday, April 4, 2025, according to EIA estimates”. “This represents a net increase of 57 billion cubic feet from the previous week. Stocks were 450 billion cubic feet less than last year at this time and 40 billion cubic feet below the five-year average of 1,870 billion cubic feet,” it added. “At 1,830 billion cubic feet, total working

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U.S. Advances AI Data Center Push with RFI for Infrastructure on DOE Lands

ORNL is also the home of the Center for Artificial Intelligence Security Research (CAISER), which Edmon Begoli, CAISER founding director, described as being in place to build the security necessary by defining a new field of AI research targeted at fighting future AI security risks. Also, at the end of 2024, Google partner Kairos Power started construction of their Hermes demonstration SMR in Oak Ridge. Hermes is a high-temperature gas-cooled reactor (HTGR) that uses triso-fueled pebbles and a molten fluoride salt coolant (specifically Flibe, a mix of lithium fluoride and beryllium fluoride). This demonstration reactor is expected to be online by 2027, with a production level system becoming available in the 2030 timeframe. Also located in a remote area of Oak Ridge is the Tennessee Valley Clinch River project, where the TVA announced a signed agreement with GE-Hitachi to plan and license a BWRX-300 small modular reactor (SMR). On Integrating AI and Energy Production The foregoing are just examples of ongoing projects at the sites named by the DOE’s RFI. Presuming that additional industry power, utility, and data center providers get on board with these locations, any of the 16 could be the future home of AI data centers and on-site power generation. The RFI marks a pivotal step in the U.S. government’s strategy to solidify its global dominance in AI development and energy innovation. By leveraging the vast resources and infrastructure of its national labs and research sites, the DOE is positioning the country to meet the enormous power and security demands of next-generation AI technologies. The selected locations, already home to critical energy research and cutting-edge supercomputing, present a compelling opportunity for industry stakeholders to collaborate on building integrated, sustainable AI data centers with dedicated energy production capabilities. With projects like Oak Ridge’s pioneering SMRs and advanced AI security

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Generac Sharpens Focus on Data Center Power with Scalable Diesel and Natural Gas Generators

In a digital economy defined by constant uptime and explosive compute demand, power reliability is more than a design criterion—it’s a strategic imperative. In response to such demand, Generac Power Systems, a company long associated with residential backup and industrial emergency power, is making an assertive move into the heart of the digital infrastructure sector with a new portfolio of high-capacity generators engineered for the data center market. Unveiled this week, Generac’s new lineup includes five generators ranging from 2.25 MW to 3.25 MW. These units are available in both diesel and natural gas configurations, and form part of a broader suite of multi-asset energy systems tailored to hyperscale, colocation, enterprise, and edge environments. The product introductions expand Generac’s commercial and industrial capabilities, building on decades of experience with mission-critical power in hospitals, telecom, and manufacturing, now optimized for the scale and complexity of modern data centers. “Coupled with our expertise in designing generators specific to a wide variety of industries and uses, this new line of generators is designed to meet the most rigorous standards for performance, packaging, and after-treatment specific to the data center market,” said Ricardo Navarro, SVP & GM, Global Telecom and Data Centers, Generac. Engineering for the Demands of Digital Infrastructure Each of the five new generators is designed for seamless integration into complex energy ecosystems. Generac is emphasizing modularity, emissions compliance, and high-ambient operability as central to the offering, reflecting a deep understanding of the real-world challenges facing data center operators today. The systems are built around the Baudouin M55 engine platform, which is engineered for fast transient response and high operating temperatures—key for data center loads that swing sharply under AI and cloud workloads. The M55’s high-pressure common rail fuel system supports low NOx emissions and Tier 4 readiness, aligning with the most

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CoolIT and Accelsius Push Data Center Liquid Cooling Limits Amid Soaring Rack Densities

The CHx1500’s construction reflects CoolIT’s 24 years of DLC experience, using stainless-steel piping and high-grade wetted materials to meet the rigors of enterprise and hyperscale data centers. It’s also designed to scale: not just for today’s most power-hungry processors, but for future platforms expected to surpass today’s limits. Now available for global orders, CoolIT is offering full lifecycle support in over 75 countries, including system design, installation, CDU-to-server certification, and maintenance services—critical ingredients as liquid cooling shifts from high-performance niche to a requirement for AI infrastructure at scale. Capex Follows Thermals: Dell’Oro Forecast Signals Surge In Cooling and Rack Power Infrastructure Between Accelsius and CoolIT, the message is clear: direct liquid cooling is stepping into its maturity phase, with products engineered not just for performance, but for mass deployment. Still, technology alone doesn’t determine the pace of adoption. The surge in thermal innovation from Accelsius and CoolIT isn’t happening in a vacuum. As the capital demands of AI infrastructure rise, the industry is turning a sharper eye toward how data center operators account for, prioritize, and report their AI-driven investments. To wit: According to new market data from Dell’Oro Group, the transition toward high-power, high-density AI racks is now translating into long-term investment shifts across the data center physical layer. Dell’Oro has raised its forecast for the Data Center Physical Infrastructure (DCPI) market, predicting a 14% CAGR through 2029, with total revenue reaching $61 billion. That revision stems from stronger-than-expected 2024 results, particularly in the adoption of accelerated computing by both Tier 1 and Tier 2 cloud service providers. The research firm cited three catalysts for the upward adjustment: Accelerated server shipments outpaced expectations. Demand for high-power infrastructure is spreading to smaller hyperscalers and regional clouds. Governments and Tier 1 telecoms are joining the buildout effort, reinforcing AI as a

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Podcast: Nomads at the Frontier – AI, Infrastructure, and Data Center Workforce Evolution at DCD Connect New York

The 25th anniversary of the latest Data Center Dynamics event in New York City last month (DCD Connect NY 2025) brought record-breaking attendance, underscoring the accelerating pace of change in the digital infrastructure sector. At the heart of the discussions were evolving AI workloads, power and cooling challenges, and the crucial role of workforce development. Welcoming Data Center Frontier at their show booth were Phill Lawson-Shanks of Aligned Data Centers and Phillip Koblence of NYI, who are respectively managing director and co-founder of the Nomad Futurist Foundation. Our conversation spanned the pressing issues shaping the industry, from the feasibility of AI factories to the importance of community-driven talent pipelines. AI Factories: Power, Cooling, and the Road Ahead One of the hottest topics in the industry is how to support the staggering energy demands of AI workloads. Reflecting on NVIDIA’s latest announcements at GTC, including the potential of a 600-kilowatt rack, Lawson-Shanks described the challenges of accommodating such density. While 120-130 kW racks are manageable today, scaling beyond 300 kW will require rethinking power distribution methods—perhaps moving power sleds outside of cabinets or shifting to medium-voltage delivery. Cooling is another major concern. Beyond direct-to-chip liquid cooling, air cooling still plays a role, particularly for DIMMs, NICs, and interconnects. However, advances in photonics, such as shared laser fiber interconnects, could reduce switch power consumption, marking a potential turning point in energy efficiency. “From our perspective, AI factories are highly conceivable,” said Lawson-Shanks. “But we’re going to see hybridization for a while—clients will want to run cloud infrastructure alongside inference workloads. The market needs flexibility.” Connectivity and the Role of Tier-1 Cities Koblence emphasized the continuing relevance of major connectivity hubs like New York City in an AI-driven world. While some speculate that dense urban markets may struggle to accommodate hyperscale AI workloads,

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2025 Data Center Power Poll

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How Microgrids and DERs Could Solve the Data Center Power Crisis

Microgrid Knowledge’s annual conference will be held in Dallas, Texas this year. Energy industry leaders and microgrid developers, customers and enthusiasts will gather April 15-17 at the Sheraton Dallas, to learn from each other and discuss a wide variety of microgrid related topics. There will be sessions exploring the role microgrids can play in healthcare, military, aviation and transportation, as well as other sectors of the economy. Experts will share insights on fuels, creating flexible microgrids, integrating electric vehicle charging stations and more.  “Powering Data Centers: Collaborative Microgrid Solutions for a Growing Market” is expected to be one of the most popular sessions at the conference. Starting at 10:45am on April 16, industry experts will tackle the biggest question facing data center operators and the energy industry – how can we solve the data center energy crisis? During the session, the panelists will discuss how private entities, developers and utilities can work together to deploy microgrids and distributed energy technologies that address the data center industry’s rapidly growing power needs. They’ll share solutions, technologies and strategies to favorably position data centers in the energy queue. In advance of the conference, we sat down with two of the featured panelists to learn more about the challenges facing the data center industry and how microgrids can address the sector’s growing energy needs. We spoke with session chair Samantha Reifer, director of strategic alliances at Scale Microgrids and Elham Akhavan, senior microgrid research analyst at Wood Mackenzie. Here’s what Reifer and Akhavan had to say: The data center industry is growing rapidly. What are the critical challenges facing the sector as it expands? Samantha Reifer: The biggest barrier we’ve been hearing about from our customers and partners is whether these data centers can get power where they want to build? For a colocation

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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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