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Observe secures $156M funding boost for AI-powered observability

“We’ve always believed that observability is a data problem, and we now live in a world where systems are more complex, data volumes are larger, and—with AI—it’s frictionless for users to ask questions,” Burton wrote. “This is a game of analytics, and the observability vendor who can answer the most questions—most accurately—will win.” Observe is […]

“We’ve always believed that observability is a data problem, and we now live in a world where systems are more complex, data volumes are larger, and—with AI—it’s frictionless for users to ask questions,” Burton wrote. “This is a game of analytics, and the observability vendor who can answer the most questions—most accurately—will win.”

Observe is a SaaS platform, and customers deploy Observe agents to collect telemetry data from a variety of sources, including infrastructure such as Kubernetes, databases such as MongoDB or Snowflake, and other applications. The agents collect time-series data, logs, traces/spans, and performance data and send the data to Observe’s platform. Observe then takes the raw telemetry data, curates and normalizes it, and structures it to make it more easily navigable and usable for troubleshooting by customer teams.

“Observe gives us the visibility we need across our cloud environment, helping to reduce our mean time to resolution and operational costs, while enabling our security and infrastructure teams to stay ahead of potential issues,” said Oscar Papel, CISO at Truveta, an Observe customer, in a statement.

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India Tells Refiners to Draw Up Plans for Non-Russian Crude

India told its oil refiners to come up with plans for buying non-Russian crude, a scenario that would have far-reaching consequences for the global oil market if it ultimately meant reduced dealings with Moscow. The government has asked state-owned processors to prepare an outline of where alternate barrels can be sourced and at what volume if Russian flows get stopped, people familiar with the matter said, asking not to be named due to the sensitivity of the matter. One of the people said that the instruction amounted to scenario planning in case Russian crude were to become unavailable. The request came after a social-media post on Wednesday by US President Donald Trump threw the Asian nation’s fuel makers into disarray. Trump said in his post that India would face “penalties” because of ongoing purchases of Russian energy that helped to fund the war in Ukraine.  India is a critical source of demand for Russian oil and Moscow would have to divert millions of barrels a month to China and other buyers if New Delhi were to halt buying. They’ve helped Russian barrels to keep flowing to the world — largely undisturbed — despite wide-ranging western sanctions. So far the Indian government hasn’t set out its position and people with knowledge of the matter said it’s still evaluating the situation and will continue to do so for several more days.  India’s refiners have been racing to buy barrels from elsewhere and there are tentative signs that they might be scaling back Russian cargo purchases.  A senior executive at a major Indian oil refiner said the company would try to source more crude from the Middle East and Africa, while still looking to the government for guidance on how to proceed. The situation was not entirely unexpected, but would increase costs and

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Oil Dips on Inflation, Geopolitical Jitters

Oil fell as broader markets weakened on worse-than-expected US inflation data and crude traders cashed out after prices reached a six-week high. While West Texas Intermediate slipped 1.1% on Thursday to settle below $70 a barrel, snapping a three day rally, prices are largely still range-bound as traders await clearer signals on balances for supply and demand. “Investors are just being cautious not to overextend the rally until we have more clarity on: one OPEC, two Russia — through the weekend,” as well as the looming Aug. 1 US tariff deadline, said Frank Monkam, head of macro trading at Buffalo Bayou Commodities. US President Donald Trump said he would impose a tariff on India’s exports and a penalty for its energy purchases from Russia from Aug. 1, the latest in a series of comments in which he expressed his anger at the lack of ceasefire in Ukraine. While the market impact of disrupting Indian purchases could be significant, as Moscow would have to find new buyers if it loses one of its largest customers, the relatively muted price movements offer a sign that there’s little expectation Trump will follow through for now. It’s the latest sign of an oil market that increasingly only reacts when there is a meaningful disruption to supply. While Trump has repeatedly threatened steps that might hurt output in producer nations from Venezuela to Iran and Russia since taking office, there’s so far not been a substantial hit to global supply, even when the US bombed Iran’s nuclear facilities. India’s refiners are seeking clarity from the government in New Delhi. A senior executive at a major processor said his company would try and source more crude from the Middle East and Africa, while also looking to the government for guidance on how it should proceed. “Finding

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NYPA’s updated renewables plan would more than double capacity to 7 GW

NYPA’s updated renewables plan would more than double capacity to 7 GW | Utility Dive Skip to main content An article from Dive Brief The New York Power Authority’s draft plan includes new renewable and energy storage projects totaling more than 3.8 GW. Published July 31, 2025 An aerial view of solar panels at the Sutter Greenworks Solar Site on Sept. 19, 2021, in Calverton, New York. A draft renewable energy plan issued on July 29, 2025, by the New York Power Authority calls for adding 7 GW of solar, wind and energy storage in the state. Bruce Bennett via Getty Images Dive Brief: The New York Power Authority on Tuesday published a draft of its Renewables Updated Strategic Plan, calling for 7 GW of solar, wind and energy storage — more than doubling the total energy capacity outlined in its initial plan released in January. New York lawmakers in 2023 expanded NYPA’s authority to develop, own and operate renewable energy resources. Officials at the public power utility say they are using the new authority to continue the state’s clean energy transition at a time when federal policy is shifting away from renewables. “There has never been a more critical time for NYPA to move expeditiously as we contend with expiring federal tax credits and associated increased competition for equipment and installers,” President and CEO Justin Driscoll said in a statement. Dive Insight: Advocates say public pressure for more clean energy led to NYPA expanding its renewables plan, and the timing is particularly acute given headwinds to solar and wind coming from the White House. “Instead of cutting deals with Trump or gutting New York’s climate mandates the way he is federally, [New York Democratic Gov. Kathy] Hochul must ensure NYPA leads the nation on lowering energy bills, slashing pollution, creating good green

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USA and Pakistan Sign Trade Deal to Boost Oil Reserves, Market Ties

The US sealed a trade deal with Pakistan as their officials wrapped up talks in Washington, agreeing to develop oil reserves. The agreement involves a reduction of the so called reciprocal tariffs, especially on Pakistani exports, according to a statement by Pakistan’s finance ministry on Thursday. No details on tariffs were shared by either side. The agreement will spur US investments in Pakistan’s infrastructure, besides deepening market ties between the partners, the ministry said.  US President Donald Trump said in a post on Truth Social that the two countries will “work together on developing their massive oil reserves”, adding that officials are now selecting the company that will anchor the partnership. Relations between Islamabad and Washington have been showing signs of easing after prolonged tensions, with President Trump welcoming Pakistan’s army chief, Field Marshal Asim Munir, for rare talks at the White House in June.  Pakistan, which lists the US as one of its top export destinations, had offered to boost American imports, particularly cotton and soybean. The South Asian nation sold over $5 billion worth of goods to the US as of 2024, and imported about $2.1 billion. The US has also expressed interest in sunrise sectors such as crypto currencies. Pakistan plans to legalize and regulate digital assets as the field gains traction in key Asian markets following Trump’s pro-crypto agenda, Bloomberg News reported. WHAT DO YOU THINK? Generated by readers, the comments included herein do not reflect the views and opinions of Rigzone. All comments are subject to editorial review. Off-topic, inappropriate or insulting comments will be removed.

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Rick Stockburger Named Inaugural FESI CEO

Rick Stockburger has been appointed as the inaugural chief executive officer (CEO) of the Department of Energy’s (DOE) Foundation for Energy Security and Innovation (FESI). The DOE said in a media release that this is the first-ever independent agency-related foundation. The DOE added that the foundation has been established to support its mission and help accelerate energy technology commercialization, expand private-public collaboration, and strengthen America’s energy system. Stockburger is a decorated U.S. Army combat veteran and leader in energy innovation, known for helping accelerate energy technology startups and fostering public-private partnerships, the DOE said. He served in Kosovo and Afghanistan before moving to the energy sector, where he scaled innovative technologies from concept to market, according to the DOE. As president and CEO of BRITE Energy Innovators in Warren, Ohio, he expanded the organization’s budget and programming, generating over $250 million in economic impact for the Midwest, the DOE said. “Today’s announcement marks a new chapter in how the Department will deliver breakthrough technologies to market”, Secretary of Energy Chris Wright said. “Rick’s proven leadership and background will help advance the Department’s efforts to move emerging technologies into real-world energy deployment – strengthening American science, innovation, and energy leadership. With him in place, FESI will be a valuable partner in expanding private-sector collaboration and delivering on President Trump’s agenda to unleash American energy and innovation”. “Rick’s decorated service to our country while in the U.S. Army, combined with his leadership in technology entrepreneurship in the private sector, makes him an outstanding choice to be FESI’s first CEO”, Anthony Pugliese, DOE chief commercialization officer and director of the Office of Technology Commercialization, said. “Together, we will strengthen America’s ability to move breakthrough research into real-world impact”. FESI has already made two initial investments in DOE initiatives aimed at enhancing America’s energy infrastructure

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5 utility commissions ask FERC to undo MISO’s $22B multi-value transmission portfolio

Five state utility commissions asked the Federal Energy Regulatory Commission to change the classification of a $22 billion portfolio of “multi-value” transmission projects, a move that would make them ineligible for regional cost sharing, according to a complaint filed at the agency on Wednesday. The utility commissions from Arkansas, Louisiana, Mississippi, Montana and North Dakota contend that MISO overstated the benefits of multi-value projects in its Tranche 2.1 regional transmission portfolio, which the grid operator’s board approved in December. Unlike other types of transmission projects, multi-value projects have their costs shared across MISO’s footprint. The Tranche 2.1 portfolio contains 24 transmission projects, including some that form a 3,631-mile, 765-kV backbone. The projects are expected to go online from 2032 to 2034, according to MISO. The state commissions contend that MISO used flawed modeling and assumptions that inflated the value of the Tranche 2.1 portfolio. MISO, for example, said the low-end benefits of three key metrics — avoided capacity costs, mitigation of reliability issues and decarbonization — used to assess Tranche 2.1 totaled $38.3 billion in 2024 dollars over 20 years, making up about 74% of benefits in the scenario, according to the complaint.  However, after “correcting” MISO’s assumptions and analysis, a consultant for the utility commissions pegged the benefits of those metrics at $4.3 billion to $7.2 billion, according to the complaint. The benefits of the transmission portfolio are “significantly less than the costs,” making it ineligible for its MVP designation under MISO’s rules, the state commissions said. MISO’s Tranche 2.1 portfolio aims to give states with clean energy goals such as Minnesota, Michigan and Illinois access to remote sources of clean energy, according to the complaint. “Classifying the Tranche 2.1 projects as MVPs allows states with ambitious clean energy goals to shift transmission costs (to deliver their remote energy) to other

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Data center survey: AI gains ground but trust concerns persist

Cost issues: 76% Forecasting future data center capacity requirements: 71% Improving energy performance for facilities equipment: 67% Power availability: 63% Supply chain disruptions: 65% A lack of qualified staff: 67% With respect to capacity planning, there’s been a notable increase in the number of operators who describe themselves as “very concerned” about forecasting future data center capacity requirements. Andy Lawrence, Uptime’s executive director of research, said two factors are contributing to this concern: ongoing strong growth for IT demand, and the often-unpredictable demand that AI workloads are creating. “There’s great uncertainty about … what the impact of AI is going to be, where it’s going to be located, how much of the power is going to be required, and even for things like space and cooling, how much of the infrastructure is going to be sucked up to support AI, whether it’s in a colocation, whether it’s in an enterprise or even in a hyperscale facility,” Lawrence said during a webinar sharing the survey results. The survey found that roughly one-third of data center owners and operators currently perform some AI training or inference, with significantly more planning to do so in the future. As the number of AI-based software deployments increases, information about the capabilities and limitations of AI in the workplace is becoming available. The awareness is also revealing AI’s suitability for certain tasks. According to the report, “the data center industry is entering a period of careful adoption, testing, and validation. Data centers are slow and careful in adopting new technologies, and AI will not be an exception.”

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Micron unveils PCIe Gen6 SSD to power AI data center workloads

Competitive positioning With the launch of the 9650 SSD PCIe Gen 6, Micron competes with Samsung and SK Hynix enterprise SSD offerings, which are the dominant players in the SSD market. In December last year, SK Hynix announced the development of PS1012 U.2 Gen5 PCIe SSD, for massive high-capacity storage for AI data centers.  The PM1743 is Samsung’s PCIe Gen5 offering in the market, with 14,000 MBps sequential read, designed for high-performance enterprise workloads. According to Faruqui, PCIe Gen6 data center SSDs are best suited for AI inference performance enhancement. However, we’re still months away from large-scale adoption as no current CPU platforms are available with PCIe 6.0 support. Only Nvidia’s Blackwell-based GPUs have native PCIe 6.0 x16 support with interoperability tests in progress. He added that PCIe Gen 6 SSDs will see very delayed adoption in the PC segment and imminent 2025 2H adoption in AI, data centers, high-performance computing (HPC), and enterprise storage solutions. Micron has also introduced two additional SSDs alongside the 9650. The 6600 ION SSD delivers 122TB in an E3.S form factor and is targeted at hyperscale and enterprise data centers looking to consolidate server infrastructure and build large AI data lakes. A 245TB variant is on the roadmap. The 7600 PCIe Gen5 SSD, meanwhile, is aimed at mixed workloads that require lower latency.

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AI Deployments are Reshaping Intra-Data Center Fiber and Communications

Artificial Intelligence is fundamentally changing the way data centers are architected, with a particular focus on the demands placed on internal fiber and communications infrastructure. While much attention is paid to the fiber connections between data centers or to end-users, the real transformation is happening inside the data center itself, where AI workloads are driving unprecedented requirements for bandwidth, low latency, and scalable networking. Network Segmentation and Specialization Inside the modern AI data center, the once-uniform network is giving way to a carefully divided architecture that reflects the growing divergence between conventional cloud services and the voracious needs of AI. Where a single, all-purpose network once sufficed, operators now deploy two distinct fabrics, each engineered for its own unique mission. The front-end network remains the familiar backbone for external user interactions and traditional cloud applications. Here, Ethernet still reigns, with server-to-leaf links running at 25 to 50 gigabits per second and spine connections scaling to 100 Gbps. Traffic is primarily north-south, moving data between users and the servers that power web services, storage, and enterprise applications. This is the network most people still imagine when they think of a data center: robust, versatile, and built for the demands of the internet age. But behind this familiar façade, a new, far more specialized network has emerged, dedicated entirely to the demands of GPU-driven AI workloads. In this backend, the rules are rewritten. Port speeds soar to 400 or even 800 gigabits per second per GPU, and latency is measured in sub-microseconds. The traffic pattern shifts decisively east-west, as servers and GPUs communicate in parallel, exchanging vast datasets at blistering speeds to train and run sophisticated AI models. The design of this network is anything but conventional: fat-tree or hypercube topologies ensure that no single link becomes a bottleneck, allowing thousands of

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ABB and Applied Digital Build a Template for AI-Ready Data Centers

Toward the Future of AI Factories The ABB–Applied Digital partnership signals a shift in the fundamentals of data center development, where electrification strategy, hyperscale design and readiness, and long-term financial structuring are no longer separate tracks but part of a unified build philosophy. As Applied Digital pushes toward REIT status, the Ellendale campus becomes not just a development milestone but a cornerstone asset: a long-term, revenue-generating, AI-optimized property underpinned by industrial-grade power architecture. The 250 MW CoreWeave lease, with the option to expand to 400 MW, establishes a robust revenue base and validates the site’s design as AI-first, not cloud-retrofitted. At the same time, ABB is positioning itself as a leader in AI data center power architecture, setting a new benchmark for scalable, high-density infrastructure. Its HiPerGuard Medium Voltage UPS, backed by deep global manufacturing and engineering capabilities, reimagines power delivery for the AI era, bypassing the limitations of legacy low-voltage systems. More than a component provider, ABB is now architecting full-stack electrification strategies at the campus level, aiming to make this medium-voltage model the global standard for AI factories. What’s unfolding in North Dakota is a preview of what’s coming elsewhere: AI-ready campuses that marry investment-grade real estate with next-generation power infrastructure, built for a future measured in megawatts per rack, not just racks per row. As AI continues to reshape what data centers are and how they’re built, Ellendale may prove to be one of the key locations where the new standard was set.

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Amazon’s Project Rainier Sets New Standard for AI Supercomputing at Scale

Supersized Infrastructure for the AI Era As AWS deploys Project Rainier, it is scaling AI compute to unprecedented heights, while also laying down a decisive marker in the escalating arms race for hyperscale dominance. With custom Trainium2 silicon, proprietary interconnects, and vertically integrated data center architecture, Amazon joins a trio of tech giants, alongside Microsoft’s Project Stargate and Google’s TPUv5 clusters, who are rapidly redefining the future of AI infrastructure. But Rainier represents more than just another high-performance cluster. It arrives in a moment where the size, speed, and ambition of AI infrastructure projects have entered uncharted territory. Consider the past several weeks alone: On June 24, AWS detailed Project Rainier, calling it “a massive, one-of-its-kind machine” and noting that “the sheer size of the project is unlike anything AWS has ever attempted.” The New York Times reports that the primary Rainier campus in Indiana could include up to 30 data center buildings. Just two days later, Fermi America unveiled plans for the HyperGrid AI campus in Amarillo, Texas on a sprawling 5,769-acre site with potential for 11 gigawatts of power and 18 million square feet of AI data center capacity. And on July 1, Oracle projected $30 billion in annual revenue from a single OpenAI cloud deal, tied to the Project Stargate campus in Abilene, Texas. As Data Center Frontier founder Rich Miller has observed, the dial on data center development has officially been turned to 11. Once an aspirational concept, the gigawatt-scale campus is now materializing—15 months after Miller forecasted its arrival. “It’s hard to imagine data center projects getting any bigger,” he notes. “But there’s probably someone out there wondering if they can adjust the dial so it goes to 12.” Against this backdrop, Project Rainier represents not just financial investment but architectural intent. Like Microsoft’s Stargate buildout in

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Google and CTC Global Partner to Fast-Track U.S. Power Grid Upgrades

On June 17, 2025, Google and CTC Global announced a joint initiative to accelerate the deployment of high-capacity power transmission lines using CTC’s U.S.-manufactured ACCC® advanced conductors. The collaboration seeks to relieve grid congestion by rapidly upgrading existing infrastructure, enabling greater integration of clean energy, improving system resilience, and unlocking capacity for hyperscale data centers. The effort represents a rare convergence of corporate climate commitments, utility innovation, and infrastructure modernization aligned with the public interest. As part of the initiative, Google and CTC issued a Request for Information (RFI) with responses due by July 14. The RFI invites utilities, state energy authorities, and developers to nominate transmission line segments for potential fast-tracked upgrades. Selected projects will receive support in the form of technical assessments, financial assistance, and workforce development resources. While advanced conductor technologies like ACCC® can significantly improve the efficiency and capacity of existing transmission corridors, technological innovation alone cannot resolve the grid’s structural challenges. Building new or upgraded transmission lines in the U.S. often requires complex permitting from multiple federal, state, and local agencies, and frequently faces legal opposition, especially from communities invoking Not-In-My-Backyard (NIMBY) objections. Today, the average timeline to construct new interstate transmission infrastructure stretches between 10 and 12 years, an untenable lag in an era when grid reliability is under increasing stress. In 2024, the Federal Energy Regulatory Commission (FERC) reported that more than 2,600 gigawatts (GW) of clean energy and storage projects were stalled in the interconnection queue, waiting for sufficient transmission capacity. The consequences affect not only industrial sectors like data centers but also residential areas vulnerable to brownouts and peak load disruptions. What is the New Technology? At the center of the initiative is CTC Global’s ACCC® (Aluminum Conductor Composite Core) advanced conductor, a next-generation overhead transmission technology engineered to boost grid

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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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