Linux containers in 2025 and beyond

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Linux containers in 2025 and beyond

The upcoming years will also bring about an increase in the use of standard container practices, such as the Open Container Initiative (OCI) standard, container registries, signing, testing, and GitOps workflows used for application development to build Linux systems. We’re also likely see a significant rise in the use of bootable containers, which are self-contained […]

Cloud platforms are often the primary platform for AI experimentation and container development because of their scalability and flexibility along the integration of both AI and ML services. They’re giving birth to many significant changes in the way we process data. With data centers worldwide, cloud platforms also ensure low-latency access and regional compliance for AI applications.

As we move ahead, development teams will be able to collaborate more easily through shared development environments and efficient data storage.

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Stay ahead with more perspectives on cutting-edge power, infrastructure, energy, bitcoin and AI solutions. Explore these articles to uncover strategies and insights shaping the future of industries.

Amazon confirms 16,000 job cuts, including to AWS

Amazon is cutting about 16,000 jobs across the company, SVP of People Experience and Technology Beth Galetti wrote in an email to employees Wednesday. The cuts were widely expected — and although Galetti’s email did not mention Amazon Web Services, the cuts came as no surprise to AWS staff, some

Meta-Corning fiber deal signals a new bottleneck in AI infrastructure

The role of fiber in AI scaling As AI systems scale, limits in networking are increasingly holding back performance, leaving costly GPUs underused and reducing the payoff from large infrastructure investments. Manish Rawat, a semiconductor analyst at TechInsights, pointed out that optical fiber is now emerging as the next structural

Microsoft launches its second generation AI inference chip, Maia 200

“In practical terms, Maia 200 can effortlessly run today’s largest models, with plenty of headroom for even bigger models in the future,” Microsoft says. Maia feeds data to models differently, too, through what Microsoft refers to as a redesigned memory subsystem which features a specialized direct memory access (DMA) engine

Nvidia is still working with suppliers on RAM chips for Rubin

Nvidia changed its requirements for suppliers of the next generation of high-bandwidth memory, HBM4, but is close to certifying revised chips from Samsung Electronics for use in its AI systems, according to reports. Nvidia revised its specifications for memory chips for its Rubin platform in the third quarter of 2025,

EIA Sees USA Diesel Price Dropping in 2026

In its latest short term energy outlook (STEO), which was released on January 13, the U.S. Energy Information Administration (EIA) projected that the U.S. on-highway diesel fuel retail price will drop in 2026. According to its latest STEO, the EIA sees the diesel price averaging $3.43 per gallon in 2026. In 2025, the U.S. on-highway diesel fuel retail price came in at $3.66 per gallon, the STEO showed. A quarterly breakdown included in the STEO projected that the U.S. diesel price will average $3.50 per gallon in the first quarter of 2026, $3.40 per gallon in the second quarter, and $3.41 per gallon across the third and fourth quarters of this year. The STEO showed that, in 2025, the U.S. diesel price came in at $3.63 per gallon in the first quarter, $3.55 per gallon in the second quarter, $3.76 per gallon in the third quarter, and $3.70 per MMBtu in the fourth quarter. In its latest diesel fuel update, which was released on January 27, the EIA showed a rising trend in the average U.S. on highway diesel fuel price. According to this fuel update, the U.S. on-highway diesel fuel price averaged $3.459 per gallon on January 12, $3.530 per gallon on January 19, and $3.624 per gallon on January 26. The January 26 price was $0.035 per gallon lower than the year ago price, however, the EIA fuel update showed. Of the five Petroleum Administration for Defense District (PADD) regions highlighted in the EIA’s latest fuel update, the West Coast was shown to have the highest U.S. on-highway diesel fuel price as of January 26, at $4.301 per gallon. The Gulf Coast was shown in the update to have the lowest U.S. on-highway diesel fuel price as of January 26, at $3.325 per gallon. A glossary section of the

Chevron Adds GIP’s Thomas Horton to Board

Chevron Corp said Tuesday it has appointed Thomas Horton, a partner at Global Infrastructure Partners (GIP) of global asset manager BlackRock Inc, as an independent director, expanding its board to 13 members. Horton, 64, has joined Chevron’s Board Audit Committee, the Houston, Texas-based energy giant said in an online statement. “Horton previously held senior roles as chairman of American Airlines Group Inc, and chairman, CEO and president at American Airlines Inc and AMR Corp, where he successfully built American Airlines’ network both organically and through its combination with USAirways in 2015”, Chevron noted. Horton was also senior adviser at private equity investor Warburg Pincus. “In addition to executive management roles, Horton has served as a director with some of the Fortune 500’s top brands, including current seats on the boards of Walmart and General Electric (operating as GE Aerospace). He previously served on the boards of Qualcomm and Enlink Midstream”, Chevron added. Chair and chief executive Mike Wirth said of Horton, “His proven leadership, diverse board experience and thoughtful approach to governance will be invaluable as we continue to drive growth and create long-term value”. Chevron’s board now has 11 independent directors, according to the list of members on its website. Besides Wirth, the other non-independent is John Hess, who became a Chevron director July 2025 after Chevron acquired Hess Corp. In an earlier appointment, Chevron said November 3, 2025 that its assistant controller Amit Ghai will replace Alana Knowles as controller effective March 1, 2026. Knowles is expected to retire after 38 years with Chevron. “Ghai will lead Chevron’s accounting policy, corporate and external financial reporting, internal controls, global business services and digital finance teams”, Chevron said. Recently Wirth said he was in discussion with the board about his retirement. The 65-year-old has been chair of the board and CEO

EIA Sees USA Energy Demand Slipping Then Rising

In its latest short term energy outlook (STEO), which was released on January 13, the U.S. Energy Information Administration (EIA) projected that U.S. total energy consumption will drop in 2026 and rise in 2027. According to its latest STEO, the EIA now sees U.S. total energy consumption coming in at 95.37 quadrillion British thermal units (qBtu) this year and 95.96 qBtu next year. In 2025, U.S. total energy consumption was 96.06 qBtu the STEO showed. A quarterly breakdown included in the EIA’s latest STEO projected that U.S. total energy consumption will come in at 24.74 qBtu in the first quarter of this year, 22.39 qBtu in the second quarter, 24.03 qBtu in the third quarter, 24.21 qBtu in the fourth quarter, 24.88 qBtu in the first quarter of next year, 22.61 qBtu in the second quarter, 24.26 qBtu in the third quarter, and 24.21 qBtu in the fourth quarter of 2027. The EIA’s January STEO showed that total energy demand was 25.45 qBtu in the first quarter of 2025, 22.45 qBtu in the second quarter, 24.06 qBtu in the third quarter, and 24.09 qBtu in the fourth quarter. Liquid Fuels, NatGas In its latest STEO, the EIA projected that U.S. liquid fuels consumption will stay flat in 2026, then rise next year. According to the EIA’s January STEO, the EIA sees U.S. liquid fuels averaging 20.61 million barrels per day in 2026 and 20.69 million barrels per day in 2027. This demand came in at 20.61 million barrels per day in 2025, the STEO showed. The STEO projected that U.S. liquid fuels consumption will average 20.22 million barrels per day in the first quarter of this year, 20.69 million barrels per day in the second quarter, 20.81 million barrels per day in the third quarter, 20.71 million barrels per day

Uniper to Supply Renewable Power to nLighten Data Centers

Uniper SE has won an electricity supply contract from nLighten HQ BV covering all the latter’s data center sites across Germany. “Under the agreement, Uniper is to supply both standard power for nLighten’s German locations and a guaranteed base load supply of hydroelectric power, ensuring a constant CO2-free energy supply with exceptional traceability on an hourly basis”, said a joint statement Tuesday. The companies did not disclose the volume or duration of the contract, which involves an around-the-clock power supply. Munich-based TÜV Süd AG will provide certification for the renewable power for origin verifiability on an hourly basis, the statement said. “Instead of relying on annual renewable energy certificates, nLighten can now track the specific hydropower production that supports its operations on an hourly basis”, the companies said. “The flexible structure allows it to add additional renewable energy sources such as hydropower, wind or solar when demand increases in its German portfolio, with everything handled through Uniper as the balancing party”. “[C]onventional renewable energy certificates issued annually may claim to be ‘100 percent renewable’ but data centers often continue to purchase carbon-intensive electricity during peak times”, the statement noted. “Uniper’s 24/7 solution closes this gap: companies can prove that their digital infrastructure is powered by verified carbon-free energy hour by hour, which is verified for our German operations by third-party certification”. German power and gas utility Uniper says it has 14 gigawatts of flexible power generation capacity. Schiphol-Rijk, Netherlands-based nLighten, meanwhile, has projects across Europe. Last week Uniper and TenneT BV announced an agreement to develop a new central network node in Großkrotzenburg, Germany to serve data center-driven growth in power demand in the greater Frankfurt area. “The core of the project is the construction of a new 380-kilovolt switchyard, which will create extensive additional capacity for urgently needed customer

SC Expects Market Sentiment to Gradually Turn More Positive

In a report sent to Rigzone recently, Standard Chartered Bank Energy Research Head Emily Ashford outlined that Standard Chartered expects oil market sentiment “to gradually turn more positive”. “We expect [crude oil] market sentiment to gradually turn more positive as the bearish oversupply narrative so prevalent in H2-2025 weakens, and traders turn their attention to a more positive H2-2026,” Ashford stated in the report. “We expect the supply glut estimates of the main market commentators to be revised towards more seasonal norms, although prices are likely to remain in the low to mid $60s per barrel,” Ashford added. Ashford also outlined in the report that Standard Chartered expects “an uptick in volatility and increasing focus on risks to both supply and demand”. The Standard Chartered Bank Energy Research Head went on to note in the report that “low prices have begun to quash U.S. shale output growth” and added that, “if OPEC+’s gradual return of barrels recommences in Q2-2026, this would start to highlight the tightness and geographic concentration of spare capacity, which should be price supportive in the medium term”. In the U.S. Energy Information Administration’s (EIA) latest short term energy outlook, which was released earlier this month, the EIA projected that Lower 48 States crude oil production, including lease condensate and excluding the Gulf of America, will drop from 11.28 million barrels per day in 2025 to 11.11 million barrels per day this year. Total U.S. crude oil output, including lease condensate, is forecast in the STEO to drop from 13.61 million barrels per day in 2025 to 13.59 million barrels per day in 2026. A statement posted on OPEC’s website on January 4 revealed that, in a meeting held that day, Saudi Arabia, Russia, Iraq, UAE, Kuwait, Kazakhstan, Algeria, and Oman “reaffirmed their decision on 2 November

Woodside Expects Lower Production This Year

Woodside Energy Group Ltd’s output in 2025 exceeded guidance and set a company record but it expects a slowdown in 2026 due to downtime from preparations to start up the Scarborough Energy Project. The Perth-based liquefied natural gas (LNG)-focused producer on Wednesday reported 198.8 million barrels of oil equivalent (MMboe) in production last year, beating the company’s forecast of 192-197 MMboe. “This performance was driven by sustained plateau production at Sangomar [offshore Senegal] through late October and Pluto LNG operating at 100 percent reliability for the second half of the year”, acting chief executive Liz Westcott said in the company’s quarterly statement of results. This year Woodside expects to produce 172-186 MMboe. The projected year-on-year drop “reflects planned downtime at Pluto as we prepare the facility to begin processing Scarborough gas and for first LNG cargo in Q4 2026”, Westcott said. Westcott was referring to the Scarborough Energy Project, which includes the development of the Scarborough field off the coast of Karratha, the construction of a second gas processing train for Pluto LNG with a capacity of five million metric tons per annum (MMtpa) and modifications to Pluto Train 1, according to Woodside. Woodside expects the project to produce up to eight MMtpa of LNG and supply 225 terajoules per day of gas to the Western Australian market. In the fourth quarter of 2025 Woodside produced 48.9 MMboe, down four percent from the prior three-month period and five percent against Q4 2024. Q4 2025 production consisted of 1.71 billion cubic feet a day (Bcfd) of natural gas and 232,000 barrels per day (bpd) of liquids. The decrease was “driven by seasonal weather impacts and lower Australian east-coast demand”, Woodside said. The decline also follows Woodside’s sale of producing oil and gas assets in Greater Angostura in Trinidad and Tobago to Perenco,

Mplify launches AI-focused Carrier Ethernet certifications

“We didn’t want to just put a different sticker on it,” Vachon said. “We wanted to give the opportunity for operators to recertify their infrastructure so at least you’ve now got this very competitive infrastructure.” Testing occurs on live production networks. The automated testing platform can be completed in days once technical preparation is finished. Organizations pay once per certification with predictable annual maintenance fees required to keep certifications active. Optional retesting can refresh certification test records. Carrier Ethernet for AI The Carrier Ethernet for AI certification takes the business certification baseline and adds a performance layer specifically designed for AI workloads. Rather than creating a separate track, the AI certification requires providers to first complete the Carrier Ethernet for Business validation, then demonstrate they can meet additional stringent requirements. “What we identified was that there was another tier that we could produce a standard around for AI,” Vachon explained. “With extensive technical discussions with our membership, our CTO, and our director of certification, they identified the critical performance and functionality parameters.” The additional validation focuses on three key performance parameters: frame delay, inter-frame delay variation, and frame loss ratio aligned with AI workload requirements. Testing uses MEF 91 test requirements with AI-specific traffic profiles and performance objectives that go beyond standard business service thresholds. The program targets three primary use cases: connecting subscriber premises running AI applications to AI edge sites, interconnecting AI edge sites to AI data centers, and AI data center to data center interconnections.

Gauging the real impact of AI agents

That creates the primary network issue for AI agents, which is dealing with implicit and creeping data. There’s a singular important difference between an AI agent component and an ordinary software component. Software is explicit in its use of data. The programming includes data identification. AI is implicit in its data use; the model was trained on data, and there may well be some API linkage to databases that aren’t obvious to the user of the model. It’s also often true that when an agentic component is used, it’s determined that additional data resources are needed. Are all these resources in the same place? Probably not. The enterprises with the most experience with AI agents say it would be smart to expect some data center network upgrades to link agents to databases, and if the agents are distributed away from the data center, it may be necessary to improve the agent sites’ connection to the corporate VPN. As agents evolve into real-time applications, this requires they also be proximate to the real-time system they support (a factory or warehouse), so the data center, the users, and any real-time process pieces all pull at the source of hosting to optimize latency. Obviously, they can’t all be moved into one place, so the network has to make a broad and efficient set of connections. That efficiency demands QoS guarantees on latency as well as on availability. It’s in the area of availability, with a secondary focus on QoS attributes like latency, that the most agent-experienced enterprises see potential new service opportunities. Right now, these tend to exist within a fairly small circle—a plant, a campus, perhaps a city or town—but over time, key enterprises say that their new-service interest could span a metro area. They point out that the real-time edge applications

Photonic chip vendor snags Gates investment

“Moore’s Law is slowing, but AI can’t afford to wait. Our breakthrough in photonics unlocks an entirely new dimension of scaling, by packing massive optical parallelism on a single chip,” said Patrick Bowen, CEO of Neurophos. “This physics-level shift means both efficiency and raw speed improve as we scale up, breaking free from the power walls that constrain traditional GPUs.” The new funding includes investments from Microsoft’s investment fund M12 that will help speed up delivery of Neurophos’ first integrated photonic compute system, including datacenter-ready OPU modules. Neurophos is not the only company exploring this field. Last April, Lightmatter announced the launch of photonic chips to tackle data center bottlenecks, And in 2024, IBM said its researchers were exploring optical chips and developing a prototype in this area.

Intel wrestling with CPU supply shortage

“We have important customers in the data center side. We have important OEM customers on both data center and client and that needs to be our priority to get the limited supply we have to those customers,” he added. CEO Lip-Bu Tan added that the continuing proliferation and diversification of AI workloads is placing significant capacity constraints on traditional and new hardware infrastructure, reinforcing the growing and essential role CPUs play in the AI era. Because of this, Intel decided to simplify its server road map, focusing resources on the 16-channel Diamond Rapids product and accelerate the introduction of Coral Rapids. Intel had removed multithreading from diamond Rapids, presumably to get rid of the performance bottlenecks. With each core running two threads, they often competed for resources. That’s why, for example, Ampere does not use threading but instead applies many more cores per CPU. With Coral Rapids, Intel is not only reintroducing multi-threading back into our data center road map but working closely with Nvidia to build a custom Xeon fully integrated with their NVLink technology to Build the tighter connection between Intel Xeon processors and Nvidia GPUs. Another aspect impacting supply has been yields or the new 18A process node. Tan said he was disappointed that the company could not fully meet the demand of the markets, and that while yields are in line with internal plans, “they’re still below where I want them to be,” Tan said. Tan said yields for 18A are improving month-over-month and Intel is targeting a 7% to 8% improvement each month.

Intel’s AI pivot could make lower-end PCs scarce in 2026

However, he noted, “CPUs are not being cannibalized by GPUs. Instead, they have become ‘chokepoints’ in AI infrastructure.” For instance, CPUs such as Granite Rapids are essential in GPU clusters, and for handling agentic AI workloads and orchestrating distributed inference. How pricing might increase for enterprises Ultimately, rapid demand for higher-end offerings resulted in foundry shortages of Intel 10/7 nodes, Bickley noted, which represent the bulk of the company’s production volume. He pointed out that it can take up to three quarters for new server wafers to move through the fab process, so Intel will be “under the gun” until at least Q2 2026, when it projects an increase in chip production. Meanwhile, manufacturing capacity for Xeon is currently sold out for 2026, with varying lead times by distributor, while custom silicon programs are seeing lead times of 6 to 8 months, with some orders rolling into 2027, Bickley said. In the data center, memory is the key bottleneck, with expected price increases of more than 65% year over year in 2026 and up to 25% for NAND Flash, he noted. Some specific products have already seen price inflation of over 1,000% since 2025, and new greenfield capacity for memory is not expected until 2027 or 2028. Moor’s Sag was a little more optimistic, forecasting that, on the client side, “memory prices will probably stabilize this year until more capacity comes online in 2027.” How enterprises can prepare Supplier diversification is the best solution for enterprises right now, Sag noted. While it might make things more complex, it also allows data center operators to better absorb price shocks because they can rebalance against suppliers who have either planned better or have more resilient supply chains.

Reports of SATA’s demise are overblown, but the technology is aging fast

The SATA 1.0 interface made its debut in 2003. It was developed by a consortium consisting of Intel, Dell, and storage vendors like Seagate and Maxtor. It quickly advanced to SATA III in 2009, but there never was a SATA IV. There was just nibbling around the edges with incremental updates as momentum and emphasis shifted to PCI Express and NVMe. So is there any life to be had in the venerable SATA interface? Surprisingly, yes, say the analysts. “At a high level, yes, SATA for consumer is pretty much a dead end, although if you’re storing TB of photos and videos, it is still the least expensive option,” said Bob O’Donnell, president and chief analyst with TECHnalysis Research. Similarly for enterprise, for massive storage demands, the 20 and 30 TB SATA drives from companies like Seagate and WD are apparently still in wide use in cloud data centers for things like cold storage. “In fact, both of those companies are seeing recording revenues based, in part, on the demand for these huge, high-capacity low-cost drives,” he said. “SATA doesn’t make much sense anymore. It underperforms NVMe significantly,” said Rob Enderle, principal analyst with The Enderle Group. “It really doesn’t make much sense to continue make it given Samsung allegedly makes three to four times more margin on NVMe.” And like O’Donnell, Enderle sees continued life for SATA-based high-capacity hard drives. “There will likely be legacy makers doing SATA for some time. IT doesn’t flip technology quickly and SATA drives do wear out, so there will likely be those producing legacy SATA products for some time,” he said.

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.

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

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

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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