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HighPoint offers direct GPU-storage connection to speed AI training, inference workloads

GPUDirect uses PCI Express Gen 5 and requires a PCIe switch that supports P2P DMA capability, and not all PCIe Gen5 switches support this feature. The Rocket card uses the Broadcom PEX 89048 switch, which system integrators to build systems with GPUDirect support. The adapter features 48 PCIe 5.0 lanes, 16 of which are dedicated […]

GPUDirect uses PCI Express Gen 5 and requires a PCIe switch that supports P2P DMA capability, and not all PCIe Gen5 switches support this feature. The Rocket card uses the Broadcom PEX 89048 switch, which system integrators to build systems with GPUDirect support.

The adapter features 48 PCIe 5.0 lanes, 16 of which are dedicated to internal NVMe storage devices while the rest are dedicated to connectivity. The adapter uses MCIO 8i connectors, which support up to 16 NVMe drives, for a total of up to 2PB of high-performance storage. It supports multiple GPU nodes by ensuring each GPU has dedicated bandwidth without sacrificing NVMe performance.

The Rocker 7638D adapter enables GPUDirect Storage workflows that avoid host CPU and RAM entirely and provide predictable bandwidth (up to 64 GB/s) and latency when paired with compatible software, which includes operating system, GPU drivers, and filesystem. The device is particularly useful in scenarios involving large-scale training datasets that use plenty of storage.

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This week in 5 numbers: Rising demand, rising rates

Industry Dive is an Informa TechTarget business. This website is owned and operated by Informa TechTarget, part of a global network that informs, influences and connects the world’s technology buyers and sellers. All copyright resides with them. Informa PLC’s registered office is 5 Howick Place, London SW1P 1WG. Registered in

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OPEC Plus Poised to Agree Fresh Output Hike

OPEC+ will likely raise oil output again in November as the group continues its strategy to reclaim global market share, according to people familiar with its plans. The alliance led by Saudi Arabia will consider adding at least as much as the 137,000 barrel-a-day hike scheduled for October when it meets online Oct. 5, the people said. They asked not to be identified as the talks are private. The Organization of the Petroleum Exporting Countries and its allies have started to revive a new layer of halted output, amounting to 1.66 million barrels a day, in monthly stages despite warnings from across the oil industry of an impending surplus.  So far, the oil market has absorbed additional barrels from the group without significant ructions, and Brent futures have risen 3 percent this month.  Still, the planned October hike is sharply lower than the increments that the group announced in the two prior months, and delegates emphasized at the time that the actual supply boost would be even smaller because some countries lack the ability to increase.  The upcoming meeting also takes place against the backdrop of a planned trip by Saudi Crown Prince Mohammed bin Salman to Washington in November. He will meet President Donald Trump, who has repeatedly called for lower fuel prices while he seeks to tame inflation and reduce interest rates.  No final decision has been made yet, and deliberations could still evolve ahead of Sunday’s meeting, the people said. The expectation for the meeting was first reported by Reuters. What do you think? We’d love to hear from you, join the conversation on the Rigzone Energy Network. The Rigzone Energy Network is a new social experience created for you and all energy professionals to Speak Up about our industry, share knowledge, connect with peers and industry insiders and

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Treasuries Hold Gains Amid Oil Price Slump

Treasuries held small gains in early US trading Monday, supported by a slump in oil prices and a rally in UK government bonds, and by anticipation of buying into Tuesday’s month-end index rebalancing. Yields were lower, the two-year by about a basis point and long maturities by as much as three basis points, remaining inside last week’s ranges. US benchmark crude oil futures were down about 2% on signs OPEC+ will hike production again in November. The prospect of a US government shutdown beginning Wednesday also has implications for the Treasury market, as shutdowns are associated with gains for bonds based on their potential to restrain the economy. The market racked up gains even as Cleveland Fed President Beth Hammack — who becomes a voting member of the central bank’s rate-setting committee next year — reiterated her view that inflation remains too high to warrant cutting interest rates. Futures markets continue to anticipate about 100 basis points of additional Fed easing over the next 12 months. Expectations for Fed rate cuts rest mainly on signs of stress in the US labor market, where job creation has slowed precipitously in recent months. September data is set to be released on Friday. Tuesday’s month-end bond index rebalancing — to add eligible bonds created during the month and remove those that no longer fit the index criteria — typically drives buying by passive and other index-tracking investment funds that can support the market if their needs exceed expectations.  The rebalancing will increase the duration of the Bloomberg Treasury index by an estimated 0.06 year, less than the average for September over the past decade. 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

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Lawmakers urge PJM to take steps so clean energy projects can meet tax credit deadlines

Dive Brief: A group of 107 state lawmakers on Monday urged the PJM Interconnection to take steps to support the rapid addition of clean energy resources onto the grid to ensure the grid operator has enough power supplies to meet the region’s needs. The lawmakers in the National Caucus of Environmental Legislators want action from PJM so that renewable energy developers can take advantage of federal tax credits before they expire, according to Maryland Delegate Lorig Charkoudian, a Democrat who spearheaded the letter to PJM. “We’re asking them to work with states and move these projects forward so they can get in under the deadlines for tax credits,” Charkoudian said in an interview Friday. PJM should urge the Trump administration to stop hampering clean energy projects, which can be built quickly and would help address the United States’ power supply needs and bolster reliability, according to the lawmakers. Dive Insight: PJM has been warning since at least February 2023 that it faces a potential shortfall in power supplies, partly driven by data center development. In the letter, the lawmakers ask PJM to communicate with federal agencies about the need to support renewable energy as part of an “all-of-the-above” energy strategy that addresses reliability and affordability. The Trump administration and Congress have taken a range of actions aimed at limiting clean energy resources from coming online despite concerns about a lack of adequate power supplies, and PJM appears to be silent on the issue, Charkoudian said. “Either we have a resource adequacy issue or we don’t — and I believe we do — so we need to be getting all of this energy online as quickly as possible,” Charkoudian said. Also, the legislators want PJM to give states more information about projects that are close to finishing their interconnection reviews so states

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Vistra announces Comanche deal, plan to add 860 MW of natural gas

Vistra Corp. has reached a final investment decision to expand gas capacity at its Permian Basin Power Plant, locking in a plan to build two new natural gas power units totaling 860 MW, the company said Monday. “This expansion more than triples the site’s current capacity from 325 MW to 1,185 MW,” Vistra said in a release. The decision to expand was “based on customer demand and to meet West Texas’ growing power needs, particularly the state’s expanding oil and natural gas industries.” “As the leading competitive generator in Texas, customers from residential to commercial and industrial are turning to Vistra to help them meet their energy needs,” said Jim Burke, president and CEO of Vistra. “We recognize that energy is critical to powering this economic opportunity, and we expect Texas will play an outsized role.” Vistra also filed an 8-K with the Securities and Exchange Commission on Monday, confirming that it “has entered into a 20-year power purchase agreement (with options to extend for up to an additional 20 years) with a large, investment grade company … pursuant to which the Company has agreed to supply to the Customer 1,200 MW of carbon-free power from the Comanche Peak Nuclear Power Plant.” Vistra said it “anticipates power delivery to begin in the fourth quarter of 2027 and ramp to full capacity by 2032.” The company received permission last year from the Nuclear Regulatory Commission to extend the operation of Comanche through 2053, an additional 20 years beyond its original licenses. On Sept. 22, Jefferies downgraded Vistra’s stock to “hold” based on the lack of a deal up to that point and their view that the company’s stock, which rallied based on excitement about a deal, had gotten close to its peak price. “We still have a positive view of [the

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NOAA, Fugro Team Up to Accelerate Deep Ocean Mapping

The U.S. National Oceanic and Atmospheric Administration (NOAA) announced in a statement posted on its site recently that it and Fugro have partnered “to accelerate deep ocean mapping [and] characterization”. The statement noted that NOAA Ocean Exploration and Fugro have signed a cooperative research and development agreement (CRADA) “to develop and use uncrewed systems for ocean exploration to enhance the efficiency, reach, and impact of NOAA’s mission to explore the deep ocean”. “This collaboration unites NOAA’s scientific and operational excellence with Fugro’s cutting-edge technological expertise to expand ocean exploration capabilities,” the statement added. According to the statement, the agreement “focuses on the key objectives of seeking better ways to operate ocean exploration missions using remote technology, developing tools that enable scientists to control underwater robots in real-time from distant locations, and creating new sensors that can aid in environmental baseline studies, including the observation of critical minerals”.  This agreement also enables NOAA and Fugro to coordinate on the use of ships, USVs, underwater devices and buoys that transmit data, the statement said. “Together, NOAA and Fugro plan to advance remote mission control, develop cloud-based workflows, and improve real-time data delivery through high-bandwidth communications,” the statement added. NOAA noted in the statement that Fugro’s “extensive experience operating uncrewed vehicles, providing data services and remotely managing offshore systems and assets makes it a valuable partner for NOAA as they explore previously unexplored or poorly explored areas of the deep ocean”. “While Fugro and NOAA Ocean Exploration will develop specific projects together in the coming months, the CRADA lays the groundwork for ongoing collaboration and innovation between the public and private sectors,” NOAA highlighted. NOAA said in the statement that this CRADA “reflects NOAA Ocean Exploration’s broader mission to unlock the mysteries of the deep ocean and enable the sustainable use of marine resources

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ADNOC Seals Rio Grande LNG Stake Acquisition

Abu Dhabi National Oil Co PJSC (ADNOC), through its global investment arm XRG PJSC, has completed the purchase of an 11.7 percent stake in phase I of NextDecade Corp’s Rio Grande LNG project in Brownsville, Texas. “The transaction was undertaken through an investment vehicle of GIP [BlackRock Inc’s Global Infrastructure Partners], with XRG acquiring a portion of GIP’s existing stake”, XRG said in a statement on its website. “The transaction, initially announced in May 2024, is the company’s first gas infrastructure investment in the U.S., and reflects XRG’s long-term investment plans in the country”, XRG said. “As LNG demand is projected to grow by 60 percent by 2050, the investment in Rio Grande LNG advances XRG’s strategy to build a leading global gas and LNG business to meet structural demand from industry, AI and broader economic growth”, it said. XRG aims to build a top-five integrated gas and liquefied natural gas (LNG) business with a capacity of 20-25 million metric tons per annum (MMtpa) by 2035, as announced by the company June 3. ADNOC launched XRG late last year to drive the United Arab Emirates’ expansion in the natural gas, low-carbon energy and chemical markets. Rio Grande LNG’s first phase, which comprises the first three out of five federally approved liquefaction trains, is under construction. ADNOC has also committed to buying 1.9 MMtpa from the fourth train. Earlier this month NextDecade and its co-venturers announced a positive FID (final investment decision) on train IV and a notice for contractor Bechtel Energy Inc to proceed to construction. According to a Department of Energy (DOE) order August 13, 2020, amending Rio Grande LNG’s export authorization, the facility’s five trains each have a nominal capacity of 5.4 MMtpa. However, the Houston, Texas-based developer has said phase I would be capable of up to about

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Scaling Stargate: OpenAI’s Five New U.S. Data Centers Push Toward 10 GW AI Infrastructure

Stargate is OpenAI’s massive AI infrastructure initiative, developed as a joint venture in partnership with Oracle and SoftBank. Formally announced in January 2025, the program is accelerating rapidly with the disclosure of five new U.S. data center sites. These additions—along with the flagship development in Abilene, Texas, and other ongoing projects—bring Stargate’s total planned capacity to nearly 7 gigawatts (GW). The cumulative investment estimate has now topped $400 billion as the program heads toward its ultimate goal: a 10 GW, $500 billion buildout. While the initiative focuses on building capacity with non-Microsoft partners, Microsoft remains a key technology partner and OpenAI’s primary cloud provider (Azure). Where Are the Five New Sites? The next wave of Stargate capacity is landing in regions already familiar with large-scale data center development. Based on public reporting and company statements, the five identified sites are: Shackelford County, Texas (greater Abilene expansion): An extension of the area already hosting Vantage Data Centers’ Frontier project, a $25 billion development on 1,200 acres. Milam County, Texas (Central Texas growth corridor): Previously announced as the home of a SoftBank-led Stargate data center campus. Doña Ana County, New Mexico (Las Cruces area): Linked to Project Jupiter, a proposed $165 billion build spearheaded by BorderPlex Digital Assets, with Stack Infrastructure reported as a potential participant. Lordstown, Ohio (Eastern PJM/FirstEnergy territory): Redevelopment of a former GM/Foxconn complex, being repositioned as a large-scale AI campus through a collaboration between OpenAI, Oracle, and SoftBank. An additional Midwest site (TBD): Location yet to be disclosed. These builds are being advanced under partnership models, with Oracle expected to lead three of the sites and SoftBank/SB Energy two. Together, they reinforce Stargate’s path toward a 10 GW national roadmap. Scale and Performance Goals With the addition of the five new campuses, plus Abilene and other previously announced

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Q3 Executive Roundtable Recap

AI-scale workloads are reshaping the fundamentals of data center design. For Data Center Frontier’s Q3 2025 Executive Roundtable, three industry leaders tackled the most urgent challenges: managing thermal and water risk at scale, balancing CapEx vs. OpEx in the race to build, and breaking down silos as cooling, water, and power systems converge. <!–> Sept. 26, 2025 3 min read –>

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‘Nomads at the Summit’ Podcasts – Recorded Live at DCF Trends Summit 2025

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Equinix unveils distributed AI infrastructure targeting inferencing, cloud connectivity

Data center provider Equinix has launched its Distributed AI infrastructure, which includes a new AI-ready backbone to support high performance distributed AI deployments spanning multiple data center facilities, a global AI Proving Ground to test new solutions, and Fabric Intelligence to better support next generation enterprise workloads. Equinix designed Distributed AI from the ground up to support the scale, speed, and complexity of modern intelligent systems, such as autonomous, agentic AI capable of reasoning, acting, and learning independently. AI is inherently distributed, drawing on multiple data sources in different locations. To effectively train a model, data must be drawn from multiple locations and processed where it lies, not moved around. This requires a new kind of infrastructure that is globally distributed, deeply interconnected, and fully programmable. Distributed AI links more than 270 data centers in over 60 markets, effectively including almost all Equinix’s facilities, according to the vendor.

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Cisco expands its quantum networking portfolio with new software prototypes

The software stack supports three other prototype applications to help enable quantum networking and the data center. The first is what Pandey describes as a network-aware distributed quantum compiler that lets quantum algorithms run across multiple networked processors. “The compiler is the piece of technology you need to enable practical, pragmatic, distributed quantum computing. It takes a quantum workload, a quantum circuit, and it partitions it so that it runs in a distributed environment, in a connected set of qubits or quantum compute nodes,” Pandey said. Significantly, it’s multivendor; the quantum compute nodes can be from the same vendor or from other vendors, such as IBM: “It could be as messy a brownfield, heterogeneous environment as you want. It doesn’t matter to the compiler, which will take an algorithm, partition it across any heterogeneous, brownfield environment,” Pandey said.  “What makes it unique, and an industry-first, is that it accounts for quantum interconnect requirements between processors and supports distributed quantum error correction. Existing compilers target circuits for only single computers,” Pandey stated. “Ours compiles circuits for network-connected computers potentially made of heterogeneous quantum compute technologies and can distribute that partitioned circuit across an entire data center of processors, all connected through a quantum network.” The distributed quantum error correction is a key feature of the software. Error correction ensures the accuracy and reliability of quantum computations and is a challenge for any distributed or standalone network.  The Cisco software in this case understands the error correction intricacies of each of the quantum computing modalities in the network, and “we can ensure that those are carried over from node to node, giving us a distributed or a holistic view of the entire distributed environment and result,” Pandey said.  In addition, “we are developing our own algorithms [to determine] the best way, using our network, to do a

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NVIDIA and OpenAI Forge $100B Alliance to Power the Next AI Revolution

The new strategic partnership between OpenAI and NVIDIA, formalized via a letter of intent in September 2025, is designed to both power and finance the next generation of OpenAI’s compute infrastructure, with initial deployments expected in the second half of 2026. According to the joint press release, both parties position this as “the biggest AI infrastructure deployment in history,” explicitly aimed at training and running OpenAI’s next-generation models.  At a high level: The target scale is 10 gigawatts (GW) or more of deployed compute capacity, realized via NVIDIA systems (comprising millions of GPUs).  The first phase (1 GW) is slated for the second half of 2026, built on the forthcoming Vera Rubin platform.  NVIDIA will progressively invest up to $100 billion into OpenAI, contingent on deployment of capacity in stages.  An initial $10 billion investment from NVIDIA is tied to the execution of a definitive purchase agreement for the first gigawatt of systems.  The equity stake NVIDIA will acquire is described as non-voting / non-controlling, meaning it gives financial skin in the game without governance control.  From a strategic standpoint, tying investment to capacity deployment helps OpenAI lock in capital and hardware over a long horizon, mitigating supply-chain and financing risk. With compute frequently cited as a binding constraint on advancing models, this kind of staged, anchored commitment gives OpenAI a more predictable growth path (at least in theory; that said, the precise economic terms and risk-sharing remain to be fully disclosed.) Press statements emphasize that millions of GPUs will ultimately be involved, and that co-optimization of NVIDIA’s hardware with OpenAI’s software/stack will be a key feature of the collaboration.  Importantly, this deal also fits into OpenAI’s broader strategy of diversifying infrastructure partnerships beyond any single cloud provider. Microsoft remains a central backer and collaborator, but this NVIDIA tie-up further

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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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