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QatarEnergy Joins North Rafah Exploration Block in Egypt

QatarEnergy said Monday it had completed the purchase of a 40 percent stake in the North Rafah exploration block offshore Egypt from Eni SpA. The Italian state-backed energy major retains 60 percent as operator, state-owned QatarEnergy said in a press release. North Rafah spans nearly 3,000 square kilometers (1,158.31 square miles) in the Mediterranean Sea […]

QatarEnergy said Monday it had completed the purchase of a 40 percent stake in the North Rafah exploration block offshore Egypt from Eni SpA.

The Italian state-backed energy major retains 60 percent as operator, state-owned QatarEnergy said in a press release.

North Rafah spans nearly 3,000 square kilometers (1,158.31 square miles) in the Mediterranean Sea off the northeastern coast of Egypt, QatarEnergy noted. The block has a water depth of up to 450 meters (1,476.38 feet), it said.

The acquisition “strengthens our presence in Egypt and marks another important step in advancing our ambitious international exploration strategy”, said QatarEnergy president and chief executive Saad Sherida Al-Kaabi, who is also Qatar’s energy minister.

Earlier this month QatarEnergy said it has entered into an agreement to buy a 27 percent ownership in the North Cleopatra exploration block on Egypt’s side of the Mediterranean Sea from operator Shell PLC.

Shell will retain 36 percent. The other partners are Chevron Corp with a 27 percent interest and Egypt’s state-owned Tharwa Petroleum Co with 10 percent, according to a QatarEnergy statement October 5.

North Cleopatra spans 3,400 square kilometers with waters up to 2,600 meters (8,530.18 feet) deep, QatarEnergy noted.

The license area is in the frontier Herodotus basin and adjacent to the northern portion of the North El-Dabaa block, where QatarEnergy holds 23 percent, QatarEnergy said.

QatarEnergy obtained its North El-Dabaa stake from United States oil and gas heavyweight Chevron, in an agreement announced November 11, 2024.

North El-Dabaa lies about 10 kilometers off Egypt’s Mediterranean shore. The block has a water depth of 100-3,000 meters, according to QatarEnergy.

On May 12, 2024, QatarEnergy announced a deal to acquire 40 percent each in the Cairo and Masry exploration blocks offshore Egypt from sole owner Exxon Mobil Corp. The blocks cover around 11,400 square kilometers with waters 2,000-3,000 meters deep, according to QatarEnergy.

On March 29, 2022, QatarEnergy announced an agreement to buy from U.S. energy major ExxonMobil 40 percent in the North Marakia exploration block in Egyptian waters in the Mediterranean.

Elsewhere in Egypt, QatarEnergy previously entered deals with Shell to buy a 17 percent stake each in Blocks 3 and 4 in the Red Sea, as announced by QatarEnergy December 13, 2021.

In 2023 Egypt awarded a consortium consisting of QatarEnergy, Eni and British energy major BP PLC exploration and production rights for the East Port Said block or EGY-MED-E8. QatarEnergy and BP each own 33 percent. Operator Eni has the remaining 34 percent, according to BP’s announcement of the award October 2, 2023.

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Mobile demands spur enterprise Wi-Fi upgrades

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Anthropic signs billion-dollar deal with Google Cloud

US-based AI company Anthropic has signed a major deal with Google Cloud that is said to be worth tens of billions of dollars. As part of the deal, Anthropic will have access to up to one million of Google’s purpose-built Tensor Processing Unit (TPU) AI accelerators. “Anthropic and Google have

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Lukoil to Sell Foreign Assets amid Sanctions

(Update) October 28, 2025, 10:00 AM GMT+1: Article updated with details throughout. Lukoil PJSC, Russia’s second-largest oil producer, announced plans to sell international assets after being hit by US sanctions last week.  The company is has started considering bids from potential buyers, according to a statement posted on its website late on Monday. The divestment process is being conducted under a wind-down license from the US Treasury’s Office of Foreign Assets Control, which Lukoil said it could ask to be extended “to ensure uninterrupted operations of its international assets.” Last week, President Donald Trump’s administration slapped sanctions on Russia’s two biggest oil producers – Lukoil and state-controlled Rosneft PJSC – to pressure the Kremlin to end the war in Ukraine. The oil and gas industry is a key source of tax revenues for the nation’s budget, and two producers account for just under a half of the country’s crude exports. The goal of the White House is to make Russia’s oil trade harder, costlier and riskier, rather than stopping the flows altogether in a way that could spike global crude prices. The UK also blacklisted the two companies earlier this month. Lukoil is the most internationally diverse of Russia’s oil giants, with upstream businesses in former Soviet countries such as Kazakstan, Uzbekistan and Azerbaijan, as well as in Egypt, the United Arab Emirates and West African nations of Ghana, Nigeria, Cameroon and Congo.  In all these projects, the Russian producer holds minority stakes, and their share in Lukoil’s total crude production last year was only 5 percent, according to the company’s annual report. International assets jointly account for around a quarter of Lukoil’s current capitalization, according to estimates from Kirill Bakhtin, senior analyst at Moscow-based BCS. One notable exception is Iraq, where Lukoil holds 75 percent of the giant West Qurna 2 oil

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QatarEnergy Joins North Rafah Exploration Block in Egypt

QatarEnergy said Monday it had completed the purchase of a 40 percent stake in the North Rafah exploration block offshore Egypt from Eni SpA. The Italian state-backed energy major retains 60 percent as operator, state-owned QatarEnergy said in a press release. North Rafah spans nearly 3,000 square kilometers (1,158.31 square miles) in the Mediterranean Sea off the northeastern coast of Egypt, QatarEnergy noted. The block has a water depth of up to 450 meters (1,476.38 feet), it said. The acquisition “strengthens our presence in Egypt and marks another important step in advancing our ambitious international exploration strategy”, said QatarEnergy president and chief executive Saad Sherida Al-Kaabi, who is also Qatar’s energy minister. Earlier this month QatarEnergy said it has entered into an agreement to buy a 27 percent ownership in the North Cleopatra exploration block on Egypt’s side of the Mediterranean Sea from operator Shell PLC. Shell will retain 36 percent. The other partners are Chevron Corp with a 27 percent interest and Egypt’s state-owned Tharwa Petroleum Co with 10 percent, according to a QatarEnergy statement October 5. North Cleopatra spans 3,400 square kilometers with waters up to 2,600 meters (8,530.18 feet) deep, QatarEnergy noted. The license area is in the frontier Herodotus basin and adjacent to the northern portion of the North El-Dabaa block, where QatarEnergy holds 23 percent, QatarEnergy said. QatarEnergy obtained its North El-Dabaa stake from United States oil and gas heavyweight Chevron, in an agreement announced November 11, 2024. North El-Dabaa lies about 10 kilometers off Egypt’s Mediterranean shore. The block has a water depth of 100-3,000 meters, according to QatarEnergy. On May 12, 2024, QatarEnergy announced a deal to acquire 40 percent each in the Cairo and Masry exploration blocks offshore Egypt from sole owner Exxon Mobil Corp. The blocks cover around 11,400 square kilometers

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Baker Hughes Wins New Aramco Drilling Services Contract

Baker Hughes Co has signed an agreement with Saudi Arabian Oil Co (Aramco) expanding its integrated underbalanced coiled tubing drilling (UBCTD) operations across Saudi Arabia’s natural gas fields. “Under the multi-year agreement, Baker Hughes will expand its current UBCTD fleet from four to 10 units for re-entry and greenfield drilling projects across fields in the kingdom”, the Houston, Texas-based company said in a press release. “The company will provide integrated solutions to manage all aspects of the UBCTD operations, including coiled tubing drilling units, underbalanced drilling services, operational management, well construction and geosciences to scale and accelerate their access to gas from new and established fields”. Work under the expanded contract is scheduled to start next year. “Baker Hughes’ integrated approach to UBCTD includes the industry-leading CoilTrak™ bottomhole assembly system and enhanced reservoir analysis driven by GaffneyCline™ energy advisory”, Baker Hughes said. “This unique pairing of technology and insight allows operators to more effectively navigate the subsurface environment during horizontal drilling and re-entry operations. “By combining these solutions with holistic project management services, Baker Hughes will enhance production efficiency, speed and safety while mitigating reservoir damage when compared to traditional development methods”. Amerino Gatti, Baker Hughes executive vice president for oilfield services and equipment, said, “This project is the result of nearly two decades of successful collaboration between Baker Hughes and Aramco, which have set the standard for UBCTD. By combining advanced technologies with a holistic, integrated approach, we can support Aramco to more efficiently access bypassed and hard-to-reach hydrocarbons and produce the resources that help the kingdom thrive”. “This expansion sets the stage for further innovation in UBCTD, which has the potential to shape how oil and gas are produced around the world”, Gatti added. Baker Hughes entered the Saudi UBCTD market in 2008, according to the company. In a separate contract, Baker Hughes said Monday it has been tapped

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Crude Pauses After Sanction-Fueled Rally

Oil swung between gains and losses on the back of the biggest weekly increase since June as attention turned to the wider outlook for supply as the US and China made progress on trade. West Texas Intermediate slipped 0.3% to settle just above $61, extending its decline for a second day. Top Chinese and US negotiators said they came to terms on a range of points, setting the table for President Donald Trump and counterpart Xi Jinping to finalize a deal to ease trade tensions between the world’s two biggest economies and crude importers. Still, oil was little changed Monday after adding nearly 7% last week when the US sanctioned Russian oil giants Rosneft and Lukoil to squeeze Russia over its ongoing war in Ukraine. The move added output risks to a market that’s showing signs of entering a surplus. Lukoil announced in a statement that it intends to sell its international assets due to the latest sanctions. “The market is taking a breather here,” said Dennis Kissler, senior vice president for trading at BOK Financial. “While US-China negotiations continue, no real outcome has been agreed as of yet…and the sanctions on Russia may halt some shipments though it’s more likely most of that oil will still find a home.” The Trump administration is seeking to make Russia’s trade harder, costlier and riskier, but without forcing a sudden supply shock that might spike global oil prices, officials familiar with the matter said over the weekend. The measures helped oil rebound from a five-month low last week, but part of the move was likely driven by extreme market positioning. Traders had amassed record bearish wagers on the global Brent benchmark in anticipation of oversupply in the next few months. In the meantime, commodity trading advisers, or CTAs, are set to accelerate

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Petrofac’s 7,300 Jobs at Risk

UK energy services provider Petrofac Ltd has applied to enter administration after the company’s latest plans to restructure its balance sheet unexpectedly fell through, putting thousands of jobs at risk. The company has applied to the High Court of England and Wales to appoint administrators, according to a statement on Monday. It comes after European grid operator TenneT canceled Petrofac’s work at a large offshore energy project in the North Sea, rendering the financial restructuring unviable.  The firm employs around 7,300 people globally and has been trying to strike a deal with creditors for over a year, while safeguarding key business deals that could keep the firm afloat. Its collapse would raise the pressure on the UK government to protect British jobs, with the Labour administration already coming under fire for blocking new North Sea oil licenses. The filing from the company, which employs about 2,000 people in the UK, adds to a string of challenges facing the government, including a bruising by-election defeat, pressure to raise taxes in the autumn budget, and ongoing public outrage over troubled utility Thames Water, Britain’s biggest and most indebted water supplier.  A representative for the Department for Energy Security and Net Zero said that Petrofac’s administration is a “product of longstanding issues in their global business,” adding that the UK arm is continuing to operate as normal. “The government will continue to work with the UK company as it focuses on its long-term future,” the spokesperson said.  Meanwhile, alternative restructuring and M&A solutions for the group are still being explored with creditors including its bondholder group, Petrofac said. Key Contract Petrofac’s business with TenneT was particularly crucial given it represents over 80% of revenue in the group’s engineering and construction division, according to court documents filed earlier this year. But since Petrofac was not able to meet

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Energy Department Announces New Public-Private Partnership Model, Two Supercomputers, to Accelerate American Dominance in Science and Technology

WASHINGTON— The U.S. Department of Energy (DOE) today announced two new AMD-accelerated artificial intelligence (AI) supercomputers at Oak Ridge National Laboratory (ORNL), one of which will be built at record speeds thanks to a new public-private partnership model. The supercomputers will help expand America’s leadership in scientific computing, strengthen national security, and drive the next generation of Gold Standard Science and innovation. With the new public-private partnership model, the Lux AI cluster, powered by AMD Instinct™ MI355X GPUs, AMD EPYC™ CPUs, and AMD Pensando™ advanced networking, will be deployed in early 2026 to expand DOE’s near-term AI capacity and accelerate work on critical national priorities, including fusion, fission, materials discovery, quantum, advanced manufacturing, and grid modernization. Lux will provide a secure, open, and efficient AI software stack to strengthen America’s innovation base and enhance U.S. competitiveness. “Winning the AI race requires new and creative partnerships that will bring together the brightest minds and industries American technology and science has to offer,” said U.S. Secretary of Energy Chris Wright. “That’s why the Trump administration is announcing the first example of a new commonsense approach to computing partnerships with Lux. We are also announcing, as part of a competitive procurement process, Discovery. Working with AMD and HPE, we’re bringing new capacity online faster than ever before, turning shared innovation into national strength, and proving that America leads when private-public partners build together.” “We are proud and honored to partner with the U.S. Department of Energy and Secretary Wright to accelerate America’s AI compute infrastructure,” said AMD chair and CEO Dr. Lisa Su. “This partnership exemplifies public-private collaboration at its best. With Discovery and Lux, we are delivering leadership compute systems that combine performance and energy efficiency to advance America’s research priorities and strengthen U.S. leadership in AI, energy, and national security.” DOE

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Qualcomm goes all-in on inferencing with purpose-built cards and racks

From a strategy perspective, there is a longer term enterprise play here, noted Moor’s Kimball; Humain is Qualcomm’s first customer, and a cloud service provider (CSP) or hyperscaler will likely be customer number two. However, at some point, these rack-scale systems will find their way into the enterprise. “If I were the AI200 product marketing lead, I would be thinking about how I demonstrate this as a viable platform for those enterprise workloads that will be getting ‘agentified’ over the next several years,” said Kimball. It seems a natural step, as Qualcomm saw success with its AI100 accelerator, a strong inference chip, he noted. Right now, Nvidia and AMD dominate the training market, with CUDA and ROCm enjoying a “stickiness” with customers. “If I am a semiconductor giant like Qualcomm that is so good at understanding the performance-power balance, this inference market makes perfect sense to really lean in on,” said Kimball. He also pointed to the company’s plans to re-enter the datacenter CPU space with its Oryon CPU, which is featured in Snapdragon and loosely based on technology it acquired with its $1.4 billion Nuvia acquisition. Ultimately, Qualcomm’s move demonstrates how wide open the inference market is, said Kimball. The company, he noted, has been very good at choosing target markets and has seen success when entering those markets. “That the company would decide to go more ‘in’ on the inference market makes sense,” said Kimball. He added that, from an ROI perspective, inferencing will “dwarf” training in terms of volume and dollars.

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AI data center building boom risks fueling future debt bust, bank warns

However, that’s only one part of the problem. Meeting the power demands of AI data centers will require the energy sector to make large investments. Then there’s data center demand for microprocessors, rare earth elements, and other valuable metals such as copper, which could, in a bust, make data centers the most expensively-assembled unwanted assets in history. “Financial stability consequences of an AI-related asset price fall could arise through multiple channels. If forecasted debt-financed AI infrastructure growth materializes, the potential financial stability consequences of such an event are likely to grow,” warned the BoE blog post. “For companies who depend on the continued demand for massive computational capacity to train and run inference on AI models, an algorithmic breakthrough or other event which challenges that paradigm could cause a significant re-evaluation of asset prices,” it continued. According to Matt Hasan, CEO of AI consultancy aiRESULTS, the underlying problem is the speed with which AI has emerged. “What we’re witnessing isn’t just an incremental expansion, it’s a rush to construct power-hungry, mega-scale data centers,” he told Network World. The dot.com reversal might be the wrong comparison; it dented the NASDAQ and hurt tech investment, but the damage to organizations investing in e-commerce was relatively limited. AI, by contrast, might have wider effects for large enterprises because so many have pinned their business prospects on its potential. “Your reliance on these large providers means you are indirectly exposed to the stability of their debt. If a correction occurs, the fallout can impact the services you rely on,” said Hasan.

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Intel sees supply shortage, will prioritize data center technology

“Capacity constraints, especially on Intel 10 and Intel 7 [Intel’s semiconductor manufacturing process], limited our ability to fully meet demand in Q3 for both data center and client products,” said Zinsner, adding that Intel isn’t about to add capacity to Intel 10 and 7 when it has moved beyond those nodes. “Given the current tight capacity environment, which we expect to persist into 2026, we are working closely with customers to maximize our available output, including adjusting pricing and mix to shift demand towards products where we have supply and they have demand,” said Zinsner. For that reason, Zinzner projects that the fourth quarter will be roughly flat versus the third quarter in terms of revenue. “We expect Intel products up modestly sequentially but below customer demand as we continue to navigate supply environment,” said Zinsner. “We expect CCG to be down modestly and PC AI to be up strongly sequentially as we prioritize wafer capacity for server shipments over entry-level client parts.”

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How to set up an AI data center in 90 days

“Personally, I think that a brownfield is very creative way to deal with what I think is the biggest problem that we’ve got right now, which is time and speed to market,” he said. “On a brownfield, I can go into a building that’s already got power coming into the building. Sometimes they’ve already got chiller plants, like what we’ve got with the building I’m in right now.” Patmos certainly made the most of the liquid facilities in the old printing press building. The facility is built to handle anywhere from 50 to over 140 kilowatts per cabinet, a leap far beyond the 1–2 kW densities typical of legacy data centers. The chips used in the servers are Nvidia’s Grace Blackwell processors, which run extraordinarily hot. To manage this heat load, Patmos employs a multi-loop liquid cooling system. The design separates water sources into distinct, closed loops, each serving a specific function and ensuring that municipal water never directly contacts sensitive IT equipment. “We have five different, completely separated water loops in this building,” said Morgan. “The cooling tower uses city water for evaporation, but that water never mixes with the closed loops serving the data hall. Everything is designed to maximize efficiency and protect the hardware.” The building taps into Kansas City’s district chilled water supply, which is sourced from a nearby utility plant. This provides the primary cooling resource for the facility. Inside the data center, a dedicated loop circulates a specialized glycol-based fluid, filtered to extremely low micron levels and formulated to be electronically safe. Heat exchangers transfer heat from the data hall fluid to the district chilled water, keeping the two fluids separate and preventing corrosion or contamination. Liquid-to-chip and rear-door heat exchangers are used for immediate heat removal.

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INNIO and VoltaGrid: Landmark 2.3 GW Modular Power Deal Signals New Phase for AI Data Centers

Why This Project Marks a Landmark Shift The deployment of 2.3 GW of modular generation represents utility-scale capacity, but what makes it distinct is the delivery model. Instead of a centralized plant, the project uses modular gas-reciprocating “power packs” that can be phased in step with data-hall readiness. This approach allows staged energization and limits the bottlenecks that often stall AI campuses as they outgrow grid timelines or wait in interconnection queues. AI training loads fluctuate sharply, placing exceptional stress on grid stability and voltage quality. The INNIO/VoltaGrid platform was engineered specifically for these GPU-driven dynamics, emphasizing high transient performance (rapid load acceptance) and grid-grade power quality, all without dependence on batteries. Each power pack is also designed for maximum permitting efficiency and sustainability. Compared with diesel generation, modern gas-reciprocating systems materially reduce both criteria pollutants and CO₂ emissions. VoltaGrid markets the configuration as near-zero criteria air emissions and hydrogen-ready, extending allowable runtimes under air permits and making “prime-as-a-service” viable even in constrained or non-attainment markets. 2025: Momentum for Modular Prime Power INNIO has spent 2025 positioning its Jenbacher platform as a next-generation power solution for data centers: combining fast start, high transient performance, and lower emissions compared with diesel. While the 3 MW J620 fast-start lineage dates back to 2019, this year the company sharpened its data center narrative and booked grid stability and peaking projects in markets where rapid data center growth is stressing local grids. This momentum was exemplified by an 80 MW deployment in Indonesia announced earlier in October. The same year saw surging AI-driven demand and INNIO’s growing push into North American data-center markets. Specifications for the 2.3 GW VoltaGrid package highlight the platform’s heat tolerance, efficiency, and transient response, all key attributes for powering modern AI campuses. VoltaGrid’s 2025 Milestones VoltaGrid’s announcements across 2025 reflect

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Inside Google’s multi-architecture revolution: Axion Arm joins x86 in production clusters

Matt Kimball, VP and principal analyst with Moor Insights and Strategy, pointed out that AWS and Microsoft have already moved many workloads from x86 to internally designed Arm-based servers. He noted that, when Arm first hit the hyperscale datacenter market, the architecture was used to support more lightweight, cloud-native workloads with an interpretive layer where architectural affinity was “non-existent.” But now there’s much more focus on architecture, and compatibility issues “largely go away” as Arm servers support more and more workloads. “In parallel, we’ve seen CSPs expand their designs to support both scale out (cloud-native) and traditional scale up workloads effectively,” said Kimball. Simply put, CSPs are looking to monetize chip investments, and this migration signals that Google has found its performance-per-dollar (and likely performance-per-watt) better on Axion than x86. Google will likely continue to expand its Arm footprint as it evolves its Axion chip; as a reference point, Kimball pointed to AWS Graviton, which didn’t really support “scale up” performance until its v3 or v4 chip. Arm is coming to enterprise data centers too When looking at architectures, enterprise CIOs should ask themselves questions such as what instance do they use for cloud workloads, and what servers do they deploy in their data center, Kimball noted. “I think there is a lot less concern about putting my workloads on an Arm-based instance on Google Cloud, a little more hesitance to deploy those Arm servers in my datacenter,” he said. But ultimately, he said, “Arm is coming to the enterprise datacenter as a compute platform, and Nvidia will help usher this in.” Info-Tech’s Jain agreed that Nvidia is the “biggest cheerleader” for Arm-based architecture, and Arm is increasingly moving from niche and mobile use to general-purpose and AI workload execution.

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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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