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MPLX Closes $2.4B Acquisition of Northwind Midstream Assets

MPLX LP said it has completed the $2.375 billion acquisition of Northwind Delaware Holdings LLC from Five Point Infrastructure LLC. The acquisition of Northwind, which provides sour gas gathering, treating, and processing services in Lea County, New Mexico, will enhance its Permian natural gas and natural gas liquid (NGL) value chains, MPLX said in a […]

MPLX LP said it has completed the $2.375 billion acquisition of Northwind Delaware Holdings LLC from Five Point Infrastructure LLC.

The acquisition of Northwind, which provides sour gas gathering, treating, and processing services in Lea County, New Mexico, will enhance its Permian natural gas and natural gas liquid (NGL) value chains, MPLX said in a news release.

The acquisition is expected to be immediately accretive to distributable cash flow, and inclusive of estimated incremental capital of $500 million, represents a 7x multiple on forecast 2027 EBITDA and an estimated mid-teen unlevered return, the company said.

The acquisition was financed and the incremental capital expenditures associated with in-process expansion projects will be funded by net proceeds from MPLX’s $4.5 billion senior notes issued in August, the company stated.

MPLX said that the acquired business is complementary and adjacent to its existing Delaware basin natural gas system. It consists of over 200,000 dedicated acres, more than 200 miles of gathering pipelines, two in-service acid gas injection wells at 20 million cubic feet per day (MMcfpd), and a third permitted well that will bring its total capacity to 37 MMcfpd, according to the release.

The system currently has 150 MMcfpd of sour gas treating capacity and in-process expansion projects will increase capacity to 440 MMcfpd, expected to be completed in the second half of 2026, the company said.

The system is supported by minimum volume commitments from “top regional producers,” MPLX said.

Last week, MPLX said it entered into a definitive agreement to divest its Rockies gathering and processing assets to a subsidiary of Harvest Midstream for $1.0 billion in cash consideration, subject to customary purchase price adjustments.

Harvest has contractually agreed to dedicate approximately 12 thousand barrels per day of NGLs from these assets to MPLX for a period of seven years starting in 2028, following the expiration of a pre-existing commitment, according to an earlier statement.

The assets included in the transaction are natural gas gathering and transportation pipelines and 1.2 billion cubic feet per day of processing capacity, which operated at 52 percent in 2024, MPLX said.

“Evaluating the competitive positioning of our portfolio is a strategic commitment,” MPLX President and CEO Maryann Mannen said. “The divestiture of these assets better positions our portfolio for growth, anchored in the Marcellus and Permian basins”.

The transaction is expected to close in the fourth quarter, subject to customary closing conditions, including clearance under the Hart-Scott-Rodino Antitrust Improvements Act of 1976, according to the statement.

MPLX describes itself as a diversified, large-cap master limited partnership that owns and operates midstream energy infrastructure and logistics assets and provides fuel distribution services. The company’s assets include a network of crude oil and refined product pipelines, an inland marine business, light-product terminals, storage caverns, as well as refinery tanks, docks, loading racks, and associated piping and crude and light-product marine terminals.

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JF Acquires 4 Corners

JF Petroleum Group (JF) is continuing its expansion with the acquisition of 4 Corners Petroleum Equipment, a service contractor based in Texarkana, Texas. 4 Corners was founded in 2015 by industry veteran Kenny Allen and it has since served Northeast Texas and Southwest Arkansas, JF noted in a media release.

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Quinas readies UltraRam, flash memory with DRAM speed

For starters, the memory is built on what is called a” III-V technology,” a class of semiconductor materials that are composed of elements from groups III and V of the periodic table, the company stated. These materials have unique properties that make them ideal for use in electronic devices such

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7 Wi-Fi certifications to bolster wireless networking skills

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Swift Current lands $242M in financing for PJM’s largest storage project

Swift Current Energy landed $242 million in financing for its 150-MW, four-hour Prospect Power Storage facility in Rockingham County, Virginia, the Boston-based clean energy developer said Thursday. The project is under construction; Swift Current expects it to reach commercial operation in 2026. It will sell output from the project to Dominion Energy Virginia under a 15-year power purchase agreement. Once online, the project will be the largest battery storage facility in the PJM Interconnection, according to Swift Current. PJM runs the grid and wholesale power markets in 13 mid-Atlantic and Midwestern states and the District of Columbia. Swift Current bought the project in 2023 from Clean Planet Renewable Energy, a joint venture between Open Road Renewable Energy and Eolian. “This facility will be the largest battery energy storage project constructed in Virginia to date, supporting American energy dominance by efficiently using the existing transmission lines to open up capacity on the grid for all types of power generation,” Aaron Zubaty, Eolian CEO, said in the press release. Swift Current has brought online 2.2 GW of energy projects. It owns and operates 1.1 GW of solar and wind projects in Illinois, Mississippi and Texas. Its project pipeline totals about 10 GW. Swift Current is majority-owned by funds managed by IFM Investors and Lookout Ridge Energy Partners. Truist Securities, Canadian Imperial Bank of Commerce, KeyBank and Natixis acted as joint coordinating lead arrangers for the Prospect Power project’s financing. PJM had 376 MW of battery storage capacity that could produce 378 MWh at the end of 2023, according to the U.S. Energy Information Administration’s April 25 update on the U.S. battery storage market. While PJM has little installed battery storage capacity compared with the California Independent System Operator and the Electric Reliability Council of Texas, it has about 30.6 GW of storage in its

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FERC in Focus: Will the agency maintain its independence under Trump 2.0?

This is part of Utility Dive’s ongoing “FERC in Focus” series where we explore trends, challenges and other significant developments affecting the commission. President Donald Trump is making unprecedented moves to assert control over independent agencies like the Federal Energy Regulatory Commission, and former commissioners, experts and agency observers say they are watching several key areas to gauge whether the commission will remain independent.  The White House has already moved to favor fossil fuel assets over renewable energy, require agencies to clear decisions with the Office of Management and Budget and include sunset provisions in new regulations. Trump has also shown a willingness to fire or try to remove regulators that run afoul of his preferences, such as he has done with the Nuclear Regulatory Commission and the Federal Reserve. With two Republican nominees preparing to fill empty seats at FERC, the agency is poised for a shift that could lead to more direct White House influence over the independent agency’s policymaking, said Tyson Slocum, director of Public Citizen’s Energy Program. “My guess is you’re going to see a pretty tight alignment between FERC’s priorities and the priorities of the White House, and I think that will significantly erode FERC’s historic bipartisan independence and move FERC more into being an arm of the White House,” he said. Even if the agency maintains its independence, the loss of experts and staff to the administration’s aggressive cuts to the federal workforce could hamper its work, some say.  “The agency is already chronically understaffed and so if you really see additional attrition, it’s going to be much harder for the agency to do complex, hard stuff on top of its bread-and-butter responsibilities and proceedings that really do take up a lot of time,” according to Matt Christiansen, a Wilson Sonsini attorney and former FERC general

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IPAA Announces New President and CEO

In a statement sent to Rigzone recently, the Independent Petroleum Association of America (IPAA) announced the appointment of Edith Naegele as its new President and Chief Executive Officer, effective September 22. Naegele is currently Vice President, Membership and Strategic Development & Corporate Secretary of the American Gas Association (AGA). The incoming IPAA President and CEO has served in this AGA role since joining the AGA in 2021, the IPAA highlighted, adding that, prior to her AGA position, Naegele worked for the U.S. Chamber of Commerce “in roles of increasing responsibility from 2003 with her last role as Senior Vice President where she oversaw membership development and engagement”. The AGA website notes that, at the U.S. Chamber of Commerce, Naegele was part of a development team supporting revenue of more than $180 million annually through multi-year and annual advancement plans aligned with the organization’s policy goals. “She identified and recommended new funding models and opportunities and set the strategic direction for research to increase member engagement, satisfaction and retention,” the site states. “Earlier in her career, Naegele gained experience with the energy industry working for the National Association of Regulatory Utility Commissioners and attended the Abshire-Inamori Leadership Academy within what is now the Energy Security and Climate Change Program at the Center for Strategic and International Studies,” the site adds. The IPAA outlined in its statement that, in her new role, Naegele’s priorities “will include engaging with IPAA membership across the country to better understand the issues facing the upstream oil and natural gas industry”. Jeff Eshelman, the IPAA’s current president and chief executive officer who has served the IPAA for over 27 years, plans to remain with the association in a new role, helping with the leadership transition and advising on advocacy efforts and IPAA’s Energy in Depth program which

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EQT Orders 1.5 MMtpa from Rio Grande LNG

NextDecade Corp. said Wednesday it is on track to reach a FID (final investment decision) this year for Train V of the under-construction Rio Grande LNG after roping in a new liquefied natural gas (LNG) buyer in EQT Corp. The Pittsburgh, Pennsylvania-based vertically integrated gas company signed an agreement to buy 1.5 million metric tons per annum (MMtpa) over 20 years from Train V. “The agreement will be on a free-on-board basis at a price indexed to Henry Hub, subject to NextDecade making a positive FID on Train V”, EQT said in a statement on its website. EQT president and chief executive Toby Z. Rice said, “The execution of this agreement represents continued momentum of EQT’s LNG strategy, which is focused on further diversifying the company’s end-market exposure into the rapidly growing global gas markets and accelerating long-term earnings growth”. “Consistent with our existing LNG deals, EQT will market and optimize its own cargos, providing structuring flexibility and downside protection”, Rice added. NextDecade chair and chief executive Matt Schatzman said, “The LNG we are selling from our project to EQT will play a critical role in enhancing the energy security of our allies around the world”. The Houston, Texas-based LNG developer said in a separate statement it has now secured buyers for 3.5 MMtpa from Train V. Earlier this year Japan’s JERA Co. Inc. signed up for two MMtpa over 20 years. NextDecade said it is looking to secure commitment for an additional one MMtpa “under a long-term sale and purchase agreement to support a positive FID on Train V”. “The company expects to complete commercialization of Train V in the third quarter of 2025, and subject to obtaining adequate financing, NextDecade expects to achieve a positive FID on Train V in the fourth quarter of 2025”, it said. NextDecade expects to

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Kodiak Offers $1.2B Bonds

Kodiak Gas Services Inc. is holding a two-tranche debt instrument sale with a combined principal amount of $1.2 billion to refinance existing debt. The Woodlands, Texas-based provider of oil and gas compression and related services is offering $600 million senior unsecured notes due 2033 with a 6.5 percent interest and $600 million senior unsecured notes maturing 2035 with a 6.75 percent interest. Kodiak expects to close the offering Friday subject to customary closing conditions. “The notes will be issued at par and will be guaranteed on a senior unsecured basis by the company, its existing subsidiaries and certain of its future U.S. subsidiaries that guarantee the issuer’s revolving asset-based loan credit facility (the ABL Facility)”, it said in a statement on its website. “The issuer intends to use the net proceeds from the offering to repay a portion of the outstanding indebtedness under the ABL Facility. “In connection with such repayment, the company intends to enter into an amendment to the ABL Facility that will, among other things, reduce total commitments to $2.0 billion and extend the maturity date”. As of the end of the second quarter Kodiak had $2.6 billion in debt outstanding, mainly from the ABL Facility and senior notes due 2029. As of the period, the company had $366.4 million available from the ABL Facility, according to its quarterly report August 6. Current liabilities as of June totaled $313.32 million including $50.39 million in accounts payable. Current assets stood at $345.53 million including $5.43 million in cash and cash equivalents. Revenue for 2Q 2025 was $322.84 million, down from $329.64 million for 1Q 2025 but up from $309.65 million for 2Q 2024. Net profit landed at $39.5 million, compared to $30.41 million for the prior three-month period and $6.23 million for 2Q 2024. Earnings per share of

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USA Hits New Crude Oil Production Record

The U.S. hit a new crude oil production record recently, a data page on the U.S. Energy Information Administration (EIA) website showed. The data page – which displays monthly U.S. field production of crude oil, was last updated on August 29, and includes data from January 1920 to June 2025 – revealed that monthly U.S. field production of crude oil averaged 13.58 million barrels per day in June. This figure is the highest in the data set, with the second highest figure coming in October 2024, at 13.530 million barrels per day. The third highest figure in the data set was seen in April this year, at 13.466 million barrels per day. Monthly U.S. field production of crude oil has averaged 13 million barrels per day or more on 21 occasions, according to the data page. Four of these were seen in 2023, 11 came in 2024, and six were in 2025, the data page highlighted. A data page on the EIA site showing annual U.S. field production of crude oil, which was also last updated on August 29 and which includes data from 1859 to 2024, showed that annual U.S. field production of crude oil averaged 13.235 million barrels per day in 2024. Prior to this, annual U.S. field production of crude oil had never averaged 13 million barrels per day or more, the data revealed. The closest it came to an annual average of 13 million barrels per day was in 2023, at 12.943 million barrels per day, the data showed. In a market analysis sent to Rigzone recently, Antonio Di Giacomo, Financial Markets Analyst for LATAM at XS, noted that, “in June, the United States reached a new all-time high in crude oil production, hitting 13.58 million barrels per day”. “This milestone was primarily driven by increases in Texas, New

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Inside the AI-optimized data center: Why next-gen infrastructure is non-negotiable

How are AI data centers different from traditional data centers? AI data centers and traditional data centers can be physically similar, as they contain hardware, servers, networking equipment, and storage systems. The difference lies in their capabilities: Traditional data centers were built to support general computing tasks, while AI data centers are specifically designed for more sophisticated, time and resource-intensive workloads. Conventional data centers are simply not optimized for AI’s advanced tasks and necessary high-speed data transfer. Here’s a closer look at their differences: AI-optimized vs. traditional data centers Traditional data centers: Handle everyday computing needs such as web browsing, cloud services, email and enterprise app hosting, data storage and retrieval, and a variety of other relatively low-resource tasks. They can also support simpler AI applications, such as chatbots, that do not require intensive processing power or speed. AI data centers: Built to compute significant volumes of data and run complex algorithms, ML and AI tasks, including agentic AI workflows. They feature high-speed networking and low-latency interconnects for rapid scaling and data transfer to support AI apps and edge and internet of things (IoT) use cases. Physical infrastructure Traditional data centers: Typically composed of standard networking architectures such as CPUs suitable for handling networking, apps, and storage. AI data centers: Feature more advanced graphics processing units (GPU) (popularized by chip manufacturer Nvidia), tensor processing units (TPUs) (developed by Google), and other specialized accelerators and equipment. Storage and data management Traditional data centers: Generally, store data in more static cloud storage systems, databases, data lakes, and data lakehouses. AI data centers: Handle huge amounts of unstructured data including text, images, video, audio, and other files. They also incorporate high-performance tools including parallel file systems, multiple network servers, and NVMe solid state drives (SSDs). Power consumption Traditional data centers: Require robust cooling

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From Cloud to Concrete: How Explosive Data Center Demand is Redefining Commercial Real Estate

The world will generate 181 ZB of data in 2025, an increase of 23.13% year over year and 2.5 quintillion bytes (a quintillion byte is also called an exabyte, EB) created daily, according to a report from Demandsage. To put that in perspective: One exabyte is equal to 1 quintillion bytes, which is 1,000,000,000,000,000,000 bytes. That’s 29 TB every second, or 2.5 million TB per day. It’s no wonder data centers have become so crucial for creating, consuming, and storing data — and no wonder investor interest has skyrocketed.  The surging demand for secure, scalable, high-performance retail and wholesale colocation and hyperscale data centers is spurred by the relentless, global expansion of cloud computing and demand for AI as data generation from businesses, governments, and consumers continues to surge. Power access, sustainable infrastructure, and land acquisition have become critical factors shaping where and how data center facilities are built.  As a result, investors increasingly view these facilities not just as technology assets, but as a unique convergence of real estate, utility infrastructure, and mission-critical systems. Capitalizing on this momentum, private equity and real estate investment firms are rapidly expanding into the sector through acquisitions, joint ventures, and new funds—targeting opportunities to build and operate facilities with a focus on energy efficiency and scalability.

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Ai4 2025 Navigates Rapid Change in AI Policy, Education

The pace of innovation in artificial intelligence is fundamentally reshaping the landscape of education, and the changes are happening rapidly. At the forefront of this movement stand developers, policy makers, educational practitioners, and associated experts at the recent Ai4 2025 conference (Aug. 11-13) in Las Vegas, where leading voices such as Geoffrey Hinton “The Godfather of AI,” top executives from Google and U.S. Bank, and representatives from multiple government agencies gathered to chart the future of AI development. Importantly, educators and academic institutions played a central role, ensuring that the approach to AI in schools is informed by those closest to the classroom. Key discussions at Ai4 and recent educator symposia underscored both the promise and peril of swift technological change. Generative AI, with its lightning-fast adoption since the advent of tools like ChatGPT, is opening new possibilities for personalized learning, skills development, and operational efficiency. But participants were quick to note that acceleration brings good and bad consequences. On one hand, there’s excitement about practical classroom implementations and the potential for students to engage with cutting-edge technology. On the other, concerns about governance, ethics, safety, and the depth of genuine learning remain at the forefront. This urgency to “do this right” is echoed by teachers, unions, and developers who are united by the challenges and opportunities on the ground. Their voices highlight the need for agreement on education policy and associated regulations to keep pace with technological progress, create frameworks for ethical and responsible use, and ensure that human agency remains central in shaping the future of childhood and learning. In this rapidly evolving environment, bringing all stakeholders to the table is no longer optional; it is essential for steering AI in education toward outcomes that benefit both students and society. Global Context: America, China, and the AI Race

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Two Lenses on One Market: JLL and CBRE Show Data Centers in a Pinch

The two dominant real estate research houses, JLL and CBRE, have released midyear snapshots of the North American data center market, and both paint the same picture in broad strokes: demand remains insatiable, vacancy has plunged to record lows, and the growth of AI and hyperscale deployments is reshaping every aspect of the business. But their lenses capture different angles of the same story: one emphasizing preleasing and capital flows, the other highlighting hyperscale requirements and regional shifts. Vacancy Falls Through the Floor JLL sets the stage with a stark headline: colocation vacancy is nearing 0%. The JLL Midyear 2025 North America Data Center report warns that this scarcity “is constraining economic growth and undermining national security,” underscoring the role of data centers as critical infrastructure. CBRE’s North American Data Center Trends H1 2025 numbers back this up, recording an all-time low North America vacancy rate of 1.6%, the tightest in more than a decade. Both agree that market loosening is years away — JLL projecting vacancy hovering around 2% through 2027, CBRE noting 74.3% of new capacity already spoken for. The takeaway seems clear: without preleasing, operators and tenants alike are effectively shut out of core markets. Absorption and Preleasing Drive Growth JLL drills down into the mechanics. With virtually all absorption tied to preleasing, the firm points to Northern Virginia (647 MW) and Dallas (575 MW) as the twin engines of growth in H1, joined by Chicago, Austin/San Antonio, and Atlanta. CBRE’s absorption math is slightly different, but the conclusion aligns: Northern Virginia again leads the nation, with 538.6 MW net absorption and a remarkable 80% surge in under-construction capacity. CBRE sharpens the view by noting that the fiercest competition is at the top end: single-tenant requirements of 10 MW or more are setting pricing records as hyperscalers

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Data Center Frontier Trends Summit 2025: AI, Power Constraints, and Moonshots Take the Stage in Reston

Aug. 28, RESTON, Va. — It’s the last day of the second-annual Data Center Frontier Trends Summit, marking the conclusion of a gathering of significant players in the data center world and their customers, all of whom are looking to get a better handle on the data center industry as it grapples with AI-fueled power demands, grid constraints, and an urgent need for infrastructure innovation. Taking place in the heart of Northern Virginia’s Data Center Alley, acknowledged as the world’s premier data center hotspot, the conference in Reston, VA saw a significant increase in attendance in its second year, going from just over 300 attendees in its inaugural year to close to five hundred attendees this year. Not unexpected, many of the attendees were newcomers to the event, attracted by the strong list of speakers focused on critical topics to the industry, with an emphasis on power and artificial intelligence. Many conversation with the attendees had them identifying specific topics that were primary motivators to attend, while one attendee simply told us “after reading the presentation descriptions and the speakers list, how could we not attend?” From the opening keynote “Playbook Interrupted” presented by Chris Downie, CEO of Flexential, the tone and message of the conference was made clear. Touching on topics such as AI’s insatiable resource appetite, tightening energy policies, and power scarcity, Chris made it clear that todays’ data centers are breaking old frameworks and demanding new strategies for growth and resilience. The message was clear; times have changed and industry executives needed to be ready to change with them. Staying ahead of the curve was going to be more difficult, but just as important. It was tyime to develop a new playbook for your business operations. Getting to the Core of It With the demand for AI centric

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NTT Data, Google Cloud Forge Alliance to Expand AI, Cloud Modernization

The partnership is designed to accelerate development of repeatable, scalable solutions, according to reps. NTT Data’s GenAI framework called “Takumi” is at the heart of this development, designed to help clients move from idea to deployment by integrating with Google Cloud’s AI stack supporting rapid prototyping and GenAI use-case creation. This initiative expands NTT Data’s Smart AI Agent Ecosystem, which unites strategic technology partnerships, specialized assets, and an AI-ready talent engine to help users deploy and manage AI at scale.  New Business Group NTT Data has established a dedicated global Google Cloud Business Group comprising thousands of engineers, architects, and advisory consultants. This team will collaborate with Google Cloud teams to help clients adopt and scale AI-powered cloud technologies. The company also is investing in training and certification programs so teams across sales, presales, and delivery can sell, migrate, and implement AI-powered cloud solutions. NTT Data says it will certify 5,000 engineers in Google Cloud technology, a step that underscores the scale of resources both firms are committing to meet surging enterprise demand. Both companies are co-investing in global sales and go-to-market campaigns designed to fast-track adoption across priority industries. A Landmark Moment for NTT—and the Industry Marv Mouchawar, Head of Global Innovation at NTT Data, said the partnership is a significant milestone in the company’s mission to drive innovation and digital transformation across industries. “By combining NTT Data’s deep expertise in AI, cloud-native modernization and enterprise solutions with Google Cloud’s advanced technologies, we are helping businesses accelerate their AI-powered cloud adoption globally and unlock new opportunities for growth,” she noted. For the data center industry, this partnership is notable not just as a technology alignment but as a signal of where digital infrastructure is headed. Hyperscale cloud providers continue to expand their reach through partnerships with major service providers,

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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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