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TXO Identifies Potential 3 Tcfe of Gas in San Juan Basin

TXO Partners LP said Wednesday it has identified potential natural gas of nearly three trillion cubic feet equivalent in the Mancos Shale of the San Juan Basin in the Southwestern United States. “On an oil equivalent basis, we believe this could represent as much as five times our current total reserve base”, chair and chief […]

TXO Partners LP said Wednesday it has identified potential natural gas of nearly three trillion cubic feet equivalent in the Mancos Shale of the San Juan Basin in the Southwestern United States.

“On an oil equivalent basis, we believe this could represent as much as five times our current total reserve base”, chair and chief executive Bob Simpson said in an online statement.

“The catalyst for action in developing this project is commodity price, and we anticipate strong natural gas economics ahead”.

The Fort Worth, Texas-based company holds production rights in a contiguous area of 58,500 acres in the Mancos field. It also holds water rights and an option for “key” gas gathering systems in the basin, according to TXO.

“We believe the Mancos Shale development will be a game-changer for our reserve holdings and production potential”, added Gary Simpson, president for production and development. “TXO acreage and operations reside in prime position. Offset drilling on adjoining acreage has confirmed well results. 

“Given all the important criteria—reservoir characteristics, acreage location, productivity data, and infrastructure access—we have identified a tactical 3,520-acre block as phase I for developing and monetizing reserves, representing about six percent of our current Mancos position.

“Specifically, our internal engineers estimate that this single position holds about 200 to 300 Bcf [billion cubic feet] of natural gas with 25 Bcfe estimated per drill well and has the potential to almost double our existing natural gas reserves.

“Importantly, the company’s acres for exploitation are held by production with no leasehold expiration dates.

“We expect to drill, develop, and monetize at an economically opportune time and pace”.

TXO closed higher at $17.93 on the New York Stock Exchange on Wednesday.

Last year TXO expanded with the acquisition of Williston Basin assets in Montana and North Dakota through separate transactions with Eagle Mountain Energy Partners, a portfolio company of Pearl Energy Investments, and Vendera.

With a total price of $243 million in cash plus 2.5 million common shares of TXO, the acquisitions are expected to add about 4,500 barrels of oil equivalent a day to TXO’s production. The assets are the Elm Coulee field in Montana and the Russian Creek field in North Dakota.

“This acquisition in the Elm Coulee field represents the return to a region where our team previously had success”, Simpson said in a company statement June 25, 2024, announcing the agreements. “We expect the significant oil-in-place targets, with the application of our technology, to create equity value while delivering high returns.”

“These transactions provide the right blend of low-decline rate, high margin and growth potential for TXO”, Brent Clum, president of business operations and chief financial officer, said then.

The transactions were completed August 2024, TXO confirmed in its third-quarter report published November 5, 2024.

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Tool sprawl, AI complicate enterprise network operations

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Energy Department Announces New Genesis Mission Awards to Advance Super Intelligence for Science

WASHINGTON—The U.S. Department of Energy (DOE) today announced 12 Phase II Genesis Mission project awards totaling $159 million. Building on the Genesis Mission’s growing portfolio of projects, first announced in July, these Phase II project awards will unleash scientific discoveries with Super Intelligence (SI). President Trump launched the Genesis Mission in November 2025 to accelerate discovery and strengthen U.S. leadership in science, medicine, and technology. “These projects represent a critical step in turning the promise of Super Intelligence for science into transformative scientific capability,” said DOE Under Secretary for Science Dr. Darío Gil. “The Phase II teams have already demonstrated what is possible when SI is integrated with scientific expertise, data, and computing. These awards give them the opportunity to take that work to the next level. By bringing together our National Labs, universities, and industry partners, we are building on extraordinary work already underway and accelerating the pace of discovery.” The Phase II awards are developing new, powerful capabilities to tackle the Nation’s most complex National Science and Technology Challenges. By connecting America’s leading scientists with advanced SI, supercomputing, scientific data, and DOE’s world-class research infrastructure, the Genesis Mission is strengthening U.S. leadership at the frontiers of science and technology. Awarded Projects Through DOE’s Office of Science, the 12 newly awarded projects are: Accelerating the path to commercial fusion energy via an AI-enabled digital twin platform for SPARC: Led by Commonwealth Fusion Systems, this project will build a digital twin to simulate and optimize operations of a fusion demonstration device.  Decoding the RNA Structurome to Secure AI Advantage for the Bioeconomy: Led by the University of California San Diego, the project will expand the RNA structure database five-fold for training SI models to unlock the ability to engineer resilient crops and sustainable microbes.  Lattice Quantum Chromodynamics (LQCD) at the

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Energy Department Launches Genesis Mission Graduate Fellowship to Advance American Scientific Leadership

WASHINGTON—The U.S. Department of Energy (DOE) today announced the Genesis Mission Graduate Fellowship Pilot, a new funding opportunity designed to develop the next generation of American scientists and engineers and strengthen U.S. scientific leadership. Through accelerated, four-year doctoral pathways, the program will equip domestic graduate students with critical expertise in both Super Intelligence (SI) and core scientific and engineering disciplines. The inaugural fellowship advances President Trump’s historic Genesis Mission by investing in the education, development, and retention of domestic talent needed to accelerate U.S. scientific discovery and innovation. “To secure America’s position at the forefront of global scientific innovation, we must cultivate a workforce that is fluent in both foundational sciences and advanced Super Intelligence,” said DOE Under Secretary for Science Dr. Darío Gil. “The Genesis Mission Graduate Fellowship will bridge this critical gap by combining rigorous academic training with hands-on, high-impact experiences across our National Laboratories and industry partners.” DOE will fund an inaugural group of pilot projects led by domestic doctoral-granting institutions, supporting an initial cohort of approximately 100 Ph.D. fellows. As part of their four-year doctoral pathways, fellows will complete two high-impact, hands-on research experiences—one at a DOE National Laboratory or DOE User Facility and one with an industry partner—preparing them to lead the next generation of scientific discovery and innovation. Total planned funding is up to $100 million, with $20 million in Fiscal Year 2027, and outyear funding contingent on congressional appropriations. A webinar will be held on November 4, 2026, 4:00 PM ET. Register on Zoom. For more information, please visit the DOE Office of Science Funding Opportunities page.

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U.S. Department of Energy Awards $96 Million to 67 Early Career Scientists

WASHINGTON—The U.S. Department of Energy’s (DOE) Office of Science today announced the selection of 67 early career scientists to receive a combined $96 million through the 2026 Early Career Research Program (ECRP). Today’s announcement advances President Trump’s Executive Order Restoring Gold Standard Science by supporting exceptional researchers pursuing rigorous, mission-driven research in areas critical to America’s scientific and technological leadership, including Super Intelligence (SI), fusion energy, and quantum science. “Groundbreaking science begins with empowering extraordinary people,” said DOE Under Secretary for Science Dr. Darío Gil. “These 67 early career researchers represent the very best of American ingenuity. DOE is proud to invest in their vision as they push the boundaries of knowledge and cement U.S. leadership in the technologies that will define our century.” The 2026 Early Career Research Program (ECRP) selectees represent 39 universities, 11 DOE National Laboratories and Office of Science User Facilities, and 26 states. By investing in exceptional researchers at a pivotal stage in their careers, ECRP empowers the next generation of STEM leaders to pursue bold, innovative research that drives DOE’s mission and ensures America continues to lead the world in science and innovation. Since its inception in 2010, the program has made 1,238 awards, including 797 to university researchers and 441 to DOE National Laboratory researchers. Awards to scientists at institutions of higher education are approximately $875,000 over five years, while awards to scientists at DOE National Laboratories or Office of Science User Facilities are approximately $2,750,000 over five years. Information about the 67 selectees and their research projects is available on the Office of Science Awards page. Profiles of previous award recipients, including information about how the program helped advance their research and careers, are available on the Early Career Program profiles page. Selection for award negotiations is not a commitment by DOE

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National Hydrogen and Fuel Cell Day 2026: Celebrating the “Swiss Army Knife” of the Periodic Table

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Rompetrol targets 2028 startup for two refinery solar projects

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Equinor discovers gas at Gullfaks South

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DCF Global: Five Markets Redrawing the AI Infrastructure Map

The Global Constraint Is Execution These five markets demonstrate that the worldwide AI infrastructure buildout is no longer organized around a single development model. Spain is using permitting reform to attract investment. China is concentrating construction around energy resources. India is translating enormous capital commitments into an expanding development pipeline. Latin America is combining hyperscale growth with national industrial objectives. And Southeast Asia is creating interconnected infrastructure markets whose boundaries increasingly extend beyond individual cities and countries. Not every market is competing for the same business. Sovereign cloud services, enterprise applications, AI training clusters, and large-scale inference platforms carry different requirements involving power, connectivity, latency, data residency, and operating economics. But the infrastructure questions remain remarkably consistent. Can a project obtain enough electricity? Can transmission and supporting networks be delivered on schedule? Will the supply chain provide the required equipment? Can the facility be constructed and commissioned efficiently? And will the development retain the regulatory certainty and community acceptance required to operate for decades? The gap between announced development and actual capacity is becoming a defining measurement of the industry. Cushman & Wakefield estimates that Asia-Pacific alone had approximately 26.5 GW of data center capacity in its development pipeline during H1 2026. Of that total, roughly 4.8 GW was under construction, with another 21.7 GW in planning. Those figures reveal both the extraordinary scale of the opportunity and the considerable infrastructure work still required to realize it. What the Global Buildout Means for North America For U.S. data center operators, developers, engineering firms, equipment suppliers, and investors, international expansion is not a separate story. It is increasingly part of the same global competition for capital, equipment, power infrastructure, and specialized expertise. The transformers, switchgear, generators, advanced cooling systems, fiber networks, and electrical distribution equipment required by a major AI campus

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Bidding war over key component could eliminate third hard disk maker

What if the three remaining hard disk manufacturers became two? Seagate Technology and Western Digital control 90% of the market, according to market researcher TrendForce, with Toshiba picking up the crumbs. Seagate and WD both make their own magnetic drive heads, but Toshiba relies on a third party, TDK, which also sells to Seagate and WD when they need extra capacity. Seeking to guarantee supplies of this critical component, Toshiba made a bid for TDK’s drive head business earlier this year, according to Bloomberg. Concerned that this could affect its ability to meet the growing demand for hard disks from AI data centers, Seagate made a counteroffer, Bloomberg reported. TDK is staying mum.

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Oracle reportedly lands $7B GPU deal for Tencent

Oracle has reportedly signed a five-year, $7 billion agreement to provide Chinese technology conglomerate Tencent with access to roughly 100,000 advanced AI accelerators deployed in Oracle data centers across Southeast Asia, helping Tencent to sidestep restrictions on advanced AI equipment.  The deal, first reported by the Financial Times, would represent Tencent’s largest overseas cloud commitment with a U.S. provider. Neither Oracle nor Tencent has publicly confirmed the agreement or disclosed the specific AI processors involved. Under the reported terms, Tencent would pay about 30% of the contract value upfront—roughly $2.1 billion—with the remainder paid over the five-year term. That would give Oracle a substantial source of upfront funding for the expensive data center infrastructure required to build out the infrastructure.

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NVIDIA’s DSX Ready Brings Power and Cooling Into the AI Factory Blueprint

NVIDIA is extending its influence over AI infrastructure beyond the GPU, server rack and network, introducing qualification requirements for the power and cooling systems that increasingly determine the scale and performance of AI data centers. The company’s new NVIDIA DSX Ready program, announced September 21, establishes requirements for specific infrastructure products intended for use with NVIDIA’s DSX AI factory reference designs. Its first two categories—battery energy storage systems (BESS) and coolant distribution units (CDUs)—address two of the most pressing engineering challenges in AI infrastructure: managing rapidly changing electrical demand and removing heat from increasingly dense computing systems. The initial qualified suppliers are Hitachi Energy, LG Energy Solution and Tesla for battery storage, and LG Electronics, LiquidStack and Vertiv for liquid cooling. While the announcement might initially resemble another NVIDIA partner program, its technical details suggest something more consequential. The company is establishing performance criteria for the electrical and mechanical equipment supporting its computing platforms, connecting those requirements to an expanding ecosystem of qualified suppliers. Subsequent partner announcements offer a clearer view of what that means in practice. They describe battery systems designed to respond to AI load fluctuations, coolant distribution equipment operating at multi-megawatt capacities, and integrated cooling architectures intended to make more of a data center’s available power usable for computing. The initiative also coincides with the arrival of Chris Malone, formerly a data center infrastructure executive at OpenAI, Meta and Google, as NVIDIA’s vice president of the DSX Platform. Together, the developments point toward a closer relationship between computing architecture and facility engineering, with NVIDIA seeking to influence not only the processors deployed in AI factories but the infrastructure requirements that support their operation. From Reference Design to Infrastructure Qualification DSX Ready is an extension of the broader NVIDIA DSX AI Factory Platform, introduced in May 2026. As

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Brookfield’s AREP Deal Extends the AI Infrastructure Stack to Powered Land

The transaction goes beyond Brookfield investing in another portfolio of buildings. It is investing in a developer whose principal product increasingly begins before the building, with land, entitlements, substations, transmission access and utility capacity. PowerHouse Has Become a Gigawatt-Scale Development Platform PowerHouse was founded with a strong Northern Virginia orientation, but its development map now stretches well beyond Data Center Alley as its current portfolio includes projects in Virginia, Texas, Pennsylvania, North Carolina, Nevada, Indiana, Illinois and Kentucky. The company lists 515 MW across its Northern VA Ashburn properties, another 900 MW at its PH 95 development in Spotsylvania, 1.35 GW in Carlisle, Pennsylvania, 1.8 GW at Joliet, Illinois, and substantial campuses across multiple Texas and Indiana locations. The various projects do a good job of illustrating how the definition of a hyperscale development site is changing. At PowerHouse Arcola in Loudoun County, Virginia, PowerHouse announced a long-term hyperscale lease earlier this year. The 37-acre campus includes two planned data center buildings totaling approximately 615,000 square feet and is designed for up to 120 MW of utility capacity. PowerHouse emphasizes not only the buildings but the campus’s on-site substation, fiber access, power security and support for high-density GPU and liquid-cooled deployments. In Texas, it might be that everything really is bigger, and PowerHouse’s Grand Prairie development covers approximately 810 acres and 8.5 million developable square feet. Its project page cites maximum utility power of 1.8 GW and a development schedule extending through 2029 and beyond. The Texas development plans also include a proposed Circle T campus in Westlake outside Fort Worth, which calls for as many as four roughly 300,000-square-foot facilities totaling approximately 300 MW. According to reporting on local filings, PowerHouse has funded a 350-MW Oncor substation intended to serve the campus and the town’s pump station. The company’s development in

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AI Is Turning Energy Storage Into Active Power Infrastructure

AI Turns the Power Problem Into a Transient Problem At the heart of the issue is the changing behavior of the IT load. In a conventional data center, DeLattre said, large numbers of independent loads create a relatively predictable electrical profile. AI clusters introduce much greater synchronization. As GPUs begin processing a common workload, large numbers of accelerators can increase their power consumption simultaneously. Instead of asking the electrical infrastructure to serve a relatively smooth load, the facility can experience fast power pulses moving through the system. Hybrid supercapacitors are intended to act as a buffer between that dynamic compute load and the infrastructure supplying it. During an upward transient, storage provides some of the incremental power demanded by the IT load. When demand falls, the storage system recharges. The objective is not to create additional energy. It is to keep every upstream component — from the UPS to generators and ultimately the utility connection — from having to respond directly to every rapid change taking place inside the AI cluster. From the perspective of the upstream power source, DeLattre said, the goal is to make a highly dynamic AI load appear significantly smoother. That distinction between energy and power is central to Musashi’s argument for hybrid supercapacitors. A conventional supercapacitor, also known as an electric double-layer capacitor, can deliver very high power almost instantly but stores relatively little energy. A lithium-ion battery can store considerably more energy, but DeLattre argues that it is less suited to being aggressively charged and discharged tens or hundreds of thousands of times. Musashi’s hybrid technology uses a capacitor architecture with a lithium-doped graphite electrode intended to increase energy density while preserving the fast response and high cycling capability associated with capacitors. DeLattre reduces the distinction to a simple formulation. “Batteries are very good

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Microsoft will invest $80B in AI data centers in fiscal 2025

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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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