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LNG Exports Grow at Slowest Pace Since 2015, Data Show

Global liquefied natural gas exports grew at the slowest pace since 2015, threatening to keep prices elevated until new supply comes online to meet rising demand. Annual LNG shipments are set to rise 0.4% to roughly 414 million tons this year, according to data compiled by Kpler. Delays to US projects and sanctions against Russia’s newest […]

Global liquefied natural gas exports grew at the slowest pace since 2015, threatening to keep prices elevated until new supply comes online to meet rising demand.

Annual LNG shipments are set to rise 0.4% to roughly 414 million tons this year, according to data compiled by Kpler. Delays to US projects and sanctions against Russia’s newest facility curbed new supply into the market.

The LNG market has been finely balanced since the 2022 invasion of Ukraine cut Russian pipeline gas to Europe, forcing the continent to depend more on the super-chilled fuel. The lack of new exports has made the market susceptible to price spikes for buyers in Europe and Asia.  

The market could find some relief in 2025 as new US projects ramp up production and another facility starts in Canada. Venture Global LNG Inc.’s Plaquemines plant exported its first shipment last week, and Cheniere Energy Inc.’s Corpus Christi plant began production from the first phase of its expansion on Monday.

The US was the world’s largest exporter, shipping a record 87 million tons in 2024, roughly on par with the previous year, Kpler data showed.

China was the biggest LNG buyer for the second year in a row. The country received over 78 million tons, up 8.5% year-over-year, according to the data. That’s still slightly lower than 2021, when China imported about 80 million tons.



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CoreWeave brings Nvidia Vera Rubin, AI tools to its cloud services

Forge brings together experiment tracking, evaluation, agent observability, post-training, inference and model management. The platform is designed to let teams use their preferred models, frameworks and cloud environments rather than locking them into a single AI stack, CoreWeave stated. The company described Forge as a continuous AI development loop in

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Memory squeeze set to tighten through 2028, Micron says

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Cisco SD-WAN Manager hit by zero-day admin access attack

“While every configuration is affected, the practical exposure is not identical across organizations: an internet-accessible management interface presents a much more immediate risk than one isolated within a tightly controlled administrative network,” Grover said, reinforcing Cisco’s advice. Compromising the management layer can give an attacker considerably more leverage than having

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Energy Department Announces Up to $400 Million for Basic Research to Advance the Frontiers of Science

WASHINGTON—The U.S. Department of Energy (DOE) today announced its annual funding opportunity of up to $400 million to advance the frontiers of scientific knowledge and lay the foundation for future technologies and innovation. The funding delivers on President Trump’s Executive Order Restoring Gold Standard Science by supporting rigorous, transparent, and mission-driven research across DOE’s Office of Science to strengthen America’s scientific and technological leadership. “Foundational research is where the breakthroughs that shape America’s future begin,” said DOE Under Secretary for Science Darío Gil. “Through this investment, we are empowering our nation’s researchers to pursue bold ideas, push the boundaries of discovery, and build the scientific foundations for tomorrow’s technologies—strengthening America’s global leadership in science and innovation.” The funding will support research across DOE’s Office of Science and its major programs to tackle some of the nation’s greatest scientific challenges and accelerate discoveries in areas critical to America’s future. Research will span Advanced Scientific Computing Research, Basic Energy Sciences, Biological and Environmental Research, Fusion Energy Sciences, High Energy Physics, Nuclear Physics, and Isotope R&D and Production. The Notice of Funding Opportunity (NOFO), informally known as the “Open Call,” is issued annually at the beginning of each Fiscal Year (FY). It provides a vehicle for DOE’s Office of Science to solicit applications from institutions for research support in areas not covered by more specific, topical NOFOs issued by the office in FY 2027. More details about this Notice of Funding Opportunity can be found here. DOE’s Office of Science is the nation’s largest supporter of basic research in the physical sciences, funds research at hundreds of universities nationwide, and stewards 10 of DOE’s National Laboratories.

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Magnolia sells non-core South Texas assets, adds Karnes-area acreage during WildFire integration

The company disclosed the transaction as part of an operational update following the recent closing of its acquisition of WildFire Energy. Chris Stavros, Magnolia chairman, president, and chief executive officer, said integration of the WildFire assets is progressing as planned as the company works to build a larger Eagle Ford and Austin Chalk position across South Texas. Production, capital outlook Third-quarter 2026 production is expected to average 116,000-118,000 boe/d (about 42% oil), reflecting the WildFire acquisition and the impact of the divested properties, Magnolia said. Drilling and completion (D&C) capital spending for the quarter is expected to total $155-165 million. For fourth-quarter 2026, the first full quarter reflecting the WildFire acquisition, production is forecast at 159,000-161,000 boe/d with oil accounting for 49-50% of volumes. D&C spending is expected to be about $235 million. For 2027, Magnolia expects both oil production and total production to grow 4-5% from a second-quarter 2026 pro forma base of about 78,000 bo/d and 158,000 boe/d, respectively, after accounting for volumes associated with the asset sale. The company currently estimates 2027 D&C capital spending of $900-950 million, including the impact of modest oilfield service cost inflation.

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US Senate negotiators reach permitting bill deal, ending yearslong impasse

US Senate negotiators introduced bipartisan permitting legislation Sept. 30 that would accelerate federal reviews, sharply curtail the window for legal challenges to energy projects, and improve predictability for developers. The agreement is a breakthrough in the Senate, where lawmakers have struggled for years to advance permitting reform. The Bipartisan American Affordability and Jobs Act would impose a 150-day window for certain challenges to federal permitting decisions and provide greater certainty that permitted energy and infrastructure projects retain their approvals. It also would reform Clean Water Act reviews that can delay energy infrastructure, establishing more predictable environmental reviews. The changes could reduce regulatory and litigation uncertainty for interstate gas pipelines, which are often subject to both federal environmental reviews and state water-quality certifications. The four senators behind the deal—Mike Lee (R-Utah), Martin Heinrich (D-NM), Shelley Moore Capito (R-W.Va.), and Sheldon Whitehouse (D-R.I.)—said the agreement also addresses high-profile electricity issues by expanding federal authority over transmission permitting and requiring data centers to pay associated transmission costs rather than shifting them to other electricity customers. The bill, released after months of negotiations, still faces hurdles. Senate negotiators reached an agreement on the legislative text, but Democrats also want assurances that wind and solar projects would benefit from the same streamlining and clarity from the Trump administration on what it means to return wind and solar permitting to “regular order,” issues that remain unresolved. The Senate would consider amendments before voting on the legislation. The target is a vote after the Nov. 3 midterm elections, with Capito noting the permitting bill could be the first vote when the Senate returns. The House has passed its own permitting legislation, the SPEED Act. While both bills would streamline federal permitting and limit litigation, they take different approaches to reforming NEPA, and the Senate legislation addresses transmission

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MRPL refinery fire at coker-adjacent plant kills one, injures another

Oil & Natural Gas Corp. Ltd. subsidiary Mangalore Refinery and Petrochemicals Ltd. (MRPL) reported one fatality and one injury after a fire at its refinery in Karnataka, Mangalore, India, on Sept. 30. The incident began at about 12:20 p.m. local time when a high-pressure cold separator ruptured in the refinery’s delayed coker gas oil hydrotreater unit, or coker heavy gas oil hydrotreating unit, MRPL said in separate regulatory filings to BSE Ltd. The company isolated the affected unit’s battery limits and deployed emergency response and firefighting teams. MRPL said the fire was brought under control and completely extinguished by 2:47 p.m. local time. During subsequent combing and inspection operations following the fire’s full extinguishing, personnel found the body of one deceased individual at the affected plant. A second person sustained burn injuries and was receiving hospital treatment, the company said. MRPL issued its first update while firefighting operations were continuing. It said one minor injury had been reported at that stage and that the injured person was out of danger. The company did not provide details on the identities of those involved, the cause of the separator rupture, or the extent of damage to the unit. It also did not disclose whether the incident affected broader refinery operations or production. MRPL said further verified information would be released as it becomes available.

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Dallas Fed survey: More than one in five firms plan to grow capex in 2027

The share of exploration and production (E&P) companies planning to add to their capital spending in 2027 versus this year has grown to 22% from 10% in June, a new Federal Reserve Bank of Dallas survey shows. Of the more than 80 E&P leaders in Texas, northern Louisiana, and southern New Mexico who responded to the latest Dallas Fed Energy Survey earlier this month, a third said their oil production has increased over the past 3 months and only 1 in 8 said they’re pumping less oil. On the capex side, 46% said their spending this quarter was up from this year’s second quarter. Both of those data points were down slightly from the Fed’s June poll. What appears to be changing more substantially on the ground in the Permian basin, Eagle Ford, and other areas in the Dallas Fed’s footprint are expectations about 2027 spending. Only 5% of E&P leaders now expect they’ll trim capex next year while 73% said they’ll keep spending level. Three months ago, those figures were 10% and 81%, respectively. That means 22% of executives now think their capex will climb in 2027 compared to less than 10% 3 months ago. And it suggests that production in the region will climb from here as producers look to take advantage of consistently high prices for their products—even if they’ve retreated from their recent highs. Jon Costello, an analyst at HFI Research, said an industry response—with Texas firms in the vanguard—to higher prices similar to how it recovered starting in late 2016 would grow total US production more than 4% to about 14.4 million b/d.

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EIA: US crude oil inventories up 900,000 bbl

US crude oil inventories for the week ended Sept. 25, excluding the Strategic Petroleum Reserve, increased by 900,000 bbl from the previous week, according to data from the US Energy Information Administration (EIA). At 427.3 million bbl, US crude oil inventories are 2% above the 5-year average for this time of year, the EIA report indicated. Gasoline output averaged 9.5 million b/d, and distillate production decreased to 5.0 million b/d. Propane-propylene inventories increased 1.8 million bbl, 20% above the 5-year average. Total commercial petroleum inventories decreased by 7 million bbl for the week. Distillate inventories decreased 2.3 million barrels, 14% below the five-year average. US crude oil refinery inputs averaged 16.3 million b/d for the week ended Sept. 25, which was 554,000 b/d less than the previous week’s average. Refineries operated at 92.5% of capacity. Crude oil imports decreased 179,000 million b/d to 5.7 million b/d. The 4-week average of 6.4 million b/d is 4.8% above the year-ago level. Gasoline imports averaged 500,000 b/d; distillate imports averaged 153,000 b/d. Over the past four weeks, total product supplied averaged 20.8 million b/d, up 2.1% year over year. The 4-week average for gasoline product supplied increased 0.3% year over year to 8.7 million b/d, while the 4-week average for distillate product supplied increased 5.2% to 3.8 million b/d. The 4-week average for jet fuel product supplied increased 6.5% year over year.  

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Data Center Private Power: Who Regulates Behind-the-Meter Generation?

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Data Center Thermal Management Series-Part 1 of 3

The biggest driver in today’s global economy is the data center, and in the process, data centers are generating and taking more heat than ever before. Heat — the generation of it and public concerns about it — is the most pressing issue facing the data center industry. In response, data center managers and engineers are viewing the problem in new ways, devising innovative, next-generation thermal control strategies that manage the problem more effectively. In the minds of IT managers and the public, data centers and AI are joined at the hip, along with increasing power demands and associated issues of environmental impact, water usage, and higher utility costs. As community activists, political leaders, and now even some prominent AI industry CEOs call for limits on AI development and data center construction, it’s imperative that the data center industry better manage the heat they’re producing — and taking. Sponsored Resources: Texas Instruments’ portfolio of data center thermal management systems spans the full coolant path. It’s been under active development at TI for decades and has evolved in response to the rising power, computing demands, and complexity of advanced data centers. Traditional thermal management techniques can’t keep up with AI’s intense computing requirements. For decades, air cooling was sufficient. Fans blew cool air across hot components and carried heat away, keeping data centers and AI servers operating reliably. But with AI training and inference pushing rack power beyond 20kW to 40kW, air alone can no longer remove heat quickly enough. In addition, air cooling is noisy and consumes too much energy. AI server racks are coming online now that draw 100kW of power, and they’re on their way to more than a megawatt in a few years. Each generation of servers grows denser, more powerful, and hotter as they move and compute massive volumes

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LiquidStack unveils liquid-cooling platform targeting AI data centers

“Operators need cooling infrastructure that can adapt as GPU platforms and rack densities evolve,” said Scott Smith, general manager of LiquidStack, in a statement. “CDU 2.X combines the performance and flexibility customers need today with the headroom to prepare for what comes next, allowing them to configure cooling around their facility and deployment strategy rather than designing the facility around the CDU.” A key feature is the platform’s support for different deployment configurations, including end-of-row and rack-adjacent installations. The idea is to give data center operators more flexibility in how they place their equipment with increasingly high thermal loads. The system offers configurable control-valve, power-feed and redundancy options, including dual-feed A/B configurations and automatic transfer switch support. These features allow operators to tailor the CDU to different facility architectures and resiliency requirements.

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If Apple returns to enterprise server game (with help from Nvidia), what market could it target?

Nvidia introduced NVLink Fusion as part of a broader effort to make its interconnect technology available to companies developing custom AI processors. The approach allows third-party silicon to be incorporated into Nvidia-oriented data center architectures, potentially extending Nvidia’s influence beyond its own GPUs. A similar strategy is already being pursued with inference-chip developer d-Matrix. Apple also already operates specialized servers for its Private Cloud Compute system, which handles Apple Intelligence workloads that require processing beyond the user’s device. Scaling that infrastructure, however, reportedly creates bandwidth, cost, and performance challenges. A commercial AI server would allow Apple to extend its silicon strategy into the data center while giving customers direct access to Apple processors rather than Apple’s own cloud services.

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From Coal to Compute: How Pennsylvania Is Rebuilding Power for AI Data Centers

Western Pennsylvania is becoming a test bed for one of the most consequential changes underway in data center development: the migration from simply finding grid capacity to building the power supply along with the data center. Two projects illustrate that transition particularly well. Aligned Data Centers is advancing the roughly $10 billion, 2-GW Project Phoenix campus at the former Bruce Mansfield coal-fired power station site in Shippingport, Beaver County. About 60 miles to the east, the former Homer City Generating Station is being transformed into the Homer City Energy Campus, centered on as much as 4.4 GW of new natural-gas generation and a proposed Amazon Web Services campus that could ultimately include 39 data center buildings. The projects share a number of similarities. Both reuse former coal-generation properties. Both already possess much of the infrastructure that greenfield data center developers spend years trying to obtain: high-voltage transmission, industrial zoning, water infrastructure, pipeline access, large parcels and proximity to the Marcellus and Utica natural-gas fields.But technically and commercially, they are also very different. Project Phoenix is essentially a data-center-led development using behind-the-meter generation, supplemented by a separate plan to repower the former coal station. While Homer City is the reverse: a power-generation project being constructed first, with the hyperscale data center development forming around the available power supply. This isn’t a competition, but it is a comparison on speed of delivery and the issues both development models face. Project Phoenix: Aligned Moves Into Pennsylvania Aligned calls Shippingport its first Pennsylvania campus and a regional flagship. The company formally broke ground on Project Phoenix on September 10, 2026, describing it as a 2-GW campus spanning three data center facilities and representing roughly $10 billion in regional investment. Aligned estimates the development will support approximately 3,000 construction jobs and 640 full-time jobs in

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OpenStack Hibiscus adds DNS security features and confidential computing to the open-source cloud platform

Type-5 support is aimed at data center integration. “It lets the tenant network prefixes be advertised directly into the physical fabric, so that really that’s basically how modern data center networks are built,” Carrez explained. “So really helps OpenStack fit into those environments without extra gateway layers that we’ve seen in use before.” Routable tenant addresses: The OVN BGP integration gains a route leaking option. An operator turns it on with the leak_routes attribute of a subnet. The extended OVN features follow the same approach. “OVN BGP features that let the tenant addresses be routable directly from the underlay, and that again is exposing how modern data centers are built directly into OpenStack,” Carrez said. Lower memory use: In deployments that use Open vSwitch, a monitoring daemon tracked keepalived state changes for HA routers. Hibiscus replaces the daemon with a shell script. The change applies to every HA router, so the savings add up across a deployment. “The 15 times reduction in memory footprint for the high availability router monitoring is, I think, really interesting,” Carrez said.

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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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