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Petronas Starts Production in Bindu Field

Malaysia’s Petroliam Nasional Berhad (Petronas) has produced the first hydrocarbons from the Bindu field, located 210 kilometers (136 miles) off the coast of Terengganu. The project is under Petronas Carigali Sdn. Bhd., which became operator of the Gas Production Sharing Contract (GPSC) April 1, 2025. The Bindu field development includes a new wellhead platform linked […]

Malaysia’s Petroliam Nasional Berhad (Petronas) has produced the first hydrocarbons from the Bindu field, located 210 kilometers (136 miles) off the coast of Terengganu.

The project is under Petronas Carigali Sdn. Bhd., which became operator of the Gas Production Sharing Contract (GPSC) April 1, 2025.

The Bindu field development includes a new wellhead platform linked to the Guntong E production hub through a 62-kilometer (38.5-mile) pipeline. Both the topside and substructure were built locally, designed to operate without personnel, and powered by a solar energy system, Petronas said in a media release.

This project represents the last greenfield development under the current GPSC terms, with the field expected to reach a peak production of 75 million standard cubic feet a day of gas from two wells, Petronas said.

Petronas Carigali operates the field with a 50 percent participating interest in the GPSC. ExxonMobil Exploration and Production Malaysia Inc. holds the remaining stake.

“This first hydrocarbon production establishes Petronas Carigali’s operational readiness as GPSC operator. It demonstrates our technical expertise, accelerates domestic gas monetization, and most importantly, ensures maximum value from Malaysia’s resources for the nation”, Hazli Sham Kassim, Chief Executive Officer of Petronas Carigali, said.

“The GPSC operations supply nearly half of Peninsular Malaysia’s gas demand, powering both industrial-scale power plants and small-to-medium enterprise manufacturers through our existing infrastructure”, he added.

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GasBuddy Reveals 2025 Labor Day USA Gasoline Price Forecast

In a statement posted on its website on Tuesday, GasBuddy, which describes itself as North America’s trusted fuel savings platform for more than 25 years, announced the release of its 2025 Labor Day U.S. gasoline price forecast. According to that statement, GasBuddy is predicting that “average gas prices on the last summer holiday weekend of 2025 will be $3.15 per gallon, 14 cents lower than in 2024, and the lowest price at the pump since Labor Day since 2020”. “While it will be the most affordable Labor Day weekend to fill up for most in the last five years, gas prices in nearly half of all states have risen in the last month due to localized refinery outages,” GasBuddy said in that statement. “However, motorists can expect more relief to arrive in the weeks ahead as much of the nation will see the transition back to cheaper winter gasoline in mid-September,” it added. “Gasoline demand will also soon begin to fall with the conclusion of the summer as motorists take fewer road trips and as temperatures start to cool off,” GasBuddy continued. In that statement, GasBuddy highlighted that the average Labor Day gas price came in at $3.29 per gallon in 2024, $3.77 per gallon in 2023, $3.79 per gallon in 2022, $3.16 per gallon in 2021, and $2.22 per gallon in 2020. “Labor Day marks the unofficial end of summer, and when it comes to gas prices, it’s been the cheapest summer to hit the road since the pandemic, a trend that will likely continue with the potential for the national average to fall below $3 per gallon this fall,” Patrick De Haan, Head of Petroleum Analysis at GasBuddy, said in the statement.   “We’ve seen a remarkably affordable summer to hit the road with incomes up and gas

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Phoenix Energy More Than Doubles Profit

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Occidental Closes Sale of Midland Basin Gas Gathering Assets to Enterprise

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Venezuela to Deploy Ships to Oil Exporting Hub After USA Move

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Blackline Receives First Purchase Order from ADNOC

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OPEC+ May Unwind 1.65MM Bpd of Cuts at Next Meeting, Analyst Warns

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HPE extends Juniper’s Mist AI to boost data center management

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Vertiv launches one-day installation package for AI data center systems

Data center infrastructure vendor Vertiv has introduced Vertiv OneCore, a fully modular data center building block design supporting AI and HPC applications intended to speed deployment of compute equipment in as little as one day. OneCore is a unified “slab-up,” factory-assembled, turnkey platform that integrates the company’s power, thermal, and IT infrastructure systems within a pre-assembled shell. Slab-up is a data center design where equipment—such as server racks and cabinets—are installed directly on a solid concrete slab floor, rather than on a raised floor system. Vertiv says the design simplifies logistics, minimizes on-site labor and complexity, and supports consistent quality, cost, and schedule outcomes. Vertiv Unify, which assists Vertiv cooling, UPS, and power management equipment to connect to building and data center management, provides integrated system visibility and centralized management. 

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Nvidia turns to software to speed up its data center networking hardware for AI

Typically chunks of AI tasks are distributed across GPUs, which then coordinate to provide a unified output. Adaptive routing ensures the network and GPUs over long distances are in sync when running AI workloads, Shainer said. Jitter bugs “If I retransmit the packet, I create jitter, which means one GPU out of many will be delayed and all the others have to wait for that GPU to finish,” Shainer said. The congestion control improvements remove bottlenecks by balancing transmissions across switches. Nvidia tested XGS algorithms in its server hardware and measured a 1.9x improvement in GPU-to-GPU communication compared to off-the-shelf networking technology, executives said during a briefing on the technology. Cloud providers already have long-distance high-speed networks. For example, Google’s large-scale Jupiter network uses optical switching for fast communications between its AI chips, which are called TPUs. It is important to separate the physical infrastructure from the software algorithms like XGS, Shainer said.

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Fluke Networks expands testing to help ease data center networking challenges

High-density fiber connections amplify contamination risks The shift toward higher-density fiber connections has significantly complicated contamination control. Modern array connectors can house up to 24 individual fibers within a single connection point. In contrast, traditional duplex connections contained just two fibers. “The slightest little bit of dust on one of those nine micron wide fibers, which, by the way, is much smaller than a human hair, the slightest little bit of dust on any one of the 24 in that connector, and it’s not going to work,” Mullins explained.  The inspection and cleaning requirements extend beyond traditional fiber testing. Each kit includes cleaning and inspection capabilities. Mullins noted that many technicians take shortcuts on fiber preparation.  “Cleaning and inspecting a fiber, every time you unplug it and plug it back in, adds, like another minute worth of work. But you know what? If you don’t do it, you’re gonna pay for it down the road,” he said. Cable identification a persistent challenge In addition to the new kits, Fluke Networks is also continuing to help solve other persistent networking issues. Physical cable identification continues to plague data center operations despite advances in network management and monitoring. Fluke’s solutions address this through multiple approaches. These include tone and probe technology, remote identification systems, and active network port discovery.

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Cisco ties storage networking gear to IBM z17 mainframe

“IBM Z systems are mainframes known for their ability to handle massive transaction volumes, support large-scale databases, and provide unmatched levels of security and uptime,” wrote Fausto Vaninetti, a senior solutions engineer for data center technologies at Cisco, in a blog post about the news. “The newest in the IBM Z system family, IBM z17 is the first mainframe fully engineered for the AI age, unlocking expanded capabilities for enterprise-scale AI, such as large language models, generative AI, and accelerated inferencing. However, the performance of mainframe applications depends on the underlying storage infrastructure.” SANs play a critical role in ensuring fast, reliable, and secure access to data, Vaninetti wrote: “For mainframe environments, which leverage high-speed [Fibre Connection] FICON protocol, having a robust SAN fabric that supports these requirements is non-negotiable. A solution that combines high throughput, low latency, and enterprise-class resilience is vital to ensure seamless operations and meet stringent service-level agreement requirements.” According to Vaninetti, some standout features of the MDS 9000 Series for mainframe environments include:

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Scaling Up: Tract’s Master-Planned Land and Infrastructure Approach to Data Center Development

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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

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OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

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