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PetroChina Boasts Stable Growth in Q1 2025

PetroChina Company Limited has reported a revenue of RMB 753.11 billion ($103.5 billion) for the first quarter, with a net income of RMB 46.81 billion ($6.4 billion), up 2.3 percent year-on-year. The company said in a media release that it sustained growth in oil and gas output while bolstering momentum in new energies. It said […]

PetroChina Company Limited has reported a revenue of RMB 753.11 billion ($103.5 billion) for the first quarter, with a net income of RMB 46.81 billion ($6.4 billion), up 2.3 percent year-on-year.

The company said in a media release that it sustained growth in oil and gas output while bolstering momentum in new energies. It said it enhanced cost management in oil and gas production, as well as improved the structure of its overseas assets.

Oil and gas output rose 0.7 percent year-on-year to 467 million barrels of oil equivalent (MMboe). Domestic production rose 1.2 percent year-on-year to 418 MMboe.

Wind and solar power generation grew 94.6 percent to 1.68 billion kilowatt-hours.

The oil, gas, and new energies business reported an operating profit of RMB 46.09 billion ($6.3 billion). The company responded to market demand by advancing refining and chemical upgrades, optimizing production plans, and focusing on specialty refined products and new materials to boost high-value-added product sales, it said.

The company said it is advancing its refining and chemical operations with key projects Jilin and Guangxi Petrochemical, and Dushanzi Petrochemical Tarim Ethane-to-Ethylene.

In Q1 2025, it processed 337 million barrels of crude oil, with refined product output at 28.57 million tons. Ethylene output reached 2.27 million tons, chemical commodities totaled 9.96 million tons, and new materials surged by 37.5 percent year-on-year to 0.80 million tons.

The company’s chemicals and new materials business generated an operating profit of RMB 5.39 billion ($741.2 million), supported by improved marketing and steady market share growth. It enhanced coordination in product dispatch and inventory management, adopted flexible marketing strategies, and promoted retail sales, maximizing efficiency across the industrial chain. The company said it has also advanced non-fuel businesses and proprietary products, improved its integrated energy service network, and expanded international trade capabilities.

Natural gas marketing boosted volume and profitability by leveraging the integrated industry chain, PetroChina said. It said it optimized procurement and sales distribution, strictly controlling costs and promoting market-oriented sales. Efforts intensified to develop high-quality direct sales, industrial, and gas power customers, achieving growth in sales volume and profitability. It sold 86.44 billion cubic meters of natural gas, a 3.7 percent year-on-year increase. Domestic sales reached 69.91 billion cubic meters, up 4.2 percent year-on-year. The marketing business generated an operating profit of RMB 13.51 billion ($1.8 billion).

The company said it will advance talent empowerment, quality and efficiency enhancement, low-cost development, cultural leadership, and digital-intelligent transformation.

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Pantheon of college football gets a Wi-Fi upgrade

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The U.S. leads the world in AI (job) anxiety

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Tigera extends cloud-native networking with Calico 3.30

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Beam employees ‘devastated’ as UK offshore wind technology firm makes all staff redundant

UK offshore and subsea technology firm Beam has made more than 100 staff redundant and ceased operations, just months after rebranding from Rovco. Writing on social media, Beam head of talent acquisition and crewing James Reynolds said: “Today marks the end of Beam. “As of today, all employees have been made redundant.” Reynolds said working for Beam has been “one of the most rewarding chapters of my career”. “From the offshore crews who braved tough conditions, to the robotics and computer vision engineers pushing the boundaries of innovation, to the brilliant minds in marketing, sales, and every team in between — it has been an honour to work alongside you,” he said. Formed from a merger of Rovco and Vaarst in September last year, the company had embarked on a recruitment drive in Edinburgh and Aberdeen as part of expansion efforts. According to its most recent accounts submitted to Companies House, Rovco reported a £8.1 million loss before tax in 2023, following an £8.7m loss in 2022. In 2023, Rovco had 106 employees across offices in Bristol, Edinburgh and Aberdeen. Rovco and Vaarst Beam chief executive officer Brian Allen founded the Bristol-based remotely operated vehicle (ROV) firm Rovco in 2016, before launching AI-focused sister company Vaarst in 2021. A Rovco employee. Since launching, the two firms have raised close to £50m from investors across three funding rounds in 2019, 2022 and 2024. In May last year, Rovco pledged to create over 100 new jobs in Scotland alongside expanding to the US and Asia. Backers of the Bristol-headquartered firm included Foresight Group, Equinor, and American defence sector investor IQT. Shock at Beam redundancies Since rebranding as Beam, the company unveiled additions to its offshore fleet including the Quantum EV ROV and the Xplorer autonomous surface vessel (ASV). Beam also launched its Scout

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Masdar, OMV Eye Green Hydrogen Partnership

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JP Morgan Analysts Say Sentiment on Oil is Neutral to Optimistic

In a research note sent to Rigzone late Tuesday by Natasha Kaneva, Head of Global Commodities Strategy at J.P. Morgan, analysts at the company, including Kaneva, said “based on numerous recent discussions with institutional and corporate clients”, they “conclude that the sentiment on oil is neutral to optimistic, particularly within the corporate community”. “Many believe we are in a ‘peak Trump’ phase, suggesting that the worst is behind us and we are now entering a period of de-escalation,” the J.P. Morgan analysts stated in the research note. “There is a prevailing view that the tailwinds from trade deal announcements and the administration’s shift in focus from tariffs to taxes and deregulation will drive oil prices back into the mid-$70s following the recent downturn,” they added. In the note, the analysts said this perspective is evident in investor positioning and the term structure of oil and oil products. “Money managers increased their net-long positions in Nymex WTI to the highest level since late January last week, while short positions in Brent fell by the most since October,” they highlighted. “Brent’s prompt spread hit its strongest level since January, and open interest on Brent climbed to a new record, with Brent September $95 calls trading more than 10,000 times last Tuesday,” they added. “Additionally, the Nymex gasoline crack settled at its highest level since the start of the month, following an eight-week consecutive drop in U.S. stockpiles, and despite concerns related to demand, product cracks in the U.S. continue to remain firmly in backwardation,” they went on to state. The J.P. Morgan analysts noted in the publication that the recent de-escalation in trade talks has reduced the probability of a bear case but warned that “the ‘Trump put’ does not extend to energy, as the administration continues to prioritize lower oil prices

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IMF Lowers Growth Outlook for Gulf Oil Producers after Price Slump

The International Monetary Fund downgraded its growth forecasts for oil exporting countries in the Middle East and North Africa, including Saudi Arabia and Iraq, citing escalating global trade tensions and lower energy prices. The IMF cut the 2025 outlook for oil exporters in the region to 2.3 percent, 1.7 percentage points lower than the fund’s forecast from October. The projections were announced by the Washington based lender on Thursday in its latest regional economic outlook. The IMF expects oil prices to decline to an average of $66.9 per barrel this year, nearly $6 below the October projection. It cited strong supply growth from non-OPEC+ countries and subdued demand because of a slowing global economy. Prices for Brent crude have slumped around 15 percent this year to roughly $63 a barrel. That’s been down to the US-led trade wars and OPEC+ announcing a faster-than-expected increase in oil output. Iraq got one of the largest downgrades. The IMF now expects its gross domestic product to contract 1.5 percent this year, rather than rise 4.1 percent, as was the presumption in October. Saudi Arabia’s outlook was lowered to 3 percent from 4.6 percent. While non-oil growth is expected to be bolstered by infrastructure projects and other diversification efforts in the Gulf, the IMF says some government spending may be lowered in line with crude prices. There’s been a “recalibration of investment spending plans resulting from softer oil prices, further amplified by the decline in oil prices from the recent escalation of trade tensions,” said the IMF. All the same, the direct impact of changes in tariffs is “generally limited” on the GCC because of the tariff exemption on energy exports and the limited non-oil exports to the US, the lender said. The whole MENA region is expected to grow 2.6 percent this year, 1.4 percentage points lower than October’s

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Subsea 7 Revenue Up 10 Percent YoY

Subsea 7 S.A. has reported $1.5 billion in revenue for the first quarter (Q1), rising 10 percent compared to the corresponding period a year prior. Robust operational results in Subsea and Conventional, along with elevated activities in Taiwan’s renewables sector, helped counterbalance seasonal slowdowns and vessel upkeep, the company said. Net financing expenses amounted to $17 million, coupled with a net loss from foreign exchange of $28 million, leading to a quarterly net income of $17 million, compared to $29 million for the same period last year, the company said. Q1 order intake was $0.9 billion, including $0.4 billion in new awards and $0.5 billion in escalations, resulting in a book-to-bill ratio of 0.6 times. Backlog at the end of March was $10.8 billion, with $4.8 billion expected in 2025, $3.5 billion in 2026, and $2.5 billion in 2027 and beyond, Subsea 7 said. “Subsea7 had a good start to 2025 with solid financial performance underpinned by strong project execution, which offset a heavy vessel maintenance schedule. The group reported 10 percent revenue growth year-on-year and Adjusted EBITDA margin expansion of 380bps, putting us on track to meet full-year expectations”, John Evans, Chief Executive Officer, said. “Although uncertainty in the global economy has increased in recent months, the outlook for long-term energy demand growth remains positive. Subsea 7’s strategy to focus on long-duration developments in cost-advantaged sectors of the deepwater adds resilience to our subsea business, and our exposure to strategic gas developments, such as the Sakarya field in Türkiye, and new oil provinces such as Namibia gives us further confidence”, Evans added. “In offshore wind, we are positive about the opportunities presented by this year’s CFD allocation round in the UK, where it is expected that the volume of projects sanctioned will nearly double year-on-year. We are well-positioned in

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PetroChina Boasts Stable Growth in Q1 2025

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AI’s energy appetite drives interest in nuclear power

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Nvidia AI supercluster targets agents, reasoning models on Oracle Cloud

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Deep Data Center: Neoclouds as the ‘Picks and Shovels’ of the AI Gold Rush

In 1849, the discovery of gold in California ignited a frenzy, drawing prospectors from around the world in pursuit of quick fortune. While few struck it rich digging and sifting dirt, a different class of entrepreneurs quietly prospered: those who supplied the miners with the tools of the trade. From picks and shovels to tents and provisions, these providers became indispensable to the gold rush, profiting handsomely regardless of who found gold. Today, a new gold rush is underway, in pursuit of artificial intelligence. And just like the days of yore, the real fortunes may lie not in the gold itself, but in the infrastructure and equipment that enable its extraction. This is where neocloud players and chipmakers are positioned, representing themselves as the fundamental enablers of the AI revolution. Neoclouds: The Essential Tools and Implements of AI Innovation The AI boom has sparked a frenzy of innovation, investment, and competition. From generative AI applications like ChatGPT to autonomous systems and personalized recommendations, AI is rapidly transforming industries. Yet, behind every groundbreaking AI model lies an unsung hero: the infrastructure powering it. Enter neocloud providers—the specialized cloud platforms delivering the GPU horsepower that fuels AI’s meteoric rise. Let’s examine how neoclouds represent the “picks and shovels” of the AI gold rush, used for extracting the essential backbone of AI innovation. Neoclouds are emerging as indispensable players in the AI ecosystem, offering tailored solutions for compute-intensive workloads such as training large language models (LLMs) and performing high-speed inference. Unlike traditional hyperscalers (e.g., AWS, Azure, Google Cloud), which cater to a broad range of use cases, neoclouds focus exclusively on optimizing infrastructure for AI and machine learning applications. This specialization allows them to deliver superior performance at a lower cost, making them the go-to choice for startups, enterprises, and research institutions alike.

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Soluna Computing: Innovating Renewable Computing for Sustainable Data Centers

Dorothy 1A & 1B (Texas): These twin 25 MW facilities are powered by wind and serve Bitcoin hosting and mining workloads. Together, they consumed over 112,000 MWh of curtailed energy in 2024, demonstrating the impact of Soluna’s model. Dorothy 2 (Texas): Currently under construction and scheduled for energization in Q4 2025, this 48 MW site will increase Soluna’s hosting and mining capacity by 64%. Sophie (Kentucky): A 25 MW grid- and hydro-powered hosting center with a strong cost profile and consistent output. Project Grace (Texas): A 2 MW AI pilot project in development, part of Soluna’s transition into HPC and machine learning. Project Kati (Texas): With 166 MW split between Bitcoin and AI hosting, this project recently exited the Electric Reliability Council of Texas, Inc. planning phase and is expected to energize between 2025 and 2027. Project Rosa (Texas): A 187 MW flagship project co-located with wind assets, aimed at both Bitcoin and AI workloads. Land and power agreements were secured by the company in early 2025. These developments are part of the company’s broader effort to tackle both energy waste and infrastructure bottlenecks. Soluna’s behind-the-meter design enables flexibility to draw from the grid or directly from renewable sources, maximizing energy value while minimizing emissions. Competition is Fierce and a Narrower Focus Better Serves the Business In 2024, Soluna tested the waters of providing AI services via a  GPU-as-a-Service through a partnership with HPE, branded as Project Ada. The pilot aimed to rent out cloud GPUs for AI developers and LLM training. However, due to oversupply in the GPU market, delayed product rollouts (like NVIDIA’s H200), and poor demand economics, Soluna terminated the contract in March 2025. The cancellation of the contract with HPE frees up resources for Soluna to focus on what it believes the company does best: designing

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Quiet Genius at the Neutral Line: How Onics Filters Are Reshaping the Future of Data Center Power Efficiency

Why Harmonics Matter In a typical data center, nonlinear loads—like servers, UPS systems, and switch-mode power supplies—introduce harmonic distortion into the electrical system. These harmonics travel along the neutral and ground conductors, where they can increase current flow, cause overheating in transformers, and shorten the lifespan of critical power infrastructure. More subtly, they waste power through reactive losses that don’t show up on a basic utility bill, but do show up in heat, inefficiency, and increased infrastructure stress. Traditional mitigation approaches—like active harmonic filters or isolation transformers—are complex, expensive, and often require custom integration and ongoing maintenance. That’s where Onics’ solution stands out. It’s engineered as a shunt-style, low-pass filter: a passive device that sits in parallel with the circuit, quietly siphoning off problematic harmonics without interrupting operations.  The result? Lower apparent power demand, reduced electrical losses, and a quieter, more stable current environment—especially on the neutral line, where cumulative harmonic effects often peak. Behind the Numbers: Real-World Impact While the Onics filters offer a passive complement to traditional mitigation strategies, they aren’t intended to replace active harmonic filters or isolation transformers in systems that require them—they work best as a low-complexity enhancement to existing power quality designs. LoPilato says Onics has deployed its filters in mission-critical environments ranging from enterprise edge to large colos, and the data is consistent. In one example, a 6 MW data center saw a verified 9.2% reduction in energy consumption after deploying Onics filters at key electrical junctures. Another facility clocked in at 17.8% savings across its lighting and support loads, thanks in part to improved power factor and reduced transformer strain. The filters work by targeting high-frequency distortion—typically above the 3rd harmonic and up through the 35th. By passively attenuating this range, the system reduces reactive current on the neutral and helps stabilize

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New IEA Report Contrasts Energy Bottlenecks with Opportunities for AI and Data Center Growth

Artificial intelligence has, without question, crossed the threshold—from a speculative academic pursuit into the defining infrastructure of 21st-century commerce, governance, and innovation. What began in the realm of research labs and open-source models is now embedded in the capital stack of every major hyperscaler, semiconductor roadmap, and national industrial strategy. But as AI scales, so does its energy footprint. From Nvidia-powered GPU clusters to exascale training farms, the conversation across boardrooms and site selection teams has fundamentally shifted. It’s no longer just about compute density, thermal loads, or software frameworks. It’s about power—how to find it, finance it, future-proof it, and increasingly, how to generate it onsite. That refrain—“It’s all about power now”—has moved from a whisper to a full-throated consensus across the data center industry. The latest report from the International Energy Agency (IEA) gives this refrain global context and hard numbers, affirming what developers, utilities, and infrastructure operators have already sensed on the ground: the AI revolution will be throttled or propelled by the availability of scalable, sustainable, and dispatchable electricity. Why Energy Is the Real Bottleneck to Intelligence at Scale The major new IEA report puts it plainly: The transformative promise of AI will be throttled—or unleashed—by the world’s ability to deliver scalable, reliable, and sustainable electricity. The stakes are enormous. Countries that can supply the power AI craves will shape the future. Those that can’t may find themselves sidelined. Importantly, while AI poses clear challenges, the report emphasizes how it also offers solutions: from optimizing energy grids and reducing emissions in industrial sectors to enhancing energy security by supporting infrastructure defenses against cyberattacks. The report calls for immediate investments in both energy generation and grid capabilities, as well as stronger collaboration between the tech and energy sectors to avoid critical bottlenecks. The IEA advises that, for countries

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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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