Oil Rebounds on Signs of US Output Decline

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Oil Rebounds on Signs of US Output Decline

Oil climbed from the lowest closing price in four years on signs that production from the US may contract in the months ahead. West Texas Intermediate advanced 3.4% to settle above $59 a barrel after tumbling more than 9% during the past six sessions. Diamondback Energy Inc., the largest independent producer in the Permian Basin, […]

Oil climbed from the lowest closing price in four years on signs that production from the US may contract in the months ahead.

West Texas Intermediate advanced 3.4% to settle above $59 a barrel after tumbling more than 9% during the past six sessions. Diamondback Energy Inc., the largest independent producer in the Permian Basin, trimmed its full-year production forecast and said it expects US shale production will drop in the coming months.

Declining US crude output would help ease the global oversupply that’s expected to form this year as OPEC and its allies bring back production at a faster-than-expected pace. Diamondback projects onshore oil rigs across the US industry will drop by almost 10% by the end of this quarter, and Chief Executive Officer Travis Stice wrote that American output is “at a tipping point.”

Meanwhile, the US cut its forecast for domestic oil production this year in a report developed prior to a weekend supply decision from OPEC and its allies, signaling that the pullback in expectations for American output is set to continue.

Oil has plunged this year as OPEC+ boosts supplies and US President Donald Trump’s trade war weighs on the outlook for demand. The cartel agreed over the weekend to a further supply boost starting in June, with Saudi Arabia warning of additional increases if overproducing members don’t fall in line.

“Given that Saudi Arabia’s preferred oil price range is near $90, its tolerance for prices around the $50 mark appears to be reaching its limit,” said Razan Hilal, a market analyst at Forex.com. “However, regaining market share through supply cut unwinds — particularly against non-OPEC producers — could help offset those losses.”

Trump said he was willing to lower tariffs on China at some point because the levies are so high that the two countries have essentially stopped doing business with each other. He added that there were no imminent plans to speak with President Xi Jinping, who is in Russia this week to showcase ties with counterpart Vladimir Putin.

Elsewhere, Oman’s foreign minister said in a social media post that the US and Iran-backed Houthis have agreed to a ceasefire in the Red Sea following tit-for-tat airport attacks in Israel and Yemen. Neither side has since confirmed. The renewed tensions come ahead of a fourth round of nuclear talks between Washington and Tehran.

Global benchmark Brent recently dipped into oversold territory on the nine-day relative strength index and pierced its lower Bollinger Bands, pointing to a market that has fallen too quickly. Chinese markets also reopened after a holiday.

Oil Prices

WTI for June delivery rose 3.4% to settle at $59.09 a barrel in New York.
Brent for July settlement advanced 3.2% to settle at $62.15 a barrel.

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India takes first big step in Quantum Computing supremacy race

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Uniper Q1 Profit Slumps

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Iberdrola Raises Quarterly Revenue to $14.6 Billion

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Welsh government completes £2m equity investment in tidal player Inyanga

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Liquid cooling technologies: reducing data center environmental impact

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Cisco unveils prototype quantum networking chip

Clock synchronization allows for coordinated time-dependent communications between end points that might be cloud databases or in large global databases that could be sitting across the country or across the world, he said. “We saw recently when we were visiting Lawrence Berkeley Labs where they have all of these data sources such as radio telescopes, optical telescopes, satellites, the James Webb platform. All of these end points are taking snapshots of a piece of space, and they need to synchronize those snapshots to the picosecond level, because you want to detect things like meteorites, something that is moving faster than the rotational speed of planet Earth. So the only way you can detect that quickly is if you synchronize these snapshots at the picosecond level,” Pandey said. For security use cases, the chip can ensure that if an eavesdropper tries to intercept the quantum signals carrying the key, they will likely disturb the state of the qubits, and this disturbance can be detected by the legitimate communicating parties and the link will be dropped, protecting the sender’s data. This feature is typically implemented in a Quantum Key Distribution system. Location information can serve as a critical credential for systems to authenticate control access, Pandey said. The prototype quantum entanglement chip is just part of the research Cisco is doing to accelerate practical quantum computing and the development of future quantum data centers. The quantum data center that Cisco envisions would have the capability to execute numerous quantum circuits, feature dynamic network interconnection, and utilize various entanglement generation protocols. The idea is to build a network connecting a large number of smaller processors in a controlled environment, the data center warehouse, and provide them as a service to a larger user base, according to Cisco. The challenges for quantum data center network fabric

Zyxel launches 100GbE switch for enterprise networks

Port specifications include: 48 SFP28 ports supporting dual-rate 10GbE/25GbE connectivity 8 QSFP28 ports supporting 100GbE connections Console port for direct management access Layer 3 routing capabilities include static routing with support for access control lists (ACLs) and VLAN segmentation. The switch implements IEEE 802.1Q VLAN tagging, port isolation, and port mirroring for traffic analysis. For link aggregation, the switch supports IEEE 802.3ad for increased throughput and redundancy between switches or servers. Target applications and use cases The CX4800-56F targets multiple deployment scenarios where high-capacity backbone connectivity and flexible port configurations are required. “This will be for service providers initially or large deployments where they need a high capacity backbone to deliver a primarily 10G access layer to the end point,” explains Nguyen. “Now with Wi-Fi 7, more 10G/25G capable POE switches are being powered up and need interconnectivity without the bottleneck. We see this for data centers, campus, MDU (Multi-Dwelling Unit) buildings or community deployments.” Management is handled through Zyxel’s NebulaFlex Pro technology, which supports both standalone configuration and cloud management via the Nebula Control Center (NCC). The switch includes a one-year professional pack license providing IGMP technology and network analytics features. The SFP28 ports maintain backward compatibility between 10G and 25G standards, enabling phased migration paths for organizations transitioning between these speeds.

Engineers rush to master new skills for AI-driven data centers

According to the Uptime Institute survey, 57% of data centers are increasing salary spending. Data center job roles that saw the highest increases were in operations management – 49% of data center operators said they saw highest increases in this category – followed by junior and mid-level operations staff at 45%, and senior management and strategy at 35%. Other job categories that saw salary growth were electrical, at 32% and mechanical, at 23%. Organizations are also paying premiums on top of salaries for particular skills and certifications. Foote Partners tracks pay premiums for more than 1,300 certified and non-certified skills for IT jobs in general. The company doesn’t segment the data based on whether the jobs themselves are data center jobs, but it does track 60 skills and certifications related to data center management, including skills such as storage area networking, LAN, and AIOps, and 24 data center-related certificates from Cisco, Juniper, VMware and other organizations. “Five of the eight data center-related skills recording market value gains in cash pay premiums in the last twelve months are all AI-related skills,” says David Foote, chief analyst at Foote Partners. “In fact, they are all among the highest-paying skills for all 723 non-certified skills we report.” These skills bring in 16% to 22% of base salary, he says. AIOps, for example, saw an 11% increase in market value over the past year, now bringing in a premium of 20% over base salary, according to Foote data. MLOps now brings in a 22% premium. “Again, these AI skills have many uses of which the data center is only one,” Foote adds. The percentage increase in the specific subset of these skills in data centers jobs may vary. The Uptime Institute survey suggests that the higher pay is motivating workers to stay in the

ExtraHop looks to eliminate ‘extra hops’ in NDR stack

This deep visibility allows ExtraHop to provide insights across the entire network stack, from basic connectivity to application-level transactions. “The benefit of going all the way through Layer 7 is I can actually see a database transaction going through on the wire,” Vasani said. “If you have application teams complaining about database query latency, we can map it to what session was that tied to and what flows was it tied to from a network perspective and is this really an app server issue, or is it a network issue, or is it an endpoint issue?” The new sensor integrates with ExtraHop’s RevealX platform, feeding telemetry into the company’s cloud-scale ML/AI engine that powers its detection and analysis capabilities. “The sensor collects the telemetry, feeds it into an ML/AI engine that sits in the cloud, and then we layer in workflow engines on top to enable the various use cases,” Vasani said. In modern distributed enterprise environments, network visibility must extend beyond traditional data centers. ExtraHop’s all-in-one sensor is designed to address this reality with deployment options that span physical appliances, virtual machines and cloud environments. ExtraHop has both virtual and physical hardware appliances for sensor deployment. ExtraHop sensors can plug into a network through multiple methods including, Network Tap, SPAN (Switched Port Analyzer) port, packet broker or a cloud provider’s vTAP capabilities.

AI’s energy appetite drives interest in nuclear power

In its new report, Deloitte said that its analysis of figures from the World Nuclear Association, the American Nuclear Society, the U.S. Department of Energy, and others showed that new nuclear power could potentially meet about 10% of the projected increase in data center demand over the next decade, assuming capacity is also significantly expanded by between 35GW and 62GW, and 30% of the expansion is earmarked for data centers. “Nuclear energy presents a potential solution for meeting some of the growing electricity demands of data centers, with its reliable and clean energy profile,” Deloitte’s report said, noting five key advantages of the technology: Reliable baseload power: Nuclear reactors operate 24/7, regardless of the weather, providing the reliable power so important to data centers. In addition, Deloitte said, “Their capacity factor, exceeding 92.5%, outperforms other sources like natural gas (56%) and renewables like wind (35%) and solar (25%).” High energy density: A small amount of fuel generates a lot of power, which minimizes the need for fuel storage and transportation. “This efficiency can translate to a smaller physical footprint and enhanced sustainability,” Deloitte said. Scalable power output: A full-sized reactor typically generates 800 megawatts (MW) or more of electricity, which accommodates the needs of large data centers. Low carbon emissions: Nuclear power plants produce virtually no greenhouse gas emissions during operation. Enhanced land use efficiency: Compared to other energy sources, nuclear power plants require relatively little land. Gartner’s Johnson echoed these advantages, and also predicted that nuclear energy, and small modular reactors (SMRs) in particular, will “provide a viable answer” to the question of what to do when electricity demand exceeds supply. They can, he said, “ensure independence from grid power fluctuations by providing dedicated on-site power for large data centers.” However, both Gartner and Deloitte also highlighted challenges in

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.

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

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

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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