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Eni Raises Gas Supply for Ivorian Power

Eni SpA has increased its natural gas supply for Côte d’Ivoire’s electricity generation with new capacity unlocked in the offshore Baleine field. “The gas produced – up to 70 million cubic feet per day – will be entirely allocated to meet local demand, ensuring a reliable supply for the country’s power generation needs and further reinforcing […]

Eni SpA has increased its natural gas supply for Côte d’Ivoire’s electricity generation with new capacity unlocked in the offshore Baleine field.

“The gas produced – up to 70 million cubic feet per day – will be entirely allocated to meet local demand, ensuring a reliable supply for the country’s power generation needs and further reinforcing Côte d’Ivoire’s role as a regional energy hub”, the Italian energy major said in an online statement Wednesday.

Baleine has also reached its oil production plateau of 60,000 barrels per day (bpd), compared to 20,000 bpd in the first phase.

Eni noted, “Baleine is the first net-zero upstream project (Scope 1 and 2) in Africa, a milestone made possible by advanced technologies to reduce its carbon footprint and innovative initiatives developed in close cooperation with the Ivorian government”.

“These include a distribution program of locally produced improved cookstove, which has already benefited over 600,000 vulnerable people, and a project for the protection and restoration of 14 classified forests, contributing to the project’s overall carbon neutrality”, the company added.

Phase 2 started production late last year, raising Baleine’s capacity to 70 million cubic feet of associated gas per day (MMcfd).

Phase 2 uses floating production, storage and offloading vessel Petrojarl Kong. It also has floating storage and offloading unit Yamoussoukro for oil export. Meanwhile gas is supplied to the Ivorian market via a pipeline built for phase 1.

Announcing the start-up of phase 2 on December 28, 2024, Eni also said then phase 3 was under study and expected to further grow Baleine’s output to 150,000 bpd of oil and 200 MMcfd of associated gas.

Baleine is one of the Ivory Coast’s two biggest hydrocarbon discoveries, along with Calao, according to Eni.

On September 1, 2021, it declared Baleine as the nation’s first commercial hydrocarbon discovery since 2001. Eni put Baleine’s preliminary estimates at 1.5 to two billion barrels of oil in place and 1.8 trillion cubic feet (Tcf) to 2.4 Tcf of associated gas.

On March 7, 2024, Eni announced the Calao field discovery. With potential resources of one to 1.5 billion barrels of oil equivalent, it is the second-biggest hydrocarbon discovery in the country according to Eni.

With the recent awarding of four offshore exploration blocks, Eni now operates 10 blocks in Ivorian waters. The four new blocks are CI-504, CI-526, CI-706 and CI-708, Eni said November 28, 2024.

Of the six older blocks, CI-101 holds Baleine, while Calao is part of block CI-205. The other four are CI-401, CI-501, CI-801 and CI-802.

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Google Cloud partners with mLogica to offer mainframe modernization

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TotalEnergies Invests $172 Million in 6 German Battery Storage Projects

TotalEnergies SE has announced an investment outlay of EUR 160 million ($172.34 million) for 6 battery energy storage system projects under construction in Germany. The projects have a combined capacity of 221 megawatts (MW). They are being developed by Kyon Energy, acquired by the French energy major last year. Construction started at the end of 2024 and commissioning is planned for early 2026, according to TotalEnergies. “The launch of these projects marks a major milestone in TotalEnergies’ development of battery energy storage capacity in Germany, where the Company has operations in the production, trading, aggregation and commercialization of clean firm power”, TotalEnergies said in a press release. “This storage capacity will allow TotalEnergies to contribute to the resilience of the German power system, by reducing congestion and adding flexibility in order to quickly boost the country’s renewables sector”. TotalEnergies said it has 2 gigawatts of storage capacity under development and 321 MW under construction in Germany. “The implementation and integration of all these battery projects will allow us to supply our customers with clean firm power, contributing directly to our targeted 12 percent profitability in this activity”, commented chair and chief executive Patrick Pouyanné. In Germany, TotalEnergies expects to have 7 GW of onshore wind and solar in development and 200 MW of installed or under construction after the completion of its acquisition of VSB Group. Announcing the EUR 1.57 billion purchase from Swiss asset manager Partners Group on December 4, 2024, TotalEnergies noted, “VSB has over 475 MW of renewable capacity in operation or under construction mainly in Germany and France, and a pipeline of 18 GW of wind, solar and battery storage technologies mainly across Germany, Poland and France”. “This transaction will strengthen TotalEnergies Integrated Power value chain in Germany, which represents half of VSB’s portfolio”, TotalEnergies said then.

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Reservoir Group’s smarter, more cost effective approach to well data collection

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E&Ps Flag ‘Uncertainty’ in Latest Dallas Fed Energy Survey

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Uganda-Tanzania Oil Pipeline Secures First Tranche of External Financing

A Uganda-Tanzania petroleum pipeline project majority-owned by TotalEnergies SE has secured the first tranche of external syndicated financing. The group of backers include regional banks African Export Import Bank, Standard Bank of South Africa Ltd., Stanbic Bank Uganda Ltd., KCB Bank Uganda and Islamic Corporation for the Development of the Private Sector (ICD), the project joint venture EACOP Ltd. said in an online statement. EACOP did not disclose any amount. The East African Crude Oil Pipeline will transport up to 246,000 barrels a day from the Lake Albert oilfields in Uganda to the port of Tanga, Tanzania, for export to the global market, according to EACOP. The funding “demonstrates the support of financial institutions on this transformative regional infrastructure”, it said. Construction was more than 50 percent complete at the end of last year, EACOP said, noting over 8,000 Ugandan and Tanzanian citizens are employed for the project. Construction started last year and is expected to take 2 years to complete, according to EACOP. Besides a 1,443-kilometer (896.63 miles), 24-inch buried pipeline, the project will also install 6 pumping stations, 2 pressure reduction stations and a marine export terminal with a 3-megawatt solar plant, according to EACOP. Early last year TotalEnergies, which owns 62 percent of EACOP, said it had commissioned an assessment of its land acquisition process for the pipeline project and an associated oil development project, following allegations by an interfaith organization that the French energy giant failed to protect hundreds of graves. “As the land acquisition process draws to a close, this mission will evaluate the land acquisition procedures implemented, the conditions for consultation, compensation and relocation of the populations concerned, and the grievance handling mechanism”, TotalEnergies said in a press release January 4, 2024. “It will also assess the actions taken by TotalEnergies EP Uganda and

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EVOL X Scottish Enterprise: It’s high tide time for Scotland’s energy mix

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Unlocking Scotland’s tidal energy potential

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Airtel connects India with 100Tbps submarine cable

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Former Arista COO launches NextHop AI for customized networking infrastructure

Sadana argued that unlike traditional networking where an IT person can just plug a cable into a port and it works, AI networking requires intricate, custom solutions. The core challenge is creating highly optimized, efficient networking infrastructure that can support massive AI compute clusters with minimal inefficiencies. How NextHop is looking to change the game for hyperscale networking NextHop AI is working directly alongside its hyperscaler customers to develop and build customized networking solutions. “We are here to build the most efficient AI networking solutions that are out there,” Sadana said. More specifically, Sadana said that NextHop is looking to help hyperscalers in several ways including: Compressing product development cycles: “Companies that are doing things on their own can compress their product development cycle by six to 12 months when they partner with us,” he said. Exploring multiple technological alternatives: Sadana noted that hyperscalers might try and build on their own and will often only be able to explore one or two alternative approaches. With NextHop, Sadana said his company will enable them to explore four to six different alternatives. Achieving incremental efficiency gains: At the massive cloud scale that hyperscalers operate, even an incremental one percent improvement can have an oversized outcome. “You have to make AI clusters as efficient as possible for the world to use all the AI applications at the right cost structure, at the right economics, for this to be successful,” Sadana said. “So we are participating by making that infrastructure layer a lot more efficient for cloud customers, or the hyperscalers, which, in turn, of course, gives the benefits to all of these software companies trying to run AI applications in these cloud companies.” Technical innovations: Beyond traditional networking In terms of what the company is actually building now, NextHop is developing specialized network switches

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Microsoft abandons data center projects as OpenAI considers its own, hinting at a market shift

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PEAK:AIO adds power, density to AI storage server

There is also the fact that many people working with AI are not IT professionals, such as professors, biochemists, scientists, doctors, clinicians, and they don’t have a traditional enterprise department or a data center. “It’s run by people that wouldn’t really know, nor want to know, what storage is,” he said. While the new AI Data Server is a Dell design, PEAK:AIO has worked with Lenovo, Supermicro, and HPE as well as Dell over the past four years, offering to convert their off the shelf storage servers into hyper fast, very AI-specific, cheap, specific storage servers that work with all the protocols at Nvidia, like NVLink, along with NFS and NVMe over Fabric. It also greatly increased storage capacity by going with 61TB drives from Solidigm. SSDs from the major server vendors typically maxed out at 15TB, according to the vendor. PEAK:AIO competes with VAST, WekaIO, NetApp, Pure Storage and many others in the growing AI workload storage arena. PEAK:AIO’s AI Data Server is available now.

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SoftBank to buy Ampere for $6.5B, fueling Arm-based server market competition

SoftBank’s announcement suggests Ampere will collaborate with other SBG companies, potentially creating a powerful ecosystem of Arm-based computing solutions. This collaboration could extend to SoftBank’s numerous portfolio companies, including Korean/Japanese web giant LY Corp, ByteDance (TikTok’s parent company), and various AI startups. If SoftBank successfully steers its portfolio companies toward Ampere processors, it could accelerate the shift away from x86 architecture in data centers worldwide. Questions remain about Arm’s server strategy The acquisition, however, raises questions about how SoftBank will balance its investments in both Arm and Ampere, given their potentially competing server CPU strategies. Arm’s recent move to design and sell its own server processors to Meta signaled a major strategic shift that already put it in direct competition with its own customers, including Qualcomm and Nvidia. “In technology licensing where an entity is both provider and competitor, boundaries are typically well-defined without special preferences beyond potential first-mover advantages,” Kawoosa explained. “Arm will likely continue making independent licensing decisions that serve its broader interests rather than favoring Ampere, as the company can’t risk alienating its established high-volume customers.” Industry analysts speculate that SoftBank might position Arm to focus on custom designs for hyperscale customers while allowing Ampere to dominate the market for more standardized server processors. Alternatively, the two companies could be merged or realigned to present a unified strategy against incumbents Intel and AMD. “While Arm currently dominates processor architecture, particularly for energy-efficient designs, the landscape isn’t static,” Kawoosa added. “The semiconductor industry is approaching a potential inflection point, and we may witness fundamental disruptions in the next 3-5 years — similar to how OpenAI transformed the AI landscape. SoftBank appears to be maximizing its Arm investments while preparing for this coming paradigm shift in processor architecture.”

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Nvidia, xAI and two energy giants join genAI infrastructure initiative

The new AIP members will “further strengthen the partnership’s technology leadership as the platform seeks to invest in new and expanded AI infrastructure. Nvidia will also continue in its role as a technical advisor to AIP, leveraging its expertise in accelerated computing and AI factories to inform the deployment of next-generation AI data center infrastructure,” the group’s statement said. “Additionally, GE Vernova and NextEra Energy have agreed to collaborate with AIP to accelerate the scaling of critical and diverse energy solutions for AI data centers. GE Vernova will also work with AIP and its partners on supply chain planning and in delivering innovative and high efficiency energy solutions.” The group claimed, without offering any specifics, that it “has attracted significant capital and partner interest since its inception in September 2024, highlighting the growing demand for AI-ready data centers and power solutions.” The statement said the group will try to raise “$30 billion in capital from investors, asset owners, and corporations, which in turn will mobilize up to $100 billion in total investment potential when including debt financing.” Forrester’s Nguyen also noted that the influence of two of the new members — xAI, owned by Elon Musk, along with Nvidia — could easily help with fundraising. Musk “with his connections, he does not make small quiet moves,” Nguyen said. “As for Nvidia, they are the face of AI. Everything they do attracts attention.” Info-Tech’s Bickley said that the astronomical dollars involved in genAI investments is mind-boggling. And yet even more investment is needed — a lot more.

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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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