Calumet reports delay in government loan for Montana renewable fuels plant

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Calumet reports delay in government loan for Montana renewable fuels plant

Update: The White House budget office on Wednesday, Jan. 29, rescinded an order freezing federal grants. Calumet Inc. subsidiary Montana Renewables LLC (MRL) has confirmed that the first tranche of a loan previously approved by the US Department of Energy (DOE) for expansion of a renewable fuels manufacturing plant in Great Falls, Mont., will undergo […]

Update: The White House budget office on Wednesday, Jan. 29, rescinded an order freezing federal grants.

Calumet Inc. subsidiary Montana Renewables LLC (MRL) has confirmed that the first tranche of a loan previously approved by the US Department of Energy (DOE) for expansion of a renewable fuels manufacturing plant in Great Falls, Mont., will undergo a ‘tactical delay.’

Finalized as of Jan. 10, $782 million—the first of a two-tranche loan guarantee—was expected to fund eligible expenses MRL previously incurred, upon payment of which MRL was expected to simultaneously make a $150-million equity investment with funds the operator currently holds, Calumet said earlier this month (OGJ Online, Jan. 13, 2025).

Calumet said Jan. 28 that it had been informed by the DOE Loan Programs Office that the initial money will undergo a delay “to confirm alignment with White House priorities.” Calumet said it was informed that the delay “should be days or weeks.”

Questions about Executive Order alignment

Included in Jan. 20 Executive Orders, President Donald Trump pushed to pause federal loans and grants while the new administration conducts reviews to assess alignment with the administration’s policies as applicable by law. A memorandum from the Office of Management and Budget said the freeze pertains to climate change and green energy provisions, but confusion remains.

Late Tuesday, a federal judge temporarily blocked the move for existing programs until Monday afternoon, just minutes before the funding freeze was to go into effect, the Associated Press reported. Judge Loren AliKhan granted an administrative stay in a case, setting a hearing for additional arguments.

In its update regarding the timing of the DOE loan, Todd Borgmann, Calumet’s chief executive officer, said “we are well aligned with White House priorities to support domestic agriculture, energy security, technical innovation and energy independence, all of which play a role in the tremendous bipartisan support this loan has received since its inception.”

“The recently issued Executive Order specifically highlights the importance of biofuels to our nation’s domestic energy policy and energy independence, and we look forward to a quick review confirming that we are aligned with the Administration’s goals.”

According to Calumet and MRL, the MaxSAF expansion is expected to boost the Great Falls biorefinery’s sustainable aviation fuel (SAF) production by more than 700% to about 300 million gal/year to bring the site’s combined SAF-renewable diesel production capacity at the site of 330 million gal/year (OGJ Online, July 10, 2023).

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Australian trio progress UK North Sea projects despite ‘challenging environment’

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Linux containers in 2025 and beyond

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Let’s Go Build Some Data Centers: PowerHouse Drives Hyperscale and AI Infrastructure Across North America

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Blue Owl Swoops In As Major Backer of New, High-Profile, Sustainable U.S. Data Center Construction

With the global demand for data centers continuing to surge ahead, fueled by the proliferation of artificial intelligence (AI), cloud computing, and digital services, it is unsurprising that we are seeing aggressive investment strategies, beyond those of the existing hyperscalers. One of the dynamic players in this market is Blue Owl Capital, a leading asset management firm that has made significant strides in the data center sector. Back in October 2024 we reported on its acquisition of IPI Partners, a digital infrastructure fund manager, for approximately $1 billion. This acquisition added over $11 billion to the assets Blue Owl manages and focused specifically on digital infrastructure initiatives. This acquisition was completed as of January 5, 2025 and IPI’s Managing Partner, Matt A’Hearn has been appointed Head of Blue Owl’s digital infrastructure strategy. A Key Player In Digital Infrastructure and Data Centers With multi-billion-dollar joint ventures and financing initiatives, Blue Owl is positioning itself as a key player in the digital infrastructure space. The company investments in data centers, the implications of its strategic moves, and the broader impact on the AI and digital economy highlights the importance of investment in the data center to the economy overall. With the rapid growth of the data center industry, it is unsurprising that aggressive investment fund management is seeing it as an opportunity. Analysts continue to emphasize that the global data center market is expected to grow at a compound annual growth rate (CAGR) of 10.2% from 2023 to 2030, reaching $517.17 billion by the end of the decade. In this rapidly evolving landscape, Blue Owl Capital has emerged as a significant contributor. The firm’s investments in data centers are not just about capitalizing on current trends but also about shaping the future of digital infrastructure. Spreading the Wealth In August 2024, Blue Owl

Global Data Center Operator Telehouse Launches Liquid Cooling Lab in the UK to Meet Ongoing AI and HPC Demand

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Flexential Partners with Lonestar to Support First Lunar Data Center

Flexential, a leading provider of secure and flexible data center solutions, this month announced that it has joined forces with Lonestar Data Holdings Inc. to support the upcoming launch of Freedom, Lonestar’s second lunar data center. Scheduled to launch aboard a SpaceX Falcon 9 rocket via Intuitive Machines, this mission is a critical step toward establishing a permanent data center on the Moon. Ground-Based Support for Lunar Data Storage Flexential’s Tampa data center will serve as the mission control platform for Lonestar’s lunar operations, providing colocation, interconnection, and professional services. The facility was chosen for its proximity to Florida’s Space Coast launch operations and its ability to deliver low-latency connectivity for critical functions. Flexential operates two data centers in Tampa and four in Florida as part of its FlexAnywhere® Platform, comprising more than 40 facilities across the U.S. “Flexential’s partnership with Lonestar represents our commitment to advancing data center capabilities beyond conventional boundaries,” said Jason Carolan, Chief Innovation Officer at Flexential. “By supporting Lonestar’s space-based data center initiative, we are helping to create new possibilities for data storage and disaster recovery. This project demonstrates how innovative data center expertise can help organizations prepare for a resilient future with off-world storage solutions.” A New Era of Space-Based Resiliency The growing demand for data center capacity, with U.S. power consumption expected to double from 17 GW in 2022 to 35 GW by 2030 (according to McKinsey & Company), is driving interest in space-based solutions. Storing data off-planet reduces reliance on terrestrial resources while enhancing security against natural disasters, warfare, and cyber threats. The Freedom data center will provide resiliency, disaster recovery, and edge processing services for government and enterprise customers requiring the highest levels of data protection. The solar-powered data center leverages Solid-State Drives (SSDs) and a Field Programmable Gate Array (FPGA) edge

Why DeepSeek Is Great for AI and HPC and Maybe No Big Deal for Data Centers

In the rapid and ever-evolving landscape of artificial intelligence (AI) and high-performance computing (HPC), the emergence of DeepSeek’s R1 model has sent ripples across industries. DeepSeek has been the data center industry’s topic of the week, for sure. The Chinese AI app surged to the top of US app store leaderboards last weekend, sparking a global selloff in technology shares Monday morning. But while some analysts predict a transformative impact within the industry, a closer examination suggests that, for data centers at large, the furor over DeepSeek might ultimately be much ado about nothing. DeepSeek’s Breakthrough in AI and HPC DeepSeek, a Chinese AI startup, this month unveiled its R1 model, claiming performance on par with, or even surpassing, leading models like OpenAI’s ChatGPT-4 and Anthropic’s Claude-3.5-Sonnet. Remarkably, DeepSeek developed this model at a fraction of the cost typically associated with such advancements, utilizing a cluster of 256 server nodes equipped with 2,048 GPUs. This efficiency has been attributed to innovative techniques and optimized resource utilization. AI researchers have been abuzz about the performance of the DeepSeek chatbot that produces results similar to ChatGPT, but is based on open-source models and reportedly trained on older GPU chips. Some researchers are skeptical of claims about DeepSeek’s development costs and means, but its performance appears to challenge common assumptions about the computing cost of developing AI applications. This efficiency has been attributed to innovative techniques and optimized resource utilization. Market Reactions and Data Center Implications The announcement of DeepSeek’s R1 model led to significant market reactions, with notable declines in tech stocks, including a substantial drop in Nvidia’s valuation. This downturn was driven by concerns that more efficient AI models could reduce the demand for high-end hardware and, by extension, the expansive data centers that house them. For now, investors are re-assessing the

Microsoft will invest $80B in AI data centers in fiscal 2025

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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

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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