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EIA Raises USA Total Energy Consumption Forecasts

In its latest short term energy outlook (STEO), which was released on October 7, the U.S. Energy Information Administration (EIA) raised its U.S. total energy consumption forecast for 2025 and 2026. According to this STEO, the EIA sees total energy consumption coming in at 95.76 quadrillion British thermal units (qBtu) this year and 96.02 qBtu […]

In its latest short term energy outlook (STEO), which was released on October 7, the U.S. Energy Information Administration (EIA) raised its U.S. total energy consumption forecast for 2025 and 2026.

According to this STEO, the EIA sees total energy consumption coming in at 95.76 quadrillion British thermal units (qBtu) this year and 96.02 qBtu next year. In its previous STEO, which was released in September, the EIA projected that total energy consumption would be 95.50 qBtu in 2025 and 95.96 qBtu in 2026.

The EIA’s October STEO showed that total energy consumption was 94.57 qBtu in 2024. In its September STEO, the EIA highlighted that this figure stood at 94.22 qBtu.

In its latest STEO, the EIA projected that total energy consumption will come in at 24.01 qBtu in the fourth quarter of 2025, 24.83 qBtu in the first quarter of 2026, 22.51 qBtu in the second quarter, 24.30 qBtu in the third quarter, and 24.38 qBtu in the fourth quarter. The STEO showed that total energy consumption hit 25.45 qBtu in the first quarter of this year, 22.45 qBtu in the second quarter, and 23.85 qBtu in the third quarter.

In its September STEO, the EIA forecast that total energy consumption would be 23.79 qBtu in the third quarter of this year, 24.00 qBtu in the fourth quarter, 24.82 qBtu in the first quarter, 22.48 qBtu in the second quarter, 24.32 qBtu in the third quarter, and 24.33 qBtu in the fourth quarter. That STEO showed that total energy consumption was 25.43 qBtu in the first quarter of 2025 and 22.28 qBtu in the second quarter.

The EIA projected that U.S. liquid fuels consumption will average 20.47 million barrels per day this year and 20.48 million barrels per day next year in its October STEO. In its previous STEO, the EIA forecast that this demand would average 20.49 million barrels per day in 2025 and 20.61 million barrels per day in 2026.

The EIA forecast that U.S. natural gas consumption will average 91.6 billion cubic feet per day across 2025 and 2026 in its latest STEO. In its September STEO, the EIA projected that this demand would average 91.5 billion cubic feet per day this year and 91.4 billion cubic feet per day next year.

U.S. renewables consumption was forecast to hit 8.82 qBtu in 2025 and 9.43 qBtu in 2026 in the EIA’s October STEO. The EIA projected that U.S. renewables demand would come in at 8.78 qBtu in 2025 and 9.38 qBtu in 2026 in its previous September STEO.

The EIA’s October and September STEOs showed that, in 2024, U.S. liquid fuels consumption averaged 20.46 million barrels per day and U.S. natural gas consumption average 90.5 billion cubic feet per day. In its latest STEO, the EIA showed that U.S. renewables consumption came in at 8.69 qBtu in 2024. The EIA’s previous STEO showed that this consumption was 8.58 qBtu last year.

The EIA noted in its STEOs that renewable energy includes minor components of non-marketed renewable energy that is neither bought nor sold, either directly or indirectly, as inputs to marketed energy. The EIA added in the STEOs that it does not estimate or project end-use consumption of non-marketed renewable energy.

In a note related to its total energy consumption figures, the EIA said in its STEOs that the conversion from physical units to Btu is calculated using a subset of conversion factors used in the calculations of gross energy consumption in EIA’s Monthly Energy Review (MER).

The EIA collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment, the EIA states on its website.

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IBM unveils advanced quantum computer in Spain

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EIA Raises USA Total Energy Consumption Forecasts

In its latest short term energy outlook (STEO), which was released on October 7, the U.S. Energy Information Administration (EIA) raised its U.S. total energy consumption forecast for 2025 and 2026. According to this STEO, the EIA sees total energy consumption coming in at 95.76 quadrillion British thermal units (qBtu) this year and 96.02 qBtu next year. In its previous STEO, which was released in September, the EIA projected that total energy consumption would be 95.50 qBtu in 2025 and 95.96 qBtu in 2026. The EIA’s October STEO showed that total energy consumption was 94.57 qBtu in 2024. In its September STEO, the EIA highlighted that this figure stood at 94.22 qBtu. In its latest STEO, the EIA projected that total energy consumption will come in at 24.01 qBtu in the fourth quarter of 2025, 24.83 qBtu in the first quarter of 2026, 22.51 qBtu in the second quarter, 24.30 qBtu in the third quarter, and 24.38 qBtu in the fourth quarter. The STEO showed that total energy consumption hit 25.45 qBtu in the first quarter of this year, 22.45 qBtu in the second quarter, and 23.85 qBtu in the third quarter. In its September STEO, the EIA forecast that total energy consumption would be 23.79 qBtu in the third quarter of this year, 24.00 qBtu in the fourth quarter, 24.82 qBtu in the first quarter, 22.48 qBtu in the second quarter, 24.32 qBtu in the third quarter, and 24.33 qBtu in the fourth quarter. That STEO showed that total energy consumption was 25.43 qBtu in the first quarter of 2025 and 22.28 qBtu in the second quarter. The EIA projected that U.S. liquid fuels consumption will average 20.47 million barrels per day this year and 20.48 million barrels per day next year in its October STEO. In its previous

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Perenco CEO Looks to Enter New Countries

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NextDecade Approves Rio Grande LNG Train 5

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USA Crude Oil Stocks Rise Week on Week

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BofA Sees Oil Price Floor ‘Likely Forming at $55’

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Roundup: Digital Realty Marks Major Milestones in AI, Quantum Computing, Data Center Development

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BlackRock’s $40B data center deal opens a new infrastructure battle for CIOs

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Nvidia, Infineon partner for AI data center power overhaul

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Meta details cutting-edge networking technologies for AI infrastructure

ESUN initiative As part of its standardization efforts, Meta said it would be a key player in the new Ethernet for Scale-Up Networking (ESUN) initiative that brings together AMD, Arista, ARM, Broadcom, Cisco, HPE Networking, Marvell, Microsoft, NVIDIA, OpenAI and Oracle to advance the networking technology to handle the growing scale-up domain for AI systems. ESUN will focus solely on open, standards-based Ethernet switching and framing for scale-up networking—excluding host-side stacks, non-Ethernet protocols, application-layer solutions, and proprietary technologies. The group will focus on the development and interoperability of XPU network interfaces and Ethernet switch ASICs for scale-up networks, the OCP wrote in a blog. ESUN will actively engage with other organizations such as Ultra-Ethernet Consortium (UEC) and long-standing IEEE 802.3 Ethernet to align open standards, incorporate best practices, and accelerate innovation, the OCP stated. Data center networking milestones The launch of ESUN is just one of the AI networking developments Meta shared at the event. Meta engineers also announced three data center networking innovations aimed at making its infrastructure more flexible, scalable, and efficient: The evolution of Meta’s Disaggregated Scheduled Fabric (DSF) to support scale-out interconnect for large AI clusters that span entire data center buildings. A new Non-Scheduled Fabric (NSF) architecture based entirely on shallow-buffer, disaggregated Ethernet switches that will support our largest AI clusters like Prometheus. The addition of Minipack3N, based on Nvidia’s Ethernet Spectrum-4 ASIC, to Meta’s portfolio of 51Tbps OCP switches that use OCP’s Switch Abstraction Interface and Meta’s Facebook Open Switching System (FBOSS) software stack. DSF is Meta’s open networking fabric that completely separates switch hardware, NICs, endpoints, and other networking components from the underlying network and uses OCP-SAI and FBOSS to achieve that, according to Meta. It supports Ethernet-based RoCE RDMA over Converged Ethernet (RoCE/RDMA)) to endpoints, accelerators and NICs from multiple vendors, such as Nvidia,

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Arm joins Open Compute Project to build next-generation AI data center silicon

Keeping up with the demand comes down to performance, and more specifically, performance per watt. With power limited, OEMs have become much more involved in all aspects of the system design, rather than pulling silicon off the shelf or pulling servers or racks off the shelf. “They’re getting much more specific about what that silicon looks like, which is a big departure from where the data center was ten or 15 years ago. The point here being is that they look to create a more optimized system design to bring the acceleration closer to the compute, and get much better performance per watt,” said Awad. The Open Compute Project is a global industry organization dedicated to designing and sharing open-source hardware configurations for data center technologies and infrastructure. It covers everything from silicon products to rack and tray design.  It is hosting its 2025 OCP Global Summit this week in San Jose, Calif. Arm also was part of the Ethernet for Scale-Up Networking (ESUN) initiative announced this week at the Summit that included AMD, Arista, Broadcom, Cisco, HPE Networking, Marvell, Meta, Microsoft, and Nvidia. ESUN promises to advance Ethernet networking technology to handle scale-up connectivity across accelerated AI infrastructures. Arm’s goal by joining OCP is to encourage knowledge sharing and collaboration between companies and users to share ideas, specifications and intellectual property. It is known for focusing on modular rather than monolithic designs, which is where chiplets come in. For example, customers might have multiple different companies building a 64-core CPU and then choose IO to pair it with, whether like PCIe or an NVLink. They then choose their own memory subsystem, deciding whether to go HBM, LPDDR, or DDR. It’s all mix and match like Legos, Awad said.

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BlackRock-Led Consortium to Acquire Aligned Data Centers in $40 Billion AI Infrastructure Deal

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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

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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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