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U.S. Advances AI Data Center Push with RFI for Infrastructure on DOE Lands

ORNL is also the home of the Center for Artificial Intelligence Security Research (CAISER), which Edmon Begoli, CAISER founding director, described as being in place to build the security necessary by defining a new field of AI research targeted at fighting future AI security risks. Also, at the end of 2024, Google partner Kairos Power […]

ORNL is also the home of the Center for Artificial Intelligence Security Research (CAISER), which Edmon Begoli, CAISER founding director, described as being in place to build the security necessary by defining a new field of AI research targeted at fighting future AI security risks.

Also, at the end of 2024, Google partner Kairos Power started construction of their Hermes demonstration SMR in Oak Ridge. Hermes is a high-temperature gas-cooled reactor (HTGR) that uses triso-fueled pebbles and a molten fluoride salt coolant (specifically Flibe, a mix of lithium fluoride and beryllium fluoride). This demonstration reactor is expected to be online by 2027, with a production level system becoming available in the 2030 timeframe.

Also located in a remote area of Oak Ridge is the Tennessee Valley Clinch River project, where the TVA announced a signed agreement with GE-Hitachi to plan and license a BWRX-300 small modular reactor (SMR).

On Integrating AI and Energy Production

The foregoing are just examples of ongoing projects at the sites named by the DOE’s RFI. Presuming that additional industry power, utility, and data center providers get on board with these locations, any of the 16 could be the future home of AI data centers and on-site power generation. The RFI marks a pivotal step in the U.S. government’s strategy to solidify its global dominance in AI development and energy innovation.

By leveraging the vast resources and infrastructure of its national labs and research sites, the DOE is positioning the country to meet the enormous power and security demands of next-generation AI technologies. The selected locations, already home to critical energy research and cutting-edge supercomputing, present a compelling opportunity for industry stakeholders to collaborate on building integrated, sustainable AI data centers with dedicated energy production capabilities. With projects like Oak Ridge’s pioneering SMRs and advanced AI security research, these sites offer not only a robust foundation for future AI infrastructure but also an opportunity to advance energy solutions that align with the nation’s long-term strategic goals. 

In addition to the focus on nuclear and renewable energy sources, natural gas generation also plays a critical role in the energy mix for the RFI sites. Many of the DOE locations are strategically positioned near existing natural gas infrastructure, offering a reliable and flexible power source to complement the ambitious AI data center projects. Natural gas facilities can provide the necessary baseload power and rapid response capabilities that AI workloads require, especially during peak demand periods. With lower carbon emissions compared to coal, natural gas serves as a transitional energy source, supporting the goal of decarbonizing the grid while providing a stable foundation for AI growth. As part of a diversified energy strategy, natural gas could help balance intermittent renewable energy generation, ensuring the continuous availability of power for AI applications, while allowing these sites to remain adaptable to future shifts in the energy landscape.

Conclusion

The integration of AI and energy production on DOE lands will not only support national security and economic growth but also drive innovation at the intersection of artificial intelligence and clean energy. As the initiative moves forward, industry players—including utility providers, energy developers, and data center operators—will play a crucial role in realizing this vision.

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Groundcover grows funding for eBPF-based observability tech

Groundcover’s expanded eBPF approach goes beyond traditional network monitoring, Azulay said: “eBPF is no longer just about network monitoring. We use it as an x-ray into operations flowing through the kernel of the operating system.”  Groundcover uses eBPF to provide full application-level traces. Azulay explained that the system can see the

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BP Warns of Rising Debt Amid Lower Output, Weak Gas Trading

BP Plc said debts mounted in the first quarter, yet another setback for the UK energy major as it struggles to turn its finances around. Net debt climbed about $4 billion from the prior quarter, BP said Friday, citing an increase in working capital. It also reported lower upstream production and weak gas trading — disappointing for a company pivoting back toward its core fossil-fuel business. The guidance comes just a few months after BP unveiled plans to refocus on oil and gas and spend less on clean energy amid pressure from activist investor Elliott Investment Management. Since the end of the quarter, turnaround efforts have come under further strain, with the oil market roiled by US President Donald Trump’s aggressive trade policy and OPEC+’s move to unleash supply. BP’s net debt totaled $23 billion at the end of last year, its ratio of debt to equity far exceeding that of Shell Plc, TotalEnergies SE, Chevron Corp. and Exxon Mobil Corp. This year the stock has fared worse than peers, particularly since Trump announced new tariffs April 2. And with oil’s sharp plunge, BP’s in a tough position to bring down borrowings and maintain shareholder returns. “We believe BP has the highest likelihood of reducing buybacks” among the oil majors, TD Cowen analyst Jason Gabelman wrote in a note. “The stock has been the weakest performer since April 2 in the peer group due to relatively high leverage and reliance on divestments.” BP saw “slightly higher” volumes in oil production and operations in the first quarter, but lower output in gas and low-carbon energy, the company said in a statement. Its large but opaque trading business, which at times helps the company ride out a softer market, failed to come to the rescue, with a “weak” contribution from gas and “average” for

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Bill to undo Biden-era water heater efficiency rule heads to Trump’s desk

Dive Brief: Dive Insight: Most tankless water heaters sold today already meet the stricter standards, but rolling back the rule will have a big impact on consumers nonetheless, according to the Appliance Standards Awareness Project. The standards were set to take effect in 2029, requiring new gas tankless water heaters to use about 13% less energy than today’s least efficient models and lowering a household’s total costs by an average of $112 over the life of the product, the group said. “American families are going to face higher bills because the Senate sided with a group of gas utilities and one particular manufacturer,” ASAP Executive Director Andrew deLaski said in a statement. “This is going to keep an outdated version of this technology on the market, with homeowners and renters paying the cost.” Gas industry officials called the vote “a victory for working-class Americans.” “President Biden’s block on certain natural gas appliances was deeply flawed legally and practically,” AGA President and CEO Karen Harbert said. “The water heater rule would have removed consumer choices, placed a disproportionate financial burden on seniors and low-income Americans and pushed financially vulnerable consumers toward less efficient electric products likely to raise their energy bills.”  The Congressional Review Act resolution of disapproval regarding the standards passed with bipartisan support in both chambers of Congress. The DOE finalized the rule in December. “The DOE should focus on promoting energy efficiency without unnecessarily driving up costs and limiting consumer choice,” National Association of Home Builders Chairman Buddy Hughes said in a statement. The measure approved Wednesday by the Senate was introduced in the House by Rep. Gary Palmer, R-Ala. “I applaud the Senate on passing this legislation to protect not only gas water heaters, but consumers,” Palmer said. “For four years, the Biden-Harris administration waged war on our home

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Department of Energy Overhauls Policy for College and University Research, Saving $405 Million Annually for American Taxpayers

WASHINGTON– The Department of Energy (DOE) today announced a new policy action aimed at halting inefficient spending by colleges and universities while continuing to expand American innovation and scientific research. In a new policy memorandum shared with grant recipients at colleges and universities, DOE announced that it will limit financial support of “indirect costs” of DOE research funding to 15%. This action is projected to generate over $405 million in annual cost savings for the American people, delivering on President Trump’s commitment to bring greater transparency and efficiency to federal government spending. “The purpose of Department of Energy funding to colleges and universities is to support scientific research – not foot the bill for administrative costs and facility upgrades,” U.S. Secretary of Energy Chris Wright said. “With President Trump’s leadership, we are ensuring every dollar of taxpayer funding is being used efficiently to support research and innovation – saving millions for the American people.” Through its grant programs, the Department provides over $2.5 billion annually to more than 300 colleges and universities to support Department-sanctioned research. A portion of the funding goes to “indirect costs”, which include both facilities and administration costs. According to DOE data, the average rate of indirect costs incurred by grant recipients at colleges and universities is more than 30%, a significantly higher rate than other for profit, non-profit and state and local government grant awardees. Limiting these costs to a standard rate of 15% will help improve efficiency, reduce costs and ensure proper stewardship of American taxpayer dollars. Full memorandum is available here: POLICY FLASH DATE: April 11, 2025 SUBJECT: Adjusting Department of Energy Grant Policy for Institutions of Higher Education (IHE)  BACKGROUND: Pursuant to 5 U.S.C. 553(a)(2), the Department of Energy (“Department”) is updating its policy with respect to Department grants awarded to institutions

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TC Energy Rules Out Sale of Canadian Mainline Pipeline

TC Energy Corp. Chief Executive Officer Francois Poirier ruled out selling the Canadian Mainline natural gas pipeline — which stretches across most of the country — as the trade war with the US pushes energy security up Canadian politicians’ priority list. President Donald Trump’s tariffs and repeated taunts about annexing Canada have highlighted the country’s vulnerability in relying on a crude pipeline that crosses through the US to supply oil for the eastern provinces’ refineries. Both of the main political parties seeking power in this month’s election have discussed the need to reduce reliance on the pipeline that goes through the Midwest.  The Mainline stretches more than 14,000 kilometers (8,700 miles) from energy-producing Alberta to major population centers in Ontario and Quebec while remaining entirely within Canada’s borders. TC Energy had once proposed converting the line from natural gas to oil before the project, known as Energy East, was abandoned amid opposition, primarily in Quebec.  TC Energy last year split off its oil pipelines into a separate company and is now focused on natural gas transportation and power generation, making the Mainline one of its marquee assets. That makes converting or selling the pipeline something the company won’t consider, Poirier said. “We have a very large group of natural gas shippers with whom we have contractual obligations to deliver natural gas for, in some cases, many more decades,” Poirier said in an interview Thursday in Toronto. “Given that all of our capacity is contracted, legally speaking, we wouldn’t be able to consider a conversion of some of our existing infrastructure to oil service.”   WHAT DO YOU THINK? Generated by readers, the comments included herein do not reflect the views and opinions of Rigzone. All comments are subject to editorial review. Off-topic, inappropriate or insulting comments will be removed. MORE FROM THIS

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Oil Rebounds but Weekly Losses Continue

Oil rebounded on Friday, but still notched its second straight weekly decline as the escalating trade war between the world’s two largest economies drove wild volatility. West Texas Intermediate futures advanced 2.4% to settle at $61.50 a barrel after China raised its tariffs on all US goods to 125%, but said it will pay no attention to further hikes from Washington. Equities rebounded as a selloff in longer-term Treasuries abated, helping buoy the commodity later in the session. The conflict between China and the US has triggered frantic selloffs in stocks, bonds and commodities on concerns the dispute will reduce global growth. The US Energy Information Administration has slashed its forecasts for crude demand this year by almost 500,000 barrels a day, and oil market gauges further along the futures curve are pointing to an oversupply. Oil has retreated about 14% in April, also hurt by an OPEC+ decision to bring back output more quickly than expected. The US levies include a punitive 145% charge on imports from China, which has retaliated with its own tariffs as ties between the two superpowers come under immense strain. US Energy Secretary Chris Wright said on Bloomberg Television on Friday that the market’s recent selloff is overblown, as the US will ultimately have a stronger economy under President Donald Trump. He added that he expects to see higher volumes of US crude and natural gas liquids produced under the current president. Oil’s retreat has led to declines in associated products, with US gasoline futures dropping almost 3% this week. “High-level economic uncertainty is challenging for a macro-sensitive commodity such as oil, and we expect prices will remain under pressure,” BMI, a unit of Fitch Solutions, said in a note. In addition, “we currently factor in a continued, gradual unwinding of the OPEC+ production

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Viking CCS pipeline wins planning consent

A pipeline that will be used to transport carbon to be buried in a depleted North Sea gas field has been awarded planning consent. An application for the Viking CCS pipeline submitted by energy firm Harbour Energy was granted official development consent by the Secretary of State for Energy Security and Net Zero. The 34-mile (55km) pipeline between Immingham and the Theddlethorpe gas terminal on the Lincolnshire coast is a key plank in the project, which is one of the UK’s so-called “track 2” CCS projects awaiting further support from government. The other is Acorn at Peterhead. Its backers have estimated the project could unlock £7 billion of investment across the Humber region by 2035, with 10,000 jobs during construction and £4bn in economic value forecast by the end of the decade. The consent marks some progress as concern grows that delays to CCS plans may risk the UK failing to meet net zero targets. Harbour had initially envisaged making a final investment on the Viking scheme decision last year. The North Sea producer has since focused on developing oil and gas production internationally following its $11.2bn acquisition of Wintershall Dea. It has also since withdrawn from another UK CCS project. The UK’s track 1 CCS projects including HyNet in the North West of England and the East Coast Cluster in Teesside were backed with £21.7 billion in government support over 10 years. The onshore, buried pipeline will transport CO₂ captured from the industrial cluster at Immingham on the first stage of its journey out to the Viking reservoirs via an existing 75-mile (120km) pipeline, the Lincolnshire offshore gas gathering system (LOGGS),  with plans for a further new 13-mile (20km) spur line. The Viking fields could store up to 300m tonnes of CO₂, with the system handling up to 10m

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U.S. Advances AI Data Center Push with RFI for Infrastructure on DOE Lands

ORNL is also the home of the Center for Artificial Intelligence Security Research (CAISER), which Edmon Begoli, CAISER founding director, described as being in place to build the security necessary by defining a new field of AI research targeted at fighting future AI security risks. Also, at the end of 2024, Google partner Kairos Power started construction of their Hermes demonstration SMR in Oak Ridge. Hermes is a high-temperature gas-cooled reactor (HTGR) that uses triso-fueled pebbles and a molten fluoride salt coolant (specifically Flibe, a mix of lithium fluoride and beryllium fluoride). This demonstration reactor is expected to be online by 2027, with a production level system becoming available in the 2030 timeframe. Also located in a remote area of Oak Ridge is the Tennessee Valley Clinch River project, where the TVA announced a signed agreement with GE-Hitachi to plan and license a BWRX-300 small modular reactor (SMR). On Integrating AI and Energy Production The foregoing are just examples of ongoing projects at the sites named by the DOE’s RFI. Presuming that additional industry power, utility, and data center providers get on board with these locations, any of the 16 could be the future home of AI data centers and on-site power generation. The RFI marks a pivotal step in the U.S. government’s strategy to solidify its global dominance in AI development and energy innovation. By leveraging the vast resources and infrastructure of its national labs and research sites, the DOE is positioning the country to meet the enormous power and security demands of next-generation AI technologies. The selected locations, already home to critical energy research and cutting-edge supercomputing, present a compelling opportunity for industry stakeholders to collaborate on building integrated, sustainable AI data centers with dedicated energy production capabilities. With projects like Oak Ridge’s pioneering SMRs and advanced AI security

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Generac Sharpens Focus on Data Center Power with Scalable Diesel and Natural Gas Generators

In a digital economy defined by constant uptime and explosive compute demand, power reliability is more than a design criterion—it’s a strategic imperative. In response to such demand, Generac Power Systems, a company long associated with residential backup and industrial emergency power, is making an assertive move into the heart of the digital infrastructure sector with a new portfolio of high-capacity generators engineered for the data center market. Unveiled this week, Generac’s new lineup includes five generators ranging from 2.25 MW to 3.25 MW. These units are available in both diesel and natural gas configurations, and form part of a broader suite of multi-asset energy systems tailored to hyperscale, colocation, enterprise, and edge environments. The product introductions expand Generac’s commercial and industrial capabilities, building on decades of experience with mission-critical power in hospitals, telecom, and manufacturing, now optimized for the scale and complexity of modern data centers. “Coupled with our expertise in designing generators specific to a wide variety of industries and uses, this new line of generators is designed to meet the most rigorous standards for performance, packaging, and after-treatment specific to the data center market,” said Ricardo Navarro, SVP & GM, Global Telecom and Data Centers, Generac. Engineering for the Demands of Digital Infrastructure Each of the five new generators is designed for seamless integration into complex energy ecosystems. Generac is emphasizing modularity, emissions compliance, and high-ambient operability as central to the offering, reflecting a deep understanding of the real-world challenges facing data center operators today. The systems are built around the Baudouin M55 engine platform, which is engineered for fast transient response and high operating temperatures—key for data center loads that swing sharply under AI and cloud workloads. The M55’s high-pressure common rail fuel system supports low NOx emissions and Tier 4 readiness, aligning with the most

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CoolIT and Accelsius Push Data Center Liquid Cooling Limits Amid Soaring Rack Densities

The CHx1500’s construction reflects CoolIT’s 24 years of DLC experience, using stainless-steel piping and high-grade wetted materials to meet the rigors of enterprise and hyperscale data centers. It’s also designed to scale: not just for today’s most power-hungry processors, but for future platforms expected to surpass today’s limits. Now available for global orders, CoolIT is offering full lifecycle support in over 75 countries, including system design, installation, CDU-to-server certification, and maintenance services—critical ingredients as liquid cooling shifts from high-performance niche to a requirement for AI infrastructure at scale. Capex Follows Thermals: Dell’Oro Forecast Signals Surge In Cooling and Rack Power Infrastructure Between Accelsius and CoolIT, the message is clear: direct liquid cooling is stepping into its maturity phase, with products engineered not just for performance, but for mass deployment. Still, technology alone doesn’t determine the pace of adoption. The surge in thermal innovation from Accelsius and CoolIT isn’t happening in a vacuum. As the capital demands of AI infrastructure rise, the industry is turning a sharper eye toward how data center operators account for, prioritize, and report their AI-driven investments. To wit: According to new market data from Dell’Oro Group, the transition toward high-power, high-density AI racks is now translating into long-term investment shifts across the data center physical layer. Dell’Oro has raised its forecast for the Data Center Physical Infrastructure (DCPI) market, predicting a 14% CAGR through 2029, with total revenue reaching $61 billion. That revision stems from stronger-than-expected 2024 results, particularly in the adoption of accelerated computing by both Tier 1 and Tier 2 cloud service providers. The research firm cited three catalysts for the upward adjustment: Accelerated server shipments outpaced expectations. Demand for high-power infrastructure is spreading to smaller hyperscalers and regional clouds. Governments and Tier 1 telecoms are joining the buildout effort, reinforcing AI as a

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Podcast: Nomads at the Frontier – AI, Infrastructure, and Data Center Workforce Evolution at DCD Connect New York

The 25th anniversary of the latest Data Center Dynamics event in New York City last month (DCD Connect NY 2025) brought record-breaking attendance, underscoring the accelerating pace of change in the digital infrastructure sector. At the heart of the discussions were evolving AI workloads, power and cooling challenges, and the crucial role of workforce development. Welcoming Data Center Frontier at their show booth were Phill Lawson-Shanks of Aligned Data Centers and Phillip Koblence of NYI, who are respectively managing director and co-founder of the Nomad Futurist Foundation. Our conversation spanned the pressing issues shaping the industry, from the feasibility of AI factories to the importance of community-driven talent pipelines. AI Factories: Power, Cooling, and the Road Ahead One of the hottest topics in the industry is how to support the staggering energy demands of AI workloads. Reflecting on NVIDIA’s latest announcements at GTC, including the potential of a 600-kilowatt rack, Lawson-Shanks described the challenges of accommodating such density. While 120-130 kW racks are manageable today, scaling beyond 300 kW will require rethinking power distribution methods—perhaps moving power sleds outside of cabinets or shifting to medium-voltage delivery. Cooling is another major concern. Beyond direct-to-chip liquid cooling, air cooling still plays a role, particularly for DIMMs, NICs, and interconnects. However, advances in photonics, such as shared laser fiber interconnects, could reduce switch power consumption, marking a potential turning point in energy efficiency. “From our perspective, AI factories are highly conceivable,” said Lawson-Shanks. “But we’re going to see hybridization for a while—clients will want to run cloud infrastructure alongside inference workloads. The market needs flexibility.” Connectivity and the Role of Tier-1 Cities Koblence emphasized the continuing relevance of major connectivity hubs like New York City in an AI-driven world. While some speculate that dense urban markets may struggle to accommodate hyperscale AI workloads,

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2025 Data Center Power Poll

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How Microgrids and DERs Could Solve the Data Center Power Crisis

Microgrid Knowledge’s annual conference will be held in Dallas, Texas this year. Energy industry leaders and microgrid developers, customers and enthusiasts will gather April 15-17 at the Sheraton Dallas, to learn from each other and discuss a wide variety of microgrid related topics. There will be sessions exploring the role microgrids can play in healthcare, military, aviation and transportation, as well as other sectors of the economy. Experts will share insights on fuels, creating flexible microgrids, integrating electric vehicle charging stations and more.  “Powering Data Centers: Collaborative Microgrid Solutions for a Growing Market” is expected to be one of the most popular sessions at the conference. Starting at 10:45am on April 16, industry experts will tackle the biggest question facing data center operators and the energy industry – how can we solve the data center energy crisis? During the session, the panelists will discuss how private entities, developers and utilities can work together to deploy microgrids and distributed energy technologies that address the data center industry’s rapidly growing power needs. They’ll share solutions, technologies and strategies to favorably position data centers in the energy queue. In advance of the conference, we sat down with two of the featured panelists to learn more about the challenges facing the data center industry and how microgrids can address the sector’s growing energy needs. We spoke with session chair Samantha Reifer, director of strategic alliances at Scale Microgrids and Elham Akhavan, senior microgrid research analyst at Wood Mackenzie. Here’s what Reifer and Akhavan had to say: The data center industry is growing rapidly. What are the critical challenges facing the sector as it expands? Samantha Reifer: The biggest barrier we’ve been hearing about from our customers and partners is whether these data centers can get power where they want to build? For a colocation

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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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