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Oil Executives Talk Permitting But Not Prices in Trump Meeting

Oil executives pressed for faster permitting — and didn’t discuss concerns about falling crude prices — during a meeting with President Donald Trump on Wednesday, Interior Secretary Doug Burgum said.  The more than hour-long session brought Trump, an unabashed champion of American oil and gas might, face to face with more than a dozen executives […]

Oil executives pressed for faster permitting — and didn’t discuss concerns about falling crude prices — during a meeting with President Donald Trump on Wednesday, Interior Secretary Doug Burgum said. 

The more than hour-long session brought Trump, an unabashed champion of American oil and gas might, face to face with more than a dozen executives eager to help shape the president’s “energy dominance” agenda. 

Executives praised Trump’s early moves to approve natural gas export licenses and unwind regulations that have raised the industry’s operational costs. The backdrop for the meeting, however, was mounting concern about the president’s plan to slash energy prices, potentially to levels that could make some domestic production unprofitable. On Wednesday, West Texas Intermediate crude, the US benchmark, closed at $67.16 per barrel, down from $75.89 Trump’s first full day in the White House this year.

Still, in the meeting, “there was really no discussion on price,” Burgum said, emphasizing that’s “set by supply and demand,” and “there’s nothing we can say in that room that would change that one iota.”

Instead, the group focused heavily on the need to speed up permitting times and ensure project approvals have lasting durability. While some moves to streamline permitting can be achieved administratively by the executive branch, oil industry leaders have emphasized the importance of getting those changes passed by Congress and enshrined into law. 

“We did talk a lot about permitting, because one of the things that this industry has faced is the onslaught of regulation that really had one goal in mind: trying to drive their business out of business,” Burgum said. In story after story, Burgum said he and Energy Secretary Chris Wright heard how “the permitting process takes longer than the actual building process on critical infrastructure in our country.”

Ahead of the meeting, participants were set to include chief executives from across the spectrum of the industry, including integrated oil companies (Exxon Mobil Corp., Chevron Corp., Shell Plc, BP PLC, ConocoPhillips, Hess Corp.); independent producers (Diamondback Energy Inc., APA Corp’s Apache, Occidental Petroleum Corp., Continental Resources Inc.); refiners (Marathon Petroleum Corp. and Phillips 66); a pipeline operator (Enbridge Inc.) and an oil field service firm (Baker Hughes Co.). A final participant list was not immediately available Wednesday afternoon. 

“As leaders of the American oil and natural gas industry, we appreciated the opportunity to meet with President Trump and key members of his cabinet today to discuss the commonsense energy solutions Americans voted for,” said Mike Sommers, president of the American Petroleum Institute. That included recommendations the trade group has outlined in its “policy road map” for administration officials. 

Lorenzo Simonelli, chief executive officer of Baker Hughes, called it “a positive meeting around continued investment in energy development and infrastructure, in line with the administration’s goals to unleash American energy.” 

In the meeting, “President Trump reaffirmed his commitment to restore America’s energy dominance and ‘drill, baby, drill,’” said Taylor Rogers, a White House spokesperson.

Wright dismissed talk of a possible $50 price target for crude. A March 10 Financial Times report cited Wright as saying the US shale sector can boost production even if oil prices dip to that level, spooking some industry leaders, given that’s below the cost of production in many US fields. Separately, Trump has praised recent declines in crude prices — weeks after he urged OPEC+ to boost output. 

“I don’t think I’ve mentioned $50 oil before,” Wright said. “I’ve always said all commodities are supply and demand.”

However, Wright added, the federal government can “do everything we can to get barriers out of the way to grow supply,” which will naturally push prices down. 

That’s already happening, Wright said, as the Trump administration embarks on a deregulation agenda that could enhance demand for fossil fuels while lowering the cost of producing oil and natural gas. “We’ve seen prices come down a little bit already in anticipation that it’s going to be easier to produce energy in the United States and it’s going to be lower risk.”



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Southwest Power Pool to develop 765-kV regional transmission ‘backbone’

Listen to the article 4 min This audio is auto-generated. Please let us know if you have feedback. Dive Brief: The Southwest Power Pool board of directors on Wednesday approved an $8.6 billion slate of 50 transmission projects across its 14-state footprint. The projects are intended to help the grid operator meet peak demand, which it expects will double, to reach 109 GW, in the next 10 years. Key to the 2025 Integrated Transmission Plan is development of a 765-kV regional transmission “backbone” that can carry four times the power SPP’s existing 345-kV lines do, and do so more efficiently. The grid operator’s transmission system “is at capacity and forecasted load growth will only exacerbate the existing strain,” it said. “Simply adding new generation will not resolve the challenges.” 765-kV transmission lines are the highest operating voltages in the U.S. but are new in both SPP and in the neighboring Electric Reliability Council of Texas market. Texas regulators approved the higher voltage lines for the first time in April. Dive Insight: Transmission developers in SPP and ERCOT are turning to 765-kV projects to mitigate line losses and move greater volumes of power into demand centers at a time when electricity demand is expected to rise significantly. “With the new load being integrated into the system, SPP could see an increase in the footprint’s annual energy consumption by as much as 136%,” the grid operator said in its ITP. “Investments in transmission are the key to keep costs low, maintain reliability, and power economic growth.” Even under conservative assumptions, SPP forecasts a 35% increase in demand, “making timely transmission investment essential,” the grid operator said. SPP selected Xcel Energy in February to construct the first 765-kV lines in its footprint. Those lines were identified in its 2024 plan. AEP Texas will build

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The week in 5 numbers: Gas valuations soar but solar leads new capacity

The price gas power merger and acquisitions have reached in some markets, according to energy analytics firm Enverus. The artificial intelligence boom, along with expectations of increased manufacturing and electrification, is driving a surge in natural gas investment, but thermal generation remains risky, some analysts say, drawing parallels to the dot com bubble at the turn of the century. 

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Our laws must catch up to data centers’ rising power

Alexandra Klass is the James G. Degnan Professor of Law at Michigan Law, and Dave Owen is the Albert Abramson ’54 Distinguished Professor of Law at UC Law San Francisco. The United States faces massive growth in electricity demand. If utilities’ projections are right, data centers will drive much of that growth. And if utilities try to meet that demand in traditional ways, the results could be bad for consumers, the environment and the tech industry. Those traditional ways assume that utilities must meet the needs of electricity customers at all times. This requires utilities to build new power plants and transmission and distribution lines and (in most states) pass those costs, plus a profit margin, on to consumers. Utilities also will not allow major new users to connect to the grid until those users’ needs can be met. These principles are a poor fit for the present moment. Building new power plants and transmission lines has become increasingly difficult. If data centers must wait until that infrastructure is fully built, they may wait for years. Worse, utilities and government officials are citing the potential data-center boom as a reason to extend the life of old, expensive, and heavily polluting coal plants or to build new gas plants. If they do so, and if they pass those costs on to consumers, retail electricity prices and pollution will rise. And if current demand projections turn out to be overestimates — which has happened during past tech booms — consumers will pay for new power plants that never needed to be built. But this unfortunate scenario is not inevitable. We are scholars of energy, natural resources, and environmental law, and in a paper we explore a better way of meeting this moment. Our inspiration comes from legal systems for allocating water, particularly in

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Oil Market Appears ‘Torn’

The oil market appears “torn”. That’s what Standard Chartered Bank Energy Research Head Emily Ashford outlined in a report sent to Rigzone by the Standard Chartered team this week, which included a Brent price forecast from Standard Chartered’s machine learning model for next Monday. “The market appears torn between the overwhelming media narrative of an impending supply glut just over the horizon on the one hand, and increasingly unpredictable U.S. policy with a focus on some of the largest producers, and the demand implications of the evolving tariff/trade war landscape on the other,” Ashford said in the statement. “Front-month Brent crude prices closed at $68.89 per barrel on 3 November, just $0.01 per barrel higher than our machine learning model SCORPIO’s forecast set last week,” Ashford added. “This week the model sees an increase of $1.67 per barrel to $66.56 per barrel settlement on Monday 10 November, mainly driven by data from the U.S. (pointing sideways but bullish altogether),” Ashford continued. In the report, Ashford cautioned that “the ongoing U.S. shutdown means that some key data releases remain on pause”. Ashford highlighted in the report that Standard Chartered’s “core view” is that crude oil sentiment “is currently overwhelmingly negative”. “We expect near-term weakness driven by perceived market oversupply and global demand indicators,” Ashford noted. “Low prices then start to quash U.S. shale output growth, and if OPEC+’s return of barrels is sustained, the market will highlight tightness and geographic concentration of spare capacity, which we expect to be supportive in the medium term,” Ashford added. Standard Chartered’s report projected that the ICE Brent nearby future crude oil price will average $68.50 per barrel overall in 2025 and $63.50 per barrel overall in 2026. The report forecast that the commodity will come in at $65 per barrel in the fourth quarter

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Aker BP, DNO Swap Norwegian Offshore Assets

DNO ASA and Aker BP ASA have signed agreements to recalibrate their exploration and production ownerships in the Norwegian continental shelf, including the Kjottkake discovery. Aker BP will assume operatorship of Kjottkake until the start of production, after which DNO will resume operatorship, according to online statements by the companies on Thursday. The move allows for faster development, with production now targeted for the first quarter of 2028, the companies said. Fornebu, Norway-based Aker BP “will draw on its alliance with suppliers and its equipment inventory to deliver the project on time”, DNO said. “Three years from discovery to production is a standout on the Norwegian continental shelf, where such tie-backs typically take at least twice as long to complete”, DNO said. DNO discovered Kjottkake earlier this year in the northern North Sea under Production License 1182 S (PL 1182 S). “The discovery was made in Paleocene injectite sandstones of excellent reservoir quality with preliminary estimates of gross recoverable resources in the range of 39 to 75 million barrels of oil equivalent (MMboe), with a mean of 55 MMboe”, DNO said in a press release March 26. “The Kjottkake exploration well encountered a 41-meter oil column and a nine-meter gas column. A sidetrack drilled horizontally 1,350 meters westwards along the reservoir in the Sotra Formation confirmed the presence of the oil column throughout the discovery”. Kjottkake sits 27 kilometers (16.78 miles) northwest of the Troll C platform and 44 kilometers southwest of the Gjoa platform, according to DNO. Under the swap agreements, DNO and Aker BP retain their Kjottkake stakes of 40 percent and 45 percent respectively. Concedo AS holds 15 percent. Also under the agreements DNO will transfer its 28.9 percent stake in the producing Vilje field to Aker BP, whose interest will increase to 75.76 percent. Aker BP

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Oil Falls as Saudi Price Cuts Signal Market Gloom

Oil extended declines after Saudi Arabia lowered the prices of its crude, signaling uncertainty surrounding the supply outlook, while equities slumped in another pressure on the commodity. West Texas Intermediate settled near $59, sliding around 0.3% on the day after falling in the previous two sessions. Volatility hit Wall Street, also weighing on oil prices. Saudi Arabia lowered the price of its main oil grade to Asia for December to the lowest level in 11 months. Even though the price cut met expectations, traders saw it as a bearish signal about the cartel’s confidence in the market’s ability to absorb new supply, with a glut widely expected to begin next year. Prices have given up ground since the US sanctioned Russia’s two largest oil producers last month over Moscow’s war in Ukraine, and abundant supplies have so far managed to cushion the impact of stunted flows from the OPEC+ member to major buyers India and China. Key price gauges indicate that supply perceptions are worsening, with the premium that front-month WTI futures command over the next month’s contract, known as the prompt spread, narrowing in the past few weeks to near February lows. That’s also true for Brent crude. Still, US shale companies are forging ahead with their production plans, with Diamondback Energy Inc., Coterra Energy Inc. and Ovintiv Inc. this week announcing they inend to raise output slightly for this year or 2026 despite oil prices falling close to the threshold needed for many US shale wells to break even. Oversupply gloom hasn’t permeated refined products markets, though. Traders are still assessing how those supplies may be impacted by the US clampdown on purchases of Russian crude and Ukraine’s strikes on its neighbor’s energy assets. Those factors, as well as diminishing global refining capacity, bolstered diesel futures and gasoil

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Designing the AI Century: 7×24 Exchange Fall ’25 Charts the New Data Center Industrial Stack

SMRs and the AI Power Gap: Steve Fairfax Separates Promise from Physics If NVIDIA’s Sean Young made the case for AI factories, Steve Fairfax offered a sobering counterweight: even the smartest factories can’t run without power—and not just any power, but constant, high-availability, clean generation at a scale utilities are increasingly struggling to deliver. In his keynote “Small Modular Reactors for Data Centers,” Fairfax, president of Oresme and one of the data center industry’s most seasoned voices on reliability, walked through the long arc from nuclear fusion research to today’s resurgent interest in fission at modular scale. His presentation blended nuclear engineering history with pragmatic counsel for AI-era infrastructure leaders: SMRs are promising, but their road to reality is paved with physics, fuel, and policy—not PowerPoint. From Fusion Research to Data Center Reliability Fairfax began with his own story—a career that bridges nuclear reliability and data center engineering. As a young physicist and electrical engineer at MIT, he helped build the Alcator C-MOD fusion reactor, a 400-megawatt research facility that heated plasma to 100 million degrees with 3 million amps of current. The magnet system alone drew 265,000 amps at 1,400 volts, producing forces measured in millions of pounds. It was an extreme experiment in controlled power, and one that shaped his later philosophy: design for failure, test for truth, and assume nothing lasts forever. When the U.S. cooled on fusion power in the 1990s, Fairfax applied nuclear reliability methods to data center systems—quantifying uptime and redundancy with the same math used for reactor safety. By 1994, he was consulting for hyperscale pioneers still calling 10 MW “monstrous.” Today’s 400 MW campuses, he noted, are beginning to look a lot more like reactors in their energy intensity—and increasingly, in their regulatory scrutiny. Defining the Small Modular Reactor Fairfax defined SMRs

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Top network and data center events 2025 & 2026

Denise Dubie is a senior editor at Network World with nearly 30 years of experience writing about the tech industry. Her coverage areas include AIOps, cybersecurity, networking careers, network management, observability, SASE, SD-WAN, and how AI transforms enterprise IT. A seasoned journalist and content creator, Denise writes breaking news and in-depth features, and she delivers practical advice for IT professionals while making complex technology accessible to all. Before returning to journalism, she held senior content marketing roles at CA Technologies, Berkshire Grey, and Cisco. Denise is a trusted voice in the world of enterprise IT and networking.

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Google’s cheaper, faster TPUs are here, while users of other AI processors face a supply crunch

Opportunities for the AI industry LLM vendors such as OpenAI and Anthropic, which still have relatively young code bases and are continuously evolving them, also have much to gain from the arrival of Ironwood for training their models, said Forrester vice president and principal analyst Charlie Dai. In fact, Anthropic has already agreed to procure 1 million TPUs for training and its models and using them for inferencing. Other, smaller vendors using Google’s TPUs for training models include Lightricks and Essential AI. Google has seen a steady increase in demand for its TPUs (which it also uses to run interna services), and is expected to buy $9.8 billion worth of TPUs from Broadcom this year, compared to $6.2 billion and $2.04 billion in 2024 and 2023 respectively, according to Harrowell. “This makes them the second-biggest AI chip program for cloud and enterprise data centers, just tailing Nvidia, with approximately 5% of the market. Nvidia owns about 78% of the market,” Harrowell said. The legacy problem While some analysts were optimistic about the prospects for TPUs in the enterprise, IDC research director Brandon Hoff said enterprises will most likely to stay away from Ironwood or TPUs in general because of their existing code base written for other platforms. “For enterprise customers who are writing their own inferencing, they will be tied into Nvidia’s software platform,” Hoff said, referring to CUDA, the software platform that runs on Nvidia GPUs. CUDA was released to the public in 2007, while the first version of TensorFlow has only been around since 2015.

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Cisco launches AI infrastructure, AI practitioner certifications

“This new certification focuses on artificial intelligence and machine learning workloads, helping technical professionals become AI-ready and successfully embed AI into their workflows,” said Pat Merat, vice president at Learn with Cisco, in a blog detailing the new AI Infrastructure Specialist certification. “The certification validates a candidate’s comprehensive knowledge in designing, implementing, operating, and troubleshooting AI solutions across Cisco infrastructure.” Separately, the AITECH certification is part of the Cisco AI Infrastructure track, which complements its existing networking, data center, and security certifications. Cisco says the AITECH cert training is intended for network engineers, system administrators, solution architects, and other IT professionals who want to learn how AI impacts enterprise infrastructure. The training curriculum covers topics such as: Utilizing AI for code generation, refactoring, and using modern AI-assisted coding workflows. Using generative AI for exploratory data analysis, data cleaning, transformation, and generating actionable insights. Designing and implementing multi-step AI-assisted workflows and understanding complex agentic systems for automation. Learning AI-powered requirements, evaluating customization approaches, considering deployment strategies, and designing robust AI workflows. Evaluating, fine-tuning, and deploying pre-trained AI models, and implementing Retrieval Augmented Generation (RAG) systems. Monitoring, maintaining, and optimizing AI-powered workflows, ensuring data integrity and security. AITECH certification candidates will learn how to use AI to enhance productivity, automate routine tasks, and support the development of new applications. The training program includes hands-on labs and simulations to demonstrate practical use cases for AI within Cisco and multi-vendor environments.

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Chip-to-Grid Gets Bought: Eaton, Vertiv, and Daikin Deals Imply a New Thermal Capital Cycle

This week delivered three telling acquisitions that mark a turning point for the global data center supply chain; and more specifically, for the high-density liquid cooling mega-play now unfolding across the power-thermal continuum. Eaton is acquiring Boyd Thermal for $9.5 billion from Goldman Sachs Asset Management. Vertiv is buying PurgeRite for about $1 billion from Milton Street Capital. And Daikin Applied has moved to acquire Chilldyne, one of the most proven negative-pressure direct-to-chip pioneers. On paper, they’re three distinct transactions. In reality, they’re chapters in the same story: the acceleration of strategic vertical integration around thermal infrastructure for AI-class compute. The Equity Layer: Private Capital Builds, Strategics Buy From an equity standpoint, these are classic handoff moments between private-equity construction and corporate consolidation. Goldman Sachs built Boyd Thermal into a global platform spanning cold plates, CDUs, and high-density liquid loop design, now sold to Eaton at an enterprise multiple north of 5× 2026E revenue. Milton Street Capital took PurgeRite from a specialist contractor in fluid flushing and commissioning into a nationwide services platform. And Daikin, long synonymous with chillers and air-side thermal, is crossing the liquid Rubicon by buying its way into the D2C ecosystem. Each deal crystallizes a simple fact: liquid cooling is no longer an adjunct; it’s core infrastructure. Private equity did its job scaling the parts. Strategic players are now paying up for the system. Eaton’s Bid: The Chip-to-Grid Thesis For Eaton, Boyd Thermal is the final missing piece in its “chip-to-grid” thesis. The company already owns the electrical side of the data center: UPS, busway, switchgear, and monitoring. Boyd plugs the thermal gap, allowing Eaton to market full rack-to-substation solutions for AI loads in the 50–100 kW+ range. It’s a statement acquisition that places Eaton squarely against Schneider Electric, Vertiv and ABB in the race to

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Space: The final frontier for data processing

There are, however, a couple of reasons why data centers in space are being considered. There are plenty of reports about how the increased amount of AI processing is affecting power consumption within data centers; the World Economic Forum has estimated that the power required to handle AI is increasing at a rate of between 26% and 36% annually. Therefore, it is not surprising that organizations are looking at other options. But an even more pressing reason for orbiting data centers is to handle the amount of data that is being produced by existing satellites, Judge said. “Essentially, satellites are gathering a lot more data than can be sent to earth, because downlinks are a bottleneck,” he noted. “With AI capacity in orbit, they could potentially analyze more of this data, extract more useful information, and send insights back to earth. My overall feeling is that any more data processing in space is going to be driven by space processing needs.” And China may already be ahead of the game. Last year, Guoxing Aerospace  launched 12 satellites, forming a space-based computing network dubbed the Three-Body Computing Constellation. When completed, it will contain 2,800 satellites, all handling the orchestration and processing of data, taking edge computing to a new dimension.

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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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