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TotalEnergies, Air Liquide Plan $628 Million Hydrogen Venture

TotalEnergies SE and Air Liquide SA plan a €600 million ($628 million) joint venture to produce green hydrogen for the French oil giant’s refinery in the Netherlands, along with a supply deal for its petrochemical plant in Belgium. The two companies aim to build a 250-megawatt electrolyzer powered by wind energy near the Zeeland refinery, […]

TotalEnergies SE and Air Liquide SA plan a €600 million ($628 million) joint venture to produce green hydrogen for the French oil giant’s refinery in the Netherlands, along with a supply deal for its petrochemical plant in Belgium.

The two companies aim to build a 250-megawatt electrolyzer powered by wind energy near the Zeeland refinery, Total said in a statement Tuesday. Separately, Total also agreed to buy green hydrogen for its Antwerp facility from a 200-megawatt electrolyzer that Air Liquide plans to build near Rotterdam.

Total’s continued drive to reduce emissions at its refineries with low-carbon hydrogen, following other recent deals with Air Liquide and Air Products & Chemicals Inc., contrasts with a more cautious approach from its peers.

“The partnership with Air Liquide takes on a new dimension and marks a new step in TotalEnergies’ ambition to decarbonize the hydrogen consumed by its refineries in Europe by 2030,” said Vincent Stoquart, President, Refining & Chemicals at TotalEnergies said in the statement.

The joint project near the Zeeland refinery is expected to be commissioned in 2029, and the one that will supply the Antwerp plant should start operating by the end of 2027, Total said. A final investment decision still hasn’t been reached.

Thanks to its existing hydrogen pipeline network, Air Liquide will also be able to serve other Dutch and Belgian customers, the French industrial gas company said in a separate statement.  

Under the agreement, Total will supply the two electrolyzers with power from an offshore wind project in the Netherlands, while Air Liquide will also buy clean power from a Vattenfall wind farm off the Dutch coast.

Upon completion, the two projects would represent a combined investment of more than €1 billion, and avoid annual emissions equivalent to as much as 500,000 tons of carbon dioxide, Air Liquide said. The company plans to use electrolyzer technologies from its joint venture with Siemens Energy AG.  



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Arista debuts unified SD-WAN edge platform

“Multi-vendor branch complexity creates the ultimate blind spot, and your adversaries are actively hiding in it,” wrote Brendan Gibbs, Arista’s vice president, AI, routing, and switching platforms, in a blog post about the new platform. Sprawling multi-vendor infrastructure creates operational headaches and increases security risks, according to Gibbs. “When you

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Helios marks AMD’s biggest AI infrastructure push yet

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Sheetz replaces VMware at more than 830 stores

The two companies have a relationship dating back to 2020, when Sheetz first deployed StorMagic’s SvSAN software as the hyperconverged storage layer with VMware across hundreds of store locations to virtualize critical in-store application. The setup supported mission-critical applications such as payment processing, loyalty programs, kitchen management and store operations.

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DOE and DOL Partner to Advance Mining Innovation and Safety

WASHINGTON—The U.S. Department of Energy (DOE) and the U.S. Department of Labor (DOL) today signed a Memorandum of Understanding (MOU) establishing a framework to accelerate the deployment of artificial intelligence (AI), automation, advanced sensors, and other emerging technologies across the nation’s mining sector. The five-year agreement strengthens federal coordination to advance mining innovation while improving worker safety, increasing productivity, and supporting the secure domestic production of critical minerals. By combining DOE’s expertise in energy technologies and resource recovery with DOL’s longstanding leadership in mine safety, the partnership advances the Trump Administration’s commitment to strengthen critical mineral supply chains, support high-paying American jobs, and unleash American energy dominance “America’s security and economic future depend on developing a strong domestic mining sector,” said U.S. Secretary of Energy Chris Wright. “By pairing the Energy Department’s technical expertise with the Labor Department’s leadership on mine safety, we can support American miners, secure domestic supply chains, and put cutting-edge technology to work for the people who power our nation.” “Today’s agreement ensures that the Department of Labor and the Department of Energy will work side by side to prepare the mining workforce, advance mining technology, and support the safe production of the coal that powers America’s future,” said Acting Secretary of Labor Keith Sonderling. “It is our commitment to you that this MOU will further President Trump’s promise to restore coal as a key driver of America’s energy supply chain and American coal will again be the envy of the world for generations to come.” Under the agreement, DOE’s Hydrocarbons and Geothermal Energy Office (HGEO) and Office of Critical Minerals and Energy Innovation (CMEI) will collaborate closely with DOL’s Mine Safety and Health Administration (MSHA) to share non-proprietary data, research, and technical expertise that supports the deployment of next-generation mining technologies. The partnership will focus

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Energy Secretary Secures Grid Amid Period of Hot Weather

WASHINGTON—The U.S. Department of Energy (DOE) issued an emergency order to mitigate blackout risks and keep Americans powered during the region’s energy emergency brought on by hot weather conditions. The order directs the Southwest Power Pool, Inc. (SPP) to dispatch specified units and to order their operation as needed to maintain reliability. The order also authorizes SPP to direct backup generation resources to operate as a last resort before declaring an Energy Emergency Alert (EEA) 3 or during an EEA 3. The order was issued pursuant to a request from SPP. “The Trump Administration is tapping into an abundant supply of unused backup generation to maintain affordable, reliable, and secure power for hardworking American families and businesses,” said U.S. Secretary of Energy Chris Wright. “The previous administration’s energy subtraction policies weakened the grid, leaving Americans more vulnerable during emergency events. Thanks to President Trump’s leadership, we are reversing those failures and using every available tool to ensure Americans have continued access to affordable, reliable, and secure energy to power and cool their homes.”  DOE estimates more than 35 gigawatts (GW) of unused backup generation remains available nationwide.   On day one of his second term, President Trump declared a national energy emergency after the Biden administration’s energy subtraction agenda left behind a grid increasingly vulnerable to blackouts.   Power outages cost the American people $44 billion per year, according to data from DOE’s National Laboratories. This order mitigates the possibility of power outages in the region and highlights the common sense policies of the Trump Administration to ensure Americans have access to affordable, reliable, and secure power. The order was effective upon issuance on July 20, 2026, and shall expire at 11:59 PM ET on July 21, 2026. 

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S&P Global: Hormuz vessel transits fall amid heightened security risks

Vessel traffic through the Strait of Hormuz remained subdued July 10-12 as heightened regional security risks continued to weigh on movements through the strategic waterway, according to S&P Global MINT and S&P Global Commodities at Sea data. A total of 73 vessels transited the strait during the 3-day period, averaging fewer than 25 crossings/day. Transits fell to 11 on July 12, the lowest since June 14, after Iran declared the strait closed amid what the Persian Gulf Strait Authority described as “illegal movements” of US military forces in the region. No inbound crossings were recorded July 12, the first such occurrence since June 12. Six of the day’s 11 transits were assessed as compliant vessels. Total crossings were 32 on July 10 and 30 on July 11. The Joint Maritime Information Center (JMIC) said July 12 that the regional threat level remained severe. Despite Iran’s closure declaration, JMIC said the southern route remained available and had been expanded for two-way vessel traffic. Energy carriers—including oil, chemical, LPG, and LNG tankers—accounted for about 48% of transits July 10-12. About two-thirds of energy-carrier crossings involved compliant vessels, although only 10 compliant energy carriers entered the Persian Gulf, mostly without visible automatic identification system (AIS) signals. Inbound tanker capacity also softened. An average 6.5 million b/d of new oil and LPG tanker capacity entered the Gulf through Hormuz July 1-12, with VLCCs and Suezmaxes accounting for nearly 80%. Average inbound capacity fell to 6 million b/d July 10-12 from 8.5 million b/d in the first week of July. All compliant outbound energy carriers transiting Hormuz during the 3-day period did so without visible AIS signals, including ADNOC-operated LNG carrier AL HAMRA and several VLCC and product tankers. Iran-linked and US-sanctioned vessels accounted for nearly 60% of all crossings during the period.

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Beyond AI Pilots: Scaling AI-Enabled Decision Making in Energy

Date: Thursday, August 6, 2026Time: 11:00 AM (GMT-04:00) Eastern Time – New YorkDuration: 60 minutes Already registered? Click here to log in now. Artificial Intelligence is rapidly becoming a strategic priority across industrial organizations, yet many companies continue to struggle with fragmented data, disconnected workflows, and AI initiatives that never move beyond pilot projects. The challenge is not access to AI—it is creating the business context, governance, and lifecycle intelligence needed to transform AI insights into measurable operational outcomes. Join Siemens Digital Industries Software to learn how Intelligence Center X, part of the Siemens Xcelerator portfolio, helps organizations connect enterprise data, workflows, and AI capabilities into a single governed environment where people and AI work together to drive faster, more informed decisions. In this session, we’ll explore how organizations can: • Move beyond isolated AI experiments to enterprise-scale deployment • Connect engineering, manufacturing, operations, supply chain, and service data into a unified intelligence framework • Enable AI agents to operate within governed, human-in-the-loop business processes • Improve operational performance through AI-assisted decision-making • Accelerate issue resolution, reduce manual effort, and increase organizational agility Attendees will also learn how Intelligence Center X combines lifecycle intelligence, industrial data models, AI orchestration, and low-code application development to create production-ready AI solutions that deliver measurable business value. Real-world examples will demonstrate how organizations have achieved significant improvements, including reductions in manual effort, faster issue resolution, improved data quality, and enhanced decision-making capabilities. Whether you are responsible for digital transformation, operations, manufacturing, engineering, or executive strategy, this webinar will provide practical insight into building a scalable foundation for industrial AI and creating a future where people and AI work together to drive business outcomes.

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TotalEnergies lets drilling, completions contract for Suriname deepwater oil project

TotalEnergies has let contracts to Halliburton for work on the GranMorgu deepwater oil development project offshore Suriname. The workscope includes drilling and completions services for a long-term program that includes applying integrated digital workflows, real time data, and remote operations control for drilling and completions. As part of the project scope, Halliburton worked with local suppliers to upgrade its liquid mud and cement plant and supported construction of Suriname’s first completions and drilling workshop, featuring advanced maintenance and repair capabilities, the service provider said in a release July 13. The aim of the GranMorgu project is to develop resources on Block 58, which lies about 150 km off the Surinamese coast. Specifically, Sapakara and Krabdagu fields, which contain estimated recoverable reserves of nearly 760 million bbl, TotalEnergies noted on its website. The project’s floating production, storage, and offloading unit (FPSO), with a capacity of 220,000 b/d, is based on tested design principles of units in nearby Guyana and designed for potential future tie-in of satellite fields. Production start-up is expected in 2028. TotalEnergies is operator of the project with 40% interest. Partners are APA Corp. (40%) and state-owned Staatsolie Maatschappij Suriname NV (20%).

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Aramco lets stimulation, completion services contract for unconventional gas development

Saudi Aramco has awarded Halliburton a multi-year contract to provide stimulation and completion services for the company’s unconventional gas development program in Saudi Arabia. Halliburton said July 15 that the award is part of a broader multibillion-dollar contract framework supporting the Kingdom’s unconventional resource expansion. Under the agreement, Halliburton will deploy intelligent fracturing automation technologies designed to optimize treatment performance in real time and support execution across multiwell development campaigns. The company said the technologies will enable greater digital integration across field operations. Development of the Jafurah unconventional gas field, the Middle East’s largest liquids-rich shale gas play, is under way. In support of the program, Halliburton plans to expand local manufacturing capacity, strengthen its supply chain network, and increase workforce development initiatives within the Kingdom as activity levels continue to grow. “Beginning in the third quarter of 2026, Halliburton will deploy the Kingdom’s first fully integrated intelligent fracturing platform through OCTIV® Auto Frac and Sensori™ fracturing monitoring services to contribute to asset value for one of the world’s largest unconventional fields,” said Rami Yassine, senior vice-president, Eastern Hemisphere, Halliburton. Jafurah background Jafurah is a key component of Aramco’s gas expansion strategy intended to help meet rising demand for natural gas in power generation and industry. In February 2026, the operator said it seeks to expand sales gas production capacity by about 80% by 2030 compared with 2021 production levels. At the time, Aramco said unconventional shale gas output from Jafurah began in December 2025. The field covers about 17,000 sq km and is estimated to contain 229 tcf of raw gas and 75 billion stb of condensate. Aramco expects the development to produce 2 bcfd of sales gas, 420 MMscfd of ethane, and about 630,000 b/d of high-value liquids by 2030.

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Time to Power: Sage Geosystems CEO Cindy Taff on Geothermal’s AI Infrastructure Moment

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Tech Explainer: Data Center Cooling – Air, Evaporative, Liquid, and Hybrid Approaches

Data Center Cooling Glossary The following definitions reflect common terminology used in Department of Energy guidance, ASHRAE TC 9.9 materials, Berkeley Lab resources and Green Grid efficiency metrics. Adiabatic Cooling — A cooling process that uses water evaporation to lower the temperature of air before it reaches a heat exchanger or cooling coil. It can reduce compressor demand but consumes water when evaporative assistance is active. Air-Cooled Data Center — A facility in which heat is removed from IT equipment primarily by moving conditioned air through servers, even if that heat is later transferred to water or refrigerant elsewhere in the cooling system. Air Handler — Equipment that moves, filters and conditions air before delivering it to a data hall or other controlled space. Air-Side Economizer — A system that uses suitable outdoor air, either directly or mixed with return air, to reduce or avoid compressor-based refrigeration. Airflow Management — The practice of delivering conditioned air where it is needed while preventing hot exhaust air from recirculating into server inlets. Approach Temperature — The temperature difference between the two fluids leaving a heat exchanger at their closest thermal point. In a cooling tower, it commonly refers to the difference between leaving-water temperature and entering-air wet-bulb temperature. A smaller approach generally indicates more effective heat transfer. ASHRAE TC 9.9 — The ASHRAE technical committee focused on mission-critical facilities, data centers, technology spaces and electronic equipment. It is a major source of environmental and thermal guidance for data center operators and equipment manufacturers. Blanking Panel — A panel installed in unused rack spaces to prevent hot exhaust air from recirculating to server intakes. British Thermal Unit, or BTU — A unit of heat energy commonly used to express the heating or cooling capacity of equipment. Cabinet — An enclosure, also commonly called

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The AI Infrastructure Split Screen: Capital Rush Meets Community Resistance

It would be difficult to construct a more revealing snapshot of the AI infrastructure market than the one delivered in mid-July. In the same news cycle, Csquare completed a billion-dollar initial public offering, Switch was linked to a potential $10 billion IPO, and Databricks reached a reported valuation of $188 billion. At the project level, developers advanced or disclosed campuses measured not in tens or hundreds of megawatts, but in gigawatts—from Meta’s expanding Louisiana complex and Google’s reported Wyoming plans to new Crusoe, QTS, MARA and Tract developments. Yet the same week brought a state-level permitting pause in New York, a decisive project rejection in Palm Beach County, planned protests across more than 20 states, and fresh disputes over parkland, water availability and local control. This is the data center and AI landscape in 2026: capital is abundant but increasingly discriminating; power is more valuable than the underlying real estate; and community consent has become nearly as important as interconnection capacity. Public Markets Put Different Prices on the AI Stack The capital-market headlines illustrated how differently investors are valuing the various layers of AI infrastructure. Csquare priced 50 million shares at $21, raising approximately $1.05 billion and establishing an equity valuation of roughly $3.2 billion. The offering was substantial, but it priced below the proposed $23-to-$27 range, and the shares finished their first trading day slightly below the offer price. Brookfield retained approximately 67% of the company’s voting power following the transaction. That reception contrasts sharply with the valuation being discussed for Switch. The DigitalBridge-backed operator has reportedly engaged Goldman Sachs and JPMorgan for a potential IPO that could raise as much as $10 billion and value Switch near $80 billion, including debt. The transaction remains prospective, but the figure is striking when compared with the $11 billion take-private agreement

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New York State just hit pause on the AI data center boom

The moratorium could result in some “border-hopping,” with enterprises hosting local servers in adjacent states like Pennsylvania, Connecticut, or New Jersey, but that’s not likely to be widespread, Kimball noted. The realistic regional impact will be “more of a slow squeeze rather than a shock,” he said. This could result in tighter colocation availability and firmer pricing in the New York Metropolitan area over the next few years. Cloud providers may also steer new AI capacity to regions like Georgia, Ohio, Texas, and Utah, where power and permitting are more predictable. An inflection point, but more trickle-down than direct impact Indeed, noted Jeremy Roberts, senior director for research and content at Info-Tech Research Group, the moratorium is an “inflection point” and a “way to placate an increasingly angry public,”.

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TeraWulf’s $19B Anthropic Lease Puts Its Brownfield AI Strategy to the Test

He added that the company’s strategy is centered on owning and operating critical infrastructure, maintaining direct relationships with customers and controlling the long-term evolution of its campuses. This Model Differs Significantly from the Previous Abernathy JV TeraWulf and Fluidstack created the Abernathy venture in 2025 to develop a 168-MW critical IT load campus on approximately 120 acres near Abernathy, Texas. The project’s total utility requirement has been described as approximately 240 MW. Fluidstack committed to a 25-year lease at the campus, with Google providing approximately $1.3 billion of credit support for Fluidstack’s obligations. TeraWulf acquired a 50.1% interest in the joint venture through an investment of approximately $450 million. The project subsequently issued $1.3 billion in senior secured notes to support construction and related expenses. The Abernathy agreements were expected to produce approximately $9.5 billion in contracted revenue for the joint venture over the initial 25-year term. Construction has been advancing toward delivery during the second half of 2026. Following the sale, Fluidstack and the other purchasers will control the project. TeraWulf agreed to sell its Abernathy interest for approximately $530 million, compared with its $450 million investment in the joint venture. The consideration is scheduled to be paid in three installments through April 2027, with the proceeds expected to support investment in infrastructure opportunities that TeraWulf intends to own and operate directly. The decision does not necessarily indicate that TeraWulf has become less interested in partnerships with Fluidstack. Fluidstack remains an important tenant at TeraWulf’s Lake Mariner campus in New York, and the companies have built a substantial pipeline of AI infrastructure together. In infrastructure terms, TeraWulf is acting as both developer and capital allocator. It originated the Abernathy project, helped secure the customer and financing structure, advanced construction and is now monetizing its interest before the campus begins

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Comparing Space-Driven Data Center Strategies: Modular Satellites vs. Integrated Rocket Nodes

In addition to developing radiation-tolerant computing, optical communications, deployable solar arrays and orbital thermal-management systems, Cowboy must successfully design, manufacture, test and license a new rocket. Its launch vehicle would require authorization from the Federal Aviation Administration in addition to the approvals needed for the satellite constellation. Cowboy nevertheless enters the race with considerably more capital than Orbital. The company announced a $275 million Series B round in May at a reported $2 billion valuation. Founded in 2024 by Robinhood co-founder Baiju Bhatt, with a focus on space-based solar power before expanding into orbital computing and launch systems. One Hundred Kilowatts Versus One Megawatt The clearest distinction between the two proposals is the capacity assigned to each node. Orbital’s production design calls for approximately 100 kilowatts of computing power per satellite. Cowboy is targeting megawatt-class spacecraft, potentially giving each Stampede node approximately 10 times the power capacity of an Orbital satellite. At their stated maximum scales, Orbital’s 100,000 satellites would provide approximately 10 gigawatts. If Cowboy ultimately achieved one megawatt across all 20,000 Stampede spacecraft, its theoretical aggregate capacity would approach 20 gigawatts. Those figures should be treated as design objectives, not capacity forecasts. Neither company has demonstrated even one operational node at its proposed production power level. Orbital’s smaller satellites may be easier to test and deploy incrementally. The company can begin with a single hosted GPU, progress to a purpose-built prototype and expand as launch economics and customer demand permit. Cowboy’s larger nodes could provide more useful computing capacity with fewer satellites and potentially fewer launches. Combining the rocket stage and data center would also reduce the amount of structural mass that does not directly support power generation or computing. The tradeoff is concentration risk. The failure of a megawatt Cowboy spacecraft would remove considerably more capacity than

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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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