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MOL’s Tiszaújváros steam cracker processes first circular feedstock

MOL Group has completed its first certified production trial using circular feedstock at subsidiary MOL Petrochemicals Co. Ltd. complex in Tiszaújváros, Hungary, advancing the company’s strategic push toward circular economy integration in petrochemical production. Confirmed completed as of Sept. 15, the pilot marked MOL Group’s first use of post-consumer plastic waste-based feedstock in the production […]

MOL Group has completed its first certified production trial using circular feedstock at subsidiary MOL Petrochemicals Co. Ltd. complex in Tiszaújváros, Hungary, advancing the company’s strategic push toward circular economy integration in petrochemical production.

Confirmed completed as of Sept. 15, the pilot marked MOL Group’s first use of post-consumer plastic waste-based feedstock in the production of polyethylene (PE) and polypropylene (PP), the operator said via an e-mailed statement.

The process was conducted under the International Sustainability and Carbon Certification (ISCC) PLUS framework, which ensures traceability and sustainability of bio-based and circular raw materials across complex supply chains.

Péter Császár, senior vice-president of MOL Group Chemicals, said the pilot demonstrates that the company can process circular feedstocks at industrial scale while adhering to a certified mass-balance methodology.

“This is a significant step toward sustainable petrochemicals and strengthens our position in the circular economy across Central and Eastern Europe,” Császár said.

Certified mass-balance approach

As part of the pilot test, MOL Group introduced circular feedstock into the Tiszaújváros complex’s naphtha-based steam cracker, enabling the production of monomers (such as ethylene and propylene), which were then polymerized into PE and PP. MOL used the mass-balance approach, a chain-of-custody model that tracks the quantity of sustainable material in a process where traditional and circular inputs are mixed, allowing certification of the output’s recycled content.

MOL Petrochemicals in Tiszaújváros and fellow MOL subsidiary Slovnaft AS in Bratislava both received ISCC PLUS certification in 2024 for their steam-cracking and polymerization units, allowing such feedstock tracking and product attribution, the company said.

SHAPE TOMORROW strategy

The pilot production run supports MOL Group’s SHAPE TOMORROW strategy, which aims to transform the company’s downstream segment by 2030 through circular economy integration, including plans to process up to 1.5 million tonnes/year (tpy) of alternative feedstock.

MOL said it will continue trials with alternative circular feedstocks while optimizing process configurations to scale commercial operations.

The pilot test comes alongside the operator’s ongoing construction of a new olefins conversion technology (OCT) unit construction at Tiszaújváros that, once operable, will have a production capacity of 100,000 tpy of polymer-grade propylene.

Previously scheduled to reach mechanical completion in 2024, MOL said in its latest annual report that the project’s completion has been delayed to 2026 due to reasons “beyond [the company’s] control.”

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MOL’s Tiszaújváros steam cracker processes first circular feedstock

MOL Group has completed its first certified production trial using circular feedstock at subsidiary MOL Petrochemicals Co. Ltd. complex in Tiszaújváros, Hungary, advancing the company’s strategic push toward circular economy integration in petrochemical production. Confirmed completed as of Sept. 15, the pilot marked MOL Group’s first use of post-consumer plastic

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Network jobs watch: Hiring, skills and certification trends

Desire for higher compensation Improve career prospects Want more interesting work “A robust and engaged tech workforce is essential to keeping enterprises operating at the highest level,” said Julia Kanouse, Chief Membership Officer at ISACA, in a statement. “In better understanding IT professionals’ motivations and pain points, including how these

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F5 to acquire CalypsoAI for advanced AI security capabilities

CalypsoAI’s platform creates what the company calls an Inference Perimeter that protects across models, vendors, and environments. The offers several products including Inference Red Team, Inference Defend, and Inference Observe, which deliver adversarial testing, threat detection and prevention, and enterprise oversight, respectively, among other capabilities. CalypsoAI says its platform proactively

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USA EIA Sees USA Crude Oil Production Dropping in 2026

The U.S. Energy Information Administration (EIA) expects U.S. crude oil production to drop next year, according to its latest short term energy outlook (STEO), which was released on September 9. In its September STEO, the EIA projected that total U.S. crude oil output, including lease condensate, will average 13.44 million barrels per day in 2025 and 13.30 million barrels per day in 2026. This output came in at 13.23 million barrels per day in 2024, the STEO highlighted. The STEO showed that Lower 48 states, excluding the Gulf of America, will provide 11.18 million barrels per day of the projected total in 2025 and 10.96 million barrels per day of the projected total in 2026. Of this 11.18 million barrel per day figure, the STEO expects 6.52 million barrels per day to come from the Permian region, 1.20 million barrels per day to come from the Bakken region, 1.12 million barrels per day to come from the Eagle Ford region, 0.19 million barrels per day to come from the Appalachia region, 0.03 million barrels per day to come from the Haynesville region, and 2.12 million barrels per day to come from the “rest of [the] Lower 48 states”. In 2026, the STEO sees 6.41 million barrels per day coming from the Permian region, 1.20 million barrels per day coming from the Bakken region, 1.10 million barrels per day coming from the Eagle Ford region, 0.17 million barrels per day coming from the Appalachia region, 0.03 million barrels per day to come from the Haynesville region, and 2.05 million barrels per day to come from the “rest of [the] Lower 48 states”. The EIA’s latest STEO showed that, in 2024, the Permian region produced 6.30 million barrels per day, the Bakken region produced 1.23 million barrels per day, the Eagle Ford

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Aramco Signs $11B Jafurah Deal

Aramco announced, in a statement posted on its site recently, that it has signed an $11 billion lease and leaseback deal involving its Jafurah gas processing facilities with a consortium of international investors. The consortium is led by funds managed by Global Infrastructure Partners (GIP), a part of BlackRock, Aramco highlighted in the statement. As part of the transaction, a newly formed subsidiary, Jafurah Midstream Gas Company (JMGC), will lease development and usage rights for the Jafurah Field Gas Plant and the Riyas NGL Fractionation Facility, and lease them back to Aramco for a period of 20 years, the statement noted. JMGC will receive a tariff payable by Aramco in exchange for granting Aramco the exclusive right to receive, process, and treat raw gas from Jafurah, Aramco said in the statement, which highlighted that the company will hold a 51 percent majority stake in JMGC, with the remaining 49 percent held by investors led by GIP. The transaction will not impose any restrictions on Aramco’s production volumes, according to the statement. Aramco noted in the statement that the deal is “expected to close as soon as practicable, subject to customary closing conditions”. Jafurah is the largest non-associated gas development in the Kingdom of Saudi Arabia, Aramco highlighted in the statement, pointing out that it is estimated to contain 229 trillion standard cubic feet of raw gas and 75 billion Stock Tank Barrels of condensate. In the statement, Aramco described Jafurah as a “key component in Aramco’s plans to increase gas production capacity by 60 percent between 2021 and 2030, to meet rising demand”. Aramco President and CEO Amin H. Nasser said in the statement, “Jafurah is a cornerstone of our ambitious gas expansion program, and the GIP-led consortium’s participation as investors in a key component of our unconventional gas operations demonstrates

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Ukraine Claims Strike on Saratov Oil Refinery

Ukraine attacked the Saratov crude-oil refinery in Russia’s Volga region overnight as Western nations seek to push President Vladimir Putin to the negotiating table. Explosions and a fire were registered in the vicinity of the plant, Ukraine’s General Staff said in a Telegram statement on Tuesday, adding that details of the damage are being clarified. The claim couldn’t be independently verified by Bloomberg. Russia’s largest oil producer Rosneft PJSC, which owns the refinery, didn’t respond to a request for comments. Since last month, Ukrainian military forces have intensified drone attacks on Russian energy facilities, including oil refineries, aiming to curb fuel supplies to the front lines. Last week, drones also hit Russia’s largest Baltic oil terminal in Primorsk and claimed strikes on pumping stations feeding another Baltic hub, the Ust-Luga terminal. So far this year, Ukrainian forces targeted oil-processing facilities accounting for around half of all Russian refining capacity, according to Bloomberg calculations. Yet the actual amount of fuel-supply disruption is lower than that. Goldman Sachs Group Inc. estimated that since the start of August the strikes took offline about 300,000 barrels a day of Russian refining capacity. That’s more than 5 percent of the nation’s total active oil-processing capacity, according to Bloomberg estimates. The actual supply disruptions may be less than that as refineries often manage to repel the attacks or minimize their impact, carrying out repairs as quickly as possible. Still, repeated focused strikes on refineries have exacerbated Russia’s seasonal fuel shortage, forcing the government to ban gasoline exports and divert some diesel to the domestic market. Reuters said that, following the recent drone attacks, Russia’s crude-pipeline operator Transneft PJSC has informed the nation’s producers about reducing the volumes of crude it accepts for storage and warned it may reduce oil intake if its infrastructure incurs further damage. Transneft

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Israel and Chevron Ink Pipeline Deal Raising Gas Exports to Egypt

State-owned Israel Natural Gas Lines Ltd (INGL) signed an agreement to allow the Chevron Corp-led Leviathan consortium to use the planned Nitzana pipeline to ship more natural gas from the Israeli offshore field to Egypt, Leviathan co-venturer NewMed Energy LP said Tuesday. Israel’s government approved the Nitzana Project, which consists of the onshore pipeline and supporting infrastructure, about two years ago, as announced by the Energy and Infrastructure Ministry May 8, 2023. Designed to raise Israel’s capacity to export gas to the North African country by six billion cubic meters (211.89 billion cubic feet), the pipeline will stretch about 65 kilometers (40.39 miles) from the Ramat Hovav area to the Egyptian border near Nitzana, according to the ministry’s announcement. Israel’s Natural Gas Authority has allotted at least 33.33 percent or 140 million British thermal units (MMBtu) of the pipeline’s capacity to the Leviathan group, according to NewMed Energy, Leviathan’s biggest owner. On September 1 the Leviathan partners told the Natural Gas Authority and INGL they are prepared to bear the full cost of the Nitzana pipeline’s construction in exchange for 100 percent of the pipeline’s capacity should the other exporters do not exercise their rights to receive an allocation, NewMed Energy said in a regulatory filing Tuesday announcing the Transmission Agreement between Leviathan operator Chevron and INGL. Under the Transmission Agreement, the Leviathan group’s expected share of the Nitzana Project’s budget of approximately $610 million is $92 million, assuming a pipeline capacity allocation of 33.33 percent. Additionally, “Chevron shall pay a transmission tariff comprising a capacity fee and a throughput fee for the gas quantity actually transmitted, in accordance with the standard transmission tariffs in Israel”, NewMed Energy said. “INGL undertook to provide interruptible transmission services of additional quantities of gas over and above the Basic Capacity [140 MMBtu], subject

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Aquaterra Bags INPEX Contracts for Subsea Analysis in Indonesia

INPEX Corp has awarded Aquaterra Energy Ltd analysis contracts to support the Japanese oil and gas company’s drilling campaigns offshore Indonesia. “Under the contract, Aquaterra Energy will deliver multi-phase conductor and riser analysis for a series of deepwater wells in water depths ranging from 600 to 800 meters, providing technical input to support decision-making at the earliest stages of project development”, Norwich, England-based Aquaterra said in a press release Tuesday. “The scopes of work, awarded following competitive tender, include structural analysis and the definition of operating envelopes, technical limits covering weather conditions, rig movement and fatigue. These inputs will help shape INPEX’s planning process, including considerations such as rig selection and equipment specification. “Aquaterra’s early involvement will play a key role in helping define safe operating limits, giving INPEX greater confidence in its technical planning ahead of drilling”. Aquaterra said it will deliver the works over the next six months. “These latest awards follow a series of recent long-term offshore analysis wins globally – including in the UK, Qatar and Egypt – and reflect growing demand from operators for early technical input that supports effective offshore energy project delivery”, Aquaterra said. Aquaterra chief executive George Morrison said the INPEX contracts “reflect the growing demand across the APAC [Asia-Pacific] region for trusted technical insight at the earliest stages of offshore planning”. INPEX is part of a consortium that recently signed a production sharing contract (PSC) for an area off the coast of the Indonesian province of East Java. The Serpang PSC spans 8,497.73 square kilometers (3,280.99 square miles). The water depth is up to 100 meters (328.08 feet), according to INPEX. “The Serpang Working Area is situated in a location where several oil and gas fields have been discovered, approximately 200 kilometers east of Surabaya, the capital city of East Java Province”, INPEX said

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Another week of indecision for oil prices

Oil, fundamental analysis Crude prices hovered in a tight $2.30/bbl range this week as indecision on direction led to consolidation. The market ebbed and flowed with bearish fundamentals pitted against bullish geopolitical events. Attacks, and threats of more sanctions, were pitted against output increases and an across-the-board crude and product inventory build in establishing price direction. Ultimately, the bulls won out. WTI was as low as $61.70/bbl on Friday with its high on Wednesday at $64.10. Brent crude also hit its high on Friday at $68.15/bbl but its low was Monday at $65.50/bbl. Both grades settled higher than last week’s levels while the WTI/Brent spread has widened to ($4.55). Prices fell Monday after the OPEC+ group’s Sunday decision to increase output by 137,000 b/d next month. However, given the smaller volume than the previous increases and, the fact that historically, the group has failed to meet the new quotas, the market actually closed higher than the previous Friday. Tuesday’s Israeli attack on Hamas targets in the heart of Qatar sent prices rallying while Russia’s violation of Poland’s airspace only added more geopolitical drama to the week. The drones were shot down by NATO planes. This week, the UK put sanctions on those who are shipping Russian crude to effectuate an actual curtailment of the flow of Urals to other countries. While Ukraine has attacked various oil ‘infrastructure’ sites in Russia, they have thus far not impacted supply or demand to a great extent. However, the recent drone attack on the Baltic Sea port of Primorsk, a key oil tanker loading facility, could hamper Russian exports. The International Energy Agency (IEA) in Paris raised its forecast for the growth in global oil demand by 60,000 b/d to 740,000 b/d this year. However, the agency also increased its supply forecast for this

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Power shortages are the only thing slowing the data center market

Another major shortage – which should not be news to anyone – is power. Lynch said that it is the primary reason many data centers are moving out of the heavily congested areas, like Northern Virginia and Santa Clara, and into secondary markets. Power is more available in smaller markets than larger ones. “If our client needs multi-megawatt capacity in Silicon Valley, we’re being told by the utility providers that that capacity will not be available for up to 10 years from now,” so out of necessity, many have moved to secondary markets, such as Hillsborough, Oregon, Reno, Nevada, and Columbus, Ohio. The growth of hyperscalers as well as AI is driving up the power requirements of facilities further into the multi-megawatt range. The power industry moves at a very different pace than the IT world, much slower and more deliberate. Lynch said the lead time for equipment makes it difficult to predict when some large scale, ambitious data centers can be completed. A multi-megawatt facility may even require new transmission lines to be built out as well. This translates into longer build times for new data centers. CBRE found that the average data center now takes about three years to complete, up from 2 years just a short time ago. Intel, AMD, and Nvidia haven’t even laid out a road map for three years, but with new architectures coming every year, a data center risks being obsolete by the time it’s completed. However, what’s the alternative? To wait? Customers will never catch up at that rate, Lynch said.   That is simply not a viable option, so development and construction must go on even with short supplies of everything from concrete and steel to servers and power transformers.

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Arista continues to defy expectations, build enterprise momentum

During her keynote, Ullal noted Arista is not only selling high-speed switches for AI data centers but also leveraging its own technology to create a new category of “AI centers” that simplify network management and operations, with a goal of 60% to 80% growth in the AI market. Arista has its sights set on enterprise expansion Arista hired Todd Nightingale as its new president a couple of month ago, and the reason should be obvious to industry watchers: to grow the enterprise business. Nightingale recently served as CEO of Fastly, but he is best known for his tenure as Cisco. He joined when Cisco acquired Meraki, where he was the CEO. Ullal indicated the campus and WAN business would grow from the current $750 million to $800 million run rate to $1.25 billion, which is a whopping 60% growth. Some of this will come from VeloCloud being added to Arista’s numbers, but not all of it. Arista’s opportunity in campus and WAN is in bringing its high performance, resilient networking to this audience. In a survey I conducted last year, 93% of respondents stated the network is more important to business operations than it was two years ago. During his presentation, Nightingale talked about this shift when he said: “There is no longer such a thing as a network that is not mission critical. We think of mission critical networks for military sites and tier one hospitals, but every hotel and retailer who has their Wi-Fi go down and can’t transact business will say the network is critical.” Also, with AI, inferencing traffic is expected to put a steady load on the network, and any kind of performance hiccup will have negative business ramifications. Historically, Arista’s value proposition for companies outside the Fortune 2000 was a bit of a solution

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Arista touts liquid cooling, optical tech to reduce power consumption for AI networking

Both technologies will likely find a role in future AI and optical networks, experts say, as both promise to reduce power consumption and support improved bandwidth density. Both have advantages and disadvantages as well – CPOs are more complex to deploy given the amount of technology included in a CPO package, whereas LPOs promise more simplicity.  Bechtolsheim said that LPO can provide an additional 20% power savings over other optical forms. Early tests show good receiver performance even under degraded conditions, though transmit paths remain sensitive to reflections and crosstalk at the connector level, Bechtolsheim added. At the recent Hot Interconnects conference, he said: “The path to energy-efficient optics is constrained by high-volume manufacturing,” stressing that advanced optics packaging remains difficult and risky without proven production scale.  “We are nonreligious about CPO, LPO, whatever it is. But we are religious about one thing, which is the ability to ship very high volumes in a very predictable fashion,” Bechtolsheim said at the investor event. “So, to put this in quantity numbers here, the industry expects to ship something like 50 million OSFP modules next calendar year. The current shipment rate of CPO is zero, okay? So going from zero to 50 million is just not possible. The supply chain doesn’t exist. So, even if the technology works and can be demonstrated in a lab, to get to the volume required to meet the needs of the industry is just an incredible effort.” “We’re all in on liquid cooling to reduce power, eliminating fan power, supporting the linear pluggable optics to reduce power and cost, increasing rack density, which reduces data center footprint and related costs, and most importantly, optimizing these fabrics for the AI data center use case,” Bechtolsheim added. “So what we call the ‘purpose-built AI data center fabric’ around Ethernet

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Network and cloud implications of agentic AI

The chain analogy is critical here. Realistic uses of AI agents will require core database access; what can possibly make an AI business case that isn’t tied to a company’s critical data? The four critical elements of these applications—the agent, the MCP server, the tools, and the data— are all dragged along with each other, and traffic on the network is the linkage in the chain. How much traffic is generated? Here, enterprises had another surprise. Enterprises told me that their initial view of their AI hosting was an “AI cluster” with a casual data link to their main data center network. With AI agents, they now see smaller AI servers actually installed within their primary data centers, and all the traffic AI creates, within the model and to and from it, now flows on the data center network. Vendors who told enterprises that AI networking would have a profound impact are proving correct. You can run a query or perform a task with an agent and have that task parse an entire database of thousands or millions of records. Someone not aware of what an agent application implies in terms of data usage can easily create as much traffic as a whole week’s normal access-and-update would create. Enough, they say, to impact network capacity and the QoE of other applications. And, enterprises remind us, if that traffic crosses in/out of the cloud, the cloud costs could skyrocket. About a third of the enterprises said that issues with AI agents generated enough traffic to create local congestion on the network or a blip in cloud costs large enough to trigger a financial review. MCP tool use by agents is also a major security and governance headache. Enterprises point out that MCP standards haven’t always required strong authentication, and they also

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There are 121 AI processor companies. How many will succeed?

The US currently leads in AI hardware and software, but China’s DeepSeek and Huawei continue to push advanced chips, India has announced an indigenous GPU program targeting production by 2029, and policy shifts in Washington are reshaping the playing field. In Q2, the rollback of export restrictions allowed US companies like Nvidia and AMD to strike multibillion-dollar deals in Saudi Arabia.  JPR categorizes vendors into five segments: IoT (ultra-low-power inference in microcontrollers or small SoCs); Edge (on-device or near-device inference in 1–100W range, used outside data centers); Automotive (distinct enough to break out from Edge); data center training; and data center inference. There is some overlap between segments as many vendors play in multiple segments. Of the five categories, inference has the most startups with 90. Peddie says the inference application list is “humongous,” with everything from wearable health monitors to smart vehicle sensor arrays, to personal items in the home, and every imaginable machine in every imaginable manufacturing and production line, plus robotic box movers and surgeons.  Inference also offers the most versatility. “Smart devices” in the past, like washing machines or coffee makers, could do basically one thing and couldn’t adapt to any changes. “Inference-based systems will be able to duck and weave, adjust in real time, and find alternative solutions, quickly,” said Peddie. Peddie said despite his apparent cynicism, this is an exciting time. “There are really novel ideas being tried like analog neuron processors, and in-memory processors,” he said.

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Data Center Jobs: Engineering, Construction, Commissioning, Sales, Field Service and Facility Tech Jobs Available in Major Data Center Hotspots

Each month Data Center Frontier, in partnership with Pkaza, posts some of the hottest data center career opportunities in the market. Here’s a look at some of the latest data center jobs posted on the Data Center Frontier jobs board, powered by Pkaza Critical Facilities Recruiting. Looking for Data Center Candidates? Check out Pkaza’s Active Candidate / Featured Candidate Hotlist (and coming soon free Data Center Intern listing). Data Center Critical Facility Manager Impact, TX There position is also available in: Cheyenne, WY; Ashburn, VA or Manassas, VA. This opportunity is working directly with a leading mission-critical data center developer / wholesaler / colo provider. This firm provides data center solutions custom-fit to the requirements of their client’s mission-critical operational facilities. They provide reliability of mission-critical facilities for many of the world’s largest organizations (enterprise and hyperscale customers). This career-growth minded opportunity offers exciting projects with leading-edge technology and innovation as well as competitive salaries and benefits. Electrical Commissioning Engineer New Albany, OH This traveling position is also available in: Richmond, VA; Ashburn, VA; Charlotte, NC; Atlanta, GA; Hampton, GA; Fayetteville, GA; Cedar Rapids, IA; Phoenix, AZ; Dallas, TX or Chicago, IL. *** ALSO looking for a LEAD EE and ME CxA Agents and CxA PMs. *** Our client is an engineering design and commissioning company that has a national footprint and specializes in MEP critical facilities design. They provide design, commissioning, consulting and management expertise in the critical facilities space. They have a mindset to provide reliability, energy efficiency, sustainable design and LEED expertise when providing these consulting services for enterprise, colocation and hyperscale companies. This career-growth minded opportunity offers exciting projects with leading-edge technology and innovation as well as competitive salaries and benefits.  Data Center Engineering Design ManagerAshburn, VA This opportunity is working directly with a leading mission-critical data center developer /

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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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