Multicloud explained: Why it pays to diversify your cloud strategy

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Multicloud explained: Why it pays to diversify your cloud strategy

Flexibility. While most cloud vendors pitch themselves as a total cloud solution, the truth is that each major offering has strengths and weaknesses, and companies may not want to commit to one vendor if they have multiple cloud use cases. For instance, an organization might use Microsoft’s Azure cloud for its analytics capabilities, but Amazon’s AWS […]

Flexibility. While most cloud vendors pitch themselves as a total cloud solution, the truth is that each major offering has strengths and weaknesses, and companies may not want to commit to one vendor if they have multiple cloud use cases.

For instance, an organization might use Microsoft’s Azure cloud for its analytics capabilities, but Amazon’s AWS to develop Alexa Skills applications. Even workloads developed to be theoretically vendor neutral may see better performance on different cloud platforms.

Geographic proximity and network performance. The whole notion of the cloud entices you to think of a cloud server as being somewhere “out there,” unconstrained by the limits of physical reality. In practice, some cloud vendors are going to be able to offer cloud servers that are physically closer to your users and customers than others, or that have a network connection to them with lower latency. You might want to turn to those providers for mission-critical, high-performance needs while using others as appropriate. And having clouds in different geographic regions can have regulatory as well as performance benefits, as you can store and secure data as appropriate for various data protection laws.

Keeping your eggs in multiple baskets. If your cloud provider were to suffer a massive and prolonged outage, that would have major repercussions on your business. While that’s pretty unlikely if you go with one of the hyperscalers, it’s possible with a more specialized vendor.

And even with the big players, you may discover annoyances, performance problems, unanticipated charges, or other issues that might cause you to rethink your relationship. Using services from multiple vendors makes it easier to end a relationship that feels like it’s gone stale without you having to retool your entire infrastructure.

It can be a great means to determine which cloud providers are best for which workloads. And it can’t hurt as a negotiating tactic when contracts expire or when you’re considering adding new cloud services.

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A timeline of Broadcom/VMware and Siemens licensing dispute

June 24: VMware responds, saying that Siemens distributed infringing VMware products to its US subsidiaries in violation of US copyright law by accessing VMware’s US server. July 1: Nah uh, says Siemens. First, any actions taken by the parent company occurred in Germany. Also, downloading allegedly copyrighted software does not

JPMorgan launches carbon market blockchain app

Dive Brief: JPMorgan Chase is working to allow voluntary carbon markets to issue blockchain tokens at the registry level that represent ownership of carbon credits, permitting market participants to issue, transfer and retire credits, the bank announced Wednesday. JPMorgan is currently exploring testing processes with carbon registries from S&P Global

IBM Power11 challenges x86 and GPU giants with security-first server strategy

The IBM Power Cyber Vault solution is designed to provide protection against cyberattacks such as data corruption and encryption with proactive immutable snapshots that are automatically captured, stored, and tested on a custom-defined schedule, IBM said. Power11 also uses NIST-approved built-in quantum-safe cryptography designed to help protect systems from harvest-now, decrypt-later attacks

With Power 11, IBM bets big on security and reliability instead of taking Nvidia head-on

Working around the competition The launch invites comparisons with other AI chips on the market, but analysts say IBM’s Power11 servers are built for targeted use in specific industries. “These systems don’t compete on raw performance with offerings from Intel or Nvidia, but IBM can offer a stronger value proposition

XCF Targets $1B Global SAF Production Portfolio

XCF Global Inc. announced Thursday an investment plan of nearly $1 billion over the next three years to build sustainable aviation fuel (SAF) production facilities, with most of its in-the-pipeline projects in the United States. The package includes $350 million already invested in New Rise Reno in Nevada, which has a nameplate capacity of 38 million gallons a year. It started production early this year. The announcement follows XCF Global Capital Inc. and Focus Impact BH3 Acquisition Co.’s completion of their merger, creating what they said is the first publicly traded pure-play SAF producer in the U.S. Under its U.S. expansion plan, XCF has acquired three sites “ready for development”, it said in an online statement Thursday. The projects are planned to each have a nameplate capacity of 40 million gallons per annum. XCF expects to put them into operation by 2028. Expected to be completed 2027, New Rise Reno 2 will rise next to the existing plant, “enabling economies of scale and leveraging shared utilities and logistics infrastructure”, XCF said. Another project in Ft. Myers, Florida, will be built on a site with access to port infrastructure. It is expected to be completed 2028. The third, also targeted for start-up 2028, will rise in Wilson, North Carolina, eyeing East Coast markets. “These new sites are expected to replicate New Rise Reno’s modular, patent-pending site design and bundled technology stack, allowing for rapid deployment, flexible production, and capital-efficient scaling”, XCF said. “Each facility is expected to have the ability to produce multiple renewable fuel products, including SAF and renewable diesel, supporting a multi-product revenue strategy that maximizes plant utilization and financial performance”. XCF is also pursuing other “high-potential” markets, the statement said. Last month it announced a non-binding memorandum of understanding with Continual Renewable Ventures for an Australian SAF and

ADNOC Bags 3-Year LNG Order from SEFE

ADNOC Gas PLC will supply Germany’s state-owned SEFE Securing Energy for Europe GmbH 700,000 metric tons a year of liquefied natural gas (LNG) for three years starting 2025, the companies said Thursday. Abu Dhabi National Oil Co.’s gas processing and sales arm will source the LNG from the Das Island liquefaction facility, which has a capacity of six million metric tons per annum (MMtpa). The contract is valued about $400 million. “Das Island’s LNG plant has shipped over 3,500 LNG cargoes worldwide since starting operations in 1977, strengthening ADNOC Gas’ long-term relationships with key global energy partners”, a joint statement said. SEFE chief commercial officer Frederic Barnaud commented, “This new medium-term LNG contract builds on the long-term supply agreement with ADNOC that we signed last year, thereby adding another flexible source of LNG to our portfolio – to the benefit of both Europe’s security of supply and our global market trading activities”. In November 2024, ADNOC and SEFE announced an agreement under which ADNOC will deliver one MMtpa of LNG from the Ruwais LNG project to SEFE for 15 years. Targeted to start production 2028, the 9.6-MMtpa facility on the Persian Gulf coast would more than double ADNOC’s LNG output. ADNOC announced a positive final investment decision June 2024. SEFE-Venture Global Deal Separately on Wednesday SEFE and Venture Global Inc. said they had finalized an agreement to increase SEFE’s offtake from the CP2 LNG project in Cameron Parish, Louisiana, to three MMtpa. The deal adds 750,000 metric tons a year to their 2023 agreement. “Venture Global is expected to become Germany’s largest LNG supplier, with a combined 5 MTPA [million metric tons per annum] of 20-year offtake agreements signed with SEFE and EnBW”, the Arlington, Virginia-based developer said in a statement online. “In addition to its existing long-term agreements, Venture Global

Aker Solutions Secures Troll C Preparation Job for Fram Sor Tie-In

Aker Solutions ASA has bagged a contract from its compatriot Equinor ASA to prepare the topside of Troll C to receive and process production from the Fram Sor subsea tie-in project. The company said in a media release the deal is valued between NOK 0.5 billion ($49.6 million) and NOK 1.5 billion ($148.9 million). Fram Sor is planned as a subsea connection to Troll C, leveraging the platform’s current processing capacity. Situated 20 kilometers (12.4 miles) north of Troll C, the tie-in involves modifications to Troll C’s topside. The scope covers engineering, procurement, construction, installation, and commissioning, along with services for the new subsea templates, Aker Solutions said. The company added that it had previously carried out the front-end engineering and design for the project, led by its office in Bergen. Project management, detailed engineering, procurement, and shop engineering will be managed by Aker Solutions’ Bergen and Mumbai offices. Fabrication is planned at the company’s yard in Egersund. The project will begin immediately, with production set to start at the end of 2029. The contract will be recorded in the Life Cycle segment as order intake for the third quarter of 2025. Equinor and its partners committed over NOK 21 billion ($2.1 billion) to the Fram Sor subsea development. According to Equinor, Fram Sor is a combined development of several discoveries, which will export oil and gas via Troll C. The recoverable volumes are estimated at 116 million barrels of oil equivalent, with 75 percent being oil and 25 percent gas. The plan for development and operation, already submitted to Energy Minister Terje Aasland, includes a first for the Norwegian Continental Shelf, according to Equinor. That is, Fram Sor will use all-electric Christmas trees that eliminate the need for hydraulic fluid supplied from the platform and improve the monitoring capabilities

NATO Innovation Fund, Norway Invest in Robotic Offshore Assets Maintenance

The NATO Innovation Fund (NIF) said it had led a financing round with participation from Norwegian sovereign investment fund Investinor AS for Kongsberg Ferrotech AS, a Norwegian company offering robotic solutions for the maintenance and repair of offshore infrastructure including oil and gas facilities. The support will help Kongsberg Ferrotech, whose offerings have already been deployed by energy giants, grow its reach across North Atlantic Treaty Organization countries, according to a statement posted on NIF’s website. For pipelines, Kongsberg Ferrotech has developed a set of robotic solutions called Nautilus to reduce inspection and repair time to just days. “With about 160,000-kilometer subsea pipelines around the world, unmitigated leaks are causing environmental spills on a daily basis. A typical inspection and repair campaign using conventional technology can take from weeks to months – involving very expensive vessels, manual divers and a number of suppliers. The repair cost alone runs into millions of dollars. If production shut-down is required, the total cost can easily reach tens of millions”, the statement said. With diver-free Nautilus, “most repairs can be performed without affecting the production, offering significant cost savings and up to 70 percent reduction in response time and C02 footprint”, the statement said. It added, “Kongsberg Ferrotech enables in-situ repair of critical submerged assets – extending their life – by creating a water-evacuated ‘dry habitat’ at depth. Its patented technology can seal and evacuate water around areas to be repaired”. “The company’s unique robotic platform – where both inspection and repair are performed in the same operation and in the same dive – can address a wide range of subsea assets from pipelines and risers to wind-turbine monopiles and merchant marine vessels”, the statement said. “When a defect is identified, the robot can deliver a specifically tailored repair; either a ‘cold’, non-metallic repair or a hot, 3D

SEFE Increases LNG Purchase from Venture Global

Venture Global, Inc. and Securing Energy for Europe GmbH (SEFE) have entered into an agreement under which SEFE’s subsidiary, SEFE Energy GmbH, will purchase an additional 0.75 million metric tons per annum (mtpa) of liquefied natural gas (LNG) from CP2 LNG for 20 years. The agreement amends the existing sales and purchase agreement signed by the companies in 2023, increasing the total volume of LNG purchased by SEFE from CP2 LNG to 3.0 mtpa, Venture Global said in a news release. “Venture Global is thrilled to expand our strategic partnership with Germany and SEFE and play a leading role in ensuring security of energy supply and affordability for not only Germany but the rest of the European gas market,” Venture Global CEO Mike Sabel said. German state-owned energy firm SEFE is one of the LNG customers for CP2, Venture Global’s third project, in Europe, Asia, and the rest of the world, Venture Global said. To date, approximately 11.5 mtpa of CP2 phase one has been sold, raising the total contracted capacity for all of Venture Global’s projects to 41.5 mtpa, the company said. Venture Global said it is expected to become Germany’s largest LNG supplier, with a combined 5 MTPA of 20-year offtake agreements signed with SEFE and EnBW. In addition to its existing long-term agreements, Venture Global has supplied Germany with almost 80 cargoes of LNG from its Calcasieu Pass and Plaquemines LNG facilities, enough to power 8 million German homes for one year. Last week, Venture Global entered into a new 20-year sales and purchase agreement with PETRONAS LNG Ltd. (PLL), a subsidiary of the Malaysian state-owned oil and gas company, PETRONAS. Under the terms of the agreement, PETRONAS will purchase 1 mtpa of LNG from CP2 LNG for 20 years. This builds upon Venture Global’s existing agreement

Seatrium Wins FSRU Conversion Contract from Karpowership

Singapore-based Seatrium Limited said it was awarded a floating storage and regasification unit (FSRU) conversion contract by Kinetics, an energy transition intiative by Turkish mobile power generation firm Karpowership. The project involves the conversion of a liquefied natural gas (LNG) carrier into an FSRU named LNGT Turkiye, Seatrium said in a news release. The scope of work includes the installation of a regasification module, a spread-mooring system, and integration of key supporting systems such as cargo handling, offloading, utility, electrical, and automation systems. The project is scheduled to begin in the third quarter, according to the release. Financial terms of the contract were not disclosed. The contract follows Kinetics’ confirmation of the option for a fourth FSRU conversion project with Seatrium announced in April 2024, as well as the award of three LNG carrier conversions into FSRUs for the company, with an option for a fourth project, Seatrium said. Seatrium Executive Vice President for Repairs and Upgrades Alvin Gan said, “We truly appreciate the trust from Kinetics in awarding us this important seventh FSRU project. This contract is a testament to the successful strategic partnership between our companies, that includes four projects delivered to date: Karmol LNGT Powership Africa, Asia, Europe, and most recently, Antarctica. Presently, two more FSRU conversion projects for Kinetics are in progress at our yard, with deliveries scheduled later this year and in the first quarter of 2026”. “These projects underscore Seatrium’s unwavering commitment to excellence, innovation, and customer satisfaction, further cementing our position as a pioneer and market leader in the specialized FSRU conversion sector,” Gan added. Kinetics CEO Mehmet Katmer said, “We are pleased to strengthen our excellent partnership with Seatrium as we expand our FSRU fleet to meet the highest industry standards. Seatrium’s proven track record, engineering expertise, and technical capabilities make them

Enterprises will strengthen networks to take on AI, survey finds

Private data centers: 29.5% Traditional public cloud: 35.4% GPU as a service specialists: 18.5% Edge compute: 16.6% “There is little variation from training to inference, but the general pattern is workloads are concentrated a bit in traditional public cloud and then hyperscalers have significant presence in private data centers,” McGillicuddy explained. “There is emerging interest around deploying AI workloads at the corporate edge and edge compute environments as well, which allows them to have workloads residing closer to edge data in the enterprise, which helps them combat latency issues and things like that. The big key takeaway here is that the typical enterprise is going to need to make sure that its data center network is ready to support AI workloads.” AI networking challenges The popularity of AI doesn’t remove some of the business and technical concerns that the technology brings to enterprise leaders. According to the EMA survey, business concerns include security risk (39%), cost/budget (33%), rapid technology evolution (33%), and networking team skills gaps (29%). Respondents also indicated several concerns around both data center networking issues and WAN issues. Concerns related to data center networking included: Integration between AI network and legacy networks: 43% Bandwidth demand: 41% Coordinating traffic flows of synchronized AI workloads: 38% Latency: 36% WAN issues respondents shared included: Complexity of workload distribution across sites: 42% Latency between workloads and data at WAN edge: 39% Complexity of traffic prioritization: 36% Network congestion: 33% “It’s really not cheap to make your network AI ready,” McGillicuddy stated. “You might need to invest in a lot of new switches and you might need to upgrade your WAN or switch vendors. You might need to make some changes to your underlay around what kind of connectivity your AI traffic is going over.” Enterprise leaders intend to invest in infrastructure

CoreWeave acquires Core Scientific for $9B to power AI infrastructure push

Such a shift, analysts say, could offer short-term benefits for enterprises, particularly in cost and access, but also introduces new operational risks. “This acquisition may potentially lower enterprise pricing through lease cost elimination and annual savings, while improving GPU access via expanded power capacity, enabling faster deployment of Nvidia chipsets and systems,” said Charlie Dai, VP and principal analyst at Forrester. “However, service reliability risks persist during this crypto-to-AI retrofitting.” This also indicates that struggling vendors such as Core Scientific and similar have a way to cash out, according to Yugal Joshi, partner at Everest Group. “However, it does not materially impact the availability of Nvidia GPUs and similar for enterprises,” Joshi added. “Consolidation does impact the pricing power of vendors.” Concerns for enterprises Rising demand for AI-ready infrastructure can raise concerns among enterprises, particularly over access to power-rich data centers and future capacity constraints. “The biggest concern that CIOs should have with this acquisition is that mature data center infrastructure with dedicated power is an acquisition target,” said Hyoun Park, CEO and chief analyst at Amalgam Insights. “This may turn out to create challenges for CIOs currently collocating data workloads or seeking to keep more of their data loads on private data centers rather than in the cloud.”

CoreWeave achieves a first with Nvidia GB300 NVL72 deployment

The deployment, Kimball said, “brings Dell quality to the commodity space. Wins like this really validate what Dell has been doing in reshaping its portfolio to accommodate the needs of the market — both in the cloud and the enterprise.” Although concerns were voiced last year that Nvidia’s next-generation Blackwell data center processors had significant overheating problems when they were installed in high-capacity server racks, he said that a repeat performance is unlikely. Nvidia, said Kimball “has been very disciplined in its approach with its GPUs and not shipping silicon until it is ready. And Dell almost doubles down on this maniacal quality focus. I don’t mean to sound like I have blind faith, but I’ve watched both companies over the last several years be intentional in delivering product in volume. Especially as the competitive market starts to shape up more strongly, I expect there is an extremely high degree of confidence in quality.” CoreWeave ‘has one purpose’ He said, “like Lambda Labs, Crusoe and others, [CoreWeave] seemingly has one purpose (for now): deliver GPU capacity to the market. While I expect these cloud providers will expand in services, I think for now the type of customer employing services is on the early adopter side of AI. From an enterprise perspective, I have to think that organizations well into their AI journey are the consumers of CoreWeave.” “CoreWeave is also being utilized by a lot of the model providers and tech vendors playing in the AI space,” Kimball pointed out. “For instance, it’s public knowledge that Microsoft, OpenAI, Meta, IBM and others use CoreWeave GPUs for model training and more. It makes sense. These are the customers that truly benefit from the performance lift that we see from generation to generation.”

Oracle to power OpenAI’s AGI ambitions with 4.5GW expansion

“For CIOs, this shift means more competition for AI infrastructure. Over the next 12–24 months, securing capacity for AI workloads will likely get harder, not easier. Though cost is coming down but demand is increasing as well, due to which CIOs must plan earlier and build stronger partnerships to ensure availability,” said Pareekh Jain, CEO at EIIRTrend & Pareekh Consulting. He added that CIOs should expect longer wait times for AI infrastructure. To mitigate this, they should lock in capacity through reserved instances, diversify across regions and cloud providers, and work with vendors to align on long-term demand forecasts. “Enterprises stand to benefit from more efficient and cost-effective AI infrastructure tailored to specialized AI workloads, significantly lower their overall future AI-related investments and expenses. Consequently, CIOs face a critical task: to analyze and predict the diverse AI workloads that will prevail across their organizations, business units, functions, and employee personas in the future. This foresight will be crucial in prioritizing and optimizing AI workloads for either in-house deployment or outsourced infrastructure, ensuring strategic and efficient resource allocation,” said Neil Shah, vice president at Counterpoint Research. Strategic pivot toward AI data centers The OpenAI-Oracle deal comes in stark contrast to developments earlier this year. In April, AWS was reported to be scaling back its plans for leasing new colocation capacity — a move that AWS Vice President for global data centers Kevin Miller described as routine capacity management, not a shift in long-term expansion plans. Still, these announcements raised questions around whether the hyperscale data center boom was beginning to plateau. “This isn’t a slowdown, it’s a strategic pivot. The era of building generic data center capacity is over. The new global imperative is a race for specialized, high-density, AI-ready compute. Hyperscalers are not slowing down; they are reallocating their capital to

Arista Buys VeloCloud to reboot SD-WANs amid AI infrastructure shift

What this doesn’t answer is how Arista Networks plans to add newer, security-oriented Secure Access Service Edge (SASE) capabilities to VeloCloud’s older SD-WAN technology. Post-acquisition, it still has only some of the building blocks necessary to achieve this. Mapping AI However, in 2025 there is always more going on with networking acquisitions than simply adding another brick to the wall, and in this case it’s the way AI is changing data flows across networks. “In the new AI era, the concepts of what comprises a user and a site in a WAN have changed fundamentally. The introduction of agentic AI even changes what might be considered a user,” wrote Arista Networks CEO, Jayshree Ullal, in a blog highlighting AI’s effect on WAN architectures. “In addition to people accessing data on demand, new AI agents will be deployed to access data independently, adapting over time to solve problems and enhance user productivity,” she said. Specifically, WANs needed modernization to cope with the effect AI traffic flows are having on data center traffic. Sanjay Uppal, now VP and general manager of the new VeloCloud Division at Arista Networks, elaborated. “The next step in SD-WAN is to identify, secure and optimize agentic AI traffic across that distributed enterprise, this time from all end points across to branches, campus sites, and the different data center locations, both public and private,” he wrote. “The best way to grab this opportunity was in partnership with a networking systems leader, as customers were increasingly looking for a comprehensive solution from LAN/Campus across the WAN to the data center.”

Data center capacity continues to shift to hyperscalers

However, even though colocation and on-premises data centers will continue to lose share, they will still continue to grow. They just won’t be growing as fast as hyperscalers. So, it creates the illusion of shrinkage when it’s actually just slower growth. In fact, after a sustained period of essentially no growth, on-premises data center capacity is receiving a boost thanks to genAI applications and GPU infrastructure. “While most enterprise workloads are gravitating towards cloud providers or to off-premise colo facilities, a substantial subset are staying on-premise, driving a substantial increase in enterprise GPU servers,” said John Dinsdale, a chief analyst at Synergy Research Group.

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.

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

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

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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