Stay Ahead, Stay ONMINE

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 […]

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 design to combine human expertise and contextual intelligence on one side with AI-based techniques on the other.

“When automated red teaming is complemented by targeted human insight, the resulting defense strategy becomes significantly more resilient,” writes OpenAI in the first paper (Ahmad et al., 2024).

The company’s premise is that using external testers to identify the most high-impact real-world scenarios, while also evaluating AI outputs, leads to continuous model improvements. OpenAI contends that combining these methods delivers a multi-layered defense for their models that identify potential vulnerabilities quickly. Capturing and improving models with the human contextual intelligence made possible by a human-in-the-middle design is proving essential for red-teaming AI models.

Why red teaming is the strategic backbone of AI security

Red teaming has emerged as the preferred method for iteratively testing AI models. This kind of testing simulates a variety of lethal and unpredictable attacks and aims to identify their most potent and weakest points. Generative AI (gen AI) models are difficult to test through automated means alone, as they mimic human-generated content at scale. The practices described in OpenAI’s two papers seek to close the gaps automated testing alone leaves, by measuring and verifying a model’s claims of safety and security.

In the first paper (“OpenAI’s Approach to External Red Teaming”) OpenAI explains that red teaming is “a structured testing effort to find flaws and vulnerabilities in an AI system, often in a controlled environment and collaboration with developers” (Ahmad et al., 2024). Committed to leading the industry in red teaming, the company had over 100 external red teamers assigned to work across a broad base of adversarial scenarios during the pre-launch vetting of GPT-4 prior to launch.

Research firm Gartner reinforces the value of red teaming in its forecast, predicting that IT spending on gen AI will soar from $5 billion in 2024 to $39 billion by 2028. Gartner notes that the rapid adoption of gen AI and the proliferation of LLMs is significantly expanding these models’ attack surfaces, making red teaming essential in any release cycle.

Practical insights for security leaders

Even though security leaders have been quick to see the value of red teaming, few are following through by making a commitment to get it done. A recent Gartner survey finds that while 73% of organizations recognize the importance of dedicated red teams, only 28% actually maintain them. To close this gap, a simplified framework is needed that can be applied at scale to any new model, app, or platform’s red teaming needs.

In its paper on external red teaming OpenAI defines four key steps for using a human-in-the-middle design to make the most of human insights:

  • Defining testing scope and teams: Drawing on subject matter experts and specialists across key areas of cybersecurity, regional politics, and natural sciences, OpenAI targets risks that include voice mimicry and bias. The ability to recruit cross-functional experts is, therefore, crucial. (To gain an appreciation for how committed OpenAI is to this methodology and its implications for stopping deepfakes, please see our article “GPT-4: OpenAI’s shield against $40B deepfake threat to enterprises.”)
  • Selecting model versions for testing, then iterating them across diverse teams: Both of OpenAI’s papers emphasize that cycling red teams and models using an iterative approach delivers the most insightful results. Allowing each red team to cycle through all models is conducive to greater team learning of what is and isn’t working.
  • Clear documentation and guidance: Consistency in testing requires well-documented APIs, standardized report formats, and explicit feedback loops. These are essential elements for successful red teaming.
  • Making sure insights translate into practical and long-lasting mitigations: Once red teams log vulnerabilities, they drive targeted updates to models, policies and operational plans — ensuring security strategies evolve in lockstep with emerging threats.

Scaling adversarial testing with GPT-4T: The next frontier in red teaming

AI companies’ red teaming methodologies are demonstrating that while human expertise is resource-intensive, it remains crucial for in-depth testing of AI models.

In OpenAI’s second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning” (Beutel et al., 2024), OpenAI addresses the challenge of scaling adversarial testing using an automated, multi-pronged approach that combines human insights with AI-generated attack strategies.

The core of this methodology is GPT-4T, a specialized variant of the GPT-4 model engineered to produce a wide range of adversarial scenarios.

Here’s how each component of the methodology contributes to a stronger adversarial testing framework:

  • Goal diversification. OpenAI describes how it is using GPT-4T to create a broad spectrum of scenarios, starting with initially benign-seeming prompts and progressing to more sophisticated phishing campaigns. Goal diversification focuses on anticipating and exploring the widest possible range of potential exploits. By using GPT-4T’s capacity for diverse language generation, OpenAI contends that red teams avoid tunnel vision and stay focused on probing for vulnerabilities that manual-only methods miss.
  • Reinforcement learning (RL). A multi-step RL framework rewards the discovery of new and previously unseen vulnerabilities. The purpose is to train the automated red team by improving each iteration. This enables security leaders to refocus on genuine risks rather than sifting through volumes of low-impact alerts. It aligns with Gartner’s projection of a 30% drop in false positives attributable to gen AI in application security testing by 2027. OpenAI writes, “Our multi-step RL approach systematically rewards the discovery of newly identified vulnerabilities, driving continuous improvement in adversarial testing.”
  • Auto-generated rewards: OpenAI defines this as a system that tracks and updates scores for partial successes by red teams, assigning incremental rewards for identifying each unprotected weak area of a model.

Securing the future of AI: Key takeaways for security leaders

OpenAI’s recent papers show why a structured, iterative process that combines internal and external testing delivers the insights needed to keep improving models’ accuracy, safety, security and quality.

Security leaders’ key takeaways from these papers should include: 

Go all-in and adopt a multi-pronged approach to red teaming. The papers emphasize the value of combining external, human-led teams with real-time simulations of AI attacks generated randomly, as they reflect how chaotic intrusion attempts can be. OpenAI contends that while humans excel at spotting context-specific gaps, including biases, automated systems identify weaknesses that emerge only under stress testing and repeated sophisticated attacks.

Test early and continuously throughout model dev cycles. The white papers make a compelling argument against waiting for production-ready models and instead beginning testing with early-stage versions. The goal is to find emerging risks and retest later to make sure the gaps in models were closed before launch.

Whenever possible, streamline documentation and feedback with real-time feedback loops. Standardized reporting and well-documented APIs, along with explicit feedback loops, help convert red team findings into actionable, trackable mitigations. OpenAI emphasizes the need to get this process in place before beginning red teaming, to accelerate fixes and remediation of problem areas.

Using real-time reinforcement learning is critically important, as is the future of AI red teaming. OpenAI makes the case for automating frameworks that reward discoveries of new attack vectors as a core part of the real-time feedback loops. The goal of RL is to create a continuous loop of improvement. 

Don’t settle for anything less than actionable insights from the red team process. It’s essential to treat every red team discovery or finding as a catalyst for updating security strategies, improving incident response plans, and revamping guidelines as required.

Budget for the added expense of enlisting external expertise for red teams. A central premise of OpenAI’s approach to red teaming is to actively recruit outside specialists who have informed perspectives and knowledge of advanced threats. Areas of expertise valuable to AI-model red teams include deepfake technology, social engineering, identity theft, synthetic identity creation, and voice-based fraud. “Involving external specialists often surfaces hidden attack paths, including sophisticated social engineering and deepfake threats.” (Ahmad et al., 2024)

Papers:

Beutel, A., Xiao, K., Heidecke, J., & Weng, L. (2024). “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning.” OpenAI.

Ahmad, L., Agarwal, S., Lampe, M., & Mishkin, P. (2024). “OpenAI’s Approach to External Red Teaming for AI Models and Systems.” OpenAI.

Shape
Shape
Stay Ahead

Explore More Insights

Stay ahead with more perspectives on cutting-edge power, infrastructure, energy,  bitcoin and AI solutions. Explore these articles to uncover strategies and insights shaping the future of industries.

Shape

VMware customers in Europe face up to 1,500% price increases under Broadcom ownership

Regulatory storm brewing The pricing crisis has triggered formal regulatory attention across Europe. Germany’s VOICE IT customer association has filed a complaint with the European Commission, while ECCO explicitly calls for regulatory intervention, including reinstating previous contracts and suspending Broadcom’s ongoing litigation. “Unless Broadcom promptly implements critical changes, the company’s

Read More »

Two Elliott Nominees Set to Join Phillips 66 Board

Two names put forward by Elliott Investment Management LP and another two endorsed by Phillips 66 are expected to have won at the refiner’s directorial election during its annual meeting of shareholders on Wednesday. “Based on the preliminary results, the elected Phillips 66 directors are expected to be Robert W.

Read More »

Net Zero Teesside subsidy challenge quashed after climate appeal lost

A legal battle against the Net Zero Teesside (NZT) gas-fired power generation and carbon capture and storage project in the north-east of England was quashed in the appeal courts this week. Environmental consultant Andrew Boswell has lost his climate case against the project and its developers BP and Equinor in the Court of Appeal at the Royal Courts of Justice. Prime minister Keir Starmer sent a clear message earlier this year that he wanted to crack down on disruptive legal cases against major energy infrastructure in the UK. The energy secretary is responsible for approving environmental impact assessments for major infrastructure such as the NZT carbon capture projects, which Boswell sought to have repealed on the basis of an emissions calculation that he said was “out of date”. A second legal case against gas plant challenging government funding for the project is unlikely to be heard in court now that environmental campaigner Boswell has lost his appeal case against the project’s climate impact. NZT is a major project in the East Coast Cluster, one of two areas focused on carbon capture and storage (CCS) backed by £21.7 billion of government support. Boswell told Energy Voice that the second case was subject to a stay in court around the subsidy challenge. In that second case, he claimed that the project secured £10bn of subsidies, including a £6bn loan guarantee, only after he had launched his legal challenge. He argued in the High Court last year that the project’s emissions are greater than those that were accounted for in the impact assessment, and that it ignored upstream emissions produced outside the UK. He also said the project will create a sustained market for unabated gas production, which due to declining reserves in the North Sea, will make the country reliant on imports

Read More »

Texas RRC Announces Milestone in Boots on the Ground Initiative

In a statement posted on its website this week, the Railroad Commission of Texas (RRC) said it recently crossed a milestone in one of its key instruction programs, “training more than 300 employees in Phase I of the agency’s Boots on the Ground initiative”. The RRC noted in the statement that the goal of the program is to bring more consistency across all the agency’s oil and gas districts in how to apply commission rules and processes, “improving efficiency in the RRC’s day to day operations to protect Texans and the environment”. Phase I of the initiative is named ‘Introduction to Statewide Rules’ and covers the rules that inspectors and technical staff primarily deal with in the field, the RRC highlighted in the statement. “This program brings clarity and understanding to the rules which helps inspectors do their job well,” Dana McClendon, the division trainer with the RRC’s Oil and Gas Division, said in the statement. “Our goal is to make sure everyone leaves more confident to do the inspections the state relies on to ensure operators are complying with safety regulations,” McClendon added. In the statement, the RRC said the training’s in-depth discussion of rules and collaborative classroom environment helps inspectors understand how their field work can have a lasting impact. The organization added that, “through robust training initiatives like Boots on the Ground”, the RRC “supports responsible energy production, helping the state generate billions of dollars in tax revenue”.  In a statement posted on its site back in February 2019, the RRC announced the launch of its “first ever new inspector training school – Boots on the Ground”. That statement noted that this training “will focus on new oil and gas inspectors with less than two years tenure at the RRC” and said the school “will ensure inspectors

Read More »

Jo Bamford-owned hydrogen network to cut costs by 40%

The billionaire investor who rescued ailing Wrightbus before the pandemic now has plans to install a distributed hydrogen network across the country. And he wants government to reconsider its policies. Jo Bamford-owned HydraB Power, the consortium that bought Wrightbus out of bankruptcy in 2019, is developing a wide-ranging hydrogen production and distribution network. “HySpeed, which is the new idea we’re talking to government about today, is for another gigawatt of capacity with the consortium of off-takers and manufacturers that can take the cost of hydrogen down – we think [by] over 40%,” operating partner Harry Bowcott said in an interview. “Which, of course, makes the subsidy more productive and gets you in a meaningful way towards having hydrogen at parity cost versus diesel – without subsidy.” The company engaged ministers and lords outside Portcullis House in Westminster on Wednesday, demonstrating a hydrogen fuel cell Wrightbus. Bowcott said the company wants government to consider two planks of policy that could unlock investment in the hydrogen economy at next month’s spending review. HydraB Power is calling for two policy changes: first, it wants multiple projects included as part of HAR funding. It has also asked the government to expedite a consultation on the safety case for injecting hydrogen into the natural gas grid, which Bowcott said it would be ready to do from 2026. The company HydraB Power operates several portfolio companies involved in hydrogen production, distribution and usage. These include green hydrogen producer HyGen Energy Holdings, bus manufacturer Wrightbus, hydrogen refuelling and distribution infrastructure Ryze Power and transport decarbonisation finance solution provider Fuze. HySpeed ahead The consortium wants to unlock £6.5bn of investment in the hydrogen economy and create 24,300 jobs across the UK by 2030 through project HySpeed, a 1 GW green hydrogen project that, it claims, will reduce carbon emissions by

Read More »

QatarEnergy, ExxonMobil LNG Project to Start Production This Year

The Golden Pass LNG project in Sabine Pass, Texas, will begin production by year-end, QatarEnergy chief executive Saad Sherida Al-Kaabi said. Together with QatarEnergy’s North gas field expansion projects at home, the project with Exxon Mobil Corp. will more than double QatarEnergy’s LNG production from the current 77 million metric tons per annum (MMtpa) to 160 MMtpa, according to Al-Kaabi. The first liquefaction train from the North Field east expansion project will start production by mid-2026. “As for North Field West, it is in the engineering phase and will be going into the construction phase somewhere in 2027”, Al-Kaabi, who is also Qatar’s energy affairs minister, told the World Gas Conference in Beijing, as quoted in a statement from QatarEnergy. “QatarEnergy will be the largest single LNG exporter as a company while Qatar, as a country, will be the second-largest exporter of LNG after the United States for a very long time”, Al-Kaabi said. On March 5 the United States Department of Energy extended the deadline for the start of export operations at Golden Pass LNG by two years to March 2027. Golden Pass LNG is permitted to export the equivalent of up to 937 billion cubic feet a year of natural gas to FTA and non-FTA countries on a non-additive basis. The permits expire December 31, 2050. Last year the JV, 70 percent owned by QatarEnergy and 30 percent by ExxonMobil, requested the DOE under the Biden administration to move the deadline of September 30, 2025, by 18 months for both FTA and non-FTA authorizations. On April 28, 2025, the JV secured regulatory approval to commission the project. The go-ahead from the Federal Energy Regulatory Commission (FERC) applies to Golden Pass LNG’s boil-off gas compression system, LNG storage, liquefaction system, LNG pumps, and end flash gas compression system. The

Read More »

Industry Groups React to House Passage of One Big Beautiful Bill

In a statement posted on the American Petroleum Institute (API) website on Thursday, API President and CEO Mike Sommers applauded the House of Representatives for passing the One Big Beautiful Bill Act “to help restore American energy dominance”. “By preserving competitive tax policies, beginning to reverse the ‘methane fee,’ opening lease sales and advancing important progress on permitting, this historic legislation is a win for our nation’s energy future,” Sommers added. “We look forward to working with the Senate to strengthen pro-investment provisions and keep America at the forefront of energy innovation,” he continued. In a statement sent to Rigzone yesterday, Independent Petroleum Association of America (IPAA) President and CEO Jeff Eshelman said Trump’s One Big Beautiful Bill “is a win for American energy”. “Multiple House committees included language in the bill passed today [Thursday] that improves the ability of independent oil and natural gas producers to supply reliable, affordable energy to the American people,” he added. “IPAA is pleased that the legislation reinstates oil and natural gas lease sales for onshore and offshore federal lands and makes common sense reforms to the permitting and leasing process on federal lands,” Eshelman said. “IPAA members, the small businesses of the oil patch, are grateful that industry tax treatments including intangible drilling costs and percentage depletion were protected, along with carried interest deductions being preserved,” he continued. Eshelman added, however, that the IPAA is “disappointed that the legislation does not include a full repeal of the Methane Emissions Reduction Program (MERP) including the methane tax”. “Included within the bill is a 10-year delay of the MERP, but IPAA has consistently urged, and will continue to argue, for a full repeal of the statute,” Eshelman noted. “IPAA and our members congratulate House leadership on H.Con.Res.14 and stand ready to help ensure this legislation is approved

Read More »

Energy Voice Out Loud: Live from All-Energy with RX Global

Join Energy Voice Out Loud as we broadcast from the show floor of All-Energy 2025, the UK’s largest renewable and low-carbon energy event. In this special episode, our reporters sit down with the five All-Energy Ambassadors to explore the key themes and insights shaping the future of energy. Hear from: Dr Kerry-Ann Adamson, VP & Global Hydrogen Lead at Capgemini Clare Foster, Partner & Head of Clean Energy at Shepherd and Wedderburn Iain Sinclair, Executive Director at Global Energy Lesley McNeil, Head of External & Corporate Affairs at Muirhall Energy Christianna Logan, Director of Customers & Stakeholders at SSEN Transmission Each ambassador shares their unique perspective on their area of expertise, highlights from the sessions they’re involved in, and the vital role All-Energy plays in driving innovation, collaboration, and progress across the sector. Energy Voice Out Loud: Live from All-Energy 2025 

Read More »

New Intel Xeon 6 CPUs unveiled; one powers rival Nvidia’s DGX B300

He added that his read is that “Intel recognizes that Nvidia is far and away the leader in the market for AI GPUs and is seeking to hitch itself to that wagon.” Roberts said, “basically, Intel, which has struggled tremendously and has turned over its CEO amidst a stock slide, needs to refocus to where it thinks it can win. That’s not competing directly with Nvidia but trying to use this partnership to re-secure its foothold in the data center and squeeze out rivals like AMD for the data center x86 market. In other words, I see this announcement as confirmation that Intel is looking to regroup, and pick fights it thinks it can win. “ He also predicted, “we can expect competition to heat up in this space as Intel takes on AMD’s Epyc lineup in a push to simplify and get back to basics.” Matt Kimball, vice president and principal analyst, who focuses on datacenter compute and storage at Moor Insights & Strategy, had a much different view about the announcement. The selection of the Intel sixth generation Xeon CPU, the 6776P, to support Nvidia’s DGX B300 is, he said, “important, as it validates Intel as a strong choice for the AI market. In the big picture, this isn’t about volumes or revenue, rather it’s about validating a strategy Intel has had for the last couple of generations — delivering accelerated performance across critical workloads.”  Kimball said that, In particular, there are a “couple things that I would think helped make Xeon the chosen CPU.”

Read More »

AWS clamping down on cloud capacity swapping; here’s what IT buyers need to know

As of June 1, AWS will no longer allow sub-account transfers or new commitments to be pooled and reallocated across customers. Barrow says the shift is happening because AWS is investing billions in new data centers to meet demand from AI and hyperscale workloads. “That infrastructure requires long-term planning and capital discipline,” he said. Phil Brunkard, executive counselor at Info-Tech Research Group UK, emphasized that AWS isn’t killing RIs or SPs, “it’s just closing a loophole.” “This stops MSPs from bulk‑buying a giant commitment, carving it up across dozens of tenants, and effectively reselling discounted EC2 hours,” he said. “Basically, AWS just tilted the field toward direct negotiations and cleaner billing.” What IT buyers should do now For enterprises that sourced discounted cloud resources through a broker or value-added reseller (VAR), the arbitrage window shuts, Brunkard noted. Enterprises should expect a “modest price bump” on steady‑state workloads and a “brief scramble” to unwind pooled commitments.  If original discounts were broker‑sourced, “budget for a small uptick,” he said. On the other hand, companies that buy their own RIs or SPs, or negotiate volume deals through AWS’s Enterprise Discount Program (EDP), shouldn’t be impacted, he said. Nothing changes except that pricing is now baselined.

Read More »

DriveNets extends AI networking fabric with multi-site capabilities for distributed GPU clusters

“We use the same physical architecture as anyone with top of rack and then leaf and spine switch,” Dudy Cohen, vice president of product marketing at DriveNets, told Network World. “But what happens between our top of rack, which is the switch that connects NICs (network interface cards) into the servers and the rest of the network is not based on Clos Ethernet architecture, rather on a very specific cell-based protocol. [It’s] the same protocol, by the way, that is used in the backplane of the chassis.” Cohen explained that any data packet that comes into an ingress switch from the NIC is cut into evenly sized cells, sprayed across the entire fabric and then reassembled on the other side. This approach distinguishes DriveNets from other solutions that might require specialized components such as Nvidia BlueField DPUs (data processing units) at the endpoints. “The fabric links between the top of rack and the spine are perfectly load balanced,” he said. “We do not use any hashing mechanism… and this is why we can contain all the congestion avoidance within the fabric and do not need any external assistance.” Multi-site implementation for distributed GPU clusters The multi-site capability allows organizations to overcome power constraints in a single data center by spreading GPU clusters across locations. This isn’t designed as a backup or failover mechanism. Lasser-Raab emphasized that it’s a single cluster in two locations that are up to 80 kilometers apart, which allows for connection to different power grids. The physical implementation typically uses high-bandwidth connections between sites. Cohen explained that there is either dark fiber or some DWDM (Dense Wavelength Division Multiplexing) fibre optic connectivity between the sites. Typically the connections are bundles of four 800 gigabit ethernet, acting as a single 3.2 terabit per second connection.

Read More »

Intel eyes exit from NEX unit as focus shifts to core chip business

“That’s something we’re going to expand and build on,” Tan said, according to the report, pointing to Intel’s commanding 68% share of the PC chip market and 55% share in data centers. By contrast, the NEX unit — responsible for silicon and software that power telecom gear, 5G infrastructure, and edge computing — has struggled to deliver the kind of strategic advantage Intel needs. According to the report, Tan and his team view it as non-essential to Intel’s turnaround plans. The report described the telecom side of the business as increasingly disconnected from Intel’s long-term objectives, while also pointing to fierce competition from companies like Broadcom that dominate key portions of the networking silicon market and leave little room for Intel to gain a meaningful share. Financial weight, strategic doubts Despite generating $5.8 billion in revenue in 2024, the NEX business was folded into Intel’s broader Data Center and Client Computing groups earlier this year. The move was seen internally as a signal that NEX had lost its independent strategic relevance and also reflects Tan’s ruthless prioritization.  To some in the industry, the review comes as little surprise. Over the past year, Intel has already shed non-core assets. In April, it sold a majority stake in Altera, its FPGA business, to private equity firm Silver Lake for $4.46 billion, shelving earlier plans for a public listing. This followed the 2022 spinoff of Mobileye, its autonomous driving arm. With a $19 billion loss in 2024 and revenue falling to $53.1 billion, the chipmaker also aims to streamline management, cut $10 billion in costs, and bet on AI chips and foundry services, competing with Nvidia, AMD, and TSMC.

Read More »

Tariff uncertainty weighs on networking vendors

“Our guide assumes current tariffs and exemptions remain in place through the quarter. These include the following: China at 30%, partially offset by an exemption for semiconductors and certain electronic components; Mexico and Canada at 25% for the components and products that are not eligible for the current exemptions,” Cisco CFO Scott Herron told Wall Street analysts in the company’s quarterly earnings report on May 14. At this time, Cisco expects little impact from tariffs on steel and aluminum and retaliatory tariffs, Herron said. “We’ll continue to leverage our world-class supply chain team to help mitigate the impact,” he said, adding that “the flexibility and agility we have built into our operations over the last few years, the size and scale of our supply chain, provides us some unique advantages as we support our customers globally.” “Once the tariff scenario stabilizes, there [are] steps that we can take to mitigate it, as you’ve seen us do with China from the first Trump administration. And only after that would we consider price [increases],” Herron said. Similarly, Extreme Networks noted the changing tariff conditions during its earnings call on April 30. “The tariff situation is very dynamic, I think, as everybody knows and can appreciate, and it’s kind of hard to call. Yes, there was concern initially given the magnitude of tariffs,” said Extreme Networks CEO Ed Meyercord on the earnings call. “The larger question is, will all of the changes globally in trade and tariff policy have an impact on demand? And that’s hard to call at this point. And we’re going to hold as far as providing guidance or judgment on that until we have finality come July.” Financial news Meanwhile, AI is fueling high expectations and influencing investments in enterprise campus and data center environments.

Read More »

Liquid cooling becoming essential as AI servers proliferate

“Facility water loops sometimes have good water quality, sometimes bad,” says My Troung, CTO at ZutaCore, a liquid cooling company. “Sometimes you have organics you don’t want to have inside the technical loop.” So there’s one set of pipes that goes around the data center, collecting the heat from the server racks, and another set of smaller pipes that lives inside individual racks or servers. “That inner loop is some sort of technical fluid, and the two loops exchange heat across a heat exchanger,” says Troung. The most common approach today, he says, is to use a single-phase liquid — one that stays in liquid form and never evaporates into a gas — such as water or propylene glycol. But it’s not the most efficient option. Evaporation is a great way to dissipate heat. That’s what our bodies do when we sweat. When water goes from a liquid to a gas it’s called a phase change, and it uses up energy and makes everything around it slightly cooler. Of course, few servers run hot enough to boil water — but they can boil other liquids. “Two phase is the most efficient cooling technology,” says Xianming (Simon) Dai, a professor at University of Texas at Dallas. And it might be here sooner than you think. In a keynote address in March at Nvidia GTC, Nvidia CEO Jensen Huang unveiled the Rubin Ultra NVL576, due in the second half of 2027 — with 600 kilowatts per rack. “With the 600 kilowatt racks that Nvidia is announcing, the industry will have to shift very soon from single-phase approaches to two-phase,” says ZutaCore’s Troung. Another highly-efficient cooling approach is immersion cooling. According to a Castrol survey released in March, 90% of 600 data center industry leaders say that they are considering switching to immersion

Read More »

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.

Read More »

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

Read More »

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

Read More »

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

Read More »