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Google, CTC Global partner to deploy advanced conductors

Google and conductor manufacturer CTC Global on Tuesday said they are partnering to ask states, utilities and transmission developers to identify areas to deploy advanced conductors, which can carry more power than standard transmission lines but use existing towers and poles. Responses to a request for information are due on July 14, and a request […]

Google and conductor manufacturer CTC Global on Tuesday said they are partnering to ask states, utilities and transmission developers to identify areas to deploy advanced conductors, which can carry more power than standard transmission lines but use existing towers and poles.

Responses to a request for information are due on July 14, and a request for proposals will “shortly follow,” Google and CTC Global said in a release shared in advance with Utility Dive. “Applications are encouraged from areas where Google has existing or announced data centers, as well as their associated wholesale markets,” the release states.

The partnership will focus on U.S. transmission lines that have the most potential to accelerate grid capacity using CTC Global’s conductors, and it will prioritize projects that would “deliver the greatest immediate impact and that support load growth where Google operates,” the release said.

Advanced conductors are one of the alternative transmission technologies that the Federal Energy Regulatory Commission’s Order 1920 requires transmission providers “in each transmission planning region to consider more fully.”

FERC said in an explainer that the order’s goal “is to identify efficient and cost-effective solutions to meet transmission needs and optimize the transmission system without the need to build additional transmission facilities.”

Google and CTC Global invited states, utilities and transmission developers to start responding to the RFI immediately. They said “selected partners and projects” will gain access to cost assistance, workforce training on the deployment of CTC Global’s ACCC conductors and “support for technical project studies … to validate the technology’s integration and impact.”

CTC Global CEO J.D. Sitton said in the release that the partnership is a “positive turning point to lower electricity costs, generate economic growth, and advance U.S. energy dominance … [helping] ensure that the U.S. invests in cost-effective solutions for the long-term that help the U.S. continue to lead the AI revolution.”

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Essential commands for Linux server management

Any Linux systems administrator needs to be proficient with a wide range of commands for user management, file handling, system monitoring, networking, security and more. This article covers a range of commands that are essential for managing a Linux server. Keep in mind that some commands will depend on the

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China Oil Demand Will Peak Earlier Than Expected, IEA Says

China’s oil demand will stop growing earlier than expected, reinforcing the outlook for a global peak and prolonged supply surplus this decade, the International Energy Agency said. The IEA slashed forecasts for Chinese consumption until 2030 by about 1 million barrels a day amid “extraordinary” domestic sales of electric vehicles. It predicts the nation’s demand – which has dominated world growth this century – will top out in 2027, and worldwide oil use two years after that. While the Israel-Iran conflict has stirred concern over immediate energy stockpiles, “oil markets look set to be well-supplied in the years ahead,” IEA Executive Director Fatih Birol said. The agency was created in the 1970s to advise major consumers on energy policy. Crude prices surged the most in three years Friday as Israel launched airstrikes on OPEC member Iran, though the gains have since cooled as oil exports remain unaffected. US futures traded near $70 per barrel Monday, down 19% from last year’s peak, amid expectations of an impending surplus.  China’s oil use will reach a maximum 16.9 million barrels a day by 2027, peaking roughly two years earlier than previously forecast, according to the IEA’s report. Besides the ascent of EVs, high-speed rail and trucks powered with natural gas will help displace crude oil. China National Petroleum Corp., the country’s largest energy producer, predicted in December that peak demand may arrive as early as this year. The IEA projects that global oil demand growth will slow to a “trickle” the next few years, with consumption at a maximum of 105.5 million barrels a day in 2029 – roughly in line with last year’s forecast. It would then decline slightly the following year. With China fading, the anticipated worldwide demand growth – amounting to about 2.5 million barrels a day total by 2030 – will largely come from

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‘Shoulder season’ reliability a growing concern in ERCOT, other ISOs: Aurora Energy Research

Dive Brief: Power generators and large customers should embrace flexibility as rising power demand increases the risk of load-shedding events — interruptions in the delivery of electricity — during the spring and fall, Aurora Energy Research said in a June 6 report. The Electric Reliability Council of Texas could see shoulder-season load-shedding events by 2030, according to a model based on past thermal generator outage conditions, the report says. It will have a ramping requirement of at least 10 GW for 16% of hours by 2035, underscoring the need for a fleet of flexible resources to respond to sudden demand swings, it says.  Batteries and gas peaking plants provide crucial flexibility on the generation side, while flexibility from data centers and other large loads could prevent load-shedding and avoid 10 GW of new generation capacity by 2030, Aurora said. Dive Insight: Aurora’s modeling in ERCOT, the PJM Interconnection and other ISOs shows that the historically uneventful shoulder seasons increasingly present reliability concerns for grid operators due to aging infrastructure and ever-more-volatile weather conditions. A May 25 load-shed event that affected nearly 100,000 customers in New Orleans highlights the risk, Aurora said.  Two Louisiana nuclear power plants with more than 2 GW of combined capacity were offline during the event, one unexpectedly due to a cooling system issue. At the same time, a critical 500-kV transmission line serving New Orleans was out of service because it had been damaged in an early March tornado. Other lines in the area overloaded as demand spiked amid unseasonably hot weather.  About 70% of the 6.3 GW of outages contributing to the event were unplanned; flexible resources like batteries could have addressed some of the shortfall, representatives for the Midcontinent Independent System Operator told the New Orleans City Council on June 3. Existing capacity accreditation

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Meta signs geothermal power deal for New Mexico data centers

Dive Brief: Meta announced a deal with geothermal energy producer XGS Energy Thursday that will provide the tech and social media giant with carbon-free power to support its New Mexico data center operations In exchange, Meta will support XGS’s development of 150 MW of next-generation geothermal energy production capacity in the state, according to the June 12 release. New Mexico Gov. Michelle Lujan Grisham reportedly said the new plant will result in a $1 billion private sector investment, in addition to creating 3,000 construction jobs and 100 plant operation jobs. The deal adds to the growing corporate demand for geothermal energy, which provides carbon-free power generation without weather dependence. Meta previously signed its first geothermal agreement with Sage Geosystems last year for power generation east of the Rocky Mountains. Dive Insight: XGS’s new geothermal plant will be built in two phases and is unique, as the company uses proprietary geothermal power production technology that works with zero operational water use, according to the release. The project’s completion will include an initial smaller phase of construction and a later, larger phase, with both expected to be completed and operational by 2030, the companies said.  On its own, this XGS project is expected to increase the total geothermal production in New Mexico by “a factor of 10,” according to the release. Meta Global Head of Energy Urvi Parekh said the social media giant is “excited” to work with XGS “to unlock a new category of energy supply” for its New Mexico operations. “Advances in AI require continued energy to support infrastructure development,” Parekh said in Thursday’s release. “With next-generation geothermal technologies like XGS ready for scale, geothermal can be a major player in supporting the advancement of technologies like AI as well as domestic data center development.” For Meta, it is the

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NRG, LS Power ask FERC to approve $12B gas-fired power plant, demand-response deal

NRG Energy and LS Power on Thursday asked the Federal Energy Regulatory Commission to approve a $12 billion deal under which NRG would buy about 13 GW in gas-fired generation and CPower, a company with 6 GW in demand-response resources, from LS Power. If completed, the transaction will increase NRG’s market share in the New York Independent System Operator and PJM Interconnection footprints, and in certain submarkets in NYISO and PJM, but not enough to give NRG the ability to exert market power, the companies said in an application at FERC. Under the deal, NRG’s capacity in PJM would jump to 9.5 GW from 2.1 GW and NRG would own 2.2 GW in New York, up from 1.2 GW, according to the application. Related to the deal, LS Power would buy energy, capacity and ancillary services via a power purchase agreement from a 985-MW unit at the Ravenswood Generating Station in Queens, New York, according to the application. The PPA would start at the deal’s closing and continue through April 30, 2029. Under the deal, NRG would also buy 765 MW in ISO New England and 2 GW in the Electricity Reliability Council of Texas market. NRG and LS Power asked FERC to approve the transaction by Oct. 24. They expect to close the deal early next year. The New York State Public Service Commission must sign off on the transaction. Under the deal, which NRG and LS Power announced on May 12, LS Power will acquire about 11% of NRG’s outstanding common stock. However, to prevent LS Power and its affiliates from controlling more than 10% of NRG’s voting shares — a threshold that triggers heightened oversight by FERC — NRG will deliver any share that exceeds the 10% threshold to an independent trustee, according to the application. The transaction

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Senate: Don’t fumble the energy future

Dean Granoff is founder and principal of the Climate Technology Group. As the U.S. Senate works to craft a budget deal, it faces a defining choice: Will American industry seize the economic rewards of a modern energy system, or allow our competitors to take the lead? The version of the “Big Beautiful Bill” passed by the House stripped away incentives that support modern clean energy infrastructure and innovation, security and competitiveness, downing the very tools that put the United States on track for global energy leadership.  But U.S. senators and their constituents are pushing back, saying that undoing the incentives would raise electricity prices and cut jobs.  As a group of four GOP senators wrote to Senate Majority Leader John Thune, “A wholesale repeal, or termination of certain individual credits, would create uncertainty, jeopardizing capital allocation, long-term project planning, and job creation in the energy sector and across our broader economy.” Now, 13 House Republicans are urging the Senate to restore the incentives, and there is a chance they could get their way. This is not about ideology.  Wherever you are on the political spectrum, clean energy competitiveness is about “economic prosperity, a healthier planet and true national security,” according to Sen. John Curtis (R-Utah). Globally over $2 trillion was invested in clean energy technologies and infrastructure last year — double the amount spent on fossil-based infrastructure. The U.S. must not abandon its position in this ascendent sector. Markets are moving decisively towards modern clean energy systems because technologies like solar, wind, and batteries are generally cheaper and faster to install than their legacy competitors. A broad array of related new technologies is following close behind.  This isn’t a fluke; it’s basic economics. Clean energy systems generate, store and deliver power without fuel, so that once the infrastructure is in

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Mitsubishi Said To Be in Advanced Talks on $8B Aethon Deal

Mitsubishi Corp. is in advanced talks to buy the assets of Aethon Energy Management for close to $8 billion, people familiar with the matter said, in what would be the Japanese conglomerate’s biggest ever acquisition. Tokyo-based Mitsubishi could announce a deal with the US energy-focused investment firm in the next couple of months, according to the people. Abu Dhabi National Oil Co. had also been considering a potential transaction involving Aethon, Bloomberg News reported in April. A deal would likely be structured as a purchase of Aethon’s portfolio, which includes natural gas production operations and midstream assets, some of the people said. While a deal is close, talks could still be delayed or falter, they said, asking not to be identified discussing confidential information. It’s also possible another bidder could emerge for Aethon, they added. A representative for Aethon declined to comment, while a spokesperson for Adnoc didn’t respond to requests for comment. Mitsubishi said in a statement that no decision has been made regarding Aethon. Dallas-based Aethon is among the most active drillers in the Haynesville shale basin that straddles East Texas and northern Louisiana. Aethon is close to several LNG export terminals along the Gulf Coast. Mitsubishi, one of Japan’s major trading companies, is a key supplier of liquefied natural gas and has a stake in a US export facility in Louisiana. Japan’s government sees the artificial intelligence boom potentially lifting power demand over the next decade, and has urged the nation’s private firms to invest in gas. The talks mean that Mitsubishi is looking to double down on one of its most profitable business segments: natural gas. Japan’s trading houses, which include Warren Buffett’s Berkshire Hathaway Inc. as an investor, have outperformed the market over the last few years due in part to strong profits from overseas

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Next-gen AI chips will draw 15,000W each, redefining power, cooling, and data center design

“Dublin imposed a 2023 moratorium on new data centers, Frankfurt has no new capacity expected before 2030, and Singapore has just 7.2 MW available,” said Kasthuri Jagadeesan, Research Director at Everest Group, highlighting the dire situation. Electricity: the new bottleneck in AI RoI As AI modules push infrastructure to its limits, electricity is becoming a critical driver of return on investment. “Electricity has shifted from a line item in operational overhead to the defining factor in AI project feasibility,” Gogia noted. “Electricity costs now constitute between 40–60% of total Opex in modern AI infrastructure, both cloud and on-prem.” Enterprises are now forced to rethink deployment strategies—balancing control, compliance, and location-specific power rates. Cloud hyperscalers may gain further advantage due to better PUE, renewable access, and energy procurement models. “A single 15,000-watt module running continuously can cost up to $20,000 annually in electricity alone, excluding cooling,” said Manish Rawat, analyst at TechInsights. “That cost structure forces enterprises to evaluate location, usage models, and platform efficiency like never before.” The silicon arms race meets the power ceiling AI chip innovation is hitting new milestones, but the cost of that performance is no longer just measured in dollars or FLOPS — it’s in kilowatts. The KAIST TeraLab roadmap demonstrates that power and heat are becoming dominant factors in compute system design. The geography of AI, as several experts warn, is shifting. Power-abundant regions such as the Nordics, the Midwest US, and the Gulf states are becoming magnets for data center investments. Regions with limited grid capacity face a growing risk of becoming “AI deserts.”

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Edge reality check: What we’ve learned about scaling secure, smart infrastructure

Enterprises are pushing cloud resources back to the edge after years of centralization. Even as major incumbents such as Google, Microsoft, and AWS pull more enterprise workloads into massive, centralized hyperscalers, use cases at the edge increasingly require nearby infrastructure—not a long hop to a centralized data center—to take advantage of the torrents of real-time data generated by IoT devices, sensor networks, smart vehicles, and a panoply of newly connected hardware. Not long ago, the enterprise edge was a physical one. The central data center was typically located in or very near the organization’s headquarters. When organizations sought to expand their reach, they wanted to establish secure, speedy connections to other office locations, such as branches, providing them with fast and reliable access to centralized computing resources. Vendors initially sold MPLS, WAN optimization, and SD-WAN as “branch office solutions,” after all. Lesson one: Understand your legacy before locking in your future The networking model that connects centralized cloud resources to the edge via some combination of SD-WAN, MPLS, or 4G reflects a legacy HQ-branch design. However, for use cases such as facial recognition, gaming, or video streaming, old problems are new again. Latency, middle-mile congestion, and the high cost of bandwidth all undermine these real-time edge use cases.

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Cisco capitalizes on Isovalent buy, unveils new load balancer

The customer deploys the Isovalent Load Balancer control plane via automation and configures the desired number of virtual load-balancer appliances, Graf said. “The control plane automatically deploys virtual load-balancing appliances via the virtualization or Kubernetes platform. The load-balancing layer is self-healing and supports auto-scaling, which means that I can replace unhealthy instances and scale out as needed. The load balancer supports powerful L3-L7 load balancing with enterprise capabilities,” he said. Depending on the infrastructure the load balancer is deployed into, the operator will deploy the load balancer using familiar deployment methods. In a data center, this will be done using a standard virtualization automation installation such as Terraform or Ansible. In the public cloud, the load balancer is deployed as a public cloud service. In Kubernetes and OpenShift, the load balancer is deployed as a Kubernetes Deployment/Operator, Graf said.  “In the future, the Isovalent Load Balancer will also be able to run on top of Cisco Nexus smart switches,” Graf said. “This means that the Isovalent Load Balancer can run in any environment, from data center, public cloud, to Kubernetes while providing a consistent load-balancing layer with a frictionless cloud-native developer experience.” Cisco has announced a variety of smart switches over the past couple of months on the vendor’s 4.8T capacity Silicon One chip. But the N9300, where Isovalent would run, includes a built-in programmable data processing unit (DPU) from AMD to offload complex data processing work and free up the switches for AI and large workload processing. For customers, the Isovalent Load Balancer provides consistent load balancing across infrastructure while being aligned with Kubernetes as the future for infrastructure. “A single load-balancing solution that can run in the data center, in public cloud, and modern Kubernetes environments. This removes operational complexity, lowers cost, while modernizing the load-balancing infrastructure in preparation

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Oracle’s struggle with capacity meant they made the difficult but responsible decisions

IDC President Crawford Del Prete agreed, and said that Oracle senior management made the right move, despite how difficult the situation is today. “Oracle is being incredibly responsible here. They don’t want to have a lot of idle capacity. That capacity does have a shelf life,” Del Prete said. CEO Katz “is trying to be extremely precise about how much capacity she puts on.” Del Prete said that, for the moment, Oracle’s capacity situation is unique to the company, and has not been a factor with key rivals AWS, Microsoft, and Google. During the investor call, Katz said that her team “made engineering decisions that were much different from the other hyperscalers and that were better suited to the needs of enterprise customers, resulting in lower costs to them and giving them deployment flexibility.” Oracle management certainly anticipated a flurry of orders, but Katz said that she chose to not pay for expanded capacity until she saw finalized “contracted noncancelable bookings.” She pointed to a huge capex line of $9.1 billion and said, “the vast majority of our capex investments are for revenue generating equipment that is going into data centers and not for land or buildings.”

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Winners and losers in the Top500 supercomputer ranking

GPU winner: AMD AMD is finally making a showing for itself, albeit modestly, in GPU accelerators. For the June 2025 edition of the list, AMD Instinct accelerators are in 23 systems, a nice little jump from the 10 systems on the June 2024 list. Of course, it helps with the sales pitch when AMD processors and coprocessors can be found powering the No. 1 and No. 2 supercomputers in the world. GPU loser: Intel Intel’s GPU efforts have been a disaster. It failed to make a dent in the consumer space with its Arc GPUs, and it isn’t making much headway in the data center, either. There were only four systems running GPU Max processors on the list, and that’s up from three a year ago. Still, it’s pitiful showing given the effort Intel made. Server winners: HPE, Dell, EVIDAN, Nvidia The four server vendors — servers, not component makers — all saw share increases. Nvidia is also a server vendor, selling its SuperPOD AI servers directly to customers. They all gained at the expense of Lenovo and Arm. Server loser: Lenovo It saw the sharpest drop in server share, going from 163 systems in June of 2024 to 136 in this most recent listing. Loser: Arm Other than the 13 Nvidia Grace chips, the ARM architecture was completely absent from this spring’s list.

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Micron joins HBM4 race with 36GB 12-high stack, eyes AI and data center dominance

Race to power the next generation of AI By shipping samples of the HMB4 to the key customers, Micron has joined SK hynix in the HBM4 race. In March this year, SK hynix shipped the 12-Layer HBM4 samples to customers. SK hynix’s HBM4 has implemented bandwidth capable of processing more than 2TB of data per second, processing data equivalent to more than 400 full-HD movies (5GB each) in a second, said the company. “HBM competitive landscape, SK hynix has already sampled and secured approval of HBM4 12-high stack memory early Q1’2025 to NVIDIA for its next generation Rubin product line and plans to mass produce HBM4 in 2H 2025,” said Danish Faruqui, CEO, Fab Economics. “Closely following, Micron is pending Nvidia’s tests for its latest HBM4 samples, and Micron plans to mass produce HBM4 in 1H 2026. On the other hand, the last contender, Samsung is struggling with Yield Ramp on HBM4 Technology Development stage, and so has to delay the customer samples milestones to Nvidia and other players while it earlier shared an end of 2025 milestone for mass producing HBM4.” Faruqui noted another key differentiator among SK hynix, Micron, and Samsung: the base die that anchors the 12-high DRAM stack. For the first time, both SK hynix and Samsung have introduced a logic-enabled base die on 3nm and 4nm process technology to enable HBM4 product for efficient and faster product performance via base logic-driven memory management. Both Samsung and SK hynix rely on TSMC for the production of their logic-enabled base die. However, it remains unclear whether Micron is using a logic base die, as the company lacks in-house capability to fabricate at 3nm.

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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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