California Gov. Newsom uses judicial streamlining provision to advance 600 MW of solar, storage

Stay Ahead, Stay ONMINE

California Gov. Newsom uses judicial streamlining provision to advance 600 MW of solar, storage

California Gov. Gavin Newsom, D, announced Wednesday that he has certified the Cornucopia Hybrid Solar Project using the California Environmental Quality Act’s judicial streamlining provision, speeding up the construction of 300 MW of solar along with 300 MW of battery storage. Once a project is certified, courts must decide on CEQA challenges to it within […]

Once a project is certified, courts must decide on CEQA challenges to it within 270 days to the extent feasible, while still allowing those challenges to be heard, said a release from Newsom’s office.

The BayWa r.e. Americas project will be located in Fresno County, California, and is expected to power around 300,000 homes in the area.

Newsom’s office said the project’s combined 300 MW of generation and 300 MW of battery capacity will allow the solar farm to dispatch electricity at times of peak demand, “including evening and nighttime hours when renewable generation is limited.”

The project’s developers also plan for it to be agrivoltaic, with sheep “grazing alongside solar panels to help manage vegetation,” said the governor’s office.

A project’s selection for a judicial streamlining certification can reduce lawsuit-related delays from three to five years to around 270 days, said the governor’s office. This process was authorized by a 2021 state law allowing the governor to make those certifications, and a 2023 state law expanding the list of eligible projects to include certain green infrastructure projects.

Only 24 projects have been certified under the law so far. The certification came a few days after California regulators approved new maintenance and operation standards for battery storage resources, including a requirement for facility owners to develop emergency response and emergency action plans, following a January fire at Vistra Energy’s Moss Landing battery facility in California.

“The project aligns with California efforts focused on proactively addressing safety for battery storage systems through comprehensive state-level collaborations and regulatory updates,” said Newsom’s office.

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.

Google Cloud partners with mLogica to offer mainframe modernization

Other than the partnership with mLogica, Google Cloud also offers a variety of other mainframe migration tools, including Radis and G4 that can be employed to modernize specific applications. Enterprises can also use a combination of migration tools to modernize their mainframe applications. Some of these tools include the Gemini-powered

Red Hat’s AI portfolio evolves to address enterprise deployment challenges

RHEL AI lets companies deploy workloads where they need them, including cloud, on premises, or on the edge, IDC analyst Michele Rosen says. “AI applications need to live as close as possible to their data,” she says. “For security, latency, and what have you. So you want to have a

Ethernet roadmap: AI drives high-speed, efficient Ethernet networks

“While the IEEE P802.3dj project is working toward defining 200G per lane for Ethernet by late 2026, the industry is (loudly) asking for 400G per lane yesterday, if not sooner,” Jones wrote in a recent Ethernet Alliance blog. In a post about Ethernet’s AI evolution, John D’Ambrosia wrote about the

ControlMonkey aims to bring order to cloud disaster recovery chaos

“Most companies don’t have full coverage of everything in their infrastructure within infrastructure as code, so there are a lot of blind spots—you don’t know what you don’t know,” Twizer emphasized. On top of that he noted that keeping IaC in a state that always represents the existing configuration can be

Canacol Posts $25MM Loss on Deferred Tax Payment

Canacol Energy Ltd. has reported $25.4 million, or $0.75 per share, in net loss for the fourth quarter (Q4), compared to a net profit of $29.9 million for the same three-month period in 2023. The natural gas exploration and production company, based in Canada but operating in Colombia, attributed the gap to a deferred income tax expense of $28.9 million for Q4 2024 and a deferred income tax recovery of $31.7 million for Q4 2023. However, Canacol’s adjusted earnings before interest, depreciation, amortization and exploration for Q4 2024 rose 43 percent year-on-year to $76.1 million, according to results published online by the company. That is thanks to a higher operating netback, offset by lower realized contractual volumes. Operating netback grew 39 percent year-over-year to $6.12 per thousand cubic feet in Q4 2024. “The increase is due to an increase in average sales prices, net of transportation expenses, offset by an increase in royalties”, Canacol said. Revenues, net of royalties and transport expenses, increased 23 percent to $98.3 million. Canacol attributed the increase to higher sales prices, offset by lower sales volumes. Realized contractual gas sales volumes fell 4 percent year-on-year to 158 million cubic feet a day. Net capital expenditures dropped to $28.6 million, from $72.2 million for Q4 2023. “The decrease is due to reduced spending on land and seismic, workovers, and drilling and completion”, Canacol said. It ended the year with $79.2 million in cash and cash equivalents and $45.5 million in working capital surplus. “The Corporation expects that commodity pricing will remain strong for the remainder of 2025, and for this reason, in 2025, the Corporation lowered its take-or-pay volumes to maximize exposure to the spot sales market”, Canacol said. “In line with maintaining and growing Canacol’s reserves and production in its core assets in the LMV

DNO Announces ‘Important’ Oil, Gas Discovery in North Sea

In a statement posted on its site on Wednesday, Norwegian oil and gas operator DNO ASA announced “an important oil and gas discovery in Northern North Sea license PL1182 S”. The discovery was made in Paleocene injectite sandstones “of excellent reservoir quality”, the statement highlighted. Preliminary estimates of gross recoverable resources are “in the range of 39 to 75 million barrels of oil equivalent, with a mean of 55 million barrels of oil equivalent”, the statement pointed out. DNO noted in the statement that the Kjøttkake exploration well encountered a 41 meter (134.5 foot) oil column and a nine meter 9 (29.5 foot) gas column. A sidetrack drilled horizontally 1,350 meters (4,429 feet) westwards along the reservoir in the Sotra Formation confirmed the presence of the oil column throughout the discovery, DNO added. “We are on a hot streak in Norway,” DNO Executive Chairman Bijan Mossavar-Rahmani said in the statement. “Our latest and most exciting discovery this year, Kjøttkake, is close to existing infrastructure in the Troll-Gjøa area, and we will be relentless in pursuing its commercialization,” Mossavar-Rahmani added. DNO highlighted in the statement that Kjøttkake is the company’s tenth discovery since 2021 in the “Troll-Gjøa exploration and development hotspot”. This find follows the company’s Røver Nord, Kveikje, Ofelia, Røver Sør, Heisenberg, Carmen, Kyrre, Cuvette and Ringand discoveries, DNO pointed out in the statement. DNO went on to note that it has also “racked up discoveries in other parts of the Norwegian Continental Shelf, including Norma (2023) and Othello (2024), both play-opening finds and both operated by DNO”. DNO holds a 40 percent operated stake in PL1182 S, according to its statement, which outlined that its partners in the license comprise Aker BP ASA, with a 30 percent stake, Concedo AS, with a 15 percent interest, and Japex Norge AS, with another 15 percent

Map: UK offshore wind and net-zero ambitions

The UK is a global leader in offshore wind energy, with ambitious targets to scale up capacity as part of its net-zero strategy. By 2030, the UK government aims to deploy 50GW of offshore wind, including 5GW of floating offshore wind. Looking further ahead, projections for 2050 suggest the sector could reach 100GW or more. As a result, the offshore wind sector will play a pivotal role in decarbonising the UK electricity grid and supporting energy security. In addition, the transition from fossil fuels to renewable energy could provide a significant jobs opportunity for offshore oil and gas workers in the UK. Many of the skills required for deploying wind projects, particularly floating developments, already exist within the oil and gas sector. For communities in the north east of Scotland such as Aberdeen, ensuring a just transition for workers will be crucial for maintaining economic stability. Investors driving offshore wind expansion The UK offshore wind market has attracted significant investment from both domestic and international companies. Ørsted, RWE, SSE Renewables, ScottishPower Renewables, Corio Generation, and Copenhagen Infrastructure Partners (CIP) are among the largest investors in the UK market. The UK government is supporting investment into offshore wind and other forms of renewable energy through the Contracts for Difference (CfD) scheme. In the most recent sixth allocation round (AR6), the government awarded more than 3.3 GW of offshore wind capacity. It followed a disastrous result in the AR5 auction in 2023, which saw no CfD bids from the offshore wind sector. In order to achieve its ambition to decarbonise the UK electricity grid by 2030, the Labour government is introducing reforms for AR7 to entice more bidders. ScotWind and INTOG leasing rounds Two of the most significant recent developments in the UK offshore wind sector came from Scotland’s ScotWind and Innovation

ExxonMobil to Lay Off About 250 UK Workers

Exxon Mobil Corp. will shrink its UK headcount by about 250 positions as the Texas oil giant consolidates its operations in the country. Exxon’s longtime Leatherhead office south of London is due to shut in 2026 and employees at that site who will remain at the energy major are expected to relocate to Exxon’s refinery and petrochemical complex in Fawley, according to a statement from the company on Wednesday. Amid this consolidation of its UK operations, Exxon will continue to hire new people at its London trading hub, which the firm has been trying to expand. “The UK is an important country for Exxon Mobil,” according to the statement. “We are investing in strong businesses, including growing our London Trading hub and revitalizing our Fawley Petrochemical Complex. We will continue to have a meaningful presence in the country.” What do you think? We’d love to hear from you, join the conversation on the Rigzone Energy Network. The Rigzone Energy Network is a new social experience created for you and all energy professionals to Speak Up about our industry, share knowledge, connect with peers and industry insiders and engage in a professional community that will empower your career in energy. MORE FROM THIS AUTHOR Bloomberg

OMV Petrom, Romgaz Spud First Well in Neptun Deep Gas Project

SNGN Romgaz SA and OMV Petrom SA have launched development drilling in the Neptun Deep gas block on Romania’s side of the Black Sea, expecting to start production 2027. At its peak Neptun Deep will add 8 billion cubic meters (282.52 billion cubic feet) a year to Romania’s natural gas production, according to the partners. They are undertaking the project as 50-50 co-venturers. OMV Petrom, majority-owned by Austria’s state-backed OMV Group with investment from the Romanian state, and Romania’s majority state-owned Romgaz peg their investment in the project at up to EUR 4 billion ($4.3 billion). “By developing this project, Romania can secure its natural gas needs from domestic sources and become an important player in the European market”, OMV Petrom chief executive Christina Verchere said in a joint press release. Romgaz deputy chief executive Aristotel Jude commented, “The well spud in Neptun Deep is the first offshore key-operation in the Black Sea and represents the fulfillment of the development-exploitation work programs by both titleholders, being within the project schedule”. The Neptun Deep project will exploit the Domino and Pelican South fields. The block sits some 160 kilometers (99.42 miles) from shore in water depths of about 1,000 meters (3,280.84 feet), according to figures from Romgaz. Ten wells are to be drilled: 6 in Domino and 4 in Pelican South. The first well spudded is in Pelican South; the well will take around 2-3 months to complete drilling, the joint statement said. The rig is Transocean Barents, while integrated drilling services have been contracted to Halliburton Energy Services Romania and Newpark Drilling Fluids Eastern Europe. “The well foundations for Pelican were successfully installed using an advanced technology for offshore drilling, the CAN-ductor from Neodrill, that minimizes the overall environmental footprint of the drilling process”, the statement said. Infrastructure for the

NSTA Expects UK Crude Oil Output to Continue Dropping in 2025

The North Sea Transition Authority (NSTA) expects UK crude oil production to continue dropping this year, according to data published on its website recently. UK crude oil production is projected to average 0.53 million barrels per day in 2025 in the NSTA’s updated output forecasts, which show that this production averaged 0.77 million barrels per day in 2021, 0.71 million barrels per day in 2022, 0.63 million barrels per day in 2023, and 0.56 million barrels per day in 2024. Looking further ahead, the data projects that UK crude oil output will average 0.50 million barrels per day in 2026, 0.46 million barrels per day in 2027, 0.43 million barrels per day in 2028, 0.40 million barrels per day in 2029, and 0.37 million barrels per day in 2030. The NSTA expects UK oil production to average 0.60 million barrels per day in 2025, 0.56 million barrels per day in 2026, 0.52 million barrels per day in 2027, 0.48 million barrels per day in 2028, 0.45 million barrels per day in 2029, and 0.42 million barrels per day in 2030. This production came in at 0.85 million barrels per day in 2021, 0.79 million barrels per day in 2022, 0.70 million barrels per day in 2023, and 0.63 million barrels per day in 2024, according to the data. UK net gas output is projected to average 0.41 million barrels of oil equivalent per day in 2025 in the figures. This production is expected to come in at 0.35 million barrels of oil equivalent per day in 2026, 0.31 million barrels of oil equivalent per day in 2027, 0.27 million barrels of oil equivalent per day in 2028, 0.23 million barrels of oil equivalent per day in 2029, and 0.20 million barrels of oil equivalent per day in 2030, the data

Microsoft abandons data center projects as OpenAI considers its own, hinting at a market shift

A potential ‘oversupply position’ In a new research note, TD Cowan analysts reportedly said that Microsoft has walked away from new data center projects in the US and Europe, purportedly due to an oversupply of compute clusters that power AI. This follows reports from TD Cowen in February that Microsoft had “cancelled leases in the US totaling a couple of hundred megawatts” of data center capacity. The researchers noted that the company’s pullback was a sign of it “potentially being in an oversupply position,” with demand forecasts lowered. OpenAI, for its part, has reportedly discussed purchasing billions of dollars’ worth of data storage hardware and software to increase its computing power and decrease its reliance on hyperscalers. This fits with its planned Stargate Project, a $500 billion, US President Donald Trump-endorsed initiative to build out its AI infrastructure in the US over the next four years. Based on the easing of exclusivity between the two companies, analysts say these moves aren’t surprising. “When looking at storage in the cloud — especially as it relates to use in AI — it is incredibly expensive,” said Matt Kimball, VP and principal analyst for data center compute and storage at Moor Insights & Strategy. “Those expenses climb even higher as the volume of storage and movement of data grows,” he pointed out. “It is only smart for any business to perform a cost analysis of whether storage is better managed in the cloud or on-prem, and moving forward in a direction that delivers the best performance, best security, and best operational efficiency at the lowest cost.”

PEAK:AIO adds power, density to AI storage server

There is also the fact that many people working with AI are not IT professionals, such as professors, biochemists, scientists, doctors, clinicians, and they don’t have a traditional enterprise department or a data center. “It’s run by people that wouldn’t really know, nor want to know, what storage is,” he said. While the new AI Data Server is a Dell design, PEAK:AIO has worked with Lenovo, Supermicro, and HPE as well as Dell over the past four years, offering to convert their off the shelf storage servers into hyper fast, very AI-specific, cheap, specific storage servers that work with all the protocols at Nvidia, like NVLink, along with NFS and NVMe over Fabric. It also greatly increased storage capacity by going with 61TB drives from Solidigm. SSDs from the major server vendors typically maxed out at 15TB, according to the vendor. PEAK:AIO competes with VAST, WekaIO, NetApp, Pure Storage and many others in the growing AI workload storage arena. PEAK:AIO’s AI Data Server is available now.

SoftBank to buy Ampere for $6.5B, fueling Arm-based server market competition

SoftBank’s announcement suggests Ampere will collaborate with other SBG companies, potentially creating a powerful ecosystem of Arm-based computing solutions. This collaboration could extend to SoftBank’s numerous portfolio companies, including Korean/Japanese web giant LY Corp, ByteDance (TikTok’s parent company), and various AI startups. If SoftBank successfully steers its portfolio companies toward Ampere processors, it could accelerate the shift away from x86 architecture in data centers worldwide. Questions remain about Arm’s server strategy The acquisition, however, raises questions about how SoftBank will balance its investments in both Arm and Ampere, given their potentially competing server CPU strategies. Arm’s recent move to design and sell its own server processors to Meta signaled a major strategic shift that already put it in direct competition with its own customers, including Qualcomm and Nvidia. “In technology licensing where an entity is both provider and competitor, boundaries are typically well-defined without special preferences beyond potential first-mover advantages,” Kawoosa explained. “Arm will likely continue making independent licensing decisions that serve its broader interests rather than favoring Ampere, as the company can’t risk alienating its established high-volume customers.” Industry analysts speculate that SoftBank might position Arm to focus on custom designs for hyperscale customers while allowing Ampere to dominate the market for more standardized server processors. Alternatively, the two companies could be merged or realigned to present a unified strategy against incumbents Intel and AMD. “While Arm currently dominates processor architecture, particularly for energy-efficient designs, the landscape isn’t static,” Kawoosa added. “The semiconductor industry is approaching a potential inflection point, and we may witness fundamental disruptions in the next 3-5 years — similar to how OpenAI transformed the AI landscape. SoftBank appears to be maximizing its Arm investments while preparing for this coming paradigm shift in processor architecture.”

Nvidia, xAI and two energy giants join genAI infrastructure initiative

The new AIP members will “further strengthen the partnership’s technology leadership as the platform seeks to invest in new and expanded AI infrastructure. Nvidia will also continue in its role as a technical advisor to AIP, leveraging its expertise in accelerated computing and AI factories to inform the deployment of next-generation AI data center infrastructure,” the group’s statement said. “Additionally, GE Vernova and NextEra Energy have agreed to collaborate with AIP to accelerate the scaling of critical and diverse energy solutions for AI data centers. GE Vernova will also work with AIP and its partners on supply chain planning and in delivering innovative and high efficiency energy solutions.” The group claimed, without offering any specifics, that it “has attracted significant capital and partner interest since its inception in September 2024, highlighting the growing demand for AI-ready data centers and power solutions.” The statement said the group will try to raise “$30 billion in capital from investors, asset owners, and corporations, which in turn will mobilize up to $100 billion in total investment potential when including debt financing.” Forrester’s Nguyen also noted that the influence of two of the new members — xAI, owned by Elon Musk, along with Nvidia — could easily help with fundraising. Musk “with his connections, he does not make small quiet moves,” Nguyen said. “As for Nvidia, they are the face of AI. Everything they do attracts attention.” Info-Tech’s Bickley said that the astronomical dollars involved in genAI investments is mind-boggling. And yet even more investment is needed — a lot more.

IBM broadens access to Nvidia technology for enterprise AI

The IBM Storage Scale platform will support CAS and now will respond to queries using the extracted and augmented data, speeding up the communications between GPUs and storage using Nvidia BlueField-3 DPUs and Spectrum-X networking, IBM stated. The multimodal document data extraction workflow will also support Nvidia NeMo Retriever microservices. CAS will be embedded in the next update of IBM Fusion, which is planned for the second quarter of this year. Fusion simplifies the deployment and management of AI applications and works with Storage Scale, which will handle high-performance storage support for AI workloads, according to IBM. IBM Cloud instances with Nvidia GPUs In addition to the software news, IBM said its cloud customers can now use Nvidia H200 instances in the IBM Cloud environment. With increased memory bandwidth (1.4x higher than its predecessor) and capacity, the H200 Tensor Core can handle larger datasets, accelerating the training of large AI models and executing complex simulations, with high energy efficiency and low total cost of ownership, according to IBM. In addition, customers can use the power of the H200 to process large volumes of data in real time, enabling more accurate predictive analytics and data-driven decision-making, IBM stated. IBM Consulting capabilities with Nvidia Lastly, IBM Consulting is adding Nvidia Blueprint to its recently introduced AI Integration Service, which offers customers support for developing, building and running AI environments. Nvidia Blueprints offer a suite pre-validated, optimized, and documented reference architectures designed to simplify and accelerate the deployment of complex AI and data center infrastructure, according to Nvidia. The IBM AI Integration service already supports a number of third-party systems, including Oracle, Salesforce, SAP and ServiceNow environments.

Nvidia’s silicon photonics switches bring better power efficiency to AI data centers

Nvidia typically uses partnerships where appropriate, and the new switch design was done in collaboration with multiple vendors across different aspects, including creating the lasers, packaging, and other elements as part of the silicon photonics. Hundreds of patents were also included. Nvidia will licensing the innovations created to its partners and customers with the goal of scaling this model. Nvidia’s partner ecosystem includes TSMC, which provides advanced chip fabrication and 3D chip stacking to integrate silicon photonics into Nvidia’s hardware. Coherent, Eoptolink, Fabrinet, and Innolight are involved in the development, manufacturing, and supply of the transceivers. Additional partners include Browave, Coherent, Corning Incorporated, Fabrinet, Foxconn, Lumentum, SENKO, SPIL, Sumitomo Electric Industries, and TFC Communication. AI has transformed the way data centers are being designed. During his keynote at GTC, CEO Jensen Huang talked about the data center being the “new unit of compute,” which refers to the entire data center having to act like one massive server. That has driven compute to be primarily CPU based to being GPU centric. Now the network needs to evolve to ensure data is being fed to the GPUs at a speed they can process the data. The new co-packaged switches remove external parts, which have historically added a small amount of overhead to networking. Pre-AI this was negligible, but with AI, any slowness in the network leads to dollars being wasted.

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

Stay Ahead, Stay ONMINE