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Are utility demand response program costs outstripping their benefits in California?

Collin Smith is a regulatory affairs manager at Leap, a company that helps distributed energy resources participate in wholesale markets. California’s electricity prices are skyrocketing. In October, Gov. Gavin Newsom issued an executive order aimed at tackling this issue, calling for the California Public Utilities Commission to evaluate the cost-effectiveness of ratepayer-funded programs and determine […]

Collin Smith is a regulatory affairs manager at Leap, a company that helps distributed energy resources participate in wholesale markets.

California’s electricity prices are skyrocketing. In October, Gov. Gavin Newsom issued an executive order aimed at tackling this issue, calling for the California Public Utilities Commission to evaluate the cost-effectiveness of ratepayer-funded programs and determine where program spending may be outstripping those programs’ benefits. Among the trends worth scrutinizing is the state’s increasing shift towards utility-run supply-side demand response programs.

In 2015, California sub-divided its DR programs, creating a class of programs known as “supply-side DR,” or SSDR. This class of programs allowed DR aggregators to bid demand-side resources directly into California’s wholesale market and earn capacity payments through its Resource Adequacy program. 

The logic was simple: both energy prices in the wholesale market and capacity prices in RA are determined by the laws of supply and demand, producing the most cost-effective pricing for these respective energy products. As a result, using these mechanisms to procure DR resources would naturally direct California’s load-serving entities to procure the least-cost options, supporting California’s longstanding goal of developing DR programs that can cost-effectively meet the needs of the grid

Who pays the price of a program?

Over the last decade, third-party DR providers, or DRPs, have begun participating directly in these markets at scale, but California also allows investor-owned utilities to participate via their own SSDR programs. However, unlike third-party DRPs, the costs for IOU-run programs are largely divorced from market dynamics. Administrative costs for third-party DRPs are covered by their balance sheets, so they cannot be higher than what those DRPs can recover from the market. By contrast, administrative costs for IOU-run programs are recovered directly from ratepayers, so their costs can be whatever the IOU says it needs to run them.

These administrative costs can be significant. For example, Pacific Gas & Electric’s costs for implementing its legacy Capacity Bidding Program in 2024-27 were 9% of its overall CBP budget for those years. The administrative costs for its new Automated Response Technology program (approved in 2023) were even higher, coming in at 12% of the program’s budget. The difference is even larger in objective terms, because ART has a larger budget overall due to the higher incentives it pays participants. 

In total, PG&E is approved to spend $4.76 million in administrative costs over the first four years of ART, more than twice the $2.35 million allocated for CBP over the same period — despite the fact that ART’s load reduction is expected to be roughly the same as CBP’s. Yet, just one year after ART was approved, PG&E requested an additional $1.97 million to expand its CBP program to serve the same customer base targeted by ART. It’s clear that PG&E’s recent proposals are increasing costs to customers; what’s less clear is whether the benefits of these programs are keeping pace.

Moving in the wrong direction

While it’s reasonable for IOUs to seek funding for programs that benefit their customers, rising electricity costs make it critical to ensure these budgets align with actual needs. Already, there’s evidence that this is not the case. For example, PG&E stated that it could fully fund the expansions to its CBP programs with unspent funds from its original budget. Although it’s great that this expansion wouldn’t further increase rates, why was so much of the budget unspent in the first place? And would it not be better to return these unspent funds to customers as a bill credit, as Gov. Newsom requested in his executive order?

The fact is that, because IOU costs aren’t subject to market forces, there’s a greater risk that their costs are higher than needed. Despite this, CPUC policy has steadily been pushing more customers to choose IOU-run SSDR programs over third-party options. Recent CPUC decisions have tied lucrative incentives like Automated DR and the Self-Generation Incentive Program to participation in CBP or certain IOU tariffs, despite the fact that third party options provide similar (if not greater) support to the grid. In fact, the reason PG&E proposed expanding its CBP program in the first place was to accommodate SGIP recipients that were unable to enroll in a DR program that fit the CPUC’s narrow list of “qualified” options. 

In the past, the CPUC has worked to maintain a level playing field between third-party and IOU run SSDR programs, recognizing that greater customer choice is an important component of a cost-effective DR sector. But in a December 2023 decision, the CPUC walked back this principle, stating that “any actions that are meant to prop up the third-party DRPs vis-à-vis the IOUs must also provide cost-effective benefits to ratepayers.” The focus on cost-effectiveness is correct, but the logic is backward. Third-party DRPs are funded by their shareholders and are already subject to competitive pressures that keep their costs low. It’s IOU programs that are required to justify their costs to ratepayers. 

Open competition naturally pushes costs down, a principle that is as applicable to DR as it is to other sections of the economy. California, however, is currently moving in the opposite direction with incentive policies that favor IOUs over third-party DRPs. This pushes customers into DR programs with less accountable cost structures and ultimately requires IOUs to request more ratepayer funds to expand these programs. If the intent of Gov. Newsom’s executive order was to tamp down costs from ratepayer-funded programs, current CPUC policy is doing the opposite.

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Nvidia launches research center to accelerate quantum computing breakthrough

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Global oil demand has made a strong start to 2025, analysts at Standard Chartered Bank, including Commodities Research Head Paul Horsnell, said in a report sent to Rigzone by Horsnell on Thursday. “Based on a variety of national sources and the 19 March Joint Organizations Data Initiative (JODI) release, we estimate that demand averaged 102.77 million barrels per day in January, a year on year increase of 2.19 million barrels per day,” the Standard Chartered Bank analysts said in the report. “This is in line with the U.S. Energy Information Administration (EIA) estimate for January that put demand at 102.74 million barrels per day and growth at 1.85 million barrels per day,” they added. In the report, the Standard Chartered Bank analysts noted that January is usually the seasonal low point for global demand and said they expect demand “to move above 105.0 million barrels per day for the first time in June before reaching a 2025 high of 105.6 million barrels per day in August”. “Our forecast for 2025 demand growth stands at 1.41 million barrels per day. After weakening in H2-2024, our forecast is now back where it stood at its initiation in January 2024,” they added. “While the main downside risk to demand comes from U.S. tariff policy and the economic uncertainty it creates, for now demand-side fundamentals appear robust despite negative sentiment,” they continued. The Standard Chartered Bank analysts stated in the report that they expect global demand to exceed supply by 0.9 million barrels per day in the second quarter and by 0.5 million barrels per day in the third quarter. Rigzone has contacted the Trump transition team and the White House for comment on Standard Chartered Bank’s report. At the time of writing, neither have responded to Rigzone. In a research note sent to

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Voyager Midstream Acquires Phillips 66 Stake in Panola NGL Pipeline

Voyager Midstream Holdings LLC has completed the purchase of a non-operating stake in a Texas natural gas liquid (NGL) pipeline from Phillips 66. The 254-mile Panola Pipeline, operated by Enterprise Products Partners LP, transports Y-Grade NGLs from Panola County to fractionation facilities in Mont Belvieu city. “Voyager’s interest in the Panola Pipeline is a strategic fit with the company’s existing footprint in East Texas and North Louisiana”, Houston, Texas-based Voyager said in an online statement, referring to assets also acquired from Phillips 66. Voyager chief executive Will Harvey commented, “Panola Pipeline is a critical NGL pipeline connecting the major East Texas gas processing complexes and Gulf Coast demand markets”. “We are excited to work alongside our partners in Panola Pipeline to safely transport liquids to satisfy growing demand for NGLs along the Gulf Coast”, Harvey added. Voyager did not disclose the financial details of the transaction. It said that in conjunction with the acquisition, it has entered into a credit facility with the Bank of Oklahoma. “This credit facility, along with existing equity commitments from Pearl, provides Voyager with substantial flexibility and capital to continue growing its business in support of its customers”, it said. Pearl Energy Investments launched Voyager in 2023 as a platform for the acquisition and development of crude oil, natural gas and produced water infrastructure across key basins in North America. Voyager operates about 550 miles of natural gas pipelines and associated compression. It also has 400 million cubic feet a day of cryogenic gas processing capacity and 12,000 barrels per day of liquid fractionation capacity. It also operates Carthage Hub, a gas trading and delivery hub capable of handling over 1 billion cubic feet per day. Carthage Hub interconnects multiple markets across the United States including LNG markets in Texas and Louisiana. All of these

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BP makes first divestment of target $20bn asset sale

Energy firm BP has sold a stake worth $1 billion (£733m) in the Trans-Anatolian Natural Gas Pipeline (TANAP) to Apollo as part of the first tranche of a $20bn asset sale target. The US asset manager will take a 25% non-operated stake in BP Pipelines (TANAP) (BP TANAP) which itself holds BP’s 12% interest in TANAP, owner and operator of the pipeline that carries natural gas from Azerbaijan across Turkey. The sale comes after BP chief executive Murray Auchincloss unveiled plans to review assets for a potential sale including its core lubricants business, Castrol and its solar business, BP Lightsource. The $20bn target was announced alongside a “fundamental reset” for the firm as it turns focus to its traditional oil and gas production business. The deal marks the second such sale agreed with US fund manager, Apollo. Last year Apollo snapped up another $1bn BP-owned stake in Trans Adriatic Pipeline (TAP). TANAP, running for approximately 1,120 miles (1,800km) across Turkey, is the central section of the Southern Gas Corridor project (SGC) pipeline system. The SGC transports gas from the BP-operated Shah Deniz gas field in the Azerbaijan sector of the Caspian Sea to markets in Europe, including Italy and Greece. It connects to TAP at the Greek-Turkish border, which crosses Northern Greece, Albania and the Adriatic Sea before coming ashore in Southern Italy to connect to the Italian natural gas network. BP said the deal allows it to “monetise” its interest in TANAP while retaining control of the asset. BP executive vice president for gas and low carbon energy William Lin said: “This unlocks capital from our global portfolio while retaining our role in this strategic asset for bringing Azerbaijan gas to Europe. BP and Apollo will continue to explore further strategic cooperation and mutually beneficial opportunities.” Apollo partner Skardon Baker

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‘First Major Project’ for GB Energy Announced

A release posted on the UK government website on Friday announced that the “first major project” for Great British Energy (GB Energy) “is to put rooftop solar panels on around 200 schools and 200 NHS sites, saving hundreds of millions on their energy bills”. Hundreds of schools, NHS trusts and communities across the UK will benefit from new rooftop solar power and renewable schemes to save money on their energy bills, thanks to a total GBP 200 million ($258.6 million) investment from the UK government and Great British Energy, the release stated. “In England around GBP 80 million ($103.4 million) in funding will support around 200 schools, alongside GBP 100 million ($129.3 million) for nearly 200 NHS sites, covering a third of NHS trusts, to install rooftop solar panels that could power classrooms and operations, with potential to sell leftover energy back to the grid,” the release noted. The first panels are expected to be in schools and hospitals by the end of summer 2025, according to the release. The release stated that local authorities and community energy groups will also be supported by nearly GBP 12 million ($15.5 million) to help build local clean energy projects. A further GBP 9.3 million ($12.0 million) will power schemes in Scotland, Wales, and Northern Ireland including community energy or rooftop solar for public buildings, the release added. “Great British Energy’s first major project will be to help our vital public institutions save hundreds of millions on bills to reinvest on the frontline,” Energy Secretary Ed Miliband said in the release. “Great British Energy will provide power for pupils and patients,” he added. “Parents at the school gate and patients in hospitals will experience the difference Great British Energy can make. This is our clean energy superpower mission in action, with lower bills

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Raymond James Sees Biggest Crop of New Oil Projects in a Decade

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Net zero cannot be ‘in isolation’ from fossil fuels, industry chief to say

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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.

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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.”

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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.

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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.

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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.

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Critical vulnerability in AMI MegaRAC BMC allows server takeover

“In disruptive or destructive attacks, attackers can leverage the often heterogeneous environments in data centers to potentially send malicious commands to every other BMC on the same management segment, forcing all devices to continually reboot in a way that victim operators cannot stop,” the Eclypsium researchers said. “In extreme scenarios, the net impact could be indefinite, unrecoverable downtime until and unless devices are re-provisioned.” BMC vulnerabilities and misconfigurations, including hardcoded credentials, have been of interest for attackers for over a decade. In 2022, security researchers found a malicious implant dubbed iLOBleed that was likely developed by an APT group and was being deployed through vulnerabilities in HPE iLO (HPE’s Integrated Lights-Out) BMC. In 2018, a ransomware group called JungleSec used default credentials for IPMI interfaces to compromise Linux servers. And back in 2016, Intel’s Active Management Technology (AMT) Serial-over-LAN (SOL) feature which is part of Intel’s Management Engine (Intel ME), was exploited by an APT group as a covert communication channel to transfer files. OEM, server manufacturers in control of patching AMI released an advisory and patches to its OEM partners, but affected users must wait for their server manufacturers to integrate them and release firmware updates. In addition to this vulnerability, AMI also patched a flaw tracked as CVE-2024-54084 that may lead to arbitrary code execution in its AptioV UEFI implementation. HPE and Lenovo have already released updates for their products that integrate AMI’s patch for CVE-2024-54085.

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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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