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Not just hype — here are real-world use cases for AI agents

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Just seven or eight months ago, when a customer called in to or emailed Baca Systems with a service question, a human agent handling the query would begin searching for similar cases in the system and […]

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More


Just seven or eight months ago, when a customer called in to or emailed Baca Systems with a service question, a human agent handling the query would begin searching for similar cases in the system and analyzing technical documents. 

This process would take roughly five to seven minutes; then the agent could offer the “first meaningful response” and finally begin troubleshooting. 

But now, with AI agents powered by Salesforce, that time has been shortened to as few as five to 10 seconds. 

“That’s a big [reduction],” Andrew Russo, enterprise architect at Baca Systems, told VentureBeat. He emphasized that, “for us, it’s not about how do we eliminate headcount, reduce staffing. Our goal is, how do we make sure the customer is back up and running as quickly as possible?”

Closing time gaps, delivering faster time to resolution

BACA Systems, a Michigan-based robotics manufacturing company, first implemented Salesforce in 2014, eventually adding Service Cloud to replace its “vanilla, or maybe more like strawberry ice cream, basic service cloud,” Russo explained. The company then did a “giant digital transformation” in 2021, bringing on Salesforce’s enterprise resource planning (ERP) platform. 

Team members soon began working with predictive AI for sales and manufacturing forecasts; then the company evolved to AI agents, implementing Salesforce’s Agentforce within the last year. 

An initial key use case was service calls. Russo explained that about 57% of questions coming in from customers are hardware-related (for instance, a machine falling or requiring calibration). 

Now, instead of having to sift through databases for previous customer calls and similar cases, human reps can ask the AI agent to find the relevant information. The AI runs in the background and allows humans to respond right away, Russo noted. 

AI can also support preventative maintenance. For instance, a circuit breaker might be continually tripping, indicating that there’s a short in the wire that should be investigated, Russo explained. This could help eliminate ongoing issues that haven’t been resolved in the past. 

“It’s all about how do we deliver faster time to resolution for customers,” said Russo.

AI agents generating sales leads, handling customer inquiries

Another critical use case is sales, because as a small company, Baca naturally doesn’t have hundreds of sales people or even dozens (in fact they have less than 10). 

“We have a boatload of leads that we haven’t had time to actually make a reachout to,” said Russo. “Our goal is: How do we start to engage those?”

AI can serve as a sales development representative (SDR) to send out general inquires and emails, have a back-and-forth dialogue, then pass the prospect to a member of the sales team, Russo explained. Bringing on additional salespeople to handle such tasks would require tens of thousands of dollars for salaries, but if AI can develop new deals, its upfront cost is “very easy to justify.”

In coming months, the company plans to deploy customer-facing service agents that can interact with human users via text message to open and handle cases without initial need for human intervention. If the AI agent isn’t able to solve a problem, it will escalate the issue to a human rep. 

The intent is, “How do we keep delivering more value to customers on the service side and create more deals on the sales side?” Russo noted. 

Outside sales and service, Baca is using AI to generate emails, create receivables and craft “very stern collections letters” when required. Russo, for his part, is using the technology for part deduplication checking, leveraging retrieval-augmented generation (RAG) with prompt builders to detect duplicates to prevent bad data from porting into Salesforce. 

There’s been little to no pushback from employees, he reports: The company started small, initially giving a select group of users access. Others then quickly began inquiring. “They actually started to beg [us] to give them access,” Russo noted. “No one’s scared of it; they like using it because it helps make their job better.”

The company is keeping that deliberate, incremental approach as it further incorporates AI so it can remain agile. “Our goals are not changing, it’s just how we get there and the road we’re taking,” said Russo. “It’s a different road, it’s a better road — it’s the highway.”

AI serving up savings for ezCater

Corporate catering is more complicated than it might sound. There can be shifts in headcounts, food preferences and dietary restrictions as well as other logistical challenges. This sometimes has organizers at ezCater scrambling. 

“Concierge agents have really struggled to keep up with the pace,” Erin DeCesare, CTO of the workplace catering platform, told VentureBeat. 

But once the company implements Salesforce’s Agentforce, a customer needing to modify an order will be able to communicate their needs with AI in natural language, and the AI agent will automatically make adjustments. When more complex issues come up — such as a reconfiguration of an order or an all-out venue change — the AI agent will quickly push the matter up to a human rep. 

“This is a huge cost savings for us,” said DeCesare,

Another intended use case is “restaurant discovery” — that is, AI agents will be able to guide users to the best venue based on inputs about their food preferences, budget, location and other factors. This will be supported by data from millions of workplace food orders. “This is what NLP and AI is perfect for,” said DeCesare. 

ezCater is initially incorporating AI agents in-house to assist concierge agents, and the human agents love it, she reports. “We’re giving them tools to be better, and be able to handle more calls.”

There’s been a shift in the comfort level of engineers, too, as they are able to conceive of agents more structurally. “They can test and trust in a way that feels like software development,” said DeCesare. “It’s more like what they would expect in the software development lifecycle.”

Business partners are also excited about the possibilities for tasks such as business analysis or process maps. “The technology has become so accessible in the last six months,” said DeCesare. “You can easily see how this is going to rapidly become the norm. We’re going to be in a very different world 12 months from now.”

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Governing AI in utilities: Insights from West Monroe’s AI summit

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Kyndryl service aims to control agentic AI across the enterprise

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Why the nuclear energy renaissance is real — and necessary

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North America Continues Rig Addition Streak

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FERC rejects MISO petition to limit market monitor’s transmission planning oversight

Federal regulators on Friday rejected calls by the Midcontinent Independent System Operator and its transmission owners that the grid operator’s independent market monitor be effectively barred from transmission planning oversight. MISO’s tariff “unambiguously” authorizes MISO’s market monitor to review and analyze actions that affect the competitiveness, economic efficiency and operation of the grid operator’s markets and services — and transmission planning is one of those actions, FERC said in a decision released Friday. “The [MISO] tariff authorizes the IMM to review and analyze MISO’s transmission planning activities and emphasizes that the IMM should consider the competitive or other market impacts of any MISO action governing or affecting any of the markets and services,” FERC said. MISO filed a petition for declaratory order on May 7 asking FERC to find that the grid operator’s tariff limits the market monitor’s involvement in transmission planning. The petition grew out of Potomac Economic’s criticism of MISO’s needs and cost-benefit analysis that underpinned its roughly $22 billion Tranche 2.1 transmission portfolio that was approved in December, according to filings at FERC. The market monitor argued that MISO overstated its transmission needs and the benefits from its proposed project portfolio. MISO transmission owners such as Ameren, Duke Energy and Entergy supported limiting Potomac Economics’ role in transmission planning. The petition was opposed by the Organization of MISO States, which represents state utility commissions, and consumer advocates. The dispute arose as electric utility bills have surged in the last four years, with millions of people struggling to pay their bills, FERC Chairman Mark Christie said in a concurring statement. “Despite the understandable concern and publicity over capacity market auction results in MISO and [the PJM Interconnection] over the past year, transmission costs are the single biggest driver of skyrocketing monthly power bills and have been for years,”

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Qualus Acquires ADM

Qualus Corp. (Qualus), a U.S.-based power solutions firm and innovator, has acquired ADM Associates LLC (ADM), one of the nation’s leading energy research, evaluation, measurement, and verification (EM&V) firms. Qualus said in a media release that ADM brings expertise in advisory services, planning, program evaluation, regulatory compliance, energy modeling, data science, and software development, particularly in energy efficiency, demand response, and emerging technologies. “Expanding our expertise in energy efficiency has been a key part of our strategy to further enhance our ability to provide smart, efficient, and effective comprehensive solutions to complex energy transformation challenges”, Greg Herasymuik, President and CEO of Qualus, said. “Dr. Taghi Alereza has built a strong brand supported by an impressive team, and we are honored to welcome them to Qualus and be entrusted with ADM’s legacy”. ADM’s pioneering research for agencies such as the Department of Energy has established standards that are now industry benchmarks, Qualus noted. The company provides a wide array of integrated services, from developing strategies to help utilities implement new energy-saving technologies, to data science and software development for advanced energy analytics and AI integration, Qualus added. “We are very impressed with Qualus’ culture, leadership, capabilities, and strategic market position”, Alereza, ADM’s co-founder and CEO, said. “Qualus allows us to scale quickly and smartly, providing our services to more clients in the U.S. and Canada, while providing our team opportunities to grow professionally at an exciting time in our industry”. To contact the author, email [email protected] WHAT DO YOU THINK? Generated by readers, the comments included herein do not reflect the views and opinions of Rigzone. All comments are subject to editorial review. Off-topic, inappropriate or insulting comments will be removed. MORE FROM THIS AUTHOR

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Martin Midstream Partners Posts $2.41MM Loss for Q2

Martin Midstream Partners LP has reported $2.41 million, or $0.06 per unit, in net loss for the second quarter, compared to a net loss of $1.03 million for the prior three-month period and a net profit of $3.78 million for Q2 2024. Q2 2025 results for the Gulf Coast-focused company were marked by lower land transport rates and product margins, which dragged down revenues to $180.68 million, compared to $184.53 million for Q2 2024. Kilgore, Texas-based Martin Midstream Partners maintained its dividend at $0.005 per unit for Q2 2025. “For the quarter, our Sulfur Services segment delivered sales volumes and margins that exceeded our internal projections”, said Bob Bondurant, president and chief executive of the general partner, Martin Midstream GP LLC. “This performance positioned the segment for a successful first half of the year as the Sulfur Services segment prepares to enter turnaround season during the third quarter. “In the Transportation segment, utilization in the marine business was slightly below expectations due to equipment repairs, which reduced cash flow for the quarter. Results from land transportation partially offset the shortfall from marine operations. Land transportation rates continued to show signs of pressure compared to internal projections, but lower-than-expected operating expenses contributed to improved cash flow. “Our Specialty Products segment faced temporary volume reductions this quarter in the grease business unit due to shifts in our customer portfolio, which we expect to normalize soon. At the same time, results from the lubricants business exceeded expectations and helped partially offset the underperformance in the grease business unit. “Lastly, the Terminaling and Storage segment delivered results slightly below our internal projections for the quarter due to higher operating expenses. However, the segment remains fundamentally stable, and we anticipate favorable performance over the second half of the year”. Sales of specialty products totaled $60.34 million

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Oceaneering Signs Contracts with Esso, USA Navy Division

Oceaneering International, Inc. said its subsidiaries have been awarded a contract by ExxonMobil affiliate Esso Exploration Angola (Block 15) Limited for services supporting Esso’s offshore operations in Angola Block 15. Oceaneering Angola, S.A. and Oceaneering Marine Technologies Ltd. entered into the contract, which began on July 1. The contract, awarded through a bidding process, is expected to generate $80 million to $90 million in revenue over its three-year term, Oceaneering said in a news release. The scope of work includes the provision of multiple work-class remote operated vehicles (ROVs), ROV tooling, intervention workover control systems (IWOCS), satellite communication systems, and subsea inspection, hydrate remediation, and engineering services. The services will be deployed from Esso-supplied facilities, intervention vessels, and drilling rigs, according to the release. Oceaneering Subsea Robotics Senior Vice President Martin McDonald said, “Securing this contract renewal with Esso, a key customer, through a competitive process reinforces our position as a trusted partner in Angola’s offshore energy sector. This award not only reflects our capabilities in [the] country for subsea robotics and intervention services but also supports our continued growth in a strategically important region”. Further, Oceaneering ‘s Aerospace and Defense Technologies (ADTech) segment was awarded a follow-on, single award, fixed price, indefinite-delivery, and indefinite-quantity contract to manufacture Virginia Class Submarine support equipment for the Naval Surface Warfare Center Philadelphia Division (NSWCPD) of the U.S. Navy following a bidding process. Under the contract, which started in early June, Oceaneering is tasked with manufacturing work platforms to support maintenance for Virginia Class Submarines’ sail and vertical payload tubes. The contract value is approximately $33 million if all options are exercised over the five-year ordering period, the company said in an earlier statement. In June, Oceaneering’s Offshore Projects Group (OPG) segment entered into a vessel services agreement with an undisclosed major operator

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Cisco upgrades 400G optical receiver to boost AI infrastructure throughput

“In the data center, what’s really changed in the last year or so is that with AI buildouts, there’s much, much more optics that are part of 400G and 800G. It’s not so much using 10G and 25G optics, which we still sell a ton of, for campus applications. But for AI infrastructure, the 400G and 800G optics are really the dominant optics for that application,” Gartner said. Most of the AI infrastructure builds have been for training models, especially in hyperscaler environments, Gartner said. “I expect, towards the tail end of this year, we’ll start to see more enterprises deploying AI infrastructure for inference. And once they do that, because it has an Nvidia GPU attached to it, it’s going to be a 400G or 800G optic.” Core enterprise applications – such as real-time trading, high-frequency transactions, multi-cloud communications, cybersecurity analytics, network forensics, and industrial IoT – can also utilize the higher network throughput, Gartner said. 

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Supermicro bets big on 4-socket X14 servers to regain enterprise trust

In April, Dell announced its PowerEdge R470, R570, R670, and R770 servers with Intel Xeon 6 Processors with P-cores, but with single and double-socket servers. Similarly, Lenovo’s ThinkSystem V4 servers are also based on the Intel Xeon 6 processor but are limited to dual socket configurations. The launch of 4-socket servers by Supermicro reflects a growing enterprise need for localized compute that can support memory-bound AI and reduce the complexity of distributed architectures. “The modern 4-socket servers solve multiple pain points that have intensified with GenAI and memory-intensive analytics. Enterprises are increasingly challenged by latency, interconnect complexity, and power budgets in distributed environments. High-capacity, scale-up servers provide an architecture that is more aligned with low-latency, large-model processing, especially where data residency or compliance constraints limit cloud elasticity,” said Sanchit Vir Gogia, chief analyst and CEO at Greyhound Research. “Launching a 4-socket Xeon 6 platform and packaging it within their modular ‘building block’ strategy shows Supermicro is focusing on staying ahead in enterprise and AI data center compute,” said Devroop Dhar, co-founder and MD at Primus Partner. A critical launch after major setbacks Experts peg this to be Supermicro’s most significant product launch since it became mired in governance and regulatory controversies. In 2024, the company lost Ernst & Young, its second auditor in two years, following allegations by Hindenburg Research involving accounting irregularities and the alleged export of sensitive chips to sanctioned entities. Compounding its troubles, Elon Musk’s AI startup xAI redirected its AI server orders to Dell, a move that reportedly cost Supermicro billions in potential revenue and damaged its standing in the hyperscaler ecosystem. Earlier this year, HPE signed a $1 billion contract to provide AI servers for X, a deal Supermicro was also bidding for. “The X14 launch marks a strategic reinforcement for Supermicro, showcasing its commitment

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Moving AI workloads off the cloud? A hefty data center retrofit awaits

“If you have a very specific use case, and you want to fold AI into some of your processes, and you need a GPU or two and a server to do that, then, that’s perfectly acceptable,” he says. “What we’re seeing, kind of universally, is that most of the enterprises want to migrate to these autonomous agents and agentic AI, where you do need a lot of compute capacity.” Racks of brand-new GPUs, even without new power and cooling infrastructure, can be costly, and Schneider Electric often advises cost-conscious clients to look at previous-generation GPUs to save money. GPU and other AI-related technology is advancing so rapidly, however, that it’s hard to know when to put down stakes. “We’re kind of in a situation where five years ago, we were talking about a data center lasting 30 years and going through three refreshes, maybe four,” Carlini says. “Now, because it is changing so much and requiring more and more power and cooling you can’t overbuild and then grow into it like you used to.”

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My take on the Gartner Magic Quadrant for LAN infrastructure? Highly inaccurate

Fortinet being in the leader quadrant may surprise some given they are best known as a security vendor, but the company has quietly built a broad and deep networking portfolio. I have no issue with them being considered a leader and believe for security conscious companies, Fortinet is a great option. Challenger Cisco is the only company listed as a challenger, and its movement out of the leader quadrant highlights just how inaccurate this document is. There is no vendor that sells more networking equipment in more places than Cisco, and it has led enterprise networking for decades. Several years ago, when it was a leader, I could argue the division of engineering between Meraki and Catalyst could have pushed them out, but it didn’t. So why now? At its June Cisco Live event, the company launched a salvo of innovation including AI Canvas, Cisco AI Assistant, and much more. It’s also continually improved the interoperability between Meraki and Catalyst and announced several new products. AI Canvas is a completely new take, was well received by customers at Cisco Live, and reinvents the concept of AIOps. As I stated above, because of the December cutoff time for information gathering, none of this was included, but that makes Cisco’s representation false. Also, I find this MQ very vague in its “Cautions” segment. As an example, it states: “Cisco’s product strategy isn’t well-aligned with key enterprise needs.” Some details here would be helpful. In my conversations with Cisco, which includes with Chief Product Officer and President Jeetu Patel, the company has reiterated that its strategy is to help customers be AI-ready with products that are easier to deploy and manage, more automated, and with a lower cost to run. That seems well-aligned with customer needs. If Gartner is hearing customers want networks

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Equinix, AWS embrace liquid cooling to power AI implementations

With AWS, it deployed In-Row Heat Exchangers (IRHX), a custom-built liquid cooling system designed specifically for servers using Nvidia’s Blackwell GPUs, it’s most powerful but also its hottest running processors used for AI training and inference. The IRHX unit has three components: a water‑distribution cabinet, an integrated pumping unit, and in‑row fan‑coil modules. It uses direct to chip liquid cooling just like the equinox servers, where cold‑plates attached to the chip draw heat from the chips and is cooled by the liquid. The warmed coolant then flows through the coils of heat exchangers, where high‑speed fans Blow on the pipes to cool them, like a car radiator. This type of cooling is nothing new, and there are a few direct to chip liquid cooling solutions on the market from Vertiv, CoolIT, Motivair, and Delta Electronics all sell liquid cooling options. But AWS separates the pumping unit from the fan-coil modules, letting a single pumping system to support large number of fan units. These modular fans can be added or removed as cooling requirements evolve, giving AWS the flexibility to adjust the system per row and site. This led to some concern that Amazon would disrupt the market for liquid cooling, but as a Dell’Oro Group analyst put it, Amazon develops custom technologies for itself and does not go into competition or business with other data center infrastructure companies.

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Intel CEO: We are not in the top 10 semiconductor companies

The Q&A session came on the heels of layoffs across the company. Tan was hired in March, and almost immediately he began to promise to divest and reduce non-core assets. Gelsinger had also begun divesting the company of losers, but they were nibbles around the edge. Tan is promising to take an axe to the place. In addition to discontinuing products, the company has outsourced marketing and media relations — for the first time in more than 25 years of covering this company, I have no internal contacts at Intel. Many more workers are going to lose their jobs in coming weeks. So far about 500 have been cut in Oregon and California but many more is expected — as much as 20% of the overall company staff may go, and Intel has over 100,000 employees, according to published reports. Tan believes the company is bloated and too bogged down with layers of management to be reactive and responsive in the same way that AMD and Nvidia are. “The whole process of that (deciding) is so slow and eventually nobody makes a decision,” he is quoted as saying. Something he has decided on is AI, and he seems to have decided to give up. “On training, I think it is too late for us,” Tan said, adding that Nvidia’s position in that market is simply “too strong.” So there goes what sales Gaudi3 could muster. Instead, Tan said Intel will focus on “edge” artificial intelligence, where AI capabilities Are brought to PCs and other remote devices rather than big AI processors in data centers like Nvidia and AMD are doing. “That’s an area that I think is emerging, coming up very big and we want to make sure that we capture,” Tan said.

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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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