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McAfee launches scam detector to stop scams before they strike

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Scams are everywhere. McAfee’s new scam detector spots and stops scams across text, email, and video to keep you from being fooled. McAfee today announced at CES 2025 the launch of McAfee Scam Detector – the […]

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Scams are everywhere. McAfee’s new scam detector spots and stops scams across text, email, and video to keep you from being fooled.

McAfee today announced at CES 2025 the launch of McAfee Scam Detector – the most comprehensive protection against text, email, and video scams. Today’s scams are smarter, sneakier, and more convincing than ever – and they’re everywhere. One in three Americans admit falling for a text, email, or video scam in the last 12 months.

From fake emails and suspicious texts to deepfake videos that look incredibly real, scammers are using clever tricks to steal people’s money and personal information. McAfee is helping consumers take back control with its AI-powered McAfee Scam Detector to stop scammers in their tracks.

McAfee is using AI to try to stop scams before they strike via automatic detection of scams or potential scams. Scammers have a couple of things working in their favor, said Steve Grobman, CTO of McAfee, in an interview with GamesBeat.

One is there’s a large number of private communication channels where there’s not necessarily a moderator, like on encrypted messaging or direct messaging. They could be communicating with the victim, you know, under the guise of security. The other piece is real time, and it’s one of the reasons that McAfee has made its deepfake detector product work on any video stream in the web, Grobman said.

Beginning this spring, McAfee’s Scam Detector will be included at no extra cost for McAfee customers. This must-have product uses the latest in advanced AI technology to proactively analyze and flag risky messages in real time. That ‘Hi, how are you?’ text from a stranger? It’s one of the top text scams of 2024.

I got a scam email about using an automated document signing service, with an attachment saying “termination NDA” on it. I almost fell for that one, given the urgency I associated with that one. (I wasn’t fired).

An urgent email about a failed delivery? Probably fake. And no, Elon Musk doesn’t have a unique investment opportunity for you. McAfee makes it easy to tell real from fake in seconds and gives you the winning combination of tips and technology to keep scams out of your life for good.

“I think the thing that is most clever is the personalization,” said Grobman. “One of the things that we have seen are job scams, where people have made their search public, and those scams take the form of taking your job interview to the next level but it requires a background check and we require the applicant to pay for the background check.”

He said the scanning for scams is working in real time, making it possible to catch the scammers at the right times.

Background

A year ago, Grobman talked to me about focusing on scam defense in three areas: scams that come through email, scams that come through text, and then scams that users are exposed to, more generally, in other media forms like video.

To address that, the company developed advanced AI models to protect consumers in all three of those areas and it started to deploy them in late 2024. One of those was a deepfake detector to help consumers identify whether AI generated videos are AI generated versus authentic.

The company also ran technology previews for our other modalities, namely email and text.

“And now that we’re moving into 2025 we’re very excited to move all of these technologies into a much larger scale by making them available to the vast majority of our customers,” Grobman said. “We’re evolving our AI models to take advantage of advanced AI PCs when an advanced AI PC is there. So we can run our AI models on the [PC’s own] NPU, but we also have the ability to run on other inference engines, either the CPU or GPU, which is able to give us a broader scope, to give capabilities to a broader set of users.”

The email scam defense is going to move beyond a technology preview that McAfee did in 2024 where it was available for Microsoft-based email properties. Now it can support Gmail and other properties.

“In offerings in 2025, we’ve developed advanced technology to detect deep fake images. So we did a partnership with Yahoo News in 2024 around helping to ensure that images that came through the news pipeline, that their editors, their quality assurance personnel, could best detect if anything was generated with AI image generation technology and help provide that insight.”

Protecting people in today’s Scamiverse

Every day, scammers trick people with fake emails, texts, and videos, and the results can be devastating. Americans report receiving 12 scam messages daily, losing as much as $1,000 when they fall for one, and spend 80 hours a year simply trying to figure out if the onslaught of messages they receive are real or fake, according to a McAfee survey. And deepfake scams, which use AI to create fake video, can be even worse – some people have lost up to half a million dollars, based on a McAfee survey.

It’s clear that scams have become a drain on people’s time, energy, and finances.

“I’ve had more issues with scam texts recently. I’d say within the last year, it’s just been bad. Like I’ve been getting a lot of spam emails, texts, calls…it’s a lot,” said Tina, 31, in South Carolina.

“It was a fake email for UPS. I thought that I was signing up to change my address and instead it charged my credit card,” said Alexandria, 46, in Georgia.

“While I love new technology, I have been very scared of AI generated videos and information since seeing just how realistic it can be,” said Haley, 24, from New Jersey.

“Scammers are getting smarter every day, using technology like artificial intelligence to make their tricks more convincing and harder to spot,” said Grobman. “They play on people’s emotions – like fear, urgency, or trust – to get what they want. That’s why we created McAfee Scam Detector. It warns you about scams before they can cause harm, helps you stay in control of your personal information, and helps you build the skills needed to outsmart scammers for good.”

Grobman said MAfee saw a lot of holiday scams, offering good deals for shoppers, during the recent holiday season.

“They offer deals that are too good to be true,” Grobman said. “Cyber criminals are in the business of extorting money from their victims, and generative AI is making them more effective and more efficient as well.”

How McAfee’s Scam Detector works

McAfee’s Scam Detector is powered by Smart AI, the same technology that makes McAfee’s online protection award-winning and so reliable. Here’s what this all-in-one protection does to keep people safe from email, text message, and video scams:

Email Scam Detector: Scans your inbox for suspicious emails and flags risky messages before you even open them. It also explains why a message is dangerous, so you’ll know what to look out for next time.

Text Scam Detector: Detects suspect texts that scammers use to trick you into giving them money or clicking bad links, flags risky messages before you open them, and gives you clear explanations of why they’re dangerous. You need the McAfee mobile app for iOS or Android to enable this. You would just enable this on the app.

Deepfake Detector: Spots AI-made videos, letting you know if something you’re watching may not be what it seems. Whether it’s someone pretending to be your boss or a fake celebrity endorsement, McAfee makes sure you don’t get fooled. Innovation for deepfake detection continues with expansion to more languages and will soon work seamlessly wherever you’re online – across phones, tablets, laptops, and
desktops.

The deep fake detector for AI PCs is currently available and McAfee will be expanding that to the vast majority of modern PCs, Grobman said.

By running deepfake detection at the edge on a user’s PC, the system is optimized for privacy and latency.

“If we detect something from streaming, we give that information to the user right away and we don’t have any latency,” he said. “We take full advantage of the innovation that’s happened in the hardware ecosystem and device ecosystem.”

McAfee is also showing at CES its tech that works on Mac, Android and Chromebooks — going beyond AI-based protection on Microsoft Windows.

Simple, easy protection for everyone

Free for McAfee customers: Soon, McAfee Scam Detector will be included in all McAfee+, McAfee Total Protection, and McAfee LiveSafe plans at no extra cost.

Works instantly: Once it’s set up, Scam Detector goes to work immediately. No need to copy, paste, or second-guess if a message is fake – McAfee does it for you.

Protects you wherever you’re online: Whether you’re using a phone, laptop, tablet, or Chromebook, Scam Detector keeps you safe.

For more tips on avoiding scams and staying safe online, visit the McAfee Smart AITM Hub at mcafee.ai.

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Cisco strengthens integrated IT/OT network and security controls

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MOL’s Tiszaújváros steam cracker processes first circular feedstock

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Network jobs watch: Hiring, skills and certification trends

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WTI Falls on Stockpile, Fed Moves

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XRG Walks Away From $19B Santos Takeover

Abu Dhabi National Oil Co. dropped its planned $19 billion takeover of Australian natural gas producer Santos Ltd., walking away from an ambitious effort to expand overseas after failing to agree on key terms. A “combination of factors” discouraged the company’s XRG unit from making a final bid, it said Wednesday. The decision was strictly commercial and reflected disagreement over issues including valuation and tax, people familiar with the matter said, asking not to be identified discussing private information. It’s a notable retreat for XRG, the Adnoc spinoff launched to great fanfare last year and tasked with deploying Abu Dhabi’s billions into international dealmaking. The firm has been looking to build a global portfolio, particularly in chemicals and liquefied natural gas, and nixing the Santos transaction may slow an M&A drive aimed at diversifying the Middle Eastern emirate away from crude. The company made its indicative offer in June with a consortium that included Abu Dhabi Development Holding Co. and Carlyle Group Inc. The board of Santos, Australia’s second-largest fossil-fuel producer, recommended the $5.76-a-share proposal, which represented a 28% premium to the stock price at the time. But although the shares surged that day, they have remained well below the offer price, potentially indicating investors were skeptical the consortium could land the deal. Santos extended an exclusivity period for a second time last month, saying the group had sought more time to complete due diligence and obtain approvals. “The market will ask questions about Santos’ valuation after this,” Saul Kavonic, an energy analyst at MST Marquee, said by email. Investors may be wary about “any skeletons that may be lurking there, all the more so because XRG was a less price-sensitive buyer than most, yet still couldn’t make it work.” Santos’ American depositary receipts slumped as much as 9.5% to $4.69 on Wednesday. Covestro Hurdles Following agreements for

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Slovakia and Hungary Resist Trump Bid to Halt Russian Energy

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Slovakia Resists Pressure to Quickly Halt Russian Energy

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Energy-related US CO2 emissions down 20% since 2005: EIA

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Chord Announces ‘Strategic Acquisition of Williston Basin Assets’

Chord Energy Corporation announced a “strategic acquisition of Williston Basin assets” in a statement posted on its website recently. In the statement, Chord said a wholly owned subsidiary of the company has entered into a definitive agreement to acquire assets in the Williston Basin from XTO Energy Inc. and affiliates for a total cash consideration of $550 million, subject to customary purchase price adjustments. The consideration is expected to be funded through a combination of cash on hand and borrowings, Chord noted in the statement, which highlighted that the effective date for the transaction is September 1, 2025, and that the deal is expected to close by year-end. Chord outlined in the statement that the deal includes 48,000 net acres in the Williston core, noting that “90 net 10,000 foot equivalent locations (72 net operated) extend Chord’s inventory life”. Pointing out “inventory quality” in the statement, Chord highlighted that “low average NYMEX WTI breakeven economics ($40s) compete at the front-end of Chord’s program and lower the weighted-average breakeven of Chord’s portfolio”. The company outlined that the deal is “expected to be accretive to all key metrics including cash flow, free cash flow and NAV in both near and long-term”. “We are excited to announce the acquisition of these high-quality assets,” Danny Brown, Chord Energy’s President and Chief Executive Officer, said in the statement. “The acquired assets are in one of the best areas of the Williston Basin and have significant overlap with Chord’s existing footprint, setting the stage for long-lateral development. The assets have a low average NYMEX WTI breakeven and are immediately competitive for capital,” he added. “We expect that the transaction will create significant accretion for shareholders across all key metrics, while maintaining pro forma leverage below the peer group and supporting sustainable FCF generation and return of capital,” he continued.

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Land and Expand: CleanArc Data Centers, Google, Duke Energy, Aligned’s ODATA, Fermi America

Land and Expand is a monthly feature at Data Center Frontier highlighting the latest data center development news, including new sites, land acquisitions and campus expansions. Here are some of the new and notable developments from hyperscale and colocation data center operators about which we’ve been reading lately. Caroline County, VA, Approves 650-Acre Data Center Campus from CleanArc Caroline County, Virginia, has approved redevelopment of the former Virginia Bazaar property in Ruther Glen into a 650-acre data center campus in partnership with CleanArc Data Centers Operating, LLC. On September 9, 2025, the Caroline County Board of Supervisors unanimously approved an economic development performance agreement with CleanArc to transform the long-vacant flea market site just off I-95. The agreement allows for the phased construction of three initial data center buildings, each measuring roughly 500,000 square feet, which CleanArc plans to lease to major operators. The project represents one of the county’s largest-ever private investments. While CleanArc has not released a final capital cost, county filings suggest the development could reach into the multi-billion-dollar range over its full buildout. Key provisions include: Local hiring: At least 50 permanent jobs at no less than 150% of the prevailing county wage. Revenue sharing: Caroline County will provide annual incentive grants equal to 25% of incremental tax revenue generated by the campus. Water stewardship: CleanArc is prohibited from using potable county water for data center cooling, requiring the developer to pursue alternative technologies such as non-potable sources, recycled water, or advanced liquid cooling systems. Local officials have emphasized the deal’s importance for diversifying the county’s tax base, while community observers will be watching closely to see which cooling strategies CleanArc adopts in order to comply with the water-use restrictions. Google to Build $10 Billion Data Center Campus in Arkansas Moses Tucker Partners, one of Arkansas’

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Hyperion and Alice & Bob Call on HPC Centers to Prepare Now for Early Fault-Tolerant Quantum Computing

As the data center industry continues to chase greater performance for AI and scientific workloads, a new joint report from Hyperion Research and Alice & Bob is urging high performance computing (HPC) centers to take immediate steps toward integrating early fault-tolerant quantum computing (eFTQC) into their infrastructure. The report, “Seizing Quantum’s Edge: Why and How HPC Should Prepare for eFTQC,” paints a clear picture: the next five years will demand hybrid HPC-quantum workflows if institutions want to stay at the forefront of computational science. According to the analysis, up to half of current HPC workloads at U.S. government research labs—Los Alamos National Laboratory, the National Energy Research Scientific Computing Center, and Department of Energy leadership computing facilities among them—could benefit from the speedups and efficiency gains of eFTQC. “Quantum technologies are a pivotal opportunity for the HPC community, offering the potential to significantly accelerate a wide range of critical science and engineering applications in the near-term,” said Bob Sorensen, Senior VP and Chief Analyst for Quantum Computing at Hyperion Research. “However, these machines won’t be plug-and-play, so HPC centers should begin preparing for integration now, ensuring they can influence system design and gain early operational expertise.” The HPC Bottleneck: Why Quantum is Urgent The report underscores a familiar challenge for the HPC community: classical performance gains have slowed as transistor sizes approach physical limits and energy efficiency becomes increasingly difficult to scale. Meanwhile, the threshold for useful quantum applications is drawing nearer. Advances in qubit stability and error correction, particularly Alice & Bob’s cat qubit technology, have compressed the resource requirements for algorithms like Shor’s by an estimated factor of 1,000. Within the next five years, the report projects that quantum computers with 100–1,000 logical qubits and logical error rates between 10⁻⁶ and 10⁻¹⁰ will accelerate applications across materials science, quantum

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Google Partners With Utilities to Ease AI Data Center Grid Strain

Transmission and Power Strategy These agreements build on Google’s growing set of strategies to manage electricity needs. In June of 2025, Google announced a deal with CTC Global to upgrade transmission lines with high-capacity composite conductors that increase throughput without requiring new towers. In July 2025, Google and Brookfield Asset Management unveiled a hydropower framework agreement worth up to $3 billion, designed to secure firm clean energy for data centers in PJM and Eastern markets. Alongside renewable deals, Google has signed nuclear supply agreements as well, most notably a landmark contract with Kairos Power for small modular reactor capacity. Each of these moves reflects Google’s effort to create more headroom on the grid while securing firm, carbon-free power. Workload Flexibility and Grid Innovation The demand-response strategy is uniquely suited to AI data centers because of workload diversity. Machine learning training runs can sometimes be paused or rescheduled, unlike latency-sensitive workloads. This flexibility allows Google to throttle certain compute-heavy processes in coordination with utilities. In practice, Google can preemptively pause or shift workloads when notified of peak events, ensuring critical services remain uninterrupted while still creating significant grid relief. Local Utility Impact For utilities like I&M and TVA, partnering with hyperscale customers has a dual benefit: stabilizing the grid while keeping large customers satisfied and growing within their service territories. It also signals to regulators and ratepayers that data centers, often criticized for their heavy energy footprint, can actively contribute to reliability. These agreements may help avoid contentious rate cases or delays in permitting new power plants. Policy, Interconnection Queues, and the Economics of Speed One of the biggest hurdles for data center development today is the long wait in interconnection queues. In regions like PJM Interconnection, developers often face waits of three to five years before new projects can connect

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Generators, Gas, and Grid Strategy: Inside Generac’s Data Center Play

A Strategic Leap Generac’s entry represents a strategic leap. Long established as a leader in residential, commercial, and industrial generation—particularly in the sub-2 megawatt range—the company has now expanded into mission-critical applications with new products spanning 2.2 to 3.5 megawatts. Navarro said the timing was deliberate, citing market constraints that have slowed hyperscale and colocation growth. “The current OEMs serving this market are actually limiting the ability to produce and to grow the data center market,” he noted. “Having another player … with enough capacity to compensate those shortfalls has been received very, very well.” While Generac isn’t seeking to reinvent the wheel, it is intent on differentiation. Customers, Navarro explained, want a good quality product, uneventful deployment, and a responsive support network. On top of those essentials, Generac is leveraging its ongoing transformation from generator manufacturer to energy technology company, a shift accelerated by a series of acquisitions in areas like telemetry, monitoring, and energy management. “We’ve made several acquisitions to move away from being just a generator manufacturer to actually being an energy technology company,” Navarro said. “So we are entering this space of energy efficiency, energy management—monitoring, telemetrics, everything that improves the experience and improves the usage of those generators and the energy management at sites.” That foundation positions Generac to meet the newest challenge reshaping backup generation: the rise of AI-centric workloads. Natural Gas Interest—and the Race to Shorter Lead Times As the industry looks beyond diesel, customer interest in natural gas generation is rising. Navarro acknowledged the shift, but noted that diesel still retains an edge. “We’ve seen an increase on gas requests,” he said. “But the power density of diesel is more convenient than gas today.” That tradeoff, however, could narrow. Navarro pointed to innovations such as industrial storage paired with gas units, which

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Executive Roundtable: Cooling, Costs, and Integration in the AI Data Center Era

Becky Wacker, Trane:  As AI workloads increasingly dominate new data center builds, operators face significant challenges in managing thermal loads and water resources. These challenges include significantly higher heat density, large, aggregated load spikes, uneven distribution of cooling needs, and substantial water requirements if using traditional evaporative cooling methods. The most critical risks include overheating, inefficient cooling systems, and water scarcity. These issues can lead to reduced hardware lifespan, hardware throttling, sudden shutdowns, failure to meet PUE targets, higher operational costs, and limitations on where AI data centers can be built due to water constraints. At Trane, we are evolving our solutions to meet these challenges through advanced cooling technologies such as liquid cooling and immersion cooling, which offer higher efficiency and lower thermal resistance compared to traditional air-cooling methods. Flexibility and scalability are central to our design philosophy. We believe a total system solution is crucial, integrating components such as CDUs, Fan Walls, CRAHs, and Chillers to anticipate demand and respond effectively. In addition, we are developing smart monitoring and control systems that leverage AI to predict and manage thermal loads in real-time, ensuring optimal performance and preventing overheating through Building Management Systems and integration with DCIM platforms. Our water management solutions are also being enhanced to recycle and reuse water, minimizing consumption and addressing scarcity concerns.

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Power shortages are the only thing slowing the data center market

Another major shortage – which should not be news to anyone – is power. Lynch said that it is the primary reason many data centers are moving out of the heavily congested areas, like Northern Virginia and Santa Clara, and into secondary markets. Power is more available in smaller markets than larger ones. “If our client needs multi-megawatt capacity in Silicon Valley, we’re being told by the utility providers that that capacity will not be available for up to 10 years from now,” so out of necessity, many have moved to secondary markets, such as Hillsborough, Oregon, Reno, Nevada, and Columbus, Ohio. The growth of hyperscalers as well as AI is driving up the power requirements of facilities further into the multi-megawatt range. The power industry moves at a very different pace than the IT world, much slower and more deliberate. Lynch said the lead time for equipment makes it difficult to predict when some large scale, ambitious data centers can be completed. A multi-megawatt facility may even require new transmission lines to be built out as well. This translates into longer build times for new data centers. CBRE found that the average data center now takes about three years to complete, up from 2 years just a short time ago. Intel, AMD, and Nvidia haven’t even laid out a road map for three years, but with new architectures coming every year, a data center risks being obsolete by the time it’s completed. However, what’s the alternative? To wait? Customers will never catch up at that rate, Lynch said.   That is simply not a viable option, so development and construction must go on even with short supplies of everything from concrete and steel to servers and power transformers.

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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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