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White House plan signals “open-weight first” era—and enterprises need new guardrails

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now U.S. President Donald Trump signed the AI Action Plan, which outlines a path for the U.S. to lead in the AI race. For enterprises already in the throes of […]

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U.S. President Donald Trump signed the AI Action Plan, which outlines a path for the U.S. to lead in the AI race. For enterprises already in the throes of deploying AI systems, the rules represent a clear indication of how this administration intends to treat AI going forward and could signal how providers will approach AI development. 

Much like the AI executive order signed by Joe Biden in 2023, Trump’s order primarily concerns government offices, directing how they can contract with AI models and application providers, as it is not a legislative act.  

The AI plan may not directly affect enterprises immediately, but analysts noted that anytime the government takes a position on AI, the ecosystem changes. 

“This plan will likely shape the ecosystem we all operate in — one that rewards those who can move fast, stay aligned and deliver real-world outcomes,” Matt Wood, commercial technology and innovation officer at PwC, told VentureBeat in an email. “For enterprises, the signal is clear: the pace of AI adoption is accelerating, and the cost of lagging is going up. Even if the plan centers on federal agencies, the ripple effects — in procurement, infrastructure, and norms — will reach much further. We’ll likely see new government-backed testbeds, procurement programs, and funding streams emerge — and enterprises that can partner, pilot, or productize in this environment will be well-positioned.”


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He added that the Action Plan “is not a blueprint for enterprise AI.” Still, enterprises should expect an AI development environment that prioritizes speed, scale, experimentation and less reliance on regulatory shelters. Companies working with the government should also be prepared for additional scrutiny on the models and applications they use, to ensure alignment with the government’s values. 

The Action Plan outlines how government agencies can collaborate with AI companies, prioritize recommended tasks to invest in infrastructure and encourage AI development and establish guidelines for exporting and importing AI tools. 

Charleyne Biondi, assistant vice president and analyst at Moody’s Ratings, said the plan “highlights AI’s role as an increasingly strategic asset and core driver of economic transformation.” She noted, however, that that plan doesn’t address regulatory fragmentation.

“However, current regulatory fragmentation across U.S. states could create uncertainty for developers and businesses. Striking the right balance between innovation and safety and between national ambition and regulatory clarity will be critical to ensure continued enterprise adoption and avoid unintended slowdowns,” she said. 

What is inside the action plan

The AI Action Plan is broken down into three pillars:

  1. Accelerating AI innovation
  2. Building American AI infrastructure
  3. Leading in international AI diplomacy and security. 

The key headline piece of the AI Action Plan centers on “ensuring free speech and American values,” a significant talking point for this administration. It instructs the National Institute of Standards and Technology (NIST) to remove references to misinformation and diversity, equity and inclusion. It prevents agencies from working with foundation models that have “top-down agendas.” 

It’s unclear how the government expects existing models and datasets to follow suit, or what this kind of AI would look like. Enterprises are especially concerned about potentially controversial statements AI systems can make, as evidenced by the recent Grok kerfuffle.  

It also orders NIST to research and publish findings to ensure that models from China, such as DeepSeek, Qwen and Kimi, are not aligned with the Chinese Communist Party.

However, the most consequential positions involve supporting open-source systems, creating a new testing and evaluation ecosystem, and streamlining the process for building data centers

Through the plan, the Department of Energy and the National Science Foundation are directed to develop “AI testbeds for piloting AI systems in secure, real-world settings,” allowing researchers to prototype systems. It also removes much of the red tape associated with evaluating safety testing for models. 

What has excited many in the industry is the explicit support for open-source AI and open-weight models. 

“We need to ensure America has leading open models founded on American values. Open-source and open-weight models could become global standards in some areas of business and academic research worldwide. For that reason, they also have geostrategic value. While the decision of whether and how to release an open or closed model is fundamentally up to the developer, the Federal government should create a supportive environment for open models,” the plan said. 

Understandably, open-source proponents like Hugging Face’s Clement Delangue praised this decision on social media, saying: “It’s time for the American AI community to wake up, drop the “open is not safe” bullshit, and return to its roots: open science and open-source AI, powered by an unmatched community of frontier labs, big tech, startups, universities, and non‑profits.”

BCG managing director Sesh Iyer told VentureBeat this would give enterprises more confidence in adopting open-source LLMs and could also encourage more closed-source providers “to rethink proprietary strategies and potentially consider releasing model weights.”

The plan does mention that cloud providers should prioritize the Department of Defense, which could bump some enterprises down an already crowded waiting list. 

A little more clarity on rules

The AI Action Plan is more akin to an executive order and can only direct government agencies under the purview of the Executive branch. Full AI regulation, one that endures through multiple administrations, can only be achieved through Congress. 

Enterprises understood that the change in administration may mean less emphasis on AI regulations, and braced themselves for that impact. The Trump administration revoked Biden’s EO, halting many of the projects already underway after it was signed. 

With the signing of the Action Plan, the Trump administration at least lays out its priorities and stance on AI development, which would help increase enterprise confidence in the technology. 

However, even in the absence of an EO or Congress-led regulation, enterprises were already building and expanding the AI ecosystem. Although there is some concern over the lack of rules and the uncertainty that comes with it, it was never going to stop businesses from being excited about a technology that promises to make their work easier. The plan, at least, makes it easier to grow more. 

“It lowers some external friction, like faster permits, more data center capacity, and potential funding. But real acceleration happens inside the enterprise: skills, governance, and the ability to deploy responsibly. Those who’ve already built that muscle will be best positioned to capitalize on the momentum the plan generates,” PwC’s Wood said. 

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Humana slashes engineering hours with network automation overhaul

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Data centers seek flexible power solutions for resilience, sustainability

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Saskatchewan, Ontario, Alberta Sign MoU to Facilitate O&G Transportation

Three Canadian provinces are collaborating to facilitate the transportation of oil and gas across the country. Saskatchewan Premier Scott Moe, Ontario Premier Doug Ford, and Alberta Premier Danielle Smith signed a memorandum of understanding (MoU) to coordinate the safe transportation and export of Western Canadian oil, natural gas and critical minerals to refineries, seaports and storage facilities across Canada and beyond, according to a statement from the Canadian government. The MoU establishes a collaborative framework to explore multiple pipeline and rail corridors, and expansion of processing hubs for critical minerals. The framework aims to create new and critical avenues to reach domestic and international markets, the statement said. The agreement will help strengthen interprovincial trade by linking Saskatchewan, Ontario, and Alberta through shared infrastructure development and coordinated market strategies, according to the statement. “We are sending a clear signal that Canada’s energy future will be built by Canadians, for Canadians,” Moe said. “This agreement commits our provinces to work together to unlock new markets, shore up our supply chains from mine to port and advocate for the federal reforms our industry needs. By advancing pipelines, rail connections and critical-mineral processing capacity, we are safeguarding thousands of jobs, strengthening our energy security and fostering sustainable growth”. “As the world grapples with President Trump’s unfair tariffs, it is more important than ever to build a resilient and self-reliant economy here at home,” Ford said. “This agreement sends a clear message: Ontario, Alberta and Saskatchewan are ready to get shovels in the ground and move forward on projects that will secure our long-term prosperity”. “We are taking action to grow our economy, build real infrastructure and get major projects moving,” Smith said. “Alberta is proud to lead the way in uniting with provinces that share a vision for responsible development, economic freedom and

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Enbridge to Supply Meta with Power from 600-MW Solar Project in Texas

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Canteen Workers at Exxon Refinery Suspend Strike

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Karoon CEO Julian Fowles Stepping Down; Search for Replacement Starts

Karoon Energy Ltd said that its Managing Director and CEO Julian Fowles will be leaving the company by mid-2026. The move follows the company’s decision to relocate key corporate teams and roles to Brazil and the USA, Karoon said in a news release. The company said its board, supported by an international search firm, is leading a global search process to appoint a Houston-based CEO / managing director to succeed Fowles. Fowles will remain in his role until the appointment of the new CEO / managing director or the end of the year. He will then serve a notice period through to mid-2026, where he will be available to provide continuity, if required, the company said. Karoon Chair Peter Botten said, “Following discussions with the Board, Julian will not be relocating as part of the planned transition of key corporate roles, including senior management, from Melbourne to Brazil and the USA”. “The decision to relocate these roles has not been taken lightly. The Board expects that this change, which includes simplifying Karoon’s structure, will increase efficiency and facilitate collaboration between the business units in Brazil and the USA. It will also reduce duplication and allow the Company to source high quality, local talent in our operational locations. The relocation of our corporate teams and roles, which has been carefully planned, will be phased over a period of 12 to 18 months to ensure that a meticulous handover of roles and responsibilities can be undertaken,” Botten continued. “On behalf of the Board, I would like to sincerely thank Julian for all his hard work over the past five years. Joining Karoon in 2020, Julian was instrumental in developing and delivering Karoon’s 2021 Strategic Plan. This included the successful Baúna intervention campaign, the development of the Patola field and the strategic Who

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UK Gov Announces ‘Tailored Support for Aberdeen Oil Workers’

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Storage vendors bring record capacity devices to handle massive data generation

Both are built on Seagate’s Mozaic3+ with advanced storage technology called HAMR, or Heat-Assisted Magnetic Recording. By heating the platter to as much as 500°C, they can squeeze up to 3TB per platter. Other than that, it looks like a standard hard drive: 3.5-inch enclosure, 7,200 RPM spin rotation, and SATA III interface with 6Gbps/s transfer speeds. The drivers are available now and are rather affordable. The 30TB Exos is just $599 on NewEgg.com. On the enterprise solid state drive (SSD) front, KIOXIA America has expanded its high-capacity KIOXIA LC9 Series enterprise SSD lineup with the introduction of a 245.76TB NVMe SSD. The drive comes in a 2.5-inch and Enterprise and Datacenter Standard Form Factor (EDSFF) E3.L form factor and is purpose-built for the performance and efficiency demands of generative AI environments.

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Technology is coming so fast data centers are obsolete by the time they launch

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‘Significant’ outage at Alaska Airlines not a security incident, but a hardware breakdown

The airline told Network World that when the critical piece of what it described as “third-party multi-redundant hardware” failed unexpectedly, “it impacted several of our key systems that enable us to run various operations.” The company is currently working with its vendor to replace the faulty equipment at the data center. The airline has cancelled more than 150 flights since Sunday evening, including 64 on Monday. The company said additional flight disruptions are likely as it repositions aircraft and crews throughout its network. Alaska Airlines emphasized that the safety of its flights was never compromised, and that “the IT outage is not related to any other current events, and it’s not connected to the recent cybersecurity incident at Hawaiian Airlines.” The airline did not provide additional information to Network World about the specifics of the outage. “There are many redundant components that can fail,” said Roberts, noting that it could have been something as simple as a RAID array (which combines multiple physical data storage components into one or more logical units). Or, on the network side, it could have been the failure of a pair of load balancers. “It’s interesting that redundancy didn’t save them,” said Roberts. “Perhaps multiple pieces of hardware were impacted by the same issue, like a firmware update. Or, maybe they’re just really unlucky.”

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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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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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