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OpenAI updates Operator to o3, making its $200 monthly ChatGPT Pro subscription more enticing

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More It was a big week for AI announcements following events from Microsoft, Google, and Anthropic. But OpenAI is finishing things out with news of its own. And no, we’re not just talking about its $6.5 billion […]

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It was a big week for AI announcements following events from Microsoft, Google, and Anthropic. But OpenAI is finishing things out with news of its own. And no, we’re not just talking about its $6.5 billion acquisition of Jony Ive’s design team to lead a new hardware effort, “io” at OpenAI.

Today, the company upgraded its Operator autonomous web browsing and cursor controlling agent within ChatGPT from using the prior GPT-4o multimodal large language model to the newer and more powerful o3 reasoning model.

The update, released globally today, May 23, 2025, is available as a “research preview” to paying subscribers of OpenAI’s $200 USD-monthly ChatGPT Pro plan.

Basically, that is OpenAI’s way of saying it’s not a fully “sanded down” or perfected product yet — it may still have kinks and issues.

But with rival Google offering its own top tier AI subscription bundle for a price of nearly $250 USD regularly (currently running a discount down to $125 for the first three months) to access its latest Gemini multimodal, Imagen image generation, and Veo video generation models, suddenly OpenAI’s ChatGPT Pro plan seems more affordable by comparison.

What is OpenAI’s Operator and what is it for?

Operator first debuted in January 2025 as OpenAI’s initial step into semi-autonomous agents, specifically Computer Using Agents (CUAs). The idea is to go beyond the chatbot interface of ChatGPT and allow OpenAI’s powerful AI models to start taking more actions on behalf of the user.

Thus, Operator was designed to autonomously point, click, scroll, and type to complete web-based tasks such as booking dinner reservations, compiling shopping lists, or ordering event tickets. This agentic capability allows it to complete user tasks directly through a browser interface, from booking reservations to gathering online data.

For safety, privacy and security purposes, Operator didn’t use any existing web browser on a user’s PC or Mac. Instead, it ran in a cloud-hosted virtual browser accessible via a standalone site—operator.chatgpt.com—where users could input requests and observe the agent perform tasks in real time.

It combined vision, reasoning, and interaction capabilities based on GPT-4o, marking a new direction for OpenAI in agentic AI.

The product was launched as a research preview for ChatGPT Pro subscribers and featured built-in safety measures like user confirmations, Watch Mode, and restrictions on high-risk web platforms.

It was also being tested in enterprise contexts, including travel planning and civic services, demonstrating its potential across both consumer and business environments.

o3 offers improved accuracy, structure, and success rates

With this update, OpenAI aims to enhance performance across several key dimensions. The new o3-based Operator demonstrates improved persistence and accuracy during browser interactions.

In practical terms, this means it is more likely to complete user tasks successfully and with less need for correction or repetition. Moreover, users can expect responses that are clearer, more structured, and more comprehensive.

In comparative evaluations, the new model shows a distinct preference advantage over its predecessor. Human preference studies reveal that users favor the o3 model for its style, comprehensiveness, and clarity. It also performs strongly in instruction following and efficiency, though results for factual correctness are more balanced between versions.

Performance on third-party evaluation benchmarks reflects these enhancements. On the OSWorld benchmark that measures completion of browser-based tasks, the o3 model scores 42.9 compared to 38.1 for the previous version.

However, OpenAI notes that due to limitations in the automated grading system, the actual performance gain could be closer to 20 percentage points!

On WebArena, the new model achieved a score of 62.9, up from 48.1. The most dramatic improvement appears on the GAIA benchmark, where the o3 model scores 62.2, vastly surpassing the prior model’s 12.3.

Side-by-side task comparisons further illustrate these gains. In one example involving a restaurant booking request, the new model provided a clearer and more detailed list of available reservations, including locations, Michelin ratings, and seating notes, presented in a well-formatted table. The previous version, while functional, delivered less information in a less organized manner, according to an image included with the new o3 Operator release notes:

Safeguards remain, as do general cautionary notes about usage on sensitive, financial transactions and account access

The o3 model also inherits the safety measures introduced with earlier versions, with further fine-tuning for its role as an agentic system.

OpenAI has integrated enhanced training against harmful task execution, prompt injection vulnerabilities, and mistakes involving user intent.

Evaluations show that the model now confirms 94% of sensitive actions before executing them, with 100% confirmation in financial transactions. Prompt injection susceptibility has also decreased from 23% to 20%.

Notably, the o3 Operator maintains a cautious boundary on certain high-risk web interactions, such as email or financial platforms, where it may require user supervision via Watch Mode or explicitly refuse to proceed. These measures are part of a layered approach to safety that combines model-level robustness with real-time monitoring.

While the upgrade to Operator marks a technical improvement, it also reflects OpenAI’s ongoing commitment to responsible AI deployment.

The system’s ability to take real-world actions introduces new risks, and the development team continues to refine its safety protocols accordingly.

According to OpenAI’s updated o3 system card documentation, the model remains below high-risk capability thresholds in categories such as biological and chemical misuse and has no native coding environment or terminal access, further reducing potential misuse vectors.

Operator remains a research preview and is accessible only to ChatGPT Pro users. The Responses API version of Operator will continue to be based on the GPT-4o model, at least for now.

Implications for enterprise technical decision-makers

The upgraded Operator stands to significantly enhance the workflows of professionals in AI engineering, orchestration, data management, and IT security.

For those building or maintaining machine learning models, the model’s improved accuracy and structured outputs reduce the overhead of test validation and troubleshooting.

In orchestration contexts, it offers a practical, reliable tool for automating browser-based components of complex pipelines.

Data engineers can delegate manual web interactions—such as data verification and scraping—with more confidence, freeing time for higher-level optimization work.

Security professionals, meanwhile, gain a safer way to simulate user behavior in audits and incident response exercises, thanks to the model’s layered safety mechanisms.

Across these disciplines, the o3-based Operator introduces both a capability upgrade and a risk mitigation framework, making it a practical addition to the modern technical toolkit.

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VMware customers in Europe face up to 1,500% price increases under Broadcom ownership

Regulatory storm brewing The pricing crisis has triggered formal regulatory attention across Europe. Germany’s VOICE IT customer association has filed a complaint with the European Commission, while ECCO explicitly calls for regulatory intervention, including reinstating previous contracts and suspending Broadcom’s ongoing litigation. “Unless Broadcom promptly implements critical changes, the company’s

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ICYMI: President Trump Signs Executive Orders to Usher in a Nuclear Renaissance, Restore Gold Standard Science

WASHINGTON—Today, President Trump signed several key executive orders to usher in a nuclear renaissance and restore America’s gold standard in science and innovation, directing the Department of Energy to take a leading role in unleashing the American nuclear renaissance. President Trump is taking decisive action to strengthen scientific discovery in America, rebuild public trust in science, and accelerate advanced nuclear technologies. After decades of stagnation and shuttered reactors, President Trump is providing a path forward for nuclear innovation. Today’s executive orders allow for reactor design testing at the Department of Energy’s (DOE) National Labs, clear the way for construction on federal lands to protect national and economic security, and remove regulatory barriers by requiring the Nuclear Regulatory Commission to issue timely licensing decisions. “For too long, America’s nuclear energy industry has been stymied by red tape and outdated government policies, but thanks to President Trump, the American nuclear renaissance is finally here,”Energy Secretary Chris Wright said. “With the emergence of AI and President Trump’s pro-American manufacturing policies at work, American civil nuclear energy is being unleashed at the perfect time. Nuclear has the potential to be America’s greatest source of energy addition. It works whether the wind is blowing, or the sun is shining, is possible anywhere and at different scales. President Trump’s executive orders today unshackle our civil nuclear energy industry and ensure it can meet this critical moment.” “Over the last 30 years, we stopped building nuclear reactors in America – that ends now. Today’s executive orders are the most significant nuclear regulatory reform actions taken in decades. We are restoring a strong American nuclear industrial base, rebuilding a secure and sovereign domestic nuclear fuel supply chain, and leading the world towards a future fueled by American nuclear energy. These actions are critical to American energy independence and

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Energy Secretary Issues Emergency Order to Secure Grid Reliability Ahead of Summer Months

WASHINGTON— U.S. Secretary of Energy Chris Wright issued an emergency order today to minimize the risk of blackouts and address critical grid security issues in the Midwestern region of the United States ahead of the high electricity demand expected this summer. Secretary Wright’s order directs the Midcontinent Independent System Operator (MISO), in coordination with Consumers Energy, to ensure that the 1,560 megawatt (MW) J.H. Campbell coal-fired power plant in West Olive, Michigan remains available for operation, minimizing any potential capacity shortfall that could lead to unnecessary power outages. The Campbell Plant was scheduled to shut down on May 31, which is 15 years before the end of its scheduled design life. “Today’s emergency order ensures that Michiganders and the greater Midwest region do not lose critical power generation capability as summer begins and electricity demand regularly reach high levels,” Secretary Wright said. “This administration will not sit back and allow dangerous energy subtraction policies threaten the resiliency of our grid and raise electricity prices on American families. With President Trump’s leadership, the Energy Department is hard at work securing the American people access to affordable, reliable, and secure energy that powers their lives regardless of whether the wind is blowing, or the sun is shining.” The emergency order, which is issued by the Office of Cybersecurity, Energy Security, and Emergency Response (CESER), is authorized by Section 202(c) of the Federal Power Act and is in accordance with President Trump’s Executive Order: Declaring a National Energy Emergency. It will ensure the power generation availability in the region does not dip below 2024 capacity levels. BACKGROUND: Heading into the summer months, the North American Electric Reliability Corporation (NERC) has warned the region served by MISO “is at elevated risk of operating reserve shortfalls during periods of high demand,” particularly during the summer

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WTI Settles at $61.53 in Light Trade

Oil drifted higher in thin pre-holiday trading as investors’ conviction that the US and Iran can reach a nuclear deal waned while strong US data buoyed a shaky demand picture. West Texas Intermediate edged up by 0.5% to settle above $61 a barrel, with volumes trending lower ahead of Monday’s Memorial Day holiday. The US and Iran concluded a fifth round of nuclear talks in Rome that yielded “some but not conclusive progress,” according to Iranian Foreign Minister Abbas Araghchi. A wrong turn in the negotiations, which have spurred criticism from several high-ranking Iranian officials, may lead to tighter sanctions, crimping flows from the OPEC member. Meanwhile, strong US economic data helped erase an earlier rout of nearly 2% after President Donald Trump said in a social media post that the European Union had been “very difficult to deal with” and that he would recommend a 50% tariff to be imposed on the bloc on June 1. The US dollar slumped to its lowest level since 2023, making commodities priced in the currency more attractive. Geopolitics have been a major focus for traders this week, with a report from CNN that US intelligence suggested Israel was making preparations to strike Iranian nuclear facilities driving brief gains earlier in the week. After that, Araghchi, Iran’s lead negotiator in talks with the US, said a deal was possible that would entail Tehran avoiding nuclear weapons, but not ditching uranium enrichment. Still, the outlook remains overall bearish. Crude has shed about 14% this year, hitting the lowest since 2021 last month, as OPEC+ loosened supply curbs at a faster-than-expected pace, just as the US-led tariff war posed headwinds for demand. Prices had recovered some ground as trade tensions between the US and China eased, but data this week also showed another increase in

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Poland Says Key Infrastructure at Risk After Baltic Sea Incident

Polish Prime Minister Donald Tusk warned on Thursday that the Baltic Sea is becoming “a new area of confrontation” with Russia, putting the country’s critical infrastructure increasingly at risk. His warning comes a day after Polish authorities said a sanctioned Russian ship was performing “suspicious maneuvers” near the power cable connecting Poland and Sweden. The tanker left for an unspecified Russian port after the Polish armed forces intervened, they said. The undersea power link was not damaged, but Poland is checking whether any explosive devices were planted, the prime minister said after meeting top navy commanders. The Baltic Sea has become a flashpoint in recent months after the detention of several vessels on suspicion of tearing up undersea telecommunications cables. Baltic nations have also increased scrutiny of unregistered tankers due to concerns about sanctioned Russian oil, saying that Moscow’s so-called ‘shadow fleet’ could lead to security breaches and environmental risks. Since Russia’s full-scale invasion of Ukraine there have been “too many incidents” in the Baltic Sea for Poland to take maritime security lightly, Tusk said at a meeting with Polish naval commanders in the coastal city of Gdynia on Thursday.  The risks are keenly felt in Poland, which shares a border with Russia’s ally Belarus and exclave of Kaliningrad, home to a naval base at Baltiysk. On Wednesday, Russia declared that it would defend its vessels in the Baltic Sea, one of the world’s busiest shipping routes, by all legal means after briefly deploying a fighter jet as Estonia tried to halt an oil tanker in its economic zone. In recent years, Poland has expanded its energy infrastructure to wean itself off Russian supplies. It has constructed a gas link to Norway, a liquefied natural gas import terminal as well as expanded port capacities to handle growing flows of goods and military aid to neighboring Ukraine. 

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Japanese Gas Tanker Giant Sees Difficulty Buying Chinese Vessels

Mitsui O.S.K. Lines, owner of the world’s largest fleet of liquefied natural gas carriers, said it is hard to buy Chinese vessels for the time being as the US ramps up scrutiny of the Asian country’s shipbuilding industry. “It is difficult to purchase Chinese vessels under the current circumstances, because of the port entry fees” that the US is proposing for China-built ships calling at its ports, a spokesperson for the Japanese firm said. Earlier on Friday, the Nikkei reported Mitsui O.S.K. was planning to shift new orders from China to South Korea. But the plans have not yet been finalized, the spokesperson told Bloomberg News. The Japanese firm is aiming to reduce risks, according to remarks made by President and Chief Executive Officer Takeshi Hashimoto during an interview.  “We will wait and see about new business with the Chinese,” Hashimoto said in the report, which added that Mitsui O.S.K. will not cancel any existing contracts with Chinese yards. Washington has issued a flurry of measures under President Donald Trump’s administration aimed at curbing China’s maritime dominance and reviving its own flagging shipbuilding industry. The moves have shaken up the global shipping market, prompting shipowners to rethink where they want their vessels to be built in the future. South Korean shipbuilders have sensed an opportunity. Last week, major shipbuilders HD Hyundai Co. and Hanwha Ocean Co. offered to help the US improve its shipbuilding capacity and restore its maritime dominance. South Korean builders have an 18% share of ships under construction worldwide in deadweight tons terms, while the Japanese have 11%, according to data from Clarksons Research. Mitsui O.S.K. owns a fleet of 97 LNG vessels, according to a 2024 corporate presentation. It also maintains the world’s second-largest merchant fleet at 873 vessels.  Chinese shipyards make up two-thirds of the global orderbook. In

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Trump urges UK to back North Sea and Aberdeen as its hub

President Donald Trump has said there is North Sea oil to last 100 years with the Granite City as its hub. A message posted on his site Truth Social also took aim at “unsightly windmills” – long a bugbear for Trump since he opposed the development of the Aberdeen Bay wind farm which can be seen from his golf course on the Menie Estate. The US president urged Sir Keir Starmer’s Labour government to support “modernised drilling” in the North Sea which would cut the cost of energy. Mr Trump said “large amounts of oil lay waiting to be taken” as he promoted the White House’s trade agreement with Britain. “Our negotiated deal with the United Kingdom is working out well for all,” he said. “I strongly recommend to them, however, that in order to get their energy costs down, they stop with the costly and unsightly windmills, and incentivise modernized drilling in the North Sea, where large amounts of oil lay waiting to be taken. He added on his own social media site: “A century of drilling left, with Aberdeen as the hub. “The old fashioned tax system disincentivises drilling, rather than the opposite. “UK’s energy costs would go way down, and fast!” The president’s intervention came as the UK regulator Ofgem announced the first cut in the energy price cap for year which will reduce energy costs from July. However, prices still remain high and cost of energy for households and business has often been cited as major disincentive for investment and growth. It is not the first time he has weighed in on the North Sea since becoming 45th president. In January, he claimed the UK was making a “big mistake” in its energy policies, sharing a story about US oil and gas firm APA – previously

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New Intel Xeon 6 CPUs unveiled; one powers rival Nvidia’s DGX B300

He added that his read is that “Intel recognizes that Nvidia is far and away the leader in the market for AI GPUs and is seeking to hitch itself to that wagon.” Roberts said, “basically, Intel, which has struggled tremendously and has turned over its CEO amidst a stock slide, needs to refocus to where it thinks it can win. That’s not competing directly with Nvidia but trying to use this partnership to re-secure its foothold in the data center and squeeze out rivals like AMD for the data center x86 market. In other words, I see this announcement as confirmation that Intel is looking to regroup, and pick fights it thinks it can win. “ He also predicted, “we can expect competition to heat up in this space as Intel takes on AMD’s Epyc lineup in a push to simplify and get back to basics.” Matt Kimball, vice president and principal analyst, who focuses on datacenter compute and storage at Moor Insights & Strategy, had a much different view about the announcement. The selection of the Intel sixth generation Xeon CPU, the 6776P, to support Nvidia’s DGX B300 is, he said, “important, as it validates Intel as a strong choice for the AI market. In the big picture, this isn’t about volumes or revenue, rather it’s about validating a strategy Intel has had for the last couple of generations — delivering accelerated performance across critical workloads.”  Kimball said that, In particular, there are a “couple things that I would think helped make Xeon the chosen CPU.”

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AWS clamping down on cloud capacity swapping; here’s what IT buyers need to know

As of June 1, AWS will no longer allow sub-account transfers or new commitments to be pooled and reallocated across customers. Barrow says the shift is happening because AWS is investing billions in new data centers to meet demand from AI and hyperscale workloads. “That infrastructure requires long-term planning and capital discipline,” he said. Phil Brunkard, executive counselor at Info-Tech Research Group UK, emphasized that AWS isn’t killing RIs or SPs, “it’s just closing a loophole.” “This stops MSPs from bulk‑buying a giant commitment, carving it up across dozens of tenants, and effectively reselling discounted EC2 hours,” he said. “Basically, AWS just tilted the field toward direct negotiations and cleaner billing.” What IT buyers should do now For enterprises that sourced discounted cloud resources through a broker or value-added reseller (VAR), the arbitrage window shuts, Brunkard noted. Enterprises should expect a “modest price bump” on steady‑state workloads and a “brief scramble” to unwind pooled commitments.  If original discounts were broker‑sourced, “budget for a small uptick,” he said. On the other hand, companies that buy their own RIs or SPs, or negotiate volume deals through AWS’s Enterprise Discount Program (EDP), shouldn’t be impacted, he said. Nothing changes except that pricing is now baselined.

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DriveNets extends AI networking fabric with multi-site capabilities for distributed GPU clusters

“We use the same physical architecture as anyone with top of rack and then leaf and spine switch,” Dudy Cohen, vice president of product marketing at DriveNets, told Network World. “But what happens between our top of rack, which is the switch that connects NICs (network interface cards) into the servers and the rest of the network is not based on Clos Ethernet architecture, rather on a very specific cell-based protocol. [It’s] the same protocol, by the way, that is used in the backplane of the chassis.” Cohen explained that any data packet that comes into an ingress switch from the NIC is cut into evenly sized cells, sprayed across the entire fabric and then reassembled on the other side. This approach distinguishes DriveNets from other solutions that might require specialized components such as Nvidia BlueField DPUs (data processing units) at the endpoints. “The fabric links between the top of rack and the spine are perfectly load balanced,” he said. “We do not use any hashing mechanism… and this is why we can contain all the congestion avoidance within the fabric and do not need any external assistance.” Multi-site implementation for distributed GPU clusters The multi-site capability allows organizations to overcome power constraints in a single data center by spreading GPU clusters across locations. This isn’t designed as a backup or failover mechanism. Lasser-Raab emphasized that it’s a single cluster in two locations that are up to 80 kilometers apart, which allows for connection to different power grids. The physical implementation typically uses high-bandwidth connections between sites. Cohen explained that there is either dark fiber or some DWDM (Dense Wavelength Division Multiplexing) fibre optic connectivity between the sites. Typically the connections are bundles of four 800 gigabit ethernet, acting as a single 3.2 terabit per second connection.

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Intel eyes exit from NEX unit as focus shifts to core chip business

“That’s something we’re going to expand and build on,” Tan said, according to the report, pointing to Intel’s commanding 68% share of the PC chip market and 55% share in data centers. By contrast, the NEX unit — responsible for silicon and software that power telecom gear, 5G infrastructure, and edge computing — has struggled to deliver the kind of strategic advantage Intel needs. According to the report, Tan and his team view it as non-essential to Intel’s turnaround plans. The report described the telecom side of the business as increasingly disconnected from Intel’s long-term objectives, while also pointing to fierce competition from companies like Broadcom that dominate key portions of the networking silicon market and leave little room for Intel to gain a meaningful share. Financial weight, strategic doubts Despite generating $5.8 billion in revenue in 2024, the NEX business was folded into Intel’s broader Data Center and Client Computing groups earlier this year. The move was seen internally as a signal that NEX had lost its independent strategic relevance and also reflects Tan’s ruthless prioritization.  To some in the industry, the review comes as little surprise. Over the past year, Intel has already shed non-core assets. In April, it sold a majority stake in Altera, its FPGA business, to private equity firm Silver Lake for $4.46 billion, shelving earlier plans for a public listing. This followed the 2022 spinoff of Mobileye, its autonomous driving arm. With a $19 billion loss in 2024 and revenue falling to $53.1 billion, the chipmaker also aims to streamline management, cut $10 billion in costs, and bet on AI chips and foundry services, competing with Nvidia, AMD, and TSMC.

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Tariff uncertainty weighs on networking vendors

“Our guide assumes current tariffs and exemptions remain in place through the quarter. These include the following: China at 30%, partially offset by an exemption for semiconductors and certain electronic components; Mexico and Canada at 25% for the components and products that are not eligible for the current exemptions,” Cisco CFO Scott Herron told Wall Street analysts in the company’s quarterly earnings report on May 14. At this time, Cisco expects little impact from tariffs on steel and aluminum and retaliatory tariffs, Herron said. “We’ll continue to leverage our world-class supply chain team to help mitigate the impact,” he said, adding that “the flexibility and agility we have built into our operations over the last few years, the size and scale of our supply chain, provides us some unique advantages as we support our customers globally.” “Once the tariff scenario stabilizes, there [are] steps that we can take to mitigate it, as you’ve seen us do with China from the first Trump administration. And only after that would we consider price [increases],” Herron said. Similarly, Extreme Networks noted the changing tariff conditions during its earnings call on April 30. “The tariff situation is very dynamic, I think, as everybody knows and can appreciate, and it’s kind of hard to call. Yes, there was concern initially given the magnitude of tariffs,” said Extreme Networks CEO Ed Meyercord on the earnings call. “The larger question is, will all of the changes globally in trade and tariff policy have an impact on demand? And that’s hard to call at this point. And we’re going to hold as far as providing guidance or judgment on that until we have finality come July.” Financial news Meanwhile, AI is fueling high expectations and influencing investments in enterprise campus and data center environments.

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Liquid cooling becoming essential as AI servers proliferate

“Facility water loops sometimes have good water quality, sometimes bad,” says My Troung, CTO at ZutaCore, a liquid cooling company. “Sometimes you have organics you don’t want to have inside the technical loop.” So there’s one set of pipes that goes around the data center, collecting the heat from the server racks, and another set of smaller pipes that lives inside individual racks or servers. “That inner loop is some sort of technical fluid, and the two loops exchange heat across a heat exchanger,” says Troung. The most common approach today, he says, is to use a single-phase liquid — one that stays in liquid form and never evaporates into a gas — such as water or propylene glycol. But it’s not the most efficient option. Evaporation is a great way to dissipate heat. That’s what our bodies do when we sweat. When water goes from a liquid to a gas it’s called a phase change, and it uses up energy and makes everything around it slightly cooler. Of course, few servers run hot enough to boil water — but they can boil other liquids. “Two phase is the most efficient cooling technology,” says Xianming (Simon) Dai, a professor at University of Texas at Dallas. And it might be here sooner than you think. In a keynote address in March at Nvidia GTC, Nvidia CEO Jensen Huang unveiled the Rubin Ultra NVL576, due in the second half of 2027 — with 600 kilowatts per rack. “With the 600 kilowatt racks that Nvidia is announcing, the industry will have to shift very soon from single-phase approaches to two-phase,” says ZutaCore’s Troung. Another highly-efficient cooling approach is immersion cooling. According to a Castrol survey released in March, 90% of 600 data center industry leaders say that they are considering switching to immersion

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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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