Quantum computing gets an error-correction boost from AI innovation

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Quantum computing gets an error-correction boost from AI innovation

The RIKEN team, including Nori, Clemens Gneiting, and Yexiong Zeng, developed a deep learning method to optimize GKP states, making them easier to produce while maintaining robust error correction. “Our AI-driven method fine-tunes the structure of GKP states, striking an optimal balance between resource efficiency and error resilience,” said Zeng in the statement. The results […]

The RIKEN team, including Nori, Clemens Gneiting, and Yexiong Zeng, developed a deep learning method to optimize GKP states, making them easier to produce while maintaining robust error correction.

“Our AI-driven method fine-tunes the structure of GKP states, striking an optimal balance between resource efficiency and error resilience,” said Zeng in the statement. The results were striking. “The neural network achieved a much more efficient encoding than we had initially expected,” he said.

These optimized codes require fewer squeezed states and outperform traditional GKP codes, particularly in bosonic systems like superconducting cavities or photonics.

Vyshak cautioned that AI-optimized GKP codes excel in specific platforms but may not generalize across all quantum hardware. “Surface codes and LDPC codes remain more versatile and proven, especially in superconducting or trapped-ion systems,” he said. Still, RIKEN’s work significantly lowers the experimental barrier for certain architectures, accelerating progress toward practical quantum computing.

Global race for Quantum reliability

Quantum error correction is a critical focus worldwide, with researchers and industry leaders racing to overcome the challenges of qubit fragility. A December 2024 study on AI in QEC flagged its superiority over hand-crafted methods, especially as systems scale and error syndromes grow exponentially complex.

Vyshak emphasized that AI is becoming essential for managing the complexity of error correction at scale. “The volume and complexity of error syndromes in large quantum systems overwhelm traditional decoders,” he said. Neural networks and reinforcement learning adapt to dynamic noise patterns, optimize code parameters, and reduce processing bottlenecks, giving AI-driven solutions a competitive edge.

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Trump administration to rescind, modify AI chip export curbs

Nvidia CEO Jensen Huang has been particularly noisy about this issue, telling CNBC earlier this month that the market for AI chips in China could reach $50 billion in the next couple of years, and it was important for U.S. firms to have access to that market. And Nvidia has

Nutanix partnerships target storage, AI workloads as it aims to take on VMware

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Beyond firewalls: SonicWall pivots to embrace cloud, services, AI

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Broadcom’s licensing clampdown: Subscription-less VMware users face legal ultimatum

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SSE and Equinor secure planning consent for Humber green hydrogen-to-power project

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Power Moves: OEUK’s new director of external relations, GB Energy executive appointments and more

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SPP proposes one-time framework to speed generation interconnection

Southwest Power Pool’s board of directors on Tuesday approved a proposed Expedited Resource Adequacy Study, or ERAS, which aims to “significantly accelerate the addition of new generating resources to the grid,” according to the regional grid operator. SPP plans to file amendments to its governing documents with the Federal Energy Regulatory Commission later this month in order to implement the ERAS proposal, it said in a Thursday announcement. “ERAS offers utilities who are responsible for keeping the lights on a clearly defined and impactful opportunity to address real and immediate needs,” SPP President and CEO Lanny Nickell said. “It’s not a replacement for broader interconnection reforms, but this complementary effort will ensure reliability isn’t compromised during a transitional period while we work to implement more permanent solutions.” SPP expects its excess capacity will fall to 5% in 2029, down from 24% in 2020, Nickell said in April at a trade group meeting focused on transmission issues. “Excess generating capacity is dwindling, and it’s dwindling to a point where it’s becoming dangerous,” he said. If ERAS is approved by federal regulators, staff of the regional transmission organization will work with qualified load responsible entities, or LREs, to submit projects for inclusion in the process as early as August, SPP said. Interconnection rights could be granted as soon as April 2026. Eligibility for the ERAS process is limited to new generation nominated by LREs, and projects must be capable of reaching commercial operation within five years of executing a generation interconnection agreement, the grid operator said. ERAS will be a “one-time process [that] will run separately” from SPP’s standard generation interconnection queue, it said. Projects submitted in SPP’s most recent batch of interconnection study requests will be given the option to transfer their submissions to the ERAS queue, the operator said. While SPP

Sempra to sell Mexican natural gas business to fund transmission expansion in Texas

Dive Brief: Sempra plans to sell Ecogas Mexico, a three-utility conglomerate that provides natural gas service in the Mexicali, Chihuahua and La Laguna-Durango regions in Mexico, and a minority stake in its development arm Sempra Infrastructure in order to finance expansion plans in Texas, company leaders said during a Thursday earnings call. The company plans to spend $13 billion on energy infrastructure this year alone, with $10 billion of that investment destined for the United States, Chairman, President and CEO Jeff Martin said. Analysts at Morningstar welcomed news of the sale and the company’s desire to refocus on its regulated utilities. Sempra disappointed analysts and investors in February when it cut its earnings projections amid rising costs and will “need to continue strong execution,” according to Morningstar strategist Andrew Bischof. Dive Insight: Sempra’s Texas subsidiaries continue to draw what analysts described as “huge numbers” from would-be customers hoping to connect to the utility’s electric system. And to bring those customers online, Sempra plans to invest heavily in new transmission projects. The Electric Reliability Council of Texas anticipates a need for $32 billion to $35 billion in new transmission to serve a projected 150 GW peak load by 2030, and Texas-based electric distributor Oncor is “well-positioned to construct a significant portion of the required transmission infrastructure,” according to Karen Sedgwick, executive vice president and chief financial officer for Sempra. Sempra owns 80% of Oncor. The company is already involved in the $15 billion to $17 billion Permian transmission project, which is set to become ERCOT’s first extra-high-voltage transmission project following a decision by the Public Utility Commission of Texas in April. Sempra originally anticipated that the construction of the Permian project would stretch beyond 2030, but recent regulatory decisions have shortened the timeline, prompting a need for greater near-term funding, Martin said.

Sunrun reports solid Q1 earnings amid tax, tariff uncertainty

Dive Brief: Sunrun is “actively working through scenario planning and corresponding actions if there are material changes” to U.S. clean energy tax credits in the federal budget reconciliation bill expected later this year, CEO Mary Powell said Wednesday. The country’s top residential solar company by market share “[has] a playbook” from past periods of regulatory change to reduce customer acquisition costs and raise prices if Congress eliminates or steps down the technology-neutral 48E clean electricity tax credit, Powell said during Sunrun’s first-quarter 2025 earnings call. U.S. import tariffs could also increase Sunrun’s hardware costs later this year due to its suppliers’ upstream exposure to China, but “any adverse changes to tax and tariff policy, of course, will also impact utilities and create additional pricing headroom” for its solar and energy storage systems, Powell said. Dive Insight: Sunrun subscriber additions grew 7% year over year as its storage attachment rate reached 69%, up from 50% in the first quarter of 2024, the company said in its Q1 2025 investor presentation. In the fourth quarter of 2024, Sunrun accounted for about 19% of new U.S. solar installations and 45% of new U.S. energy storage installations, according to the presentation. Sunrun’s contracted subscriber value jumped 14% in Q1 2025 to $48,727 thanks to the rising share of higher-value energy storage customers, it said. Sunrun defines contracted subscriber value as the discounted cumulative value of estimated, contracted cash flows from an individual customer. “Subscribers with storage have higher upfront margins … also unlock additional recurring revenue streams as they represent valuable energy resources for the grid,” Powell said. “While still a nascent business and small source of revenue today, this will grow significantly in the years ahead.” Sunrun owes its recent market share boost in part to Sunrun Flex, a new solar and storage

USA EIA Lowers WTI Oil Price Forecasts

The U.S. Energy Information Administration (EIA) lowered its West Texas Intermediate (WTI) spot average price forecasts for 2025 and 2026 in its latest short term energy outlook (STEO), which was released on May 6. According to that STEO, the EIA now sees the WTI spot price averaging $61.81 per barrel this year and $55.24 per barrel next year. In its previous STEO, which was released in April, the EIA projected that the WTI spot price would average $63.88 per barrel in 2025 and $57.48 per barrel in 2026. Both STEOs highlighted that the WTI spot price came in at $76.60 per barrel in 2024. The EIA’s latest STEO forecast that the WTI spot price will average $60.85 per barrel in the second quarter of 2025, $58 per barrel in the third quarter, $57 per barrel in the fourth quarter, $56 per barrel across the first and second quarters of next year, $55 per barrel in the third quarter, and $54 per barrel in the fourth quarter of 2026. This STEO pointed out that the WTI spot price averaged $71.85 per barrel in the first quarter of 2025. In its April STEO, the EIA projected that the WTI spot price would come in at $62.33 per barrel in the second quarter of 2025, $61.67 per barrel in the third quarter, $60 per barrel in the fourth quarter, $59 per barrel in the first quarter of 2026, $58 per barrel in the second quarter, $57 per barrel in the third quarter, and $56 per barrel in the fourth quarter. This STEO also highlighted that the WTI spot price averaged $71.85 per barrel in the first quarter of 2025. Back in its March STEO, the EIA forecast that the WTI spot price average would come in at $70.68 per barrel in 2025 and

Tech CEOs warn Senate: Outdated US power grid threatens AI ambitions

The implications are clear: without dramatic improvements to the US energy infrastructure, the nation’s AI ambitions could be significantly constrained by simple physical limitations – the inability to power the massive computing clusters necessary for advanced AI development and deployment. Streamlining permitting processes The tech executives have offered specific recommendations to address these challenges, with several focusing on the need to dramatically accelerate permitting processes for both energy generation and the transmission infrastructure needed to deliver that power to AI facilities, the report added. Intrator specifically called for efforts “to streamline the permitting process to enable the addition of new sources of generation and the transmission infrastructure to deliver it,” noting that current regulatory frameworks were not designed with the urgent timelines of the AI race in mind. This acceleration would help technology companies build and power the massive data centers needed for AI training and inference, which require enormous amounts of electricity delivered reliably and consistently. Beyond the cloud: bringing AI to everyday devices While much of the testimony focused on large-scale infrastructure needs, AMD CEO Lisa Su emphasized that true AI leadership requires “rapidly building data centers at scale and powering them with reliable, affordable, and clean energy sources.” Su also highlighted the importance of democratizing access to AI technologies: “Moving faster also means moving AI beyond the cloud. To ensure every American benefits, AI must be built into the devices we use every day and made as accessible and dependable as electricity.”

Networking errors pose threat to data center reliability

Still, IT and networking issues increased in 2024, according to Uptime Institute. The analysis attributed the rise in outages due to increased IT and network complexity, specifically, change management and misconfigurations. “Particularly with distributed services, cloud services, we find that cascading failures often occur when networking equipment is replicated across an entire network,” Lawrence explained. “Sometimes the failure of one forces traffic to move in one direction, overloading capacity at another data center.” The most common causes of major network-related outages were cited as: Configuration/change management failure: 50% Third-party network provider failure: 34% Hardware failure: 31% Firmware/software error: 26% Line breakages: 17% Malicious cyberattack: 17% Network overload/congestion failure: 13% Corrupted firewall/routing tables issues: 8% Weather-related incident: 7% Configuration/change management issues also attributed for 62% of the most common causes of major IT system-/software-related outages. Change-related disruptions consistently are responsible for software-related outages. Human error continues to be one of the “most persistent challenges in data center operations,” according to Uptime’s analysis. The report found that the biggest cause of these failures is data center staff failing to follow established procedures, which has increased by about 10 percentage points compared to 2023. “These are things that were 100% under our control. I mean, we can’t control when the UPS module fails because it was either poorly manufactured, it had a flaw, or something else. This is 100% under our control,” Brown said. The most common causes of major human error-related outages were reported as:

Liquid cooling technologies: reducing data center environmental impact

“Highly optimized cold-plate or one-phase immersion cooling technologies can perform on par with two-phase immersion, making all three liquid-cooling technologies desirable options,” the researchers wrote. Factors to consider There are numerous factors to consider when adopting liquid cooling technologies, according to Microsoft’s researchers. First, they advise performing a full environmental, health, and safety analysis, and end-to-end life cycle impact analysis. “Analyzing the full data center ecosystem to include systems interactions across software, chip, server, rack, tank, and cooling fluids allows decision makers to understand where savings in environmental impacts can be made,” they wrote. It is also important to engage with fluid vendors and regulators early, to understand chemical composition, disposal methods, and compliance risks. And associated socioeconomic, community, and business impacts are equally critical to assess. More specific environmental considerations include ozone depletion and global warming potential; the researchers emphasized that operators should only use fluids with low to zero ozone depletion potential (ODP) values, and not hydrofluorocarbons or carbon dioxide. It is also critical to analyze a fluid’s viscosity (thickness or stickiness), flammability, and overall volatility. And operators should only use fluids with minimal bioaccumulation (the buildup of chemicals in lifeforms, typically in fish) and terrestrial and aquatic toxicity. Finally, once up and running, data center operators should monitor server lifespan and failure rates, tracking performance uptime and adjusting IT refresh rates accordingly.

Cisco unveils prototype quantum networking chip

Clock synchronization allows for coordinated time-dependent communications between end points that might be cloud databases or in large global databases that could be sitting across the country or across the world, he said. “We saw recently when we were visiting Lawrence Berkeley Labs where they have all of these data sources such as radio telescopes, optical telescopes, satellites, the James Webb platform. All of these end points are taking snapshots of a piece of space, and they need to synchronize those snapshots to the picosecond level, because you want to detect things like meteorites, something that is moving faster than the rotational speed of planet Earth. So the only way you can detect that quickly is if you synchronize these snapshots at the picosecond level,” Pandey said. For security use cases, the chip can ensure that if an eavesdropper tries to intercept the quantum signals carrying the key, they will likely disturb the state of the qubits, and this disturbance can be detected by the legitimate communicating parties and the link will be dropped, protecting the sender’s data. This feature is typically implemented in a Quantum Key Distribution system. Location information can serve as a critical credential for systems to authenticate control access, Pandey said. The prototype quantum entanglement chip is just part of the research Cisco is doing to accelerate practical quantum computing and the development of future quantum data centers. The quantum data center that Cisco envisions would have the capability to execute numerous quantum circuits, feature dynamic network interconnection, and utilize various entanglement generation protocols. The idea is to build a network connecting a large number of smaller processors in a controlled environment, the data center warehouse, and provide them as a service to a larger user base, according to Cisco. The challenges for quantum data center network fabric

Zyxel launches 100GbE switch for enterprise networks

Port specifications include: 48 SFP28 ports supporting dual-rate 10GbE/25GbE connectivity 8 QSFP28 ports supporting 100GbE connections Console port for direct management access Layer 3 routing capabilities include static routing with support for access control lists (ACLs) and VLAN segmentation. The switch implements IEEE 802.1Q VLAN tagging, port isolation, and port mirroring for traffic analysis. For link aggregation, the switch supports IEEE 802.3ad for increased throughput and redundancy between switches or servers. Target applications and use cases The CX4800-56F targets multiple deployment scenarios where high-capacity backbone connectivity and flexible port configurations are required. “This will be for service providers initially or large deployments where they need a high capacity backbone to deliver a primarily 10G access layer to the end point,” explains Nguyen. “Now with Wi-Fi 7, more 10G/25G capable POE switches are being powered up and need interconnectivity without the bottleneck. We see this for data centers, campus, MDU (Multi-Dwelling Unit) buildings or community deployments.” Management is handled through Zyxel’s NebulaFlex Pro technology, which supports both standalone configuration and cloud management via the Nebula Control Center (NCC). The switch includes a one-year professional pack license providing IGMP technology and network analytics features. The SFP28 ports maintain backward compatibility between 10G and 25G standards, enabling phased migration paths for organizations transitioning between these speeds.

Engineers rush to master new skills for AI-driven data centers

According to the Uptime Institute survey, 57% of data centers are increasing salary spending. Data center job roles that saw the highest increases were in operations management – 49% of data center operators said they saw highest increases in this category – followed by junior and mid-level operations staff at 45%, and senior management and strategy at 35%. Other job categories that saw salary growth were electrical, at 32% and mechanical, at 23%. Organizations are also paying premiums on top of salaries for particular skills and certifications. Foote Partners tracks pay premiums for more than 1,300 certified and non-certified skills for IT jobs in general. The company doesn’t segment the data based on whether the jobs themselves are data center jobs, but it does track 60 skills and certifications related to data center management, including skills such as storage area networking, LAN, and AIOps, and 24 data center-related certificates from Cisco, Juniper, VMware and other organizations. “Five of the eight data center-related skills recording market value gains in cash pay premiums in the last twelve months are all AI-related skills,” says David Foote, chief analyst at Foote Partners. “In fact, they are all among the highest-paying skills for all 723 non-certified skills we report.” These skills bring in 16% to 22% of base salary, he says. AIOps, for example, saw an 11% increase in market value over the past year, now bringing in a premium of 20% over base salary, according to Foote data. MLOps now brings in a 22% premium. “Again, these AI skills have many uses of which the data center is only one,” Foote adds. The percentage increase in the specific subset of these skills in data centers jobs may vary. The Uptime Institute survey suggests that the higher pay is motivating workers to stay in the

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.

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

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

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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