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The Download: aluminium’s potential as a zero-carbon fuel, and what’s next for energy storage

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. This startup is about to conduct the biggest real-world test of aluminum as a zero-carbon fuel Found Energy, a startup in Boston, aims to harness the energy in scraps of aluminum metal to power industrial processes without fossil fuels. Since 2022, the company has worked to develop ways to rapidly release energy from aluminum on a small scale.Now it’s just switched on a much larger version of its aluminum-powered engine, which it claims is the largest aluminum-water reactor ever built.Early next year, it will be installed to supply heat and hydrogen to a tool manufacturing facility in the southeastern US, using the aluminum waste produced by the plant itself as fuel.If everything works as planned, this technology, which uses a catalyst to unlock the energy stored within aluminum metal, could transform a growing share of aluminum scrap into a zero-carbon fuel. Read the full story. —James Dinneen What a massive thermal battery means for energy storage Rondo Energy just turned on what it says is the world’s largest thermal battery, an energy storage system that can take in electricity and provide a consistent source of heat. The concept behind a thermal battery is overwhelmingly simple: Use electricity to heat up some cheap, sturdy material (like bricks) and keep it hot until you want to use that heat later, either directly in an industrial process or to produce electricity.  Thermal batteries could be a major tool in cutting emissions: 20% of total energy demand today is used to provide heat for industrial processes, and most of that is generated by burning fossil fuels. But the company is using its battery for enhanced oil recovery—a process that critics argue keep polluting infrastructure running longer. Read the full story. —Casey Crownhart This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 ChatGPT’s suicide discussion rules were loosened twice before a teen took his own life    The parents of Adam Raine claim the changes OpenAI made equate to a weakening in its suicide protection for users. (WSJ $)+ It did so to increase use of the chatbot, they allege in an amended lawsuit. (FT $)+ The family is accusing OpenAI of intentional misconduct rather than reckless indifference. (Rolling Stone $)2 Google claims its new quantum algorithm outperforms a supercomputerIt could accelerate advances in drug discovery and new building materials. (Ars Technica)+ Its Willow chip is at the heart of the advance. (NYT $)+ But real-world use of quantum computing is still likely to be years away. (The Guardian) 3 Reddit is suing AI search engine PerplexityFor allegedly illegally scraping its data to train the model powering Perplexity’s engine. (FT $)+ Reddit’s also seeking a permanent injunction on companies selling its data. (Engadget)+ What comes next for AI copyright lawsuits? (MIT Technology Review) 4 China has a five-year plan to become technologically self-reliantAnd semiconductors and AI will play key roles. (Bloomberg $)+ China is winning the trade war with America. (Economist $)5 DeepSeek is taking off in AfricaIts decision to make its AI cheaper and less power-intensive is paying off. (Bloomberg $)+ How DeepSeek ripped up the AI playbook. (MIT Technology Review) 6 Elon Musk is building a robot armyHe envisions his Optimus robot becoming an “incredible surgeon.” (Wired $)+ Will we ever trust robots? (MIT Technology Review) 7 Apple has pulled a pair of controversial dating apps from the App StoreTea and TeaOnHer fell short of its privacy and content moderation rules. (TechCrunch) 8 Tesla’s profits are massively downEven though it sold more cars than during its previous quarter. (NYT $)+ The company has been forced to recall tens of thousands of Cybertrucks. (Reuters)+ What happens when your EV becomes obsolete? (The Atlantic $) 9 An unexpected victim of the AWS outage? Smart beds 🛏️Some unlucky owners’ beds blared alarms and became unbearably warm. (WP $)+ If the internet stays the way it is, more bed outages could be on their way. (The Atlantic $) 10 The appeal of incredibly basic softwareApple’s TextEdit does exactly what it says on the tin. (New Yorker $) Quote of the day “I’m very excited that nerds are having our moment.” —Madhavi Sewak, a Google DeepMind researcher, says she’s glad that AI experts are being recognized, the Wall Street Journal reports. One more thing Inside the hunt for new physics at the world’s largest particle colliderIn 2012, using data from CERN’s Large Hadron Collider, researchers discovered a particle called the Higgs boson. In the process, they answered a nagging question: Where do fundamental particles, such as the ones that make up all the protons and neutrons in our bodies, get their mass?When the particle was finally found, scientists celebrated with champagne. A Nobel for two of the physicists who predicted the Higgs boson soon followed.More than a decade later, there is a sense of unease. That’s because there are still so many unanswered questions about the fundamental constituents of the universe.So researchers are trying something new. They are repurposing detectors to search for unusual-looking particles, squeezing what they can out of the data with machine learning, and planning for entirely new kinds of colliders. Read the full story. —Dan Garisto We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.)+ Mexico City is already getting into the Halloween spirit: its annual zombie parade took place over the weekend.+ Everything you need to know before travelling to Japan.+ The most stylish people alive? I’ll be the judge of that.+ Here’s something you don’t expect archeologists to uncover: Neolithic chewing gum.

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

This startup is about to conduct the biggest real-world test of aluminum as a zero-carbon fuel

Found Energy, a startup in Boston, aims to harness the energy in scraps of aluminum metal to power industrial processes without fossil fuels. Since 2022, the company has worked to develop ways to rapidly release energy from aluminum on a small scale.

Now it’s just switched on a much larger version of its aluminum-powered engine, which it claims is the largest aluminum-water reactor ever built.

Early next year, it will be installed to supply heat and hydrogen to a tool manufacturing facility in the southeastern US, using the aluminum waste produced by the plant itself as fuel.

If everything works as planned, this technology, which uses a catalyst to unlock the energy stored within aluminum metal, could transform a growing share of aluminum scrap into a zero-carbon fuel. Read the full story.

—James Dinneen

What a massive thermal battery means for energy storage

Rondo Energy just turned on what it says is the world’s largest thermal battery, an energy storage system that can take in electricity and provide a consistent source of heat.

The concept behind a thermal battery is overwhelmingly simple: Use electricity to heat up some cheap, sturdy material (like bricks) and keep it hot until you want to use that heat later, either directly in an industrial process or to produce electricity. 

Thermal batteries could be a major tool in cutting emissions: 20% of total energy demand today is used to provide heat for industrial processes, and most of that is generated by burning fossil fuels. But the company is using its battery for enhanced oil recovery—a process that critics argue keep polluting infrastructure running longer. Read the full story.

—Casey Crownhart

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 ChatGPT’s suicide discussion rules were loosened twice before a teen took his own life    
The parents of Adam Raine claim the changes OpenAI made equate to a weakening in its suicide protection for users. (WSJ $)
+ It did so to increase use of the chatbot, they allege in an amended lawsuit. (FT $)
+ The family is accusing OpenAI of intentional misconduct rather than reckless indifference. (Rolling Stone $)

2 Google claims its new quantum algorithm outperforms a supercomputer
It could accelerate advances in drug discovery and new building materials. (Ars Technica)
+ Its Willow chip is at the heart of the advance. (NYT $)
+ But real-world use of quantum computing is still likely to be years away. (The Guardian)

3 Reddit is suing AI search engine Perplexity
For allegedly illegally scraping its data to train the model powering Perplexity’s engine. (FT $)
+ Reddit’s also seeking a permanent injunction on companies selling its data. (Engadget)
+ What comes next for AI copyright lawsuits? (MIT Technology Review)

4 China has a five-year plan to become technologically self-reliant
And semiconductors and AI will play key roles. (Bloomberg $)
+ China is winning the trade war with America. (Economist $)

5 DeepSeek is taking off in Africa
Its decision to make its AI cheaper and less power-intensive is paying off. (Bloomberg $)
+ How DeepSeek ripped up the AI playbook. (MIT Technology Review)

6 Elon Musk is building a robot army
He envisions his Optimus robot becoming an “incredible surgeon.” (Wired $)
+ Will we ever trust robots? (MIT Technology Review)

7 Apple has pulled a pair of controversial dating apps from the App Store
Tea and TeaOnHer fell short of its privacy and content moderation rules. (TechCrunch)

8 Tesla’s profits are massively down
Even though it sold more cars than during its previous quarter. (NYT $)
+ The company has been forced to recall tens of thousands of Cybertrucks. (Reuters)
+ What happens when your EV becomes obsolete? (The Atlantic $)

9 An unexpected victim of the AWS outage? Smart beds 🛏️
Some unlucky owners’ beds blared alarms and became unbearably warm. (WP $)
+ If the internet stays the way it is, more bed outages could be on their way. (The Atlantic $)

10 The appeal of incredibly basic software
Apple’s TextEdit does exactly what it says on the tin. (New Yorker $)

Quote of the day

“I’m very excited that nerds are having our moment.”

—Madhavi Sewak, a Google DeepMind researcher, says she’s glad that AI experts are being recognized, the Wall Street Journal reports.

One more thing

Inside the hunt for new physics at the world’s largest particle collider

In 2012, using data from CERN’s Large Hadron Collider, researchers discovered a particle called the Higgs boson. In the process, they answered a nagging question: Where do fundamental particles, such as the ones that make up all the protons and neutrons in our bodies, get their mass?

When the particle was finally found, scientists celebrated with champagne. A Nobel for two of the physicists who predicted the Higgs boson soon followed.

More than a decade later, there is a sense of unease. That’s because there are still so many unanswered questions about the fundamental constituents of the universe.

So researchers are trying something new. They are repurposing detectors to search for unusual-looking particles, squeezing what they can out of the data with machine learning, and planning for entirely new kinds of colliders. Read the full story.

—Dan Garisto

We can still have nice things

A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.)

+ Mexico City is already getting into the Halloween spirit: its annual zombie parade took place over the weekend.
+ Everything you need to know before travelling to Japan.
+ The most stylish people alive? I’ll be the judge of that.
+ Here’s something you don’t expect archeologists to uncover: Neolithic chewing gum.

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China Keeps Importing Russian LNG After Dodging New USA Curbs

China is pushing ahead with imports of US-sanctioned Russian liquefied natural gas, after the White House stopped short of putting additional restrictions on the trade in its latest wave of sanctions. The Iris vessel, carrying a shipment from the blacklisted Arctic LNG 2 facility in Russia, docked at the Beihai import terminal in southern China on Thursday, according to ship-tracking data compiled by Bloomberg. This is China’s 11th shipment of restricted Russian LNG since late-August. The move comes after US President Donald Trump ramped up pressure on Russia by blacklisting state-run oil giants Rosneft PJSC and Lukoil PJSC, citing Moscow’s lack of commitment to Ukrainian peace. However, the White House hasn’t yet hit companies circumventing sanctions on LNG — a growing source of revenue for Moscow, which aims to triple exports of the superchilled fuel by 2030.  The lack of new restrictions on Russian LNG is notable, given that the UK slapped sanctions on Beihai last week. Meanwhile, European Union nations have adopted a new package of sanctions aimed at Russia that will target 45 entities, including 12 companies in China and Hong Kong.   China had designated Beihai as the sole entry point for shipments from Arctic LNG 2 — a Russian project already sanctioned by the US in 2023. Arctic LNG 2 started delivering the blacklisted fuel to the Asian nation in late August, a move that coincided with a visit to Beijing by Russian President Vladimir Putin. The Iris vessel loaded an LNG shipment from a floating storage unit in eastern Russia in early October, according to ship-tracking data. The fuel in storage was sourced from the Arctic LNG 2 project. The storage facility and Iris have both been previously sanctioned by the US. At least three more vessels carrying blacklisted Russian LNG are heading to the Beihai terminal, ship data

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US slaps sanctions on Russian oil giants; EU follows with LNG ban

The Treasury Department carved out an exception to allow oilfield services for the Caspian Pipeline Consortium and the Tengizchevroil project, authorizing those transactions despite the broader sanctions in place. EU sanctions on Russia The European Union (EU) ratcheted up its own sanctions on Moscow Oct. 23, announcing a phased ban on Russian LNG imports into the 27 nations that comprise the organization, with the goal of halting all trade in Russian LNG by Jan. 1, 2027. Most Russian gas travels through pipeline to Europe, but bans on piped gas have boosted LNG exports. The EU sanctions also ban transactions with Rosneft and Lukoil and institute port bans on 117 newly designated ships in Russia’s so-called “shadow fleet,” which has sought to evade previous sanctions measures. The sanctions come a week after the UK imposed its own sanctions on Lukoil and Rosneft, the shadow fleet, a major Indian oil refinery, and four Chinese oil terminals. Russia is dependent on oil and gas sales to fuel its economy. EIA estimates that Russia’s oil exports averaged 4.3 million b/d in first-half 2005, down from 4.8 million b/d in 2024.  Trade has shifted as a result of sanctions, with the EU’s imports falling to 11% (from over 50% in 2020) and Turkey’s imports taking at least half of that oil, the US independent statistical arm said. China remains the single largest importer of Russian oil, averaging 2.0 million b/d in first-half 2025. India holds the second spot, boosting imports to 1.6 million b/d in first-half 2025 from 50,000 b/d in 2020, EIA added.

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Williams buys into Louisiana LNG, sells upstream Haynesville asset

Woodside Energy Ltd. has sold a 10% interest in Louisiana LNG LLC and and 80% interest and operatorship of Driftwood Pipeline LLC to Williams Cos. As part of the transaction, Williams will contribute its share expenditure—roughly $1.9 billion—to the LNG plant and pipeline and assumes LNG offtake obligations for 10% of produced volumes. Williams will also build and operate the 2.4-bcfd Line 200 pipeline, which will use 42-in. OD pipe to transport natural gas from the 5.4-bcfd Driftwood pipeline to the 27.6-million tonne/year (tpy) Louisiana LNG plant. Woodside chief executive officer Meg O’Neill noted that this was Williams’ first investment in LNG and that the project was “on track to deliver first LNG in 2029.” Woodside last month signed its first long-term LNG offtake agreement with Petronas, which could include production from Louisiana LNG. First deliveries under the deal are also targeted for 2029. The deal was executed at a purchase price of $250 million with an effective date of Jan. 1, 2025. The total proceeds received were $378 million, including proportionate capital reimbursement since the effective date.  Relatedly, Williams agreed to sell its minority interest in the South Mansfield upstream asset of Louisiana’s Haynesville shale to JERA Co. Inc. for $398 million plus deferred monthly payments through 2029. The total transaction value is estimated at $1.5 billion. South Mansfield currently produces 500 MMcfd and includes 200 undeveloped locations, JERA said. The company plans to increase production to 1 bcfd. GEP Haynesville II LLC is also selling its majority interest in South Mansfield upstream but will continue to operate and develop the asset on a fixed fee basis. GEP continues to own and operate other Haynesville shale assets not involved in this transaction. Under JERA’s ownership, Williams will continue to gather natural gas volumes from South Mansfield and will deliver those volumes through its Louisiana Energy Gateway (LEG) system

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GE Vernova bullish on electrical infrastructure as turbine backlog grows

$10B revenue Up 10% year over year. $14.7B total orders Up 55% year over year, driven by power and electrification segments. 62 GW total gas turbine backlog Up 7 GW from Q2 2025. Includes 29 GW order backlog + 33 GW slot reservations. 102% growth in electrification Fastest-growing GEV segment Prolec Acquisition GE Vernova will pay $5.3 billion for the remaining 50% of Prolec GE, the electrical equipment and services joint venture it owns 50-50 with Xignux, a Mexican conglomerate. It expects the deal to close by mid-2026, CEO Scott Strazik said on the company’s Oct. 22 earnings call. The deal will override a contractual agreement with Xignux that largely prevented GE Vernova from selling transformers into North America, boosting its prospects there amid rapid growth in electricity demand and a utility investment supercycle. Prolec recently expanded production at facilities in Louisiana and Mexico and is progressing on a North Carolina factory expansion. Strazik said Prolec’s data center sales grew from 10% of its total in 2024 to nearly 20% in 2025, with more to come. GE Vernova sees a clear opportunity to diversify beyond transmission equipment and services into “integrated solutions with power generation and electrical equipment” for a “new archetype of customers … like data centers,” he added. “Data centers [are] coming to us and saying, ‘Co-create with us the power-to-rack solution,’” Strazik said. Electrification Growth In a Wednesday note, Jefferies energy equities analyst Julien Demoulin-Smith said the Prolec acquisition shows “a strategic preference for investment in Electrification,” which GE Vernova is “overtly signaling as its fastest growing segment vs. intense investor focus for [its] gas turbine order ramp.” Revenue in the segment jumped 32% year over year as equipment orders more than doubled. GE Vernova expects 25% organic revenue growth this year — up from previous forecasts

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OEUK to Host Cross Spectrum Energy Policy Debate

Industry body Offshore Energies UK (OEUK) announced, in a statement sent to Rigzone this week, that it will host a “cross spectrum” energy policy debate. “OEUK is to bring together key voices for a public debate on the UK’s energy future,” the industry body said in the statement. “With decisions due on major oil and gas projects, ongoing public concern about energy bills, and debate over net zero policy, the trade body has said conversation and collaboration are needed instead of confrontation, if the UK is to tackle these issues properly,” it added. OEUK noted in the statement that representatives from groups on all sides will be invited to speak at a public debate in London as OEUK “kicks off another series of open debates around the country”. The London event comes as renewed attention is focused on the development of the Rosebank oil field in the North Atlantic west of Shetland, OEUK said in the statement, adding that the group “has been calling for a pragmatic discussion on energy which allows room for facts and all points of view to be heard”. In the statement, OEUK Chief Executive David Whitehouse said, “the challenges facing the country, and indeed the world, when it comes to energy are significant and complex”. “The decisions made by government will impact people’s pockets, families, communities, and futures. We owe it to them and to ourselves to have a proper debate focused on conversation not confrontation,” he added. “OEUK believes that if we are serious about finding solutions, we must take the polarization out of the debate and find a pragmatic way through. By bringing these groups together I hope we can develop a better approach,” he went on to state. In a statement posted on its site back in April, OEUK announced that it

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Williams Acquires Stake in Woodside’s Louisiana LNG

Woodside Energy Group Ltd has roped in another partner for the under-construction Louisiana LNG with Williams Companies Inc acquiring a minority interest and entering into an offtake agreement for 1.5 million metric tons per annum (MMtpa). “The strategic partnership involves the sale by Woodside of a 10 percent interest in Louisiana LNG LLC (HoldCo) and an 80 percent interest and operatorship of Driftwood Pipeline LLC (PipelineCo) to Williams for a purchase price of $250 million at the effective date of 1 January 2025”, Woodside said in an online statement Thursday. “The total proceeds received are $378 million including proportionate capital reimbursement since the effective date”. The companies expect Tulsa, Oklahoma-based Williams to invest $1.9 billion. “As part of the investment in Louisiana LNG, Williams assumes LNG offtake obligations for 10 percent of produced volumes”, Australian oil and gas company Woodside said. “Williams’ total share of LNG production from Louisiana LNG will be 1.6 million tonnes per annum. This LNG production will be supplied to Williams under an LNG SPA [sale and purchase agreement] for approximately 1.5 Mtpa and Williams will also receive the proportionate benefit (10 percent) of the Louisiana LNG 1.0 Mtpa SPA previously signed with Uniper”, Woodside said. It was referring to its agreement with the German power and gas utility for up to two MMtpa – one MMtpa from Louisiana LNG for 13 years and up to one MMtpa from Woodside’s global LNG portfolio for a term starting with Louisiana LNG’s start of commercial operations until 2039. “Woodside’s total capital expenditure for the Louisiana LNG Project is now expected to be $9.9 billion reduced from $11.8 billion at final investment decision (FID)”, Woodside added. Williams, which currently operates over 33,000 miles of pipeline and markets of over seven billion cubic feet a day of gas at the Sequent platform, will build

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Inside Google’s multi-architecture revolution: Axion Arm joins x86 in production clusters

Matt Kimball, VP and principal analyst with Moor Insights and Strategy, pointed out that AWS and Microsoft have already moved many workloads from x86 to internally designed Arm-based servers. He noted that, when Arm first hit the hyperscale datacenter market, the architecture was used to support more lightweight, cloud-native workloads with an interpretive layer where architectural affinity was “non-existent.” But now there’s much more focus on architecture, and compatibility issues “largely go away” as Arm servers support more and more workloads. “In parallel, we’ve seen CSPs expand their designs to support both scale out (cloud-native) and traditional scale up workloads effectively,” said Kimball. Simply put, CSPs are looking to monetize chip investments, and this migration signals that Google has found its performance-per-dollar (and likely performance-per-watt) better on Axion than x86. Google will likely continue to expand its Arm footprint as it evolves its Axion chip; as a reference point, Kimball pointed to AWS Graviton, which didn’t really support “scale up” performance until its v3 or v4 chip. Arm is coming to enterprise data centers too When looking at architectures, enterprise CIOs should ask themselves questions such as what instance do they use for cloud workloads, and what servers do they deploy in their data center, Kimball noted. “I think there is a lot less concern about putting my workloads on an Arm-based instance on Google Cloud, a little more hesitance to deploy those Arm servers in my datacenter,” he said. But ultimately, he said, “Arm is coming to the enterprise datacenter as a compute platform, and Nvidia will help usher this in.” Info-Tech’s Jain agreed that Nvidia is the “biggest cheerleader” for Arm-based architecture, and Arm is increasingly moving from niche and mobile use to general-purpose and AI workload execution.

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AMD Scales the AI Factory: 6 GW OpenAI Deal, Korean HBM Push, and Helios Debut

What 6 GW of GPUs Really Means The 6 GW of accelerator load envisioned under the OpenAI–AMD partnership will be distributed across multiple hyperscale AI factory campuses. If OpenAI begins with 1 GW of deployment in 2026, subsequent phases will likely be spread regionally to balance supply chains, latency zones, and power procurement risk. Importantly, this represents entirely new investment in both power infrastructure and GPU capacity. OpenAI and its partners have already outlined multi-GW ambitions under the broader Stargate program; this new initiative adds another major tranche to that roadmap. Designing for the AI Factory Era These upcoming facilities are being purpose-built for next-generation AI factories, where MI450-class clusters could drive rack densities exceeding 100 kW. That level of compute concentration makes advanced power and cooling architectures mandatory, not optional. Expected solutions include: Warm-water liquid cooling (manifold, rear-door, and CDU variants) as standard practice. Facility-scale water loops and heat-reuse systems—including potential district-heating partnerships where feasible. Medium-voltage distribution within buildings, emphasizing busway-first designs and expanded fault-current engineering. While AMD has not yet disclosed thermal design power (TDP) specifications for the MI450, a 1 GW campus target implies tens of thousands of accelerators. That scale assumes liquid cooling, ultra-dense racks, and minimal network latency footprints, pushing architectures decisively toward an “AI-first” orientation. Design considerations for these AI factories will likely include: Liquid-to-liquid cooling plants engineered for step-function capacity adders (200–400 MW blocks). Optics-friendly white space layouts with short-reach topologies, fiber raceways, and aisles optimized for module swaps. Substation adjacency and on-site generation envelopes negotiated during early land-banking phases. Networking, Memory, and Power Integration As compute density scales, networking and memory bottlenecks will define infrastructure design. Expect fat-tree and dragonfly network topologies, 800 G–1.6 T interconnects, and aggressive optical-module roadmaps to minimize collective-operation latency, aligning with recent disclosures from major networking vendors.

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Study Finds $4B in Data Center Grid Costs Shifted to Consumers Across PJM Region

In a new report spanning 2022 through 2024, the Union of Concerned Scientists (UCS) identifies a significant regulatory gap in the PJM Interconnection’s planning and rate-making process—one that allows most high-voltage (“transmission-level”) interconnection costs for large, especially AI-scale, data centers to be socialized across all utility customers. The result, UCS argues, is a multi-billion-dollar pass-through that is poised to grow as more data center projects move forward, because these assets are routinely classified as ordinary transmission infrastructure rather than customer-specific hookups. According to the report, between 2022 and 2024, utilities initiated more than 150 local transmission projects across seven PJM states specifically to serve data center connections. In 2024 alone, 130 projects were approved with total costs of approximately $4.36 billion. Virginia accounted for nearly half that total—just under $2 billion—followed by Ohio ($1.3 billion) and Pennsylvania ($492 million) in data-center-related interconnection spending. Yet only six of those 130 projects, about 5 percent, were reported as directly paid for by the requesting customer. The remaining 95 percent, representing more than $4 billion in 2024 connection costs, were rolled into general transmission charges and ultimately recovered from all retail ratepayers. How Does This Happen? When data center project costs are discussed, the focus is usually on the price of the power consumed, or megawatts multiplied by rate. What the UCS report isolates, however, is something different: the cost of physically delivering that power: the substations, transmission lines, and related infrastructure needed to connect hyperscale facilities to the grid. So why aren’t these substantial consumer-borne costs more visible? The report identifies several structural reasons for what effectively functions as a regulatory loophole in how development expenses are reported and allocated: Jurisdictional split. High-voltage facilities fall under the Federal Energy Regulatory Commission (FERC), while retail electricity rates are governed by state public utility

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OCP Global Summit 2025 Highlights: Advancing Data Center Densification and Security

With the conclusion of the 2025 OCP Global Summit, William G. Wong, Senior Content Director at DCF’s sister publications Electronic Design and Microwaves & RF, published a comprehensive roundup of standout technologies unveiled at the event. For Data Center Frontier readers, we’ve revisited those innovations through the lens of data center impact, focusing on how they reshape infrastructure design and operational strategy. This year’s OCP Summit marked a decisive shift toward denser GPU racks, standardized direct-to-chip liquid cooling, 800-V DC power distribution, high-speed in-rack fabrics, and “crypto-agile” platform security. Collectively, these advances aim to accelerate time-to-capacity, reduce power-distribution losses at megawatt rack scales, simplify retrofits in legacy halls, and fortify data center platforms against post-quantum threats. Rack Design and Cooling: From Ad-Hoc to Production-Grade Liquid Cooling NVIDIA’s Vera Rubin compute tray, newly offered to OCP for standardization, packages Rubin-generation GPUs with an integrated liquid-cooling manifold and PCB midplane. Compared with the GB300 tray, Vera Rubin represents a production-ready module delivering four times the memory and three times the memory bandwidth: a 7.5× performance factor at rack scale, with 150 TB of memory at 1.7 PB/s per rack. The system implements 45 °C liquid cooling, a 5,000-amp liquid-cooled busbar, and on-tray energy storage with power-resilience features such as flexible 100-amp whips and automatic-transfer power-supply units. NVIDIA also previewed a Kyber rack generation targeted for 2027, pivoting from 415/480 VAC to 800 V DC to support up to 576 Rubin Ultra GPUs, potentially eliminating the 200-kg copper busbars typical today. These refinements are aimed at both copper reduction and aisle-level manageability. Wiwynn’s announcements filled in the practicalities of deploying such densities. The company showcased rack- and system-level designs across NVIDIA GB300 NVL72 (72 Blackwell Ultra GPUs with 800 Gb/s ConnectX-8 SuperNICs) for large-scale inference and reasoning, and HGX B300 (eight GPUs /

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Storage constraints add to AI data center bottleneck

AI deployment uses multiple storage layers, and each one has different requirements, says Dell’Oro’s Fung. For storing massive amounts of unstructured, raw data, cold storage on HDDs makes more sense, he says. SSDs make sense for warm storage, such as for pre-processing data and for post-training and inference. “There’s a place for each type of storage,” he says. Planning ahead According to Constellation’s Mehta, data center managers and other storage buyers should prepare by treating SSD procurement like they do GPUs. “Multi-source, lock in lanes early, and engineer to standards so vendor swaps don’t break your data path.” He recommends qualifying at least two vendors for both QLC and TLC and starting early. TrendForce’s Ao agrees. “It is better to build inventory now,” he says. “It is difficult to lock-in long term deals with suppliers now due to tight supply in 2026.” Based on suppliers’ availability, Kioxia, SanDisk, and Micron are in the best position to support 128-terabyte QLC enterprise SSD solutions, Ao says. “But in the longer term, some module houses may be able to provide similar solutions at a lower cost,” Ao adds. “We are seeing more module houses, such as Phison and Pure Storage, supporting these solutions.” And it’s not just SSD for fast storage and HDD for slow storage. Memory solutions are becoming more complex in the AI era, says Ao. “For enterprise players with smaller-scale business models, it is important to keep an eye on Z-NAND and XL-Flash for AI inference demand,” he says. These are memory technologies that sit somewhere between the SSDs and the RAM working memory. “These solutions will be more cost-effective compared to HBM or even HBF [high bandwidth flash],” he says.

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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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