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From COBOL to chaos: Elon Musk, DOGE, and the Evil Housekeeper Problem

In trying to make sense of the wrecking ball that is Elon Musk and President Trump’s DOGE, it may be helpful to think about the Evil Housekeeper Problem. It’s a principle of computer security roughly stating that once someone is in your hotel room with your laptop, all bets are off. Because the intruder has physical access, you are in much more trouble. And the person demanding to get into your computer may be standing right beside you. So who is going to stop the evil housekeeper from plugging a computer in and telling IT staff to connect it to the network? What happens if someone comes in and tells you that you’ll be fired unless you reveal the authenticator code from your phone, or sign off on a code change, or turn over your PIV card, the Homeland Security–approved smart card used to access facilities and systems and securely sign documents and emails? What happens if someone says your name will otherwise be published in an online list of traitors? Already the new administration is firing, putting on leave, or outright escorting from the building people who refuse to do what they’re told.  It’s incredibly hard to protect a system from someone—the evil housekeeper from DOGE—who has made their way inside and wants to wreck it. This administration is on the record as wanting to outright delete entire departments. Accelerationists are not only setting policy but implementing it by working within the administration. If you can’t delete a department, then why not just break it until it doesn’t work?  That’s why what DOGE is doing is a massive, terrifying problem, and one I talked through earlier in a thread on Bluesky.  Government is built to be stable. Collectively, we put systems and rules in place to ensure that stability. But whether they actually deliver and preserve stability in the real world isn’t actually about the technology used; it’s about the people using it. When it comes down to it, technology is a tool to be used by humans for human ends. The software used to run our democratically elected government is deployed to accomplish goals tied to policies: collecting money from people, or giving money to states so they can give money to people who qualify for food stamps, or making covid tests available to people. Usually, our experience of government technology is that it’s out of date or slow or unreliable. Certainly not as shiny as what we see in the private sector. And that technology changes very, very slowly, if it happens at all.  It’s not as if people don’t realize these systems could do with modernization. In my experience troubleshooting and modernizing government systems in California and the federal government, I worked with Head Start, Medicaid, child welfare, and logistics at the Department of Defense. Some of those systems were already undergoing modernization attempts, many of which were and continue to be late, over budget, or just plain broken. But the changes that are needed to make other systems more modern were frequently seen as too risky or too expensive. In other words, not important enough.  Of course, some changes are deemed important enough. The covid-19 pandemic and our unemployment insurance systems offer good examples. When covid hit, certain critical government technologies suddenly became visible. Those systems, like unemployment insurance portals, also became politically important, just like the launch of the Affordable Care Act website (which is why it got so much attention when it was botched).  Political attention can change everything. During the pandemic, suddenly it wasn’t just possible to modernize and upgrade government systems, or to make them simpler, clearer, and faster to use. It actually happened. Teams were parachuted in. Overly restrictive rules and procedures were reassessed and relaxed. Suddenly, government workers were allowed to work remotely and to use Slack. However, there is a reason this was an exception.  In normal times, rules and procedures are certainly part of what makes it very, very hard to change government technology. But they are in place to stop changes because, well, changes might break those systems and government doesn’t work without them working consistently.  A long time ago I worked on a mainframe system in California—the kind that uses COBOL. It was as solid as a rock and worked day in, day out. Because if it didn’t, and reimbursements weren’t received for Medicaid, then the state might become temporarily insolvent.  That’s why many of the rules about technology in government make it hard to make changes: because sometimes the risk of things breaking is just too high. Sometimes what’s at stake is simply keeping money flowing; sometimes, as with 911, lives are on the line. Still, government systems and the rules that govern them are ultimately only as good as the people who oversee and enforce them. The technology will only do (and not do) what people tell it to. So if anyone comes in and breaks those rules on purpose—without fear of consequence—there are few practical or technical guardrails to prevent it.  One system that’s meant to do that is the ATO, or the Authority to Operate. It does what it says: It lets you run a computer system. You are not supposed to operate a system without one.  But DOGE staffers are behaving in a way that suggests they don’t care about getting ATOs. And nothing is really stopping them. (Someone on Bluesky replied to me: “My first thought about the OPM [email] server was, “there’s no way those fuckers have an ATO.”)  You might think that there would be technical measures to stop someone right out of high school from coming in and changing the code to a government system. That the system could require two-factor authentication to deploy the code to the cloud. That you would need a smart card to log in to a specific system to do that. Nope—all those technical measures can be circumvented by coercion at the hands of the evil housekeeper.  Indeed, none of our systems and rules work without enforcement, and consequences flowing from that enforcement. But to an unprecedented degree, this administration, and its individual leaders, have shown absolutely no fear. That’s why, according to Wired, the former X and SpaceX engineer and DOGE staffer Marko Elez had the “ability not just to read but to write code on two of the most sensitive systems in the US government: the Payment Automation Manager and Secure Payment System at the Bureau of the Fiscal Service (BFS).” (Elez reportedly resigned yesterday after the Wall Street Journal began reporting on a series of racist comments he had allegedly made.) We’re seeing in real time that there are no practical technical measures preventing someone from taking a spanner to the technology that keeps our government stable, that keeps society running every day—despite the very real consequences.  So we should plan for the worst, even if the likelihood of the worst is low.  We need a version of the UK government’s National Risk Register, covering everything from the collapse of financial markets to “an attack on government” (but, unsurprisingly, that risk is described in terms of external threats). The register mostly predicts long-term consequences, with recovery taking months. That may end up being the case here.  We need to dust off those “in the event of an emergency” disaster response procedures dealing with the failure of federal government—at individual organizations that may soon hit cash-flow problems and huge budget deficits without federal funding, at statehouses that will need to keep social programs running, and in groups doing the hard work of archiving and preserving data and knowledge. In the end, all we have is each other—our ability to form communities and networks to support, help, and care for each other. Sometimes all it takes is for the first person to step forward, or to say no, and for us to rally around so it’s easier for the next person. In the end, it’s not about the technology—it’s about the people. Dan Hon is principal of Very Little Gravitas, where he helps turn around and modernize large and complex government services and products.

In trying to make sense of the wrecking ball that is Elon Musk and President Trump’s DOGE, it may be helpful to think about the Evil Housekeeper Problem. It’s a principle of computer security roughly stating that once someone is in your hotel room with your laptop, all bets are off. Because the intruder has physical access, you are in much more trouble. And the person demanding to get into your computer may be standing right beside you.

So who is going to stop the evil housekeeper from plugging a computer in and telling IT staff to connect it to the network?

What happens if someone comes in and tells you that you’ll be fired unless you reveal the authenticator code from your phone, or sign off on a code change, or turn over your PIV card, the Homeland Security–approved smart card used to access facilities and systems and securely sign documents and emails? What happens if someone says your name will otherwise be published in an online list of traitors? Already the new administration is firing, putting on leave, or outright escorting from the building people who refuse to do what they’re told. 

It’s incredibly hard to protect a system from someone—the evil housekeeper from DOGE—who has made their way inside and wants to wreck it. This administration is on the record as wanting to outright delete entire departments. Accelerationists are not only setting policy but implementing it by working within the administration. If you can’t delete a department, then why not just break it until it doesn’t work? 

That’s why what DOGE is doing is a massive, terrifying problem, and one I talked through earlier in a thread on Bluesky

Government is built to be stable. Collectively, we put systems and rules in place to ensure that stability. But whether they actually deliver and preserve stability in the real world isn’t actually about the technology used; it’s about the people using it. When it comes down to it, technology is a tool to be used by humans for human ends. The software used to run our democratically elected government is deployed to accomplish goals tied to policies: collecting money from people, or giving money to states so they can give money to people who qualify for food stamps, or making covid tests available to people.

Usually, our experience of government technology is that it’s out of date or slow or unreliable. Certainly not as shiny as what we see in the private sector. And that technology changes very, very slowly, if it happens at all. 

It’s not as if people don’t realize these systems could do with modernization. In my experience troubleshooting and modernizing government systems in California and the federal government, I worked with Head Start, Medicaid, child welfare, and logistics at the Department of Defense. Some of those systems were already undergoing modernization attempts, many of which were and continue to be late, over budget, or just plain broken. But the changes that are needed to make other systems more modern were frequently seen as too risky or too expensive. In other words, not important enough. 

Of course, some changes are deemed important enough. The covid-19 pandemic and our unemployment insurance systems offer good examples. When covid hit, certain critical government technologies suddenly became visible. Those systems, like unemployment insurance portals, also became politically important, just like the launch of the Affordable Care Act website (which is why it got so much attention when it was botched). 

Political attention can change everything. During the pandemic, suddenly it wasn’t just possible to modernize and upgrade government systems, or to make them simpler, clearer, and faster to use. It actually happened. Teams were parachuted in. Overly restrictive rules and procedures were reassessed and relaxed. Suddenly, government workers were allowed to work remotely and to use Slack.

However, there is a reason this was an exception. 

In normal times, rules and procedures are certainly part of what makes it very, very hard to change government technology. But they are in place to stop changes because, well, changes might break those systems and government doesn’t work without them working consistently. 

A long time ago I worked on a mainframe system in California—the kind that uses COBOL. It was as solid as a rock and worked day in, day out. Because if it didn’t, and reimbursements weren’t received for Medicaid, then the state might become temporarily insolvent. 

That’s why many of the rules about technology in government make it hard to make changes: because sometimes the risk of things breaking is just too high. Sometimes what’s at stake is simply keeping money flowing; sometimes, as with 911, lives are on the line.

Still, government systems and the rules that govern them are ultimately only as good as the people who oversee and enforce them. The technology will only do (and not do) what people tell it to. So if anyone comes in and breaks those rules on purpose—without fear of consequence—there are few practical or technical guardrails to prevent it. 

One system that’s meant to do that is the ATO, or the Authority to Operate. It does what it says: It lets you run a computer system. You are not supposed to operate a system without one. 

But DOGE staffers are behaving in a way that suggests they don’t care about getting ATOs. And nothing is really stopping them. (Someone on Bluesky replied to me: “My first thought about the OPM [email] server was, “there’s no way those fuckers have an ATO.”) 

You might think that there would be technical measures to stop someone right out of high school from coming in and changing the code to a government system. That the system could require two-factor authentication to deploy the code to the cloud. That you would need a smart card to log in to a specific system to do that. Nope—all those technical measures can be circumvented by coercion at the hands of the evil housekeeper. 

Indeed, none of our systems and rules work without enforcement, and consequences flowing from that enforcement. But to an unprecedented degree, this administration, and its individual leaders, have shown absolutely no fear. That’s why, according to Wired, the former X and SpaceX engineer and DOGE staffer Marko Elez had the “ability not just to read but to write code on two of the most sensitive systems in the US government: the Payment Automation Manager and Secure Payment System at the Bureau of the Fiscal Service (BFS).” (Elez reportedly resigned yesterday after the Wall Street Journal began reporting on a series of racist comments he had allegedly made.)

We’re seeing in real time that there are no practical technical measures preventing someone from taking a spanner to the technology that keeps our government stable, that keeps society running every day—despite the very real consequences. 

So we should plan for the worst, even if the likelihood of the worst is low. 

We need a version of the UK government’s National Risk Register, covering everything from the collapse of financial markets to “an attack on government” (but, unsurprisingly, that risk is described in terms of external threats). The register mostly predicts long-term consequences, with recovery taking months. That may end up being the case here. 

We need to dust off those “in the event of an emergency” disaster response procedures dealing with the failure of federal government—at individual organizations that may soon hit cash-flow problems and huge budget deficits without federal funding, at statehouses that will need to keep social programs running, and in groups doing the hard work of archiving and preserving data and knowledge.

In the end, all we have is each other—our ability to form communities and networks to support, help, and care for each other. Sometimes all it takes is for the first person to step forward, or to say no, and for us to rally around so it’s easier for the next person. In the end, it’s not about the technology—it’s about the people.

Dan Hon is principal of Very Little Gravitas, where he helps turn around and modernize large and complex government services and products.

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Lenovo expands virtualization portfolio for AI

On the services front, Lenovo is restructuring its infrastructure deployment offerings around three defined service levels: Standard Deploy, Premier Deploy, and Premier Deploy Plus. The options are designed to allow customers to select a deployment model based on multiple factors, including project complexity, business criticality, internal IT capabilities and the

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Practical quantum computers are over a decade away, says NEC

A practical, commercial quantum computer is over a decade away, executives at Japanese IT services company NEC are reported as saying. That’s why, according to Japanese news publication The Mainichi, company has pulled the plug on its plans to develop a quantum computer — although it will still continue research

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Huawei aims to deliver faster AI chips, faster

Huawei is accelerating its AI chips development, bringing forward the release of the next two models in the family powering its AI computing clusters by three to nine months. Its Ascend 960 chip family is a major component of supercomputing portfolio. It now plans to release the Ascend 960DT in

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QatarEnergy NFE LNG Train 1 to start 1H 2027; Ras Laffan repairs to take 3 years

QatarEnergy expects the 8-million tonne/year (tpy) first train of its 32-million tpy North Field East (NFE) LNG expansion project to begin operations in first-half 2027, Reuters reported, noting that the timing of additional trains would depend on ​the Strait of Hormuz crisis. Speaking at the Qatar Economic Forum Special Edition in New York, QatarEnergy chief executive officer (CEO) and Qatari minister of energy affairs, Saad al-Kaabi, attributed the uncertainty to delays in delivering equipment needed for the expansion caused by the Strait of Hormuz disruption. Regarding damage to Qatar’s natural gas infrastructure sustained during the Iran war and its possible return, al-Kaabi said that repairs to the two LNG trains damaged at Ras Laffan (17% of its production capacity) would take 3 years. A damaged gas-to-liquids (GTL) train is expected to return to service first-quarter 2027. Al-Kaabi expects “a few” NFE trains to start production as 2027 progresses, and output from the 16-million tpy North Field South (NFS) expansion to begin in 2028, according to Reuters. The NFE and NFS projects are part of the overall North Field expansion program that also includes the North Field West project, which together will raise Qatar’s LNG production capacity to 142 million tpy from the current 77 million tpy. Al-Kaabi also thanked Qatar’s neighbors for being willing to allow construction of a gas pipeline across their territories to bypass Hormuz, while noting that doing so would be “redundant” and made “no economic sense” in light of the already underway North Field expansion project. “As for resuming operations,” he added, “Qatar is ready to resume normal operations within a few weeks of the reopening of the Strait of Hormuz.” More generally, al-Kaabi rejected the notion that the Strait of Hormuz was obsolete, saying that it “carries trade in all products, not only oil and

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ESENTIA to acquire Guadalajara-Manzanillo natural gas pipeline system

ESENTIA Energy Development SAB de CV, Mexico City, has agreed to acquire 100% of the equity interests of Energía Occidente de México S de RL de CV (EOM) from TC Energy Corp., Calgary, for a gross purchase price of $400 million. EOM owns and operates the 313-km Guadalajara-Manzanillo natural gas pipeline system, which runs from the Guadalajara area in Jalisco to Manzanillo, Colima, and is directly interconnected with ESENTIA’s Villa de Reyes-Aguascalientes-Guadalajara (VAG) pipeline system operated by Esentia Pipeline de Occidente S de RL de CV, an indirect subsidiary of ESENTIA. The pipeline transports up to 500 MMcfd of natural gas, connecting imported LNG supply near Manzanillo and continental gas supply near Guadalajara to power plants and industrial customers in Colima and Jalisco. Upon closing, the acquisition will extend ESENTIA’s pipeline network to the Port of Manzanillo on Mexico’s Pacific coast, making the company the only private operator with an integrated natural gas pipeline system connecting the Permian basin in Texas to Mexico’s Pacific coast, the company said in a release Sept. 21. The deal is part of ESENTIA’s strategy to build a cross-border transportation system and would “expand ESENTIA’s ability to serve existing and prospective customers within the combined system’s area of influence, including demand from power generation, industrial customers and potential LNG-related projects,” said Daniel Bustos, chief executive officer. ESENTIA also highlighted construction of its Aguascalientes Compression Station, which is expected to increase capacity on the VAG pipeline system beginning in early 2027. The project is part of the company’s three-phase expansion plan, which includes a total estimated investment of $680 million and an increase of 660 MMcfd in natural gas transportation capacity. For TC Energy, the transaction creates “optionality to redeploy proceeds from a mature asset towards high-value growth opportunities across our North American footprint,” said François

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Energy Department Announces $99 Million for 21 Projects to Advance U.S. Geothermal Energy Development

WASHINGTON—The U.S. Department of Energy (DOE) today announced more than $99 million for 21 projects selected to advance geothermal energy development across the United States. The projects will conduct field-scale tests of next-generation geothermal technologies and exploration drilling to characterize and potentially confirm promising geothermal resources.  Thanks to President Trump’s leadership, the Energy Department is advancing American geothermal innovation to unlock the nation’s abundant domestic energy resources. Geothermal can provide reliable, around-the-clock power to help meet growing demand while strengthening U.S. energy security. “These projects will empower American innovators to unlock the tremendous geothermal resources beneath our feet,” said DOE Under Secretary of Energy Kyle Haustveit. “Under President Trump’s leadership, we’re advancing next-generation geothermal technologies that can lower costs, strengthen American energy dominance, and turn more of our vast domestic geothermal resources into reliable and affordable power.” The 21 projects will advance geothermal development in two key areas. Five projects will conduct field-scale enhanced geothermal systems (EGS) tests to validate technologies under real-world conditions, while 16 additional projects will conduct exploration drilling to identify and characterize promising next-generation geothermal resources. Together, these efforts will help reduce technical and development risk and provide the information needed to support future commercial projects and investment.   Data generated by these projects will be publicly available through DOE’s Geothermal Data Repository (GDR), giving industry, researchers, and other stakeholders access to information from the field tests and geothermal exploration activities. Making these data available can extend the value of the projects beyond individual sites by helping inform future technology development and geothermal exploration across the industry.  Learn more about the selected projects here.  Selection for award negotiations is not a commitment by DOE to issue an award or provide funding. Before funding is issued, DOE and the applicants will undergo a negotiation process, and DOE may cancel negotiations and rescind the

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INA commissions new delayed coker at Rijeka refinery

Croatia’s INA Industrija Nafte DD has started up a new delayed coking unit (DCU) at its 90,000-b/d Rijeka refinery along the northern part of the Adriatic Sea, marking a major milestone in the refinery’s upgrading project. Following mechanical completion and commissioning, INA introduced feedstock into the DCU on Sept. 1, beginning production, majority owner MOL Group said in a release Sept. 21. The unit has operated continuously since startup and has reached about 70% of design capacity, the company said. The DCU—which  converts heavy refinery residues into higher-value products—has produced all key products at required quality and is anticipated to increase diesel production by as much as 30% from the same crude volume. MOL Group said the new DCU unit—once fully operable—also will eliminate Croatia’s need to import vacuum gas oil (VGO). The Rijeka refinery upgrade represents an investment of nearly €700 million, which is included in a combined €1.3-billion joint investment by INA and MOL Group in refining and logistics modernization during the past 12 years. “The start-up of the new unit went really well,” said Zsuzsanna Ortutay, president of INA’s management board, adding that the DCU would improve the sustainability and profitability of INA’s refining business while supporting energy supply in Croatia and the surrounding region. INA  plans to increase throughput and optimize process performance at the new unit gradually, with stable operation anticipated by yearend, followed by final plant performance testing and project closeout activities. Rijeka DCU project background INA awarded a lump-sum, turnkey engineering, procurement, and construction contract for the project to Maire Tecnimont SPA subsidiary KT-Kinetics Technology SPA in December 2019. The contract covered a new delayed coking complex with coke handling and ship-loading facilities, a sour-water stripper, and amine recovery units. It also included modifications to the existing hydrocracker, sulfur recovery unit, utilities, and

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Oil prices retreat as Middle East supply concerns ease amid diplomatic talks

Oil prices fell on Monday, Sept.21, with Brent extending its retreat from recent highs, as recovering Saudi crude exports and hopes for renewed US-Iran diplomacy eased fears of an immediate Middle East supply crunch. Brent crude futures and US West Texas Intermediate (WTI) crude dipped below $100/bbl to their lowest since Sept. 9. The move extends a four-session retreat from the recent surge in crude prices as traders reassess how severely regional conflict is constraining physical oil flows. Despite the continued uncertainty in the Middle East, news of a major rebound in Saudi crude oil exports in September weighed on prices. Saudi Arabia has increased shipments through the Strait of Hormuz to compensate for disruptions to its East-West pipeline following Houthi attacks on Saudi energy infrastructure. Saudi crude flows through the strait have averaged roughly 2.9 million b/d over the past 6 days, compared with about 700,000 b/d in August, according to satellite data cited by JPMorgan analysts. US Central Command Commander Admiral Brad Cooper confirmed on Sept.19 that, thanks to US naval escorts and mine-clearance efforts, oil and LNG shipments through the Strait of Hormuz in the past 2 weeks reached the highest level in 6 months. The recovery in Gulf exports has helped ease fears that attacks on Saudi infrastructure would translate into a prolonged loss of barrels from the global market. Meanwhile, investors are closely monitoring signs of potential diplomatic progress between Washington and Tehran during this week’s UN General Assembly. US President Donald Trump has expressed a willingness to meet with Iranian President Masoud Pezeshkian, while Iran has reportedly conveyed the conditions for resuming negotiations. Expectations that talks could eventually reduce regional tensions have removed some of the geopolitical risk premium that pushed crude prices higher earlier this month. Still, physical oil markets remain strained. Middle Eastern producers

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Trump Administration Moves to Keep Indiana Coal Plants Operating to Support Grid Reliability

WASHINGTON—U.S. Secretary of Energy Chris Wright issued emergency orders to keep two Indiana coal plants operational to ensure Americans in the Midwest region of the United States have continued access to affordable, reliable, and secure electricity. The orders direct the Northern Indiana Public Service Company (NIPSCO), CenterPoint Energy, and the Midcontinent Independent System Operator, Inc. (MISO) to take all measures necessary to ensure specified generation units at both the R.M. Schahfer and F.B. Culley generating stations in Indiana are available to operate. Certain generation units at these coal plants were scheduled to shut down at the end of 2025.  The orders will minimize the risk of unnecessary blackouts for the American people. Since the U.S. Department of Energy’s (DOE) original orders were issued on December 23, 2025, the Schahfer and Culley coal plants have proven critical to MISO’s operations, operating during periods of high energy demand and low levels of intermittent energy production, including during Winter Storm Fern.   “Forcing reliable, dispatchable coal generation off the grid would compromise energy reliability and needlessly raises energy costs for Americans,” said Energy Secretary Wright. “Midwestern families should not be forced to pay the price for the misguided energy subtraction policies of the past. They deserve affordable, reliable, and secure energy, regardless of the wind blowing or the sun shining.” Thanks to President Trump’s leadership, coal generating plants across the country are being saved from premature retirement. For example, in 2025, more than 17 gigawatts of coal power electricity generation were saved from going offline.  The availability of R.M. Schahfer and F.B. Culley generating stations to operate will continue to be an asset to maintain reliability in the MISO region and is necessary to address elevated reliability risks in that region during extreme weather and reduce the risk of power outages that could threaten public health and safety. As

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Executive Roundtable: AI Infrastructure Under Pressure

Matt Vincent is Editor in Chief of Data Center Frontier, where he leads editorial strategy and coverage focused on the infrastructure powering cloud computing, artificial intelligence, and the digital economy. A veteran B2B technology journalist with more than two decades of experience, Vincent specializes in the intersection of data centers, power, cooling, and emerging AI-era infrastructure. Since assuming the EIC role in 2023, he has helped guide Data Center Frontier’s coverage of the industry’s transition into the gigawatt-scale AI era, with a focus on hyperscale development, behind-the-meter power strategies, liquid cooling architectures, and the evolving energy demands of high-density compute, while working closely with the Digital Infrastructure Group at Endeavor Business Media to expand the brand’s analytical and multimedia footprint. Vincent also hosts The Data Center Frontier Show podcast, where he interviews industry leaders across hyperscale, colocation, utilities, and the data center supply chain to examine the technologies and business models reshaping digital infrastructure. Since its inception he serves as Head of Content for the Data Center Frontier Trends Summit. Before becoming Editor in Chief, he served in multiple senior editorial roles across Endeavor Business Media’s digital infrastructure portfolio, with coverage spanning data centers and hyperscale infrastructure, structured cabling and networking, telecom and datacom, IP physical security, and wireless and Pro AV markets. He began his career in 2005 within PennWell’s Advanced Technology Division and later held senior editorial positions supporting brands such as Cabling Installation & Maintenance, Lightwave Online, Broadband Technology Report, and Smart Buildings Technology. Vincent is a frequent moderator, interviewer, and keynote speaker at industry events including the HPC Forum, where he delivers forward-looking analysis on how AI and high-performance computing are reshaping digital infrastructure. He graduated with honors from Indiana University Bloomington with a B.A. in English Literature and Creative Writing and lives in southern New Hampshire with

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California joins US states clamping down on data center gold rush

“Dismissing fears around water consumption, for example, by showing a spreadsheet at a local planning committee meeting, doesn’t resolve concerns for a community that is already suspicious,” he said. Community opposition “is real, and it’s everywhere,” and the new strategic pillar for data center builders and operators is social outreach, Kimball noted. Those proposing data centers must be able to provide credible answers about usage and community impacts, listen to concerns, and commit to transparency. Most enterprises aren’t building gigawatt campuses, he pointed out, but they are paying the price downstream in colocation availability, lead times, pricing, and other factors. Predictability is the big question, supply is already tight, and every delayed project removes capacity factored into forecasts.

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Communities are blocking data centers before they’re even proposed

“Dismissing fears around water consumption, for example, by showing a spreadsheet at a local planning committee meeting, doesn’t resolve concerns for a community that is already suspicious,” he said. Community opposition “is real, and it’s everywhere,” and the new strategic pillar for data center builders and operators is social outreach, Kimball noted. Those proposing data centers must be able to provide credible answers about usage and community impacts, listen to concerns, and commit to transparency. Most enterprises aren’t building gigawatt campuses, he pointed out, but they are paying the price downstream in colocation availability, lead times, pricing, and other factors. Predictability is the big question, supply is already tight, and every delayed project removes capacity factored into forecasts.

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Data Centre West 2026: Alberta Moves From Data Center Ambition to Execution

Firm Power Is an Architecture That brought the morning back to its recurring problem: What counts as available power? During the “Solving for Power” panel, moderator Lillian Kasa of Metlen Energy & Metals argued that data centers cannot operate on announcements. They need reliable electricity delivered on a schedule and backed by a commercial structure that can be financed. Margarita Patria of Charles River Associates made the distinction even sharper. Firm power is not merely generation. It is generation, transmission and fuel availability working together. Todd Detling of FortisAlberta added an important Alberta-specific qualification. Despite perceptions that the province had substantial transmission capacity available for new development, FortisAlberta is encountering constraints, particularly around the Edmonton and Calgary fringes. At the distribution level, the demand is already material. Detling said FortisAlberta has connected nearly 80 MW of data center load over the past several years, has approximately another 80 MW in the build queue, and has received roughly 300 MW in additional requests. Those smaller increments matter in a market dominated rhetorically by gigawatt announcements. They are another indication that developers are searching for power pathways they can execute now. AI Is Not Just a Bigger Load Tesla’s Sean Jones added another technical wrinkle: AI training loads can change extremely quickly. Data center power planning traditionally focuses heavily on annual consumption, peak demand and hourly load. GPU clusters can create significant changes at the second or even sub-second level. Jones described AI training demand falling from full load to around 30% in less than a second. That kind of movement can be difficult for onsite turbines and reciprocating generators to follow and potentially disruptive to the grid. Battery energy storage is therefore taking on a different role. The familiar data center battery story is backup power. The emerging AI story is

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Local AI is getting small enough to make every app multilingual

On-device translation used to mean a separate model for every language you wanted to support. English to French, English to German, and so on. However, that becomes unsustainable at a global scale when you’re talking about thousands of possible language pairs. Add to that the fact that most developers have to either send translation requests to the cloud to get fast, accurate results, or keep it local with restricted language support. Tether’s AI Research team has developed a family of multilingual translation models, TranslatePsy-EuroNano, that each support nine European languages, with deployment built around a pair of multilingual models rather than separate bilingual models for every language pair. What makes this possible Supporting a full European market on-device has previously meant bundling dozens of separate model files, but this is impractical for mobile apps and those building them. Tether AI’s multilingual open‑source edge translation models set the standard for efficiency, quality, and speed. For developers, the possibilities are endless. Using English as a pivot, the models remain comparable to Mozilla Firefox’s Bergamot-based translation system while dramatically reducing the size of on-device translation. At its smallest tier, Tether’s deployment is 17.6 times smaller while maintaining comparable translation quality. Tether’s deployment takes up 36MB to 89MB, depending on the tier you use. By comparison, the equivalent Firefox setup requires 18 separate bilingual models totaling 633MB to provide the same language coverage. The models are small enough to run efficiently on edge devices while supporting nine European languages from a single multilingual deployment, making multilingual experiences practical for a much wider range of software. Potential applications include travel and navigation apps, educational platforms that present lessons and resources on-device. The models are also designed for academics and researchers. Because the weights are openly available, researchers can fine-tune them for specialized domains, like customer

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AI Infrastructure Is Redrawing the Data Center Services Landscape

For gigawatt-scale AI developments, the developer may be involved with substations, transmission interconnections, generation plants, batteries or other behind-the-meter infrastructure long before servers arrive. Solaris now describes its overall portfolio as including generation, distribution, installation and commissioning, aftermarket support, and operations and maintenance. The arrival of companies with roots in energy and heavy industrial services suggests that the data center supplier base itself is changing as projects begin to resemble large industrial infrastructure developments. The Pattern Extends Across the Services Stack The transactions involving T5, Limbach, JK Technology Services and Solaris are hardly isolated. A wider wave of acquisitions and partnerships is pushing equipment manufacturers, contractors, engineering firms and specialist service providers toward broader roles across the data center lifecycle. Vertiv provided perhaps the clearest parallel in September, announcing an agreement to acquire UtilityInnovation Group for approximately $1.45 billion in cash, with additional consideration tied to performance. UIG brings microgrid controls, onsite-generation orchestration, specialized switchgear and behind-the-meter power architecture. The deal also extends a broader 2026 acquisition push by Vertiv that has added liquid-cooling specialist Strategic Thermal Labs, chiller manufacturer ThermoKey and prefabricated infrastructure provider Bmarko as the company builds out more of the AI data center infrastructure stack. Vertiv described the move as extending its portfolio upstream from the critical power and cooling systems inside the facility toward the grid interconnection and onsite generation itself — effectively creating a path from power source to chip. Days later, Flex announced a $4.4 billion agreement to acquire EPC Power, adding grid-forming and power-conversion technology designed for data centers, utility-scale energy storage and microgrids. EPC Power’s platform includes rectifiers and DC-DC conversion for emerging 800-volt data center architectures, with solid-state transformer development also planned. The company says it has more than 15 GW deployed across 62 countries and expects its annual U.S.

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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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