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A new Microsoft chip could lead to more stable quantum computers

Microsoft announced today that it has made significant progress in its 20-year quest to make topological quantum bits, or qubits—a special approach to building quantum computers that could make them more stable and easier to scale up.  Researchers and companies have been working for years to build quantum computers, which could unlock dramatic new abilities to simulate complex materials and discover new ones, among many other possible applications.  To achieve that potential, though, we must build big enough systems that are stable enough to perform computations. Many of the technologies being explored today, such as the superconducting qubits pursued by Google and IBM, are so delicate that the resulting systems need to have many extra qubits to correct errors.  Microsoft has long been working on an alternative that could cut down on the overhead by using components that are far more stable. These components, called Majorana quasiparticles, are not real particles. Instead, they are special patterns of behavior that may arise inside certain physical systems and under certain conditions. The pursuit has not been without setbacks, including a high-profile paper retraction by researchers associated with the company in 2018. But the Microsoft team, which has since pulled this research effort in house, claims it is now on track to build a fault-tolerant quantum computer containing a few thousand qubits in a matter of years and that it has a blueprint for building out chips that each contain a million qubits or so, a rough target that could be the point at which these computers really begin to show their power. This week the company announced a few early successes on that path: piggybacking on a Nature paper published today that describes a fundamental validation of the system, the company says it has been testing a topological qubit, and that it has wired up a chip containing eight of them.  “You don’t get to a million qubits without a lot of blood, sweat, and tears and solving a lot of really difficult technical challenges along the way. And I do not want to understate any of that,” says Chetan Nayak, a Microsoft technical fellow and leader of the team pioneering this approach. That said, he says, “I think that we have a path that we very much believe in, and we see a line of sight.”  Researchers outside the company are cautiously optimistic. “I’m very glad that [this research] seems to have hit a very important milestone,” says computer scientist Scott Aaronson, who heads the ​​Quantum Information Center at the University of Texas at Austin. “I hope that this stands, and I hope that it’s built up.” Even and odd The first step in building a quantum computer is constructing qubits that can exist in fragile quantum states—not 0s and 1s like the bits in classical computers, but rather a mixture of the two. Maintaining qubits in these states and linking them up with one another is delicate work, and over the years a significant amount of research has gone into refining error correction schemes to make up for noisy hardware.  For many years, theorists and experimentalists alike have been intrigued by the idea of creating topological qubits, which are constructed through mathematical twists and turns and have protection from errors essentially baked into their physics. “It’s been such an appealing idea to people since the early 2000s,” says Aaronson. “The only problem with it is that it requires, in a sense, creating a new state of matter that’s never been seen in nature.” Microsoft has been on a quest to synthesize this state, called a Majorana fermion, in the form of quasiparticles. The Majorana was first proposed nearly 90 years ago as a particle that is its own antiparticle, which means two Majoranas will annihilate when they encounter one another. With the right conditions and physical setup, the company has been hoping to get behavior matching that of the Majorana fermion within materials. In the last few years, Microsoft’s approach has centered on creating a very thin wire or “nanowire” from indium arsenide, a semiconductor. This material is placed in close proximity to aluminum, which becomes a superconductor close to absolute zero, and can be used to create superconductivity in the nanowire. Ordinarily you’re not likely to find any unpaired electrons skittering about in a superconductor—electrons like to pair up. But under the right conditions in the nanowire, it’s theoretically possible for an electron to hide itself, with each half hiding at either end of the wire. If these complex entities, called Majorana zero modes, can be coaxed into existence, they will be difficult to destroy, making them intrinsically stable.  ”Now you can see the advantage,” says Sankar Das Sarma, a theoretical physicist at the University of Maryland, College Park, who did early work on this concept. “You cannot destroy a half electron, right? If you try to destroy a half electron, that means only a half electron is left. That’s not allowed.” In 2023, the Microsoft team published a paper in the journal Physical Review B claiming that this system had passed a specific protocol designed to assess the presence of Majorana zero modes. This week in Nature, the researchers reported that they can “read out” the information in these nanowires—specifically, whether there are Majorana zero modes hiding at the wires’ ends. If there are, that means the wire has an extra, unpaired electron. “What we did in the Nature paper is we showed how to measure the even or oddness,” says Nayak. “To be able to tell whether there’s 10 million or 10 million and one electrons in one of these wires.” That’s an important step by itself, because the company aims to use those two states—an even or odd number of electrons in the nanowire—as the 0s and 1s in its qubits.  If these quasiparticles exist, it should be possible to “braid” the four Majorana zero modes in a pair of nanowires around one another by making specific measurements in a specific order. The result would be a qubit with a mix of these two states, even and odd. Nayak says the team has done just that, creating a two-level quantum system, and that it is currently working on a paper on the results. Researchers outside the company say they cannot comment on the qubit results, since that paper is not yet available. But some have hopeful things to say about the findings published so far. “I find it very encouraging,” says Travis Humble, director of the Quantum Science Center at Oak Ridge National Laboratory in Tennessee. “It is not yet enough to claim that they have created topological qubits. There’s still more work to be done there,” he says. But “this is a good first step toward validating the type of protection that they hope to create.”  Others are more skeptical. Physicist Henry Legg of the University of St Andrews in Scotland, who previously criticized Physical Review B for publishing the 2023 paper without enough data for the results to be independently reproduced, is not convinced that the team is seeing evidence of Majorana zero modes in its Nature paper. He says that the company’s early tests did not put it on solid footing to make such claims. “The optimism is definitely there, but the science isn’t there,” he says. One potential complication is impurities in the device, which can create conditions that look like Majorana particles. But Nayak says the evidence has only grown stronger as the research has proceeded. “This gives us confidence: We are manipulating sophisticated devices and seeing results consistent with a Majorana interpretation,” he says. “They have satisfied many of the necessary conditions for a Majorana qubit, but there are still a few more boxes to check,” Das Sarma said after seeing preliminary results on the qubit. “The progress has been impressive and concrete.” Scaling up On the face of it, Microsoft’s topological efforts seem woefully behind in the world of quantum computing—the company is just now working to combine qubits in the single digits while others have tied together more than 1,000. But both Nayak and Das Sarma say other efforts had a strong head start because they involved systems that already had a solid grounding in physics. Work on the topological qubit, on the other hand, has meant starting from scratch.  “We really were reinventing the wheel,” Nayak says, likening the team’s efforts to the early days of semiconductors, when there was so much to sort out about electron behavior and materials, and transistors and integrated circuits still had to be invented. That’s why this research path has taken almost 20 years, he says: “It’s the longest-running R&D program in Microsoft history.” Some support from the US Defense Advanced Research Projects Agency could help the company catch up. Early this month, Microsoft was selected as one of two companies to continue work on the design of a scaled-up system, through a program focused on underexplored approaches that could lead to utility-scale quantum computers—those whose benefits exceed their costs. The other company selected is PsiQuantum, a startup that is aiming to build a quantum computer containing up to a million qubits using photons. Many of the researchers MIT Technology Review spoke with would still like to see how this work plays out in scientific publications, but they were hopeful. “The biggest disadvantage of the topological qubit is that it’s still kind of a physics problem,” says Das Sarma. “If everything Microsoft is claiming today is correct … then maybe right now the physics is coming to an end, and engineering could begin.”  This story was updated with Henry Legg’s current institutional affiliation.

Microsoft announced today that it has made significant progress in its 20-year quest to make topological quantum bits, or qubits—a special approach to building quantum computers that could make them more stable and easier to scale up. 

Researchers and companies have been working for years to build quantum computers, which could unlock dramatic new abilities to simulate complex materials and discover new ones, among many other possible applications. 

To achieve that potential, though, we must build big enough systems that are stable enough to perform computations. Many of the technologies being explored today, such as the superconducting qubits pursued by Google and IBM, are so delicate that the resulting systems need to have many extra qubits to correct errors. 

Microsoft has long been working on an alternative that could cut down on the overhead by using components that are far more stable. These components, called Majorana quasiparticles, are not real particles. Instead, they are special patterns of behavior that may arise inside certain physical systems and under certain conditions.

The pursuit has not been without setbacks, including a high-profile paper retraction by researchers associated with the company in 2018. But the Microsoft team, which has since pulled this research effort in house, claims it is now on track to build a fault-tolerant quantum computer containing a few thousand qubits in a matter of years and that it has a blueprint for building out chips that each contain a million qubits or so, a rough target that could be the point at which these computers really begin to show their power.

This week the company announced a few early successes on that path: piggybacking on a Nature paper published today that describes a fundamental validation of the system, the company says it has been testing a topological qubit, and that it has wired up a chip containing eight of them. 

“You don’t get to a million qubits without a lot of blood, sweat, and tears and solving a lot of really difficult technical challenges along the way. And I do not want to understate any of that,” says Chetan Nayak, a Microsoft technical fellow and leader of the team pioneering this approach. That said, he says, “I think that we have a path that we very much believe in, and we see a line of sight.” 

Researchers outside the company are cautiously optimistic. “I’m very glad that [this research] seems to have hit a very important milestone,” says computer scientist Scott Aaronson, who heads the ​​Quantum Information Center at the University of Texas at Austin. “I hope that this stands, and I hope that it’s built up.”

Even and odd

The first step in building a quantum computer is constructing qubits that can exist in fragile quantum states—not 0s and 1s like the bits in classical computers, but rather a mixture of the two. Maintaining qubits in these states and linking them up with one another is delicate work, and over the years a significant amount of research has gone into refining error correction schemes to make up for noisy hardware. 

For many years, theorists and experimentalists alike have been intrigued by the idea of creating topological qubits, which are constructed through mathematical twists and turns and have protection from errors essentially baked into their physics. “It’s been such an appealing idea to people since the early 2000s,” says Aaronson. “The only problem with it is that it requires, in a sense, creating a new state of matter that’s never been seen in nature.”

Microsoft has been on a quest to synthesize this state, called a Majorana fermion, in the form of quasiparticles. The Majorana was first proposed nearly 90 years ago as a particle that is its own antiparticle, which means two Majoranas will annihilate when they encounter one another. With the right conditions and physical setup, the company has been hoping to get behavior matching that of the Majorana fermion within materials.

In the last few years, Microsoft’s approach has centered on creating a very thin wire or “nanowire” from indium arsenide, a semiconductor. This material is placed in close proximity to aluminum, which becomes a superconductor close to absolute zero, and can be used to create superconductivity in the nanowire.

Ordinarily you’re not likely to find any unpaired electrons skittering about in a superconductor—electrons like to pair up. But under the right conditions in the nanowire, it’s theoretically possible for an electron to hide itself, with each half hiding at either end of the wire. If these complex entities, called Majorana zero modes, can be coaxed into existence, they will be difficult to destroy, making them intrinsically stable. 

”Now you can see the advantage,” says Sankar Das Sarma, a theoretical physicist at the University of Maryland, College Park, who did early work on this concept. “You cannot destroy a half electron, right? If you try to destroy a half electron, that means only a half electron is left. That’s not allowed.”

In 2023, the Microsoft team published a paper in the journal Physical Review B claiming that this system had passed a specific protocol designed to assess the presence of Majorana zero modes. This week in Nature, the researchers reported that they can “read out” the information in these nanowires—specifically, whether there are Majorana zero modes hiding at the wires’ ends. If there are, that means the wire has an extra, unpaired electron.

“What we did in the Nature paper is we showed how to measure the even or oddness,” says Nayak. “To be able to tell whether there’s 10 million or 10 million and one electrons in one of these wires.” That’s an important step by itself, because the company aims to use those two states—an even or odd number of electrons in the nanowire—as the 0s and 1s in its qubits. 

If these quasiparticles exist, it should be possible to “braid” the four Majorana zero modes in a pair of nanowires around one another by making specific measurements in a specific order. The result would be a qubit with a mix of these two states, even and odd. Nayak says the team has done just that, creating a two-level quantum system, and that it is currently working on a paper on the results.

Researchers outside the company say they cannot comment on the qubit results, since that paper is not yet available. But some have hopeful things to say about the findings published so far. “I find it very encouraging,” says Travis Humble, director of the Quantum Science Center at Oak Ridge National Laboratory in Tennessee. “It is not yet enough to claim that they have created topological qubits. There’s still more work to be done there,” he says. But “this is a good first step toward validating the type of protection that they hope to create.” 

Others are more skeptical. Physicist Henry Legg of the University of St Andrews in Scotland, who previously criticized Physical Review B for publishing the 2023 paper without enough data for the results to be independently reproduced, is not convinced that the team is seeing evidence of Majorana zero modes in its Nature paper. He says that the company’s early tests did not put it on solid footing to make such claims. “The optimism is definitely there, but the science isn’t there,” he says.

One potential complication is impurities in the device, which can create conditions that look like Majorana particles. But Nayak says the evidence has only grown stronger as the research has proceeded. “This gives us confidence: We are manipulating sophisticated devices and seeing results consistent with a Majorana interpretation,” he says.

“They have satisfied many of the necessary conditions for a Majorana qubit, but there are still a few more boxes to check,” Das Sarma said after seeing preliminary results on the qubit. “The progress has been impressive and concrete.”

Scaling up

On the face of it, Microsoft’s topological efforts seem woefully behind in the world of quantum computing—the company is just now working to combine qubits in the single digits while others have tied together more than 1,000. But both Nayak and Das Sarma say other efforts had a strong head start because they involved systems that already had a solid grounding in physics. Work on the topological qubit, on the other hand, has meant starting from scratch. 

“We really were reinventing the wheel,” Nayak says, likening the team’s efforts to the early days of semiconductors, when there was so much to sort out about electron behavior and materials, and transistors and integrated circuits still had to be invented. That’s why this research path has taken almost 20 years, he says: “It’s the longest-running R&D program in Microsoft history.”

Some support from the US Defense Advanced Research Projects Agency could help the company catch up. Early this month, Microsoft was selected as one of two companies to continue work on the design of a scaled-up system, through a program focused on underexplored approaches that could lead to utility-scale quantum computers—those whose benefits exceed their costs. The other company selected is PsiQuantum, a startup that is aiming to build a quantum computer containing up to a million qubits using photons.

Many of the researchers MIT Technology Review spoke with would still like to see how this work plays out in scientific publications, but they were hopeful. “The biggest disadvantage of the topological qubit is that it’s still kind of a physics problem,” says Das Sarma. “If everything Microsoft is claiming today is correct … then maybe right now the physics is coming to an end, and engineering could begin.” 

This story was updated with Henry Legg’s current institutional affiliation.

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AI and greed cause a massive spike in memory prices

TrendForce says that as of 2Q25, HBM3e still commanded a price premium more than four times that of DDR5, so it’s hard to fault the memory manufacturers for wanting to make a buck. However, as DDR5 prices continue to rise, the gap between the two is projected to narrow significantly

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Oil Falls as Saudi Price Cuts Signal Market Gloom

Oil extended declines after Saudi Arabia lowered the prices of its crude, signaling uncertainty surrounding the supply outlook, while equities slumped in another pressure on the commodity. West Texas Intermediate settled near $59, sliding around 0.3% on the day after falling in the previous two sessions. Volatility hit Wall Street, also weighing on oil prices. Saudi Arabia lowered the price of its main oil grade to Asia for December to the lowest level in 11 months. Even though the price cut met expectations, traders saw it as a bearish signal about the cartel’s confidence in the market’s ability to absorb new supply, with a glut widely expected to begin next year. Prices have given up ground since the US sanctioned Russia’s two largest oil producers last month over Moscow’s war in Ukraine, and abundant supplies have so far managed to cushion the impact of stunted flows from the OPEC+ member to major buyers India and China. Key price gauges indicate that supply perceptions are worsening, with the premium that front-month WTI futures command over the next month’s contract, known as the prompt spread, narrowing in the past few weeks to near February lows. That’s also true for Brent crude. Still, US shale companies are forging ahead with their production plans, with Diamondback Energy Inc., Coterra Energy Inc. and Ovintiv Inc. this week announcing they inend to raise output slightly for this year or 2026 despite oil prices falling close to the threshold needed for many US shale wells to break even. Oversupply gloom hasn’t permeated refined products markets, though. Traders are still assessing how those supplies may be impacted by the US clampdown on purchases of Russian crude and Ukraine’s strikes on its neighbor’s energy assets. Those factors, as well as diminishing global refining capacity, bolstered diesel futures and gasoil

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Clearway projects strong renewables outlook while adding gas assets

300 MW Average size of Clearway’s current projects. Most of the projects slated for 2030 and beyond are 500 MW or more, the company said.  >90% Percentage of projects planned for 2031-2032 that are focused in the Western U.S or the PJM Interconnection, “where renewables are cost competitive and/or valued.” 1.8 GW Capacity of power purchase agreements meant to support data center loads the company has signed so far this year. Meeting digital infrastructure energy needs Independent power producer Clearway Energy announced a U.S. construction pipeline of 27 GW of generation and storage resources following strong third-quarter earnings. The San Francisco-based company is owned by Global Infrastructure Partners and TotalEnergies. According to its earnings presentation, it has an operating portfolio of more than 12 GW of wind, solar, gas and storage.   Clearway President and CEO Craig Cornelius said on an earnings call Tuesday that the company is positioning itself to serve large load data centers.  “Growth in both the medium and long term reflects the strong traction we’ve made in supporting the energy needs of our country’s digital infrastructure build-out and reindustrialization,” Cornelius said during the call. “We expect this to be a core driver of Clearway’s growth outlook well into the 2030s.” Cornelius noted that Clearway executed and awarded 1.8 GW of power purchase agreements meant to support data center loads so far this year, and is currently developing generation aimed at serving “gigawatt class co-located data centers across five states.” Its 27 GW pipeline of projects in development or under construction includes 8.2 GW of solar, 4.6 GW of wind, 1.3 GW of wind repowering, 8 GW of standalone storage, 2.1 GW of paired storage and 2.6 GW of natural gas aimed at serving data centers. Under the OBBBA, wind and solar projects that begin construction by July 4,

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USA Crude Oil Stocks Rise More Than 5MM Barrels WoW

U.S. commercial crude oil inventories, excluding those in the Strategic Petroleum Reserve (SPR) increased by 5.2 million barrels from the week ending October 24 to the week ending October 31. That’s what the U.S. Energy Information Administration (EIA) highlighted in its latest weekly petroleum status report, which was released on November 5 and included data for the week ending October 31. The EIA report showed that crude oil stocks, not including the SPR, stood at 421.2 million barrels on October 31, 416.0 million barrels on October 24, and 427.7 million barrels on November 1, 2024. Crude oil in the SPR stood at 409.6 million barrels on October 31, 409.1 million barrels on October 24, and 387.2 million barrels on November 1, 2024, the report highlighted. Total petroleum stocks – including crude oil, total motor gasoline, fuel ethanol, kerosene type jet fuel, distillate fuel oil, residual fuel oil, propane/propylene, and other oils – stood at 1.679 billion barrels on October 31, the report revealed. Total petroleum stocks were up 1.1 million barrels week on week and up 44.5 million barrels year on year, the report showed. “At 421.2 million barrels, U.S. crude oil inventories are about four percent below the five year average for this time of year,” the EIA said in its latest weekly petroleum status report. “Total motor gasoline inventories decreased by 4.7 million barrels from last week and are about five percent below the five year average for this time of year. Both finished gasoline and blending components inventories decreased last week,” it added. “Distillate fuel inventories decreased by 0.6 million barrels last week and are about nine percent below the five year average for this time of year. Propane/propylene inventories increased by 0.4 million barrels from last week and are 15 percent above the five year average

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Energy Transfer Bags 20-Year Deal to Deliver Gas for Entergy Louisiana

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SRP to Convert Unit 4 of SGS Station in Arizona to Use Gas

Three of the four units at the coal-fired Springerville Generation Station (SGS) in Arizona will shift to natural gas in the early 2030s. This week Salt River Project’s (SRP) board approved the conversion of Unit 4. Earlier this year Tucson Electric Power (TEP), which operates all four units, said it will convert Units 1 and 2. Unit 3, owned by the Tri-State Generation and Transmission Association, is set to be retired. “Today’s decision is the lowest-cost option to preserve the plant’s 400-megawatt (MW) generating capacity, enough to serve 90,000 homes, which is important to meeting the Valley’s growing power need in the early 2030s”, SRP said in a statement on its website. “Converting SGS Unit 4 to run on natural gas is expected to save SRP customers about $45 million compared to building a new natural gas facility and about $826 million relative to adding new long-duration lithium-ion batteries over the same period”, the public power utility added. “The decision also provides a bridge to the mid-2040s, when other generating technology options, including advanced nuclear, are mature”. Gas for the converted Unit 4 will come from a new pipeline that SRP will build. The pipeline will also supply gas to the Coronado Generating Station (CGS). On June 24 SRP announced board approval for the conversion of CGS from coal to gas. “SRP is working to more than double the capacity of its power system in the next 10 years while maintaining reliability and affordability and making continued progress toward our sustainability goals”, SRP said. “SRP will accomplish this through an all-of-the-above approach that plans to add renewables in addition to natural gas and storage resources”.  SRP currently supplies 3,000 MW of “carbon-free energy” including over 1,500 MW of solar, with nearly 1,300 MW of battery and pumped hydro storage supporting its

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Libya NOC Announces New Oil Find

In a statement posted on its Facebook page this week, which was translated, Libya’s National Oil Corporation announced the discovery of oil in the Ghaddams basin. “The National Oil Corporation announced the discovery of a new oil for the Gulf Arab Oil Company in Al-Beer H1 – MN 4 (H1-NC4) located in the Ghadams Al-Rasoubi basin,” the translated statement said. “The daily production of this well is estimated at 4,675 barrels per day of crude oil, and about two million cubic feet of gas,” it added. In the statement, the National Oil Corporation highlighted that the project is 100 percent owned by the corporation. In a statement posted on its website on October 29, Libya’s National Oil Corporation announced a new oil discovery in the Sirte Basin. “The National Oil Corporation (NOC) has announced a new oil discovery by OMV Austria Ltd. – Libya Branch in the Sirte Basin, specifically at well B1 in Block 106/4,” the National Oil Corporation said in that statement. “Production tests show that this exploratory well, reaching a depth of 10,476 feet, is producing over 4,200 barrels of oil per day, with gas production expected to exceed 2.6 million cubic feet daily,” it added. “This well marks the first discovery for OMV in Block 106/4, under the Exploration and Production Sharing Agreement (EPSA) signed in 2008 between the NOC, as the owner, and OMV, as the operator,” Libya’s National Oil Corporation pointed out. When Rigzone asked OMV for comment on this statement, an OMV spokesperson directed Rigzone to an OMV post on LinkedIn about the discovery. “OMV has safely completed an onshore exploration well in the Contract Area 106/4 (EPSA C103) of Libya’s Sirte Basin,” OMV noted in that post. “The well, drilled in the ‘Essar’ prospect, encountered oil-bearing formations with estimated contingent recoverable volumes

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Top network and data center events 2025 & 2026

Denise Dubie is a senior editor at Network World with nearly 30 years of experience writing about the tech industry. Her coverage areas include AIOps, cybersecurity, networking careers, network management, observability, SASE, SD-WAN, and how AI transforms enterprise IT. A seasoned journalist and content creator, Denise writes breaking news and in-depth features, and she delivers practical advice for IT professionals while making complex technology accessible to all. Before returning to journalism, she held senior content marketing roles at CA Technologies, Berkshire Grey, and Cisco. Denise is a trusted voice in the world of enterprise IT and networking.

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Google’s cheaper, faster TPUs are here, while users of other AI processors face a supply crunch

Opportunities for the AI industry LLM vendors such as OpenAI and Anthropic, which still have relatively young code bases and are continuously evolving them, also have much to gain from the arrival of Ironwood for training their models, said Forrester vice president and principal analyst Charlie Dai. In fact, Anthropic has already agreed to procure 1 million TPUs for training and its models and using them for inferencing. Other, smaller vendors using Google’s TPUs for training models include Lightricks and Essential AI. Google has seen a steady increase in demand for its TPUs (which it also uses to run interna services), and is expected to buy $9.8 billion worth of TPUs from Broadcom this year, compared to $6.2 billion and $2.04 billion in 2024 and 2023 respectively, according to Harrowell. “This makes them the second-biggest AI chip program for cloud and enterprise data centers, just tailing Nvidia, with approximately 5% of the market. Nvidia owns about 78% of the market,” Harrowell said. The legacy problem While some analysts were optimistic about the prospects for TPUs in the enterprise, IDC research director Brandon Hoff said enterprises will most likely to stay away from Ironwood or TPUs in general because of their existing code base written for other platforms. “For enterprise customers who are writing their own inferencing, they will be tied into Nvidia’s software platform,” Hoff said, referring to CUDA, the software platform that runs on Nvidia GPUs. CUDA was released to the public in 2007, while the first version of TensorFlow has only been around since 2015.

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Cisco launches AI infrastructure, AI practitioner certifications

“This new certification focuses on artificial intelligence and machine learning workloads, helping technical professionals become AI-ready and successfully embed AI into their workflows,” said Pat Merat, vice president at Learn with Cisco, in a blog detailing the new AI Infrastructure Specialist certification. “The certification validates a candidate’s comprehensive knowledge in designing, implementing, operating, and troubleshooting AI solutions across Cisco infrastructure.” Separately, the AITECH certification is part of the Cisco AI Infrastructure track, which complements its existing networking, data center, and security certifications. Cisco says the AITECH cert training is intended for network engineers, system administrators, solution architects, and other IT professionals who want to learn how AI impacts enterprise infrastructure. The training curriculum covers topics such as: Utilizing AI for code generation, refactoring, and using modern AI-assisted coding workflows. Using generative AI for exploratory data analysis, data cleaning, transformation, and generating actionable insights. Designing and implementing multi-step AI-assisted workflows and understanding complex agentic systems for automation. Learning AI-powered requirements, evaluating customization approaches, considering deployment strategies, and designing robust AI workflows. Evaluating, fine-tuning, and deploying pre-trained AI models, and implementing Retrieval Augmented Generation (RAG) systems. Monitoring, maintaining, and optimizing AI-powered workflows, ensuring data integrity and security. AITECH certification candidates will learn how to use AI to enhance productivity, automate routine tasks, and support the development of new applications. The training program includes hands-on labs and simulations to demonstrate practical use cases for AI within Cisco and multi-vendor environments.

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Chip-to-Grid Gets Bought: Eaton, Vertiv, and Daikin Deals Imply a New Thermal Capital Cycle

This week delivered three telling acquisitions that mark a turning point for the global data center supply chain; and more specifically, for the high-density liquid cooling mega-play now unfolding across the power-thermal continuum. Eaton is acquiring Boyd Thermal for $9.5 billion from Goldman Sachs Asset Management. Vertiv is buying PurgeRite for about $1 billion from Milton Street Capital. And Daikin Applied has moved to acquire Chilldyne, one of the most proven negative-pressure direct-to-chip pioneers. On paper, they’re three distinct transactions. In reality, they’re chapters in the same story: the acceleration of strategic vertical integration around thermal infrastructure for AI-class compute. The Equity Layer: Private Capital Builds, Strategics Buy From an equity standpoint, these are classic handoff moments between private-equity construction and corporate consolidation. Goldman Sachs built Boyd Thermal into a global platform spanning cold plates, CDUs, and high-density liquid loop design, now sold to Eaton at an enterprise multiple north of 5× 2026E revenue. Milton Street Capital took PurgeRite from a specialist contractor in fluid flushing and commissioning into a nationwide services platform. And Daikin, long synonymous with chillers and air-side thermal, is crossing the liquid Rubicon by buying its way into the D2C ecosystem. Each deal crystallizes a simple fact: liquid cooling is no longer an adjunct; it’s core infrastructure. Private equity did its job scaling the parts. Strategic players are now paying up for the system. Eaton’s Bid: The Chip-to-Grid Thesis For Eaton, Boyd Thermal is the final missing piece in its “chip-to-grid” thesis. The company already owns the electrical side of the data center: UPS, busway, switchgear, and monitoring. Boyd plugs the thermal gap, allowing Eaton to market full rack-to-substation solutions for AI loads in the 50–100 kW+ range. It’s a statement acquisition that places Eaton squarely against Schneider Electric, Vertiv and ABB in the race to

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Space: The final frontier for data processing

There are, however, a couple of reasons why data centers in space are being considered. There are plenty of reports about how the increased amount of AI processing is affecting power consumption within data centers; the World Economic Forum has estimated that the power required to handle AI is increasing at a rate of between 26% and 36% annually. Therefore, it is not surprising that organizations are looking at other options. But an even more pressing reason for orbiting data centers is to handle the amount of data that is being produced by existing satellites, Judge said. “Essentially, satellites are gathering a lot more data than can be sent to earth, because downlinks are a bottleneck,” he noted. “With AI capacity in orbit, they could potentially analyze more of this data, extract more useful information, and send insights back to earth. My overall feeling is that any more data processing in space is going to be driven by space processing needs.” And China may already be ahead of the game. Last year, Guoxing Aerospace  launched 12 satellites, forming a space-based computing network dubbed the Three-Body Computing Constellation. When completed, it will contain 2,800 satellites, all handling the orchestration and processing of data, taking edge computing to a new dimension.

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Meta’s $27B Hyperion Campus: A New Blueprint for AI Infrastructure Finance

At the end of October, Meta announced a joint venture with funds managed by Blue Owl Capital to finance, develop, and operate the previously announced “Hyperion” project, a multi-building AI megacampus in Richland Parish, Louisiana. Under the new JV structure, Blue Owl will own 80 percent and Meta 20 percent, though Meta had announced the project long before Blue Owl’s involvement was confirmed. The venture anticipates roughly $27 billion in total development costs for the buildings and the long-lived power, cooling, and connectivity infrastructure. Blue Owl contributed about $7 billion in cash at formation; Meta received a $3 billion one-time distribution and contributed land and construction-in-progress to the vehicle. Rachel Peterson, VP of Data Centers at Meta, noted that construction on the project is already well underway, with thousands of workers on-site. Structuring Capital and Control Media coverage from Reuters and others characterizes the financing package as one of the largest private-capital deals ever for a single industrial campus, with debt placements led by PIMCO and additional institutional investors. Meta keeps the project largely off its balance sheet through the joint venture while retaining the development and property-management role and serving as the anchor tenant for the campus. The JV allows Meta to smooth its capital expenditures and manage risk while maintaining execution control over its most ambitious AI site to date. The structure incorporates lease agreements and a residual-value guarantee, according to Kirkland & Ellis (Blue Owl’s counsel), enabling lenders and equity holders to underwrite a very large, long-duration asset with multiple exit paths. For Blue Owl, Hyperion represents a utility-like digital-infrastructure platform with contracted cash flows to a single A-tier counterparty: a hyperscaler running mission-critical AI workloads for training and inference. As Barron’s and MarketWatch have noted, the deal underscores Wall Street’s ongoing appetite for AI-infrastructure investments at

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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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