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The Download: cybersecurity’s shaky alert system, and mobile IVF

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Cybersecurity’s global alarm system is breaking down Every day, billions of people trust digital systems to run everything from communication to commerce to critical infrastructure. But the global early warning system that alerts security teams to dangerous software flaws is showing critical gaps in coverage—and most users have no idea their digital lives are likely becoming more vulnerable. Over the past eighteen months, two pillars of global cybersecurity have been shaken by funding issues: the US-backed National Vulnerability Database (NVD)—relied on globally for its free analysis of security threats—and the Common Vulnerabilities and Exposures (CVE) program, the numbering system for tracking software flaws.  Although the situation for both has stabilized, organizations and governments are confronting a critical weakness in our digital infrastructure: Essential global cybersecurity services depend on a complex web of US agency interests and government funding that can be cut or redirected at any time. Read the full story.  —Matthew King The first babies have been born following “simplified” IVF in a mobile lab This week I’m sending congratulations to two sets of new parents in South Africa. Babies Milayah and Rossouw arrived a few weeks ago. All babies are special, but these two set a new precedent. They’re the first to be born following “simplified” IVF performed in a mobile lab. This new mobile lab is essentially a trailer crammed with everything an embryologist needs to perform IVF on a shoestring. It was designed to deliver reproductive treatments to people who live in rural parts of low-income countries, where IVF can be prohibitively expensive or even nonexistent. And best of all: it seems to work! Read our story about why it’s such an exciting development.  —Jessica Hamzelou  This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, sign up here. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Trump is seeking huge cuts to basic scientific researchIf he gets his way, federal science funding will be slashed by a third for the next fiscal year. (NYT $)+ The foundations of America’s prosperity are being dismantled. (MIT Technology Review)+ Senators are getting ready to push back against proposed NASA cuts. (Bloomberg $) 2 Conspiracy theorists are starting to turn on TrumpHe whipped them all up over the supposed existence of Epstein’s client list, and now they’re mad nothing’s being released. (The Atlantic $)3 AI actually slows experienced software developers downThey end up wasting lots of time checking and correcting AI models’ output. (Reuters $)4 The Pentagon is becoming the largest shareholder in a rare earth minerals companyIt shows just how much competition is hotting up to secure a steady supply of these materials. (Quartz $)+ The race to produce rare earth elements. (MIT Technology Review) 5 Solar power is starting to truly transform the world’s energy system Globally, roughly a third more power was generated from the sun this spring than last. (New Yorker $)6 Cops’ favorite AI tool auto-deletes evidence of AI being used A pretty breathtaking attempt to avoid any sort of audit, transparency or accountability. (Ars Technica)+ How a new type of AI is helping police skirt facial recognition bans. (MIT Technology Review)7 Why Chinese EV brands are being forced to go globalCompetition at home is becoming so intense that many have no choice but to seek profits elsewhere. (Rest of World)+ China’s EV giants are betting big on humanoid robots. (MIT Technology Review)8 Which Big Tech execs are closest to the White House? Check out this scorecard showing how they’re all doing trying to stay in Trump’s good graces. (WSJ $)9 Elon Musk says Grok is coming to Tesla vehiclesYes, that’s the same Grok that keeps being racist. Shareholders must be delighted. (Insider $)+ X is basically becoming a strip mine for AI training data. (Axios)10 Trump Mobile is charging people’s credit cards without explanationBut I’m sure it’s all perfectly explicable and above board, right? Right?! (404 Media) Quote of the day “It has been nonstop pandemonium.” —Augustus Doricko, who founded a cloud seeding startup two years ago, tells the Washington Post he’s received a deluge of fury online from conspiracy theorists who blame him for the catastrophic Texas floods. One more thing STEPHANIE ARNETT/MIT TECHNOLOGY REVIEW | LUMMI What’s next for AI in 2025 For the last couple of years we’ve had a go at predicting what’s coming next in AI. A fool’s game given how fast this industry moves. But we gave it a go anyway back in January. As we sail pass this year’s halfway mark, it’s a good time to ask: how well did we do? Check out our predictions, and see for yourself! —James O’Donnell, Will Douglas Heaven & Melissa Heikkilä This piece is part of MIT Technology Review’s What’s Next series, looking across industries, trends, and technologies to give you a first look at the future. You can read the rest of them here.

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

Cybersecurity’s global alarm system is breaking down

Every day, billions of people trust digital systems to run everything from communication to commerce to critical infrastructure. But the global early warning system that alerts security teams to dangerous software flaws is showing critical gaps in coverage—and most users have no idea their digital lives are likely becoming more vulnerable.

Over the past eighteen months, two pillars of global cybersecurity have been shaken by funding issues: the US-backed National Vulnerability Database (NVD)—relied on globally for its free analysis of security threats—and the Common Vulnerabilities and Exposures (CVE) program, the numbering system for tracking software flaws. 

Although the situation for both has stabilized, organizations and governments are confronting a critical weakness in our digital infrastructure: Essential global cybersecurity services depend on a complex web of US agency interests and government funding that can be cut or redirected at any time. Read the full story

—Matthew King

The first babies have been born following “simplified” IVF in a mobile lab

This week I’m sending congratulations to two sets of new parents in South Africa. Babies Milayah and Rossouw arrived a few weeks ago. All babies are special, but these two set a new precedent. They’re the first to be born following “simplified” IVF performed in a mobile lab.

This new mobile lab is essentially a trailer crammed with everything an embryologist needs to perform IVF on a shoestring. It was designed to deliver reproductive treatments to people who live in rural parts of low-income countries, where IVF can be prohibitively expensive or even nonexistent. And best of all: it seems to work! Read our story about why it’s such an exciting development. 

—Jessica Hamzelou 

This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, sign up here.

The must-reads

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

1 Trump is seeking huge cuts to basic scientific research
If he gets his way, federal science funding will be slashed by a third for the next fiscal year. (NYT $)
+ The foundations of America’s prosperity are being dismantled. (MIT Technology Review)
Senators are getting ready to push back against proposed NASA cuts. (Bloomberg $)

2 Conspiracy theorists are starting to turn on Trump
He whipped them all up over the supposed existence of Epstein’s client list, and now they’re mad nothing’s being released. (The Atlantic $)

3 AI actually slows experienced software developers down
They end up wasting lots of time checking and correcting AI models’ output. (Reuters $)

4 The Pentagon is becoming the largest shareholder in a rare earth minerals company
It shows just how much competition is hotting up to secure a steady supply of these materials. (Quartz $)
The race to produce rare earth elements. (MIT Technology Review

5 Solar power is starting to truly transform the world’s energy system 
Globally, roughly a third more power was generated from the sun this spring than last. (New Yorker $)

6 Cops’ favorite AI tool auto-deletes evidence of AI being used 
A pretty breathtaking attempt to avoid any sort of audit, transparency or accountability. (Ars Technica)
How a new type of AI is helping police skirt facial recognition bans. (MIT Technology Review)

7 Why Chinese EV brands are being forced to go global
Competition at home is becoming so intense that many have no choice but to seek profits elsewhere. (Rest of World)
China’s EV giants are betting big on humanoid robots. (MIT Technology Review)

8 Which Big Tech execs are closest to the White House? 
Check out this scorecard showing how they’re all doing trying to stay in Trump’s good graces. (WSJ $)

9 Elon Musk says Grok is coming to Tesla vehicles
Yes, that’s the same Grok that keeps being racist. Shareholders must be delighted. (Insider $)
+ X is basically becoming a strip mine for AI training data. (Axios)

10 Trump Mobile is charging people’s credit cards without explanation
But I’m sure it’s all perfectly explicable and above board, right? Right?! (404 Media)

Quote of the day

“It has been nonstop pandemonium.”

—Augustus Doricko, who founded a cloud seeding startup two years ago, tells the Washington Post he’s received a deluge of fury online from conspiracy theorists who blame him for the catastrophic Texas floods.

One more thing

STEPHANIE ARNETT/MIT TECHNOLOGY REVIEW | LUMMI

What’s next for AI in 2025

For the last couple of years we’ve had a go at predicting what’s coming next in AI. A fool’s game given how fast this industry moves. But we gave it a go anyway back in January. As we sail pass this year’s halfway mark, it’s a good time to ask: how well did we do? Check out our predictions, and see for yourself!

—James O’Donnell, Will Douglas Heaven & Melissa Heikkilä

This piece is part of MIT Technology Review’s What’s Next series, looking across industries, trends, and technologies to give you a first look at the future. You can read the rest of them here.

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Spotlight report: How AI is reshaping IT

The emergence of AI as the next big game changer has IT leaders rethinking not just how IT is staffed, organized, and funded, but also how the IT team works with the business to capture the value and promise of AI. Learn more in this Spotlight Report from the editors

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SD-WAN reality check: Why enterprise ‘rip-and-replace’ isn’t happening

However, despite aggressive vendor positioning around complete infrastructure overhauls, ISG’s research shows that overlay approaches are winning. Even the most technologically advanced organizations are taking a more cautious approach to SD-WAN deployments. “Honestly, even the digitally mature enterprises are favoring controlled, phased transitions due to operational complexity, embedded legacy contracts,

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Exxon, Chevron Post Better Than Expected Results

Exxon Mobil Corp. and Chevron Corp. posted better-than-expected results after record oil production cushioned the impact of lower crude prices. Exxon pumped more oil than it has in any second quarter since the historic Mobil takeover more than 25 years ago. Meanwhile, Chevron also lifted output to an all-time high of almost 4 million barrels a day. Shares of both companies climbed. The production bumps fed by booming output in the Permian Basin and elsewhere enabled the titans of the US energy sector to surpass Wall Street expectations even as oil prices slumped and the demand outlook darkened. In the wake of the profit surprise, Exxon is keeping an eye out for more acquisitions just 16 months after its $60 billion takeover of Pioneer Natural Resources Co., Chief Executive Officer Darren Woods said during a conference call with media. Exxon is keen on “creating value” through corporate combinations that would “deliver on this equation of one plus one equaling more than three,” Woods said. “I think there are opportunities out there for us frankly, still. We’re working to see if we can’t bring some of those to fruition.”    Exxon fell 1% at 9:33 a.m. in New York. Chevron rose as much as 2%, making it the day’s best performer among S&P 500 oil stocks. The quarter was marked by wild swings in oil prices as US President Donald Trump’s trade war and OPEC+ output increases confounded supply-and-demand outlooks.  International crude prices were almost $20 a barrel lower during the period on a year-over-year basis, forcing several US producers to slow output growth, particularly in the Permian Basin. But Exxon sees no reason to stop growing in US shale.  Exxon’s worldwide oil and natural gas output reached the equivalent of 4.63 million barrels a day, while Chevron lifted production more

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EIA Fuel Update Shows Mixed Bag for USA Gasoline, Diesel Price

The U.S. Energy Information Administration’s (EIA) latest fuel update, which was released this week, showed a mixed bag for the U.S. regular gasoline price and the U.S. on-highway diesel fuel price. According to the update, the U.S. regular gasoline price averaged $3.130 per gallon on July 14, before dropping to $3.121 per gallon on July 21, then rising to $3.123 per gallon on July 28. The July 28 price is $0.361 lower than the year ago price, the update outlined. The update highlighted that the U.S. on-highway diesel fuel price came in at $3.758 per gallon on July 14, then rose to $3.812 per gallon on July 21, before dropping to $3.805 per gallon on July 28. The July 28 price is $0.037 higher than the year ago price, according to the fuel update. Of the five Petroleum Administration for Defense District (PADD) regions highlighted in the EIA’s latest fuel update, the West Coast was shown to have the highest regular gasoline price as of July 28, at $3.995 per gallon. The Gulf Coast was shown in the update to have the lowest regular gasoline price as of July 28, at $2.748 per gallon. The West Coast was also shown in the update to have the highest on-highway diesel price as of July 28, at $4.546 per gallon. The Gulf Coast was shown to have the lowest diesel price as of July 28, at $3.454 per gallon. A glossary section of the EIA site notes that the 50 U.S. states and the District of Columbia are divided into five districts, with PADD 1 further split into three subdistricts. PADDs 6 and 7 encompass U.S. territories, the site adds. According to the AAA Fuel Prices website, the average price of regular gasoline in the U.S. is $3.151 per gallon, as of August

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Brookfield Acquires Colonial Pipeline

Brookfield Infrastructure Partners LP (BIP) said Thursday it had completed the purchase of Colonial Enterprises Inc. from a consortium including Shell PLC for an enterprise value of about $9 billion. Colonial owns the namesake pipeline, the biggest pipeline for refined products in the United States in terms of capacity. Spanning 5,500 miles from Texas to New York, it carries up to 2.5 million barrels a day. Colonial says the pipeline transports about 45 percent of fuels consumed on the East Coast, serving over 50 million consumers in 14 states. Colonial was acquired from Koch Capital Investments Co. LLC (28.088 percent), KKR-Keats Pipeline Investors LP (23.443 percent), La Caisse (16.549 percent), IFM Investors (15.795 percent) and Shell Midstream Operating LLC (16.125 percent). “This acquisition was completed at an attractive transaction multiple of 9x EBITDA and we are excited to be the first single owner of this system which has had split ownership since it was constructed”, BIP said in a statement online. “We expect to benefit from a mid-teen cash yield, resulting in a seven-year payback period. “Near-term efforts will be focused on business integration and initiating our value creation activities. “The total equity consideration is approximately $3.4 billion (BIP’s share – approximately $500 million)”. Shell said separately, “The divestment reflects Shell’s focus on performance, discipline and simplification and enables the company to concentrate on areas where it has scale and competitive advantage”. “The sale values Shell’s share of Colonial at $1.45 billion, inclusive of approximately $500 million in non-recourse debt and excluding customary closing adjustments”, it added. Earlier in the second quarter of 2025, BIP completed the sale of its remaining 25 percent stake in its U.S. gas pipeline to co-owner ArcLight Capital Partners LLC. ArcLight now owns 62.5 percent of Natural Gas Pipeline Company of America (NGPL). Kinder Morgan retains a 37.5 percent interest

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The weather is changing. Here’s how utilities can adapt.

Morgan Scott is vice president of global partnerships and outreach at the Electric Power Research Institute. Extreme weather is here. Over the past month, the U.S. has experienced dangerous and deadly flash flooding and extreme heat. Projections for the 2025 wildfire season in the Western U.S. indicate significantly increased fire potential driven by drought expansion and above-average temperatures. Meanwhile, the 2025 U.S. tornado season is on track to be above the 30-year historical average, and the National Oceanic and Atmospheric Administration forecasts a 60% chance of an above-average hurricane season. Besides the devastating loss of life and the damage inflicted by these types of events, they have something else in common: they often leave communities without power to meet critical needs. Despite the inevitable occurrence of these events, there is good news for people in the paths of these natural disasters. The power sector is not waiting around to reactively address damage from the next severe weather event. Hurricanes or extreme heat may be seasonal, but preparation is not. A coalition of more than 40 energy providers and system operators — along with 100 academics, policymakers, non-profits, government agencies and others — have worked together to develop a data-driven, science-based framework to improve the resilience and reliability of the power system. The public Climate READi framework, issued and developed by independent, non-profit energy R&D institute EPRI, guides energy companies in assessing risk and vulnerability in the energy system across a wide variety of weather and climate conditions. In addition, utilities, regulators and other stakeholders can use this set of guidance, references and tools to evaluate local hazards, prioritize investments and adapt the evolving electric system to the climate of the future. The framework, developed over the past three years, highlights how factoring climate risk into investment decisions is a cost-effective

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AEP expects to add 24 GW of load by 2030, mainly from data centers

American Electric Power expects its utilities will interconnect 24 GW of new load by 2030 — up nearly 15% from its previous estimate — with 18 GW coming from data centers, according to William Fehrman, AEP president and CEO. The 24 GW is backed by signed customer commitments and consists of 13 GW in the Electric Reliability Council of Texas market, 9 GW in the PJM Interconnection and about 2.5 GW in the Southwest Power Pool, Fehrman said Wednesday during an earnings call. In ERCOT, the pending load includes about 5 GW in cryptocurrency operations and 2 GW in data centers, according to Fehrman. “Texas is clearly becoming the crypto center for us,” he said. The pending load in PJM includes about 3.7 GW of data centers in Ohio and about 3.1 GW of data centers in Indiana Michigan Power’s service territory, Fehrman said. AEP’s utilities have inquiries about possible new load totaling 190 GW, Fehrman said — a significant increase for a 37-GW system. “Potential customers are drawn to AEP’s footprint because of our advanced transmission network capable of delivering consistent large load power,” he said, adding that the company owns more 765-kV lines than all other utilities combined. AEP’s weather-normalized peak demand grew 12%, to 37.6 GW, at the end of the second quarter, up from 33.5 GW a year earlier, according to Trevor Mihalik, the company’s CFO. Data centers and other industrial customers coming online in Indiana, Ohio and Texas largely drove the increase, he said, resulting in about $200 million in additional revenue. AEP, based in Columbus, Ohio, expects weather-normalized retail electricity sales by its utilities will increase 5.7% this year, up from 3% growth in 2024. The company anticipates sales will jump 8.4% next year and 8.9% in 2027, according to an earnings presentation. In

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Carnarvon JV Completes Seismic Reprocessing Project in Bedout

Carnarvon Energy Limited said it has completed its seismic reprocessing project in the Bedout Sub-basin offshore Australia. In collaboration with its Bedout joint venture partners, Carnarvon completed the Bedout Mega Merge project, “a major advancement in subsurface imaging and exploration prospectivity definition” across the area, the company said in a news release. The project integrates 10 seismic surveys, covering 5884 square miles (15,240 square kilometers) and provides more than 80 percent seamless coverage of the Bedout JV acreage, the company said. The data was reprocessed and merged using modern geophysical techniques by DUG Technology, resulting in a unified, high-resolution dataset, according to the release. The dataset enhances the definition of the Bedout prospective resource base and associated geological risk profile. The joint venture is using the dataset for guidance in identifying areas with high exploration potential, the company said. Insights gained from the dataset will directly inform selection of the 2026 exploration target and guide the future Bedout exploration strategy, Carnarvon said. The joint venture continues to prepare for the submission of the multi-well drilling environmental plan required for future exploration activities, with drilling planned to commence in the third quarter of 2026, the company said. The second phase of the project will apply quantitative interpretation and seismic inversion techniques to refine further subsurface predictions, particularly regarding rock lithology for reservoir and seal characterization. The ongoing phase will support high-grading of prospects for future drilling, according to the release. Carnarvon CEO Philip Huizenga said, “The recently completed Mega Merge Project has provided our technical team an unparalleled, coherent view of the Bedout Sub-basin’s sub-surface, encompassing our discoveries, identified prospects and potential new targets”. “The quality and clarity of the merged dataset enables Carnarvon to confidently assist with finalizing our drilling target for the proposed 2026 drilling campaign with a focus

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DOE announces site selection for AI data centers

“The DOE is positioned to lead on advanced AI infrastructure due to its historical mandate and decades of expertise in extreme-scale computing for mission-critical science and national security challenges,” he said. “National labs are central hubs for advancing AI by providing researchers with unparalleled access to exascale supercomputers and a vast, interdisciplinary technical workforce.” “The Department of Energy is actually a very logical choice to lead on advanced AI data centers in my opinion,” said Wyatt Mayham, lead consultant at Northwest AI, which specializes in enterprise AI integration. “They already operate the country’s most powerful supercomputers. Frontier at Oak Ridge and Sierra at Lawrence Livermore are not experimental machines, they are active systems that the DOE built and continues to manage.” These labs have the physical and technical capacity to handle the demands of modern AI. Running large AI data centers takes enormous electrical capacity, sophisticated cooling systems, and the ability to manage high and variable power loads. DOE labs have been handling that kind of infrastructure for decades, says Mayham. “DOE has already built much of the surrounding ecosystem,” he says. “These national labs don’t just house big machines. They also maintain the software, data pipelines, and research partnerships that keep those machines useful. NSF and Commerce play important roles in the innovation system, but they don’t have the hands-on operational footprint the DOE has.” And Tanmay Patange, founder of AI R&D firm Fourslash, says the DOE’s longstanding expertise in high-performance computing and energy infrastructure directly overlap with the demands we have seen from AI development in places. “And the foundation the DOE has built is essentially the precursor to modern AI workloads that often require gigawatts of reliable energy,” he said. “I think it’s a strategic play, and I won’t be surprised to see the DOE pair their

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Data center survey: AI gains ground but trust concerns persist

Cost issues: 76% Forecasting future data center capacity requirements: 71% Improving energy performance for facilities equipment: 67% Power availability: 63% Supply chain disruptions: 65% A lack of qualified staff: 67% With respect to capacity planning, there’s been a notable increase in the number of operators who describe themselves as “very concerned” about forecasting future data center capacity requirements. Andy Lawrence, Uptime’s executive director of research, said two factors are contributing to this concern: ongoing strong growth for IT demand, and the often-unpredictable demand that AI workloads are creating. “There’s great uncertainty about … what the impact of AI is going to be, where it’s going to be located, how much of the power is going to be required, and even for things like space and cooling, how much of the infrastructure is going to be sucked up to support AI, whether it’s in a colocation, whether it’s in an enterprise or even in a hyperscale facility,” Lawrence said during a webinar sharing the survey results. The survey found that roughly one-third of data center owners and operators currently perform some AI training or inference, with significantly more planning to do so in the future. As the number of AI-based software deployments increases, information about the capabilities and limitations of AI in the workplace is becoming available. The awareness is also revealing AI’s suitability for certain tasks. According to the report, “the data center industry is entering a period of careful adoption, testing, and validation. Data centers are slow and careful in adopting new technologies, and AI will not be an exception.”

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Micron unveils PCIe Gen6 SSD to power AI data center workloads

Competitive positioning With the launch of the 9650 SSD PCIe Gen 6, Micron competes with Samsung and SK Hynix enterprise SSD offerings, which are the dominant players in the SSD market. In December last year, SK Hynix announced the development of PS1012 U.2 Gen5 PCIe SSD, for massive high-capacity storage for AI data centers.  The PM1743 is Samsung’s PCIe Gen5 offering in the market, with 14,000 MBps sequential read, designed for high-performance enterprise workloads. According to Faruqui, PCIe Gen6 data center SSDs are best suited for AI inference performance enhancement. However, we’re still months away from large-scale adoption as no current CPU platforms are available with PCIe 6.0 support. Only Nvidia’s Blackwell-based GPUs have native PCIe 6.0 x16 support with interoperability tests in progress. He added that PCIe Gen 6 SSDs will see very delayed adoption in the PC segment and imminent 2025 2H adoption in AI, data centers, high-performance computing (HPC), and enterprise storage solutions. Micron has also introduced two additional SSDs alongside the 9650. The 6600 ION SSD delivers 122TB in an E3.S form factor and is targeted at hyperscale and enterprise data centers looking to consolidate server infrastructure and build large AI data lakes. A 245TB variant is on the roadmap. The 7600 PCIe Gen5 SSD, meanwhile, is aimed at mixed workloads that require lower latency.

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AI Deployments are Reshaping Intra-Data Center Fiber and Communications

Artificial Intelligence is fundamentally changing the way data centers are architected, with a particular focus on the demands placed on internal fiber and communications infrastructure. While much attention is paid to the fiber connections between data centers or to end-users, the real transformation is happening inside the data center itself, where AI workloads are driving unprecedented requirements for bandwidth, low latency, and scalable networking. Network Segmentation and Specialization Inside the modern AI data center, the once-uniform network is giving way to a carefully divided architecture that reflects the growing divergence between conventional cloud services and the voracious needs of AI. Where a single, all-purpose network once sufficed, operators now deploy two distinct fabrics, each engineered for its own unique mission. The front-end network remains the familiar backbone for external user interactions and traditional cloud applications. Here, Ethernet still reigns, with server-to-leaf links running at 25 to 50 gigabits per second and spine connections scaling to 100 Gbps. Traffic is primarily north-south, moving data between users and the servers that power web services, storage, and enterprise applications. This is the network most people still imagine when they think of a data center: robust, versatile, and built for the demands of the internet age. But behind this familiar façade, a new, far more specialized network has emerged, dedicated entirely to the demands of GPU-driven AI workloads. In this backend, the rules are rewritten. Port speeds soar to 400 or even 800 gigabits per second per GPU, and latency is measured in sub-microseconds. The traffic pattern shifts decisively east-west, as servers and GPUs communicate in parallel, exchanging vast datasets at blistering speeds to train and run sophisticated AI models. The design of this network is anything but conventional: fat-tree or hypercube topologies ensure that no single link becomes a bottleneck, allowing thousands of

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ABB and Applied Digital Build a Template for AI-Ready Data Centers

Toward the Future of AI Factories The ABB–Applied Digital partnership signals a shift in the fundamentals of data center development, where electrification strategy, hyperscale design and readiness, and long-term financial structuring are no longer separate tracks but part of a unified build philosophy. As Applied Digital pushes toward REIT status, the Ellendale campus becomes not just a development milestone but a cornerstone asset: a long-term, revenue-generating, AI-optimized property underpinned by industrial-grade power architecture. The 250 MW CoreWeave lease, with the option to expand to 400 MW, establishes a robust revenue base and validates the site’s design as AI-first, not cloud-retrofitted. At the same time, ABB is positioning itself as a leader in AI data center power architecture, setting a new benchmark for scalable, high-density infrastructure. Its HiPerGuard Medium Voltage UPS, backed by deep global manufacturing and engineering capabilities, reimagines power delivery for the AI era, bypassing the limitations of legacy low-voltage systems. More than a component provider, ABB is now architecting full-stack electrification strategies at the campus level, aiming to make this medium-voltage model the global standard for AI factories. What’s unfolding in North Dakota is a preview of what’s coming elsewhere: AI-ready campuses that marry investment-grade real estate with next-generation power infrastructure, built for a future measured in megawatts per rack, not just racks per row. As AI continues to reshape what data centers are and how they’re built, Ellendale may prove to be one of the key locations where the new standard was set.

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Amazon’s Project Rainier Sets New Standard for AI Supercomputing at Scale

Supersized Infrastructure for the AI Era As AWS deploys Project Rainier, it is scaling AI compute to unprecedented heights, while also laying down a decisive marker in the escalating arms race for hyperscale dominance. With custom Trainium2 silicon, proprietary interconnects, and vertically integrated data center architecture, Amazon joins a trio of tech giants, alongside Microsoft’s Project Stargate and Google’s TPUv5 clusters, who are rapidly redefining the future of AI infrastructure. But Rainier represents more than just another high-performance cluster. It arrives in a moment where the size, speed, and ambition of AI infrastructure projects have entered uncharted territory. Consider the past several weeks alone: On June 24, AWS detailed Project Rainier, calling it “a massive, one-of-its-kind machine” and noting that “the sheer size of the project is unlike anything AWS has ever attempted.” The New York Times reports that the primary Rainier campus in Indiana could include up to 30 data center buildings. Just two days later, Fermi America unveiled plans for the HyperGrid AI campus in Amarillo, Texas on a sprawling 5,769-acre site with potential for 11 gigawatts of power and 18 million square feet of AI data center capacity. And on July 1, Oracle projected $30 billion in annual revenue from a single OpenAI cloud deal, tied to the Project Stargate campus in Abilene, Texas. As Data Center Frontier founder Rich Miller has observed, the dial on data center development has officially been turned to 11. Once an aspirational concept, the gigawatt-scale campus is now materializing—15 months after Miller forecasted its arrival. “It’s hard to imagine data center projects getting any bigger,” he notes. “But there’s probably someone out there wondering if they can adjust the dial so it goes to 12.” Against this backdrop, Project Rainier represents not just financial investment but architectural intent. Like Microsoft’s Stargate buildout in

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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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