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The poetry of data

Jane Muschenetz’s poems don’t look like the sonnets you remember studying in high school English. If anything, they’re more likely to call to mind your statistics class. Flip through the pages of her poetry chapbook Power Point and you’ll see charts, graphs, and citations galore. One poem visually documents maternal mortality rates and women’s unpaid domestic labor in such a way that the bar and pie graphs spell out the word “MOM.” Another tracks deaths from gun violence across the globe and is presented as a gun-shaped graph. Still others are written in more standard poetic form but include citations that reference documents put out by the US government, the United Nations, and news organizations. These poems are just a few of the many in Muschenetz’s latest book that wrestle with contemporary social issues using a combination of data-driven insights and the poetic form. The format is a unique one: The first time Hayley Mitchell Haugen, founding editor in chief of Muschenetz’s publisher Sheila-Na-Gig, saw the poems, she thought to herself, “I’ve never seen anything like this before.” Point Blank 13. “Incidents of firearm mortality per 100K population for high income global economies with populations over 10M,” Institute for Health Metrics Evaluation, United Nations. Graphics treatment by Ingo Muschenetz. 14. “Child and Teen Firearm Mortality in the US and Peer Countries,” per 100K population, KFF.org, July 2023; CDC. Detailed citations at technologyreview.com/Muschenetz.ORIGINALLY PUBLISHED BY WRITERS RESIST, WINTER 2023 While cold, hard numbers and poetry might seem antithetical at first blush, from Muschenetz’s perspective, the two couldn’t be a better fit. A former business consultant at Bain & Company who received her MBA at the Sloan School of Management, she released her first poetry book in her 40s, and she’s enjoyed uncovering what the artistic and scientific approaches to understanding the world have in common. “Even though it maybe feels unintuitive that poetry and science are interrelated, they both make connections that are not immediately obvious,” she says. “They test out theories; they take risks. There’s a lot of nonlinear thinking that happens in both.” Many of the poems in Power Point were inspired by watershed moments in global politics and culture, particularly ones that would shape the lives of women. From the partisan political theater on display at the confirmation hearing of US Supreme Court Justice Ketanji Brown Jackson to the passage of laws restricting women’s freedoms in Iran and Afghanistan, these events often left Muschenetz overwhelmed with frustration at the state of women’s rights today. But knowing that women’s emotions are so often dismissed, she looked for a way to turn those feelings into something that she hoped would be harder to write off than standard poetry while still evoking the openheartedness with which people tend to approach art. “I wanted something that listed just facts but expressed how angry I am,” she says. “I really wanted it to be fact-based. I wanted my sources to be publicly available and almost unassailable.” Her hope was that by repackaging these facts in the form of statistics-driven poetry, she might allow readers to receive the information in a new way—and get them thinking. From Ukraine to California Muschenetz’s childhood primed her to understand how global currents can shape an individual life from an early age. Born Yevgenia Leonidovna Veitzman to a Jewish family in the Ukrainian city of Lviv, Muschenetz says her family began trying to leave the country before she was born, hoping to escape the discrimination they faced under the Soviet government. But it wasn’t until she was 10 years old that the family was finally able to emigrate. When they were at last cleared to cross the border, they headed for San Diego, where she decided that Jane would be easier for Americans to pronounce than her given first name. (Ultimately, she would change her last name, too, when she married.) Muschenetz often felt out of place in her new home, even though she was surrounded by other immigrant kids whose parents had moved to California in search of a better life. In one way she was like many American teenage girls, though: She had a lot of feelings, especially about romantic relationships, whether real or imagined, and she often wrote poems about them.   At age 16, she began submitting her poetry to magazines and publishers, which brought her first taste of writerly rejection. “I was like, ‘Oh, well, I tried. Clearly this isn’t for me.’ Even though in my heart, since I was like four years old, I knew I was a writer and I loved literature,” she says.  Her parents were “completely horrified” about the prospect of her pursuing a career in writing, but they weren’t much more excited about what she eventually landed on instead: a degree in political science at UC San Diego. “The response was always ‘Poets get shot. Politicians get shot,’” she says.  She might not have been able to articulate it at age 18, but looking back, Muschenetz makes sense of the decision to study political science as driven by her desire to understand the global forces that caused her family to emigrate. “I wanted to know: How do we structure policy? Who makes these choices, and how can we change them and make them better?” she says. STACY KECK But the dream of writing was hard to let go of. By the time Muschenetz was a few years out of college, she’d applied for two different programs: an MFA in writing and the MBA program at Sloan. And though she didn’t get accepted to the MFA program, her time at Sloan ended up profoundly shaping the poetry she would write two decades later, giving her the statistical analysis and data interpretation skills that formed the backdrop for Power Point. Those were skills she sharpened even further in the years she spent working as a business consultant at Bain right after earning her MBA. “I don’t think the average joe could pull off [what she does in that book], because she knows how to present statistics well,” says Haugen. “She knows how to look at them analytically and offer them up in a way that a layperson can understand.” Muschenetz left the business world after four years at Bain to focus on parenting her two children, as well as serving in various volunteer capacities at their schools and with local community organizations. It wasn’t until the world shut down in 2020 with the onset of the covid-19 pandemic that she found herself getting back in touch with the creative impulses that had animated her previously. Those impulses manifested in part as visual art: Muschenetz began painting a menagerie of animals on the bases of palm fronds she would find on the ground after a big storm in San Diego. “It just felt good, even though it made no sense,” she says. “At the same time, it was keeping me sane.” Being willing to dip her toe into a creative endeavor that she knew she “didn’t have to be good at” also helped open Muschenetz to the idea of getting back to the poetry writing that had made her heart sing as a girl. “Through my high school and early college years, every margin of every notebook was covered with poems or rhymes,” she says. “And then it was just gone. It was scary for me to realize that I had cut that part out of myself, and how bad that was for me.” Coming home to poetry When Muschenetz did start writing again, she thought she might write a collection of poems rooted in domesticity and home life. She was surprised to find that what started flowing out of her instead were poems about her immigrant experience, which had never been the subject of her poetry while she was living it as a teenager. “I thought, ‘Well, shouldn’t I have gotten this out of my system?’ But here I was writing about this aspect of my identity that I never actually had written about before.”  She eventually had enough poems to pull together what became her first collection, titled All the Bad Girls Wear Russian Accents. The book reveals her propensity for weaving together dark and light, humor and tragedy, in a range of poems that cover everything from the war in Ukraine to the experience of being stereotyped for her ability to speak Russian, the language of many American movie villains.  Muschenetz initially thought that writing a book of poetry might be a onetime thing, the kind of undertaking that would allow her to check a box and move on. But as she was promoting her first book, she found herself fixating on a poem she hadn’t even written yet—one in the form of data that would spell out a word. The idea was eventually realized in “100% MOM.”  100% MOM: A PowerPoint Poem about Women and Labor Data sources include: “Life Stages and Populations by Sex,”CDC, NCHS; “Most pregnancy-related deaths are preventable, ”Hear Her Campaign, CDC, 2022; “The U.S. Maternal Mortality Crisis Continues to Worsen: An International Comparison, ”Commonwealth Fund, 2022; “The World’s Women 2020 Trends and Statistics,” United Nations; Oxfam International Inequality Reports: 2020, 2021; “Hard Work Is Not Enough: Women in Low-Paid Jobs,” National Women’s Law Center, July 2023. Detailed citations at technologyreview.com/Muschenetz.ORIGINALLY PUBLISHED IN WHALE ROAD REVIEW, SPRING 2023 That poem was the seed that grew into Power Point, and Muschenetz, whose poetry has been nominated for the Pushcart Prize three times, hasn’t looked back since. In addition to releasing that second volume of poetry, the product of what she calls the “analytic and overachieving brain” that helped her get through (and enjoy) business school, Muschenetz has used those same skills to help the poetry community in San Diego with some of the more practical needs, like grant writing, that are often lacking in communities of artists, says Katie Manning, a local poet and professor emeritus of poetry.  Muschenetz is mostly just happy to have found a way to use poetry to keep integrating and honoring the many different parts of her identity, from immigrant to business consultant.  “It is a huge disservice to all humanity when we ask our scientists or mathematicians or poets to only be that one thing, as opposed to being their whole selves,” she says.  You Are 600% Hotter than the SunBy Jane Muschenetz A cup of the Sun’s core produces ~60 milliwattsof thermal energy. By volume … less than that ofa human [350 mW]. In a sense, you are hotter thanthe Sun—there’s just not as much of you. —Henry Reich, Minute Physics Speaking roughly, in terms of heatgenerated per every human inch, you giveoff more milliwatts—surge/energy. Onlythe Sun is bigger … it matters.We are all blinded by love, the expanding/contractinguniverse is just another metaphorfor longing, and life—its own purpose.How dazzling, this science!Consider falling for a physicist—the painstakingly slow way they undressmathematical mysteries,talk about bodies in motiongets me every time—space —continuum, part, particle—Atomic. Incandescent! Youare, pound-for-pound, more Life-Source,more Bomb, more Season-Spinning Searing CenterHeart/Engine/Radiating Nuclear Dynamicthan the Sun. Can’t look directly in the mirror? Small Wonder! Imagine— none of us powerless.Originally published by Cathexis Northwest Press, May 2024  For Those of Us Forced to FleeBy Jane Muschenetz For those of us forced to fleethe world is forever shrinking down to a single question:What can you carry?The suitcase of your heart closed tighton all the things there was no room to bring—your memories of “home,” the snowflake momentsof your youth, the blooming Lilac treeoutside your bedroom window … a heavy burdensaps your strength on the long journey, bringonly what you need.Homes can be built again,a new tree can be rooted. Survive. When you have nothing left to plant, become the seed. Originally published in Issue 8, The Good Life Review, 2022. It received the 2022 Honeybee Poetry Prize and was nominated for a Pushcart Prize. Find more poetry by Jane Muschenetz at www.palmfrondzoo.com/janewriting.

Jane Muschenetz’s poems don’t look like the sonnets you remember studying in high school English. If anything, they’re more likely to call to mind your statistics class.

Flip through the pages of her poetry chapbook Power Point and you’ll see charts, graphs, and citations galore. One poem visually documents maternal mortality rates and women’s unpaid domestic labor in such a way that the bar and pie graphs spell out the word “MOM.” Another tracks deaths from gun violence across the globe and is presented as a gun-shaped graph. Still others are written in more standard poetic form but include citations that reference documents put out by the US government, the United Nations, and news organizations.

These poems are just a few of the many in Muschenetz’s latest book that wrestle with contemporary social issues using a combination of data-driven insights and the poetic form. The format is a unique one: The first time Hayley Mitchell Haugen, founding editor in chief of Muschenetz’s publisher Sheila-Na-Gig, saw the poems, she thought to herself, “I’ve never seen anything like this before.”

Point Blank
13. “Incidents of firearm mortality per 100K population for high income global economies with populations over 10M,” Institute for Health Metrics Evaluation, United Nations. Graphics treatment by Ingo Muschenetz. 14. “Child and Teen Firearm Mortality in the US and Peer Countries,” per 100K population, KFF.org, July 2023; CDC. Detailed citations at technologyreview.com/Muschenetz.
ORIGINALLY PUBLISHED BY WRITERS RESIST, WINTER 2023

While cold, hard numbers and poetry might seem antithetical at first blush, from Muschenetz’s perspective, the two couldn’t be a better fit. A former business consultant at Bain & Company who received her MBA at the Sloan School of Management, she released her first poetry book in her 40s, and she’s enjoyed uncovering what the artistic and scientific approaches to understanding the world have in common.

“Even though it maybe feels unintuitive that poetry and science are interrelated, they both make connections that are not immediately obvious,” she says. “They test out theories; they take risks. There’s a lot of nonlinear thinking that happens in both.”

Many of the poems in Power Point were inspired by watershed moments in global politics and culture, particularly ones that would shape the lives of women. From the partisan political theater on display at the confirmation hearing of US Supreme Court Justice Ketanji Brown Jackson to the passage of laws restricting women’s freedoms in Iran and Afghanistan, these events often left Muschenetz overwhelmed with frustration at the state of women’s rights today.

But knowing that women’s emotions are so often dismissed, she looked for a way to turn those feelings into something that she hoped would be harder to write off than standard poetry while still evoking the openheartedness with which people tend to approach art.

“I wanted something that listed just facts but expressed how angry I am,” she says. “I really wanted it to be fact-based. I wanted my sources to be publicly available and almost unassailable.” Her hope was that by repackaging these facts in the form of statistics-driven poetry, she might allow readers to receive the information in a new way—and get them thinking.

From Ukraine to California

Muschenetz’s childhood primed her to understand how global currents can shape an individual life from an early age. Born Yevgenia Leonidovna Veitzman to a Jewish family in the Ukrainian city of Lviv, Muschenetz says her family began trying to leave the country before she was born, hoping to escape the discrimination they faced under the Soviet government. But it wasn’t until she was 10 years old that the family was finally able to emigrate. When they were at last cleared to cross the border, they headed for San Diego, where she decided that Jane would be easier for Americans to pronounce than her given first name. (Ultimately, she would change her last name, too, when she married.)

Muschenetz often felt out of place in her new home, even though she was surrounded by other immigrant kids whose parents had moved to California in search of a better life. In one way she was like many American teenage girls, though: She had a lot of feelings, especially about romantic relationships, whether real or imagined, and she often wrote poems about them.  

At age 16, she began submitting her poetry to magazines and publishers, which brought her first taste of writerly rejection. “I was like, ‘Oh, well, I tried. Clearly this isn’t for me.’ Even though in my heart, since I was like four years old, I knew I was a writer and I loved literature,” she says. 

Her parents were “completely horrified” about the prospect of her pursuing a career in writing, but they weren’t much more excited about what she eventually landed on instead: a degree in political science at UC San Diego. “The response was always ‘Poets get shot. Politicians get shot,’” she says. 

She might not have been able to articulate it at age 18, but looking back, Muschenetz makes sense of the decision to study political science as driven by her desire to understand the global forces that caused her family to emigrate. “I wanted to know: How do we structure policy? Who makes these choices, and how can we change them and make them better?” she says.

Jane Muschenetz

STACY KECK

But the dream of writing was hard to let go of. By the time Muschenetz was a few years out of college, she’d applied for two different programs: an MFA in writing and the MBA program at Sloan. And though she didn’t get accepted to the MFA program, her time at Sloan ended up profoundly shaping the poetry she would write two decades later, giving her the statistical analysis and data interpretation skills that formed the backdrop for Power Point. Those were skills she sharpened even further in the years she spent working as a business consultant at Bain right after earning her MBA.

“I don’t think the average joe could pull off [what she does in that book], because she knows how to present statistics well,” says Haugen. “She knows how to look at them analytically and offer them up in a way that a layperson can understand.”

Muschenetz left the business world after four years at Bain to focus on parenting her two children, as well as serving in various volunteer capacities at their schools and with local community organizations. It wasn’t until the world shut down in 2020 with the onset of the covid-19 pandemic that she found herself getting back in touch with the creative impulses that had animated her previously. Those impulses manifested in part as visual art: Muschenetz began painting a menagerie of animals on the bases of palm fronds she would find on the ground after a big storm in San Diego. “It just felt good, even though it made no sense,” she says. “At the same time, it was keeping me sane.”

Being willing to dip her toe into a creative endeavor that she knew she “didn’t have to be good at” also helped open Muschenetz to the idea of getting back to the poetry writing that had made her heart sing as a girl.

“Through my high school and early college years, every margin of every notebook was covered with poems or rhymes,” she says. “And then it was just gone. It was scary for me to realize that I had cut that part out of myself, and how bad that was for me.”

Coming home to poetry

When Muschenetz did start writing again, she thought she might write a collection of poems rooted in domesticity and home life. She was surprised to find that what started flowing out of her instead were poems about her immigrant experience, which had never been the subject of her poetry while she was living it as a teenager. “I thought, ‘Well, shouldn’t I have gotten this out of my system?’ But here I was writing about this aspect of my identity that I never actually had written about before.” 

She eventually had enough poems to pull together what became her first collection, titled All the Bad Girls Wear Russian Accents. The book reveals her propensity for weaving together dark and light, humor and tragedy, in a range of poems that cover everything from the war in Ukraine to the experience of being stereotyped for her ability to speak Russian, the language of many American movie villains. 

Muschenetz initially thought that writing a book of poetry might be a onetime thing, the kind of undertaking that would allow her to check a box and move on. But as she was promoting her first book, she found herself fixating on a poem she hadn’t even written yet—one in the form of data that would spell out a word. The idea was eventually realized in “100% MOM.” 

100% MOM: A PowerPoint Poem about Women and Labor
Data sources include: “Life Stages and Populations by Sex,”CDC, NCHS; “Most pregnancy-related deaths are preventable, ”Hear Her Campaign, CDC, 2022; “The U.S. Maternal Mortality Crisis Continues to Worsen: An International Comparison, ”Commonwealth Fund, 2022; “The World’s Women 2020 Trends and Statistics,” United Nations; Oxfam International Inequality Reports: 2020, 2021; “Hard Work Is Not Enough: Women in Low-Paid Jobs,” National Women’s Law Center, July 2023. Detailed citations at technologyreview.com/Muschenetz.
ORIGINALLY PUBLISHED IN WHALE ROAD REVIEW, SPRING 2023

That poem was the seed that grew into Power Point, and Muschenetz, whose poetry has been nominated for the Pushcart Prize three times, hasn’t looked back since. In addition to releasing that second volume of poetry, the product of what she calls the “analytic and overachieving brain” that helped her get through (and enjoy) business school, Muschenetz has used those same skills to help the poetry community in San Diego with some of the more practical needs, like grant writing, that are often lacking in communities of artists, says Katie Manning, a local poet and professor emeritus of poetry. 

Muschenetz is mostly just happy to have found a way to use poetry to keep integrating and honoring the many different parts of her identity, from immigrant to business consultant. 

“It is a huge disservice to all humanity when we ask our scientists or mathematicians or poets to only be that one thing, as opposed to being their whole selves,” she says. 


You Are 600% Hotter than the Sun
By Jane Muschenetz

A cup of the Sun’s core produces ~60 milliwatts
of thermal energy. By volume … less than that of
a human [350 mW]. In a sense, you are hotter than
the Sun—there’s just not as much of you. 

—Henry Reich, Minute Physics

Speaking roughly, in terms of heat
generated per every human inch, you give
off more milliwatts—surge/energy. Only
the Sun is bigger … it matters.
We are all blinded 
by love, the expanding/contracting
universe is just another metaphor
for longing, and life—its own purpose.
How dazzling, this science!
Consider falling for a physicist—
the painstakingly slow way they undress
mathematical mysteries,
talk about bodies in motion
gets me every time—space 
—continuum, part, particle—
Atomic. Incandescent! You
are, pound-for-pound, more Life-Source,
more Bomb, more Season-Spinning Searing Center
Heart/Engine/Radiating Nuclear Dynamic
than the Sun. Can’t look directly 
in the mirror? Small Wonder! Imagine—

none of us powerless.

Originally published by Cathexis Northwest Press, May 2024 


For Those of Us Forced to Flee
By Jane Muschenetz

For those of us forced to flee
the world is forever shrinking down to a single question:
What can you carry?
The suitcase of your heart closed tight
on all the things there was no room to bring—
your memories of “home,” the snowflake moments
of your youth, the blooming Lilac tree
outside your bedroom window … a heavy burden
saps your strength on the long journey, bring
only what you need.
Homes can be built again,
a new tree can be rooted.

Survive.

When you have nothing left to plant, become the seed.

Originally published in Issue 8, The Good Life Review, 2022. It received the 2022 Honeybee Poetry Prize and was nominated for a Pushcart Prize.

Find more poetry by Jane Muschenetz at www.palmfrondzoo.com/janewriting.

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Westcott named Woodside CEO

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Executive Roundtable: AI Infrastructure Enters Its Execution Era

Miranda Gardiner, iMasons Climate Accord:  Since 2023, the digital infrastructure industry has moved definitively from planning to execution in the AI infrastructure cycle. Industry analysts forecast continued exponential growth, with active capacity at least doubling between now and 2030 and total capacity potentially tripling, quintupling, or more. In practical terms, we’ll see more digital infrastructure capacity come online in the next five year than has been built in the past 30 years, representing a historic industrial transformation requiring trillions of dollars in capital expenditure and a workforce measured in the millions. Design and organizational flexibility, integrated execution of sustainable solutions, and community-centered workforce development will separate those that thrive from those that struggle. Effective organizations will pivot quickly under these constantly shifting conditions and the leaders will be those that build fast but build right, as strategic flexibility balances long-term performance, efficiency, and regulatory compliance. We already know the resource intensity required to bring AI resources online and are working diligently to ensure this short-term, delivering streamlined and optimized solutions for everything from site selection to cooling and power management while lower lifecycle emissions. Additionally, in some regions, grid interconnection timelines and power availability are already the pacing item for data center development. Organizations that align their sustainability targets and energy procurement strategies will have a clearer path to execution. An operational model capable of delivering multiple large-scale facilities simultaneously across regions is another key piece to successful outcomes. Standardized, repeatable frameworks that reduce engineering time and accelerate permitting. We hear often about collaboration and strong partnerships, and these will be critical with utilities, regulators, and equipment manufacturers to anticipate bottlenecks before they impact schedules. Execution discipline will increasingly determine competitive advantage as the industry scales. The world and, especially, our host communities, are watching closely. Projects that move forward

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Jensen Huang Maps the AI Factory Era at NVIDIA GTC 2026

SAN JOSE, Calif. — If there was a single message that emerged from Jensen Huang’s keynote at Nvidia’s GTC conference this week, it was this: the artificial intelligence revolution is entering its infrastructure phase. For the past several years, the technology industry has been preoccupied with training ever larger models. But in Huang’s telling, that era is already giving way to something far bigger: the industrial-scale deployment of AI systems that run continuously, generating intelligence on demand. “The inference inflection point has arrived,” Huang told the audience gathered at the SAP Center. That shift carries enormous implications for the data center industry. Instead of episodic bursts of compute used to train models, the next generation of AI systems will require persistent, high-throughput infrastructure designed to serve billions, and eventually trillions, of inference requests every day. And the scale of the buildout Huang envisions is staggering. Throughout the keynote, the Nvidia CEO repeatedly referenced what he believes will become a trillion-dollar global market for AI infrastructure in the coming years, spanning accelerated computing systems, networking fabrics, storage architectures, power systems, and the facilities required to house them. At that scale, Huang argued, data centers are no longer simply IT facilities. They are truly becoming AI factories: industrial systems designed to convert electricity into tokens. “Tokens are the new commodity,” Huang said. “AI factories are the infrastructure that produces them.” Across more than two hours on stage, Huang sketched the architecture of that new computing platform, introducing new computing systems, networking technologies, software frameworks, and infrastructure blueprints designed to support what Nvidia believes will be the largest computing buildout in history. Four main themes defined the presentation: • The arrival of the inference inflection point.• The emergence of OpenClaw as a foundational operating layer for AI agents.• New hybrid inference architectures involving

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Executive Roundtable: The Coordination Imperative

Christopher Gorthy, DPR Construction:  Early collaboration of key stakeholders has become the baseline to deliver these complex projects. The teams that are successful in these environments are the ones who combine effective meeting structures with enough in‑person interaction to build real trust. Pairing those relationships with the right tools can help track key decision making, document reasoning, and keep everyone aligned on “The Why,” creating more predictable outcomes. Where the industry continues to feel fragmented is around liability, risk, and comfort with sharing design and model data. Achieving the speed these projects demand requires the entire team to understand each partner’s constraints and then working together to solve problems, communicating clearly and documenting decisions as they go. All of our partnerships are solving equations with multiple variables. Our teams must provide early feedback and solutions when faced with impacts or delays outside our control, and even earlier communications of impacts that cannot be mitigated. Open communication channels, whether through shared digital platforms or recurring working sessions, are critical to staying ahead of risk. As projects get bigger, alignment with financial institutions, insurance entities and private equity partners also have become essential.   The number of trade partners capable of taking on contracts of this size is limited, so making sure we are setting up our partners for success while also working to expand the network of qualified trade partners is a key strategy.  From a tactical standpoint, the most effective projects operate from a single integrated schedule that ties together the owner, vendors, general contractor, trades, commissioning teams, and all other stakeholders. Reinforcing this with consistent two‑ to three‑week look‑ahead reviews and onsite schedule coordination meetings regardless of contractual structure significantly increases alignment and efficiency at the project level.

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Jensen Huang After the Keynote: Inside Nvidia’s GTC 2026 Press Briefing

The Data Center as Token Factory If there was one line of thinking that defined the session, it was Huang’s insistence that the industry must stop thinking about computers as systems for data entry and retrieval. That, he said, is the old paradigm. The new one is a “token manufacturing system.” That phrase landed because it compresses a lot of Nvidia’s strategy into a single mental model. In this view, the modern data center is no longer just a warehouse of servers or a cloud abstraction layer. It is a factory, and the unit of output is increasingly the token. For Data Center Frontier readers, this is a familiar direction of travel, but Huang pushed it further than most CEOs do. He repeatedly tied Nvidia’s roadmap to token throughput, token economics, and performance per watt. He is clearly trying to establish a new baseline metric for AI infrastructure value. Not raw capacity, but how much useful intelligence a facility can produce from a fixed power envelope. That point also surfaced in his discussion of Grace and Vera CPUs. Huang’s argument was not that Nvidia intends to win every classical CPU market. It was that traditional measures such as cores per dollar are insufficient in AI data centers where the real economic risk is leaving extremely valuable GPUs idle. In other words, the CPU matters because it must move work fast enough to keep the GPU estate productive. In a power-limited, AI-heavy environment, the purpose of the CPU changes. It is no longer optimized for the old hyperscale rental model. It is optimized for keeping the token factory fed. That is a subtle but major shift. It suggests that the next-generation AI data center will be increasingly engineered around the productivity of the overall system rather than around legacy component economics.

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Project Stalled: Grid Bottlenecks Threaten the Fifth Industrial Revolution

The defining feature of our current data center cycle isn’t a shortage of customers or capital; it’s a shortage of power that can actually be delivered on time. In the space of three years, large‑load interconnection queues have gone from a planning tool to the main reason otherwise viable AI campuses are missing their deployment windows. Multi‑year delays for large loads are quickly becoming the norm, not the exception, in major markets, turning what should be a sprint to deploy AI into a long and uncertain wait. At the grid level, the same pattern is visible in the queues. Across U.S. markets, that queuing infrastructure is now a primary source of delay. Regional operators from PJM to ERCOT and NYISO report steep increases in both the number and size of large‑load requests, with data centers and other energy‑intensive digital infrastructure accounting for a growing share of new demand ( https://insidelines.pjm.com/pjm-board-outlines-plans-to-integrate-large-loads-reliably/,  https://www.nyiso.com/-/energy-intensive-projects-in-nyiso-s-interconnection-queue/,  https://www.latitudemedia.com/news/ercots-large-load-queue-has-nearly-quadrupled-in-a-single-year/). In practice, that means more projects are being told that meaningful capacity will not be available on the timeline their customers expect, forcing them into redesigns, phased power ramps, or alternative power strategies. Time, in other words, has become the scarcest resource in the data center economy. The same 60 MW AI facility that looks attractive at a 17.1% IRR when delivered on schedule can see its returns fall to 12.6% with a three‑month delay and to 8.8% with a six‑month delay—nearly halving its investment case ( https://www.thefastmode.com/expert-opinion/47210-what-we-learned-in-2025-about-data-center-builds-why-delays-will-persist-in-2026-without-greater-visibility). That is why, in this industrial revolution, the metric that matters most is speed‑to‑power: how quickly real, reliable megawatts can be made available at the fence line, not how many gigawatts exist on slides or in press releases. In this industrial revolution, that metric will do more to determine who wins than any short‑term race to buy chips or secure logos.

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Roundtable: Designing for an Uncertain AI Demand Curve

For the third installment of our Executive Roundtable for the First Quarter of 2026, Data Center Frontier examines a question at the heart of AI infrastructure strategy: How to design for a demand curve that refuses to sit still. The rapid evolution of artificial intelligence workloads has introduced a new kind of uncertainty into data center development. Training clusters continue to scale, inference workloads are proliferating, and enterprise adoption is accelerating in ways that challenge even the most aggressive forecasts. Yet beneath that growth lies a fundamental ambiguity. Not just how much capacity will be needed, but when, where, and in what form. For developers and operators, this creates a tension between speed and flexibility. The pressure to deliver capacity quickly has never been greater, as hyperscale and neocloud players race to secure power and bring AI infrastructure online. At the same time, the risk of overbuilding (or locking into infrastructure that may not align with future workloads, densities, or architectures) has become increasingly difficult to ignore. Nowhere is this tension more visible than in power and electrical design. Decisions around substation sizing, transmission commitments, switchgear capacity, and on-site generation are being made years in advance of fully understood demand profiles. These choices carry long-term consequences, shaping not only capital efficiency but the ability to adapt as AI technologies and use cases continue to evolve. The result is a shift in design philosophy. Increasingly, the industry is moving away from static, one-time provisioning toward architectures that prioritize modularity, scalability, and optionality, seeking to preserve flexibility without sacrificing near-term delivery. In this roundtable, our panel explores how developers, operators, and suppliers are navigating that balance, and what it will take to future-proof AI infrastructure in an era defined by both unprecedented growth and persistent uncertainty.

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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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