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How creativity became the reigning value of our time

Americans don’t agree on much these days. Yet even at a time when consensus reality seems to be on the verge of collapse, there remains at least one quintessentially modern value we can all still get behind: creativity.  We teach it, measure it, envy it, cultivate it, and endlessly worry about its death. And why wouldn’t we? Most of us are taught from a young age that creativity is the key to everything from finding personal fulfillment to achieving career success to solving the world’s thorniest problems. Over the years, we’ve built creative industries, creative spaces, and creative cities and populated them with an entire class of people known simply as “creatives.” We read thousands of books and articles each year that teach us how to unleash, unlock, foster, boost, and hack our own personal creativity. Then we read even more to learn how to manage and protect this precious resource.  Given how much we obsess over it, the concept of creativity can feel like something that has always existed, a thing philosophers and artists have pondered and debated throughout the ages. While it’s a reasonable assumption, it’s one that turns out to be very wrong. As Samuel Franklin explains in his recent book, The Cult of Creativity, the first known written use of creativity didn’t actually occur until 1875, “making it an infant as far as words go.” What’s more, he writes, before about 1950, “there were approximately zero articles, books, essays, treatises, odes, classes, encyclopedia entries, or anything of the sort dealing explicitly with the subject of ‘creativity.’” This raises some obvious questions. How exactly did we go from never talking about creativity to always talking about it? What, if anything, distinguishes creativity from other, older words, like ingenuity, cleverness, imagination, and artistry? Maybe most important: How did everyone from kindergarten teachers to mayors, CEOs, designers, engineers, activists, and starving artists come to believe that creativity isn’t just good—personally, socially, economically—but the answer to all life’s problems? Thankfully, Franklin offers some potential answers in his book. A historian and design researcher at the Delft University of Technology in the Netherlands, he argues that the concept of creativity as we now know it emerged during the post–World War II era in America as a kind of cultural salve—a way to ease the tensions and anxieties caused by increasing conformity, bureaucracy, and suburbanization. “Typically defined as a kind of trait or process vaguely associated with artists and geniuses but theoretically possessed by anyone and applicable to any field, [creativity] provided a way to unleash individualism within order,” he writes, “and revive the spirit of the lone inventor within the maze of the modern corporation.” Brainstorming, a new method for encouraging creative thinking, swept corporate America in the 1950s. A response to pressure for new products and new ways of marketing them, as well as a panic over conformity, it inspired passionate debate about whether true creativity should be an individual affair or could be systematized for corporate use.INSTITUTE OF PERSONALITY AND SOCIAL RESEARCH, UNIVERSITY OF CALIFORNIA, BERKELEY/THE MONACELLI PRESS I spoke to Franklin about why we continue to be so fascinated by creativity, how Silicon Valley became the supposed epicenter of it, and what role, if any, technologies like AI might have in reshaping our relationship with it.  I’m curious what your personal relationship to creativity was growing up. What made you want to write a book about it? Like a lot of kids, I grew up thinking that creativity was this inherently good thing. For me—and I imagine for a lot of other people who, like me, weren’t particularly athletic or good at math and science—being creative meant you at least had some future in this world, even if it wasn’t clear what that future would entail. By the time I got into college and beyond, the conventional wisdom among the TED Talk register of thinkers—people like Daniel Pink and Richard Florida—was that creativity was actually the most important trait to have for the future. Basically, the creative people were going to inherit the Earth, and society desperately needed them if we were going to solve all of these compounding problems in the world.  On the one hand, as someone who liked to think of himself as creative, it was hard not to be flattered by this. On the other hand, it all seemed overhyped to me. What was being sold as the triumph of the creative class wasn’t actually resulting in a more inclusive or creative world order. What’s more, some of the values embedded in what I call the cult of creativity seemed increasingly problematic—specifically, the focus on self-­realization, doing what you love, and following your passion. Don’t get me wrong—it’s a beautiful vision, and I saw it work out for some people. But I also started to feel like it was just a cover for what was, economically speaking, a pretty bad turn of events for many people.   Staff members at the University of California’s Institute of Personality Assessment and Research simulate a situational procedure involving group interaction, called the Bingo Test. Researchers of the 1950s hoped to learn how factors in people’s lives and environments shaped their creative aptitude.INSTITUTE OF PERSONALITY AND SOCIAL RESEARCH, UNIVERSITY OF CALIFORNIA, BERKELEY/THE MONACELLI PRESS Nowadays, it’s quite common to bash the “follow your passion,” “hustle culture” idea. But back when I started this project, the whole move-fast-and-break-things, disrupter, innovation-economy stuff was very much unquestioned. In a way, the idea for the book came from recognizing that creativity was playing this really interesting role in connecting two worlds: this world of innovation and entrepreneurship and this more soulful, bohemian side of our culture. I wanted to better understand the history of that relationship. When did you start thinking about creativity as a kind of cult—one that we’re all a part of?  Similar to something like the “cult of domesticity,” it was a way of describing a historical moment in which an idea or value system achieves a kind of broad, uncritical acceptance. I was finding that everyone was selling stuff based on the idea that it boosted your creativity, whether it was a new office layout, a new kind of urban design, or the “Try these five simple tricks” type of thing.  You start to realize that nobody is bothering to ask, “Hey, uh, why do we all need to be creative again? What even is this thing, creativity?” It had become this unimpeachable value that no one, regardless of what side of the political spectrum they fell on, would even think to question. That, to me, was really unusual, and I think it signaled that something interesting was happening. Your book highlights midcentury efforts by psychologists to turn creativity into a quantifiable mental trait and the “creative person” into an identifiable type. How did that play out?  The short answer is: not very well. To study anything, you of course need to agree on what it is you’re looking at. Ultimately, I think these groups of psychologists were frustrated in their attempts to come up with scientific criteria that defined a creative person. One technique was to go find people who were already eminent in fields that were deemed creative—writers like Truman Capote and Norman Mailer, architects like Louis Kahn and Eero Saarinen—and just give them a battery of cognitive and psychoanalytic tests and then write up the results. This was mostly done by an outfit called the Institute of Personality Assessment and Research (IPAR) at Berkeley. Frank Barron and Don MacKinnon were the two biggest researchers in that group. Another way psychologists went about it was to say, all right, that’s not going to be practical for coming up with a good scientific standard. We need numbers, and lots and lots of people to certify these creative criteria. This group of psychologists theorized that something called “divergent thinking” was a major component of creative accomplishment. You’ve heard of the brick test, where you’re asked to come up with many creative uses for a brick in a given amount of time? They basically gave a version of that test to Army officers, schoolchildren, rank-and-file engineers at General Electric, all kinds of people. It’s tests like those that ultimately became stand-ins for what it means to be “creative.” Are they still used?  When you see a headline about AI making people more creative, or actually being more creative than humans, the tests they are basing that assertion on are almost always some version of a divergent thinking test. It’s highly problematic for a number of reasons. Chief among them is the fact that these tests have never been shown to have predictive value—that’s to say, a third grader, a 21-year-old, or a 35-year-old who does really well on divergent thinking tests doesn’t seem to have any greater likelihood of being successful in creative pursuits. The whole point of developing these tests in the first place was to both identify and predict creative people. None of them have been shown to do that.  Reading your book, I was struck by how vague and, at times, contradictory the concept of “creativity” was from the beginning. You characterize that as “a feature, not a bug.” How so? Ask any creativity expert today what they mean by “creativity,” and they’ll tell you it’s the ability to generate something new and useful. That something could be an idea, a product, an academic paper—whatever. But the focus on novelty has remained an aspect of creativity from the beginning. It’s also what distinguishes it from other similar words, like imagination or cleverness. But you’re right: Creativity is a flexible enough concept to be used in all sorts of ways and to mean all sorts of things, many of them contradictory. I think I write in the book that the term may not be precise, but that it’s vague in precise and meaningful ways. It can be both playful and practical, artsy and technological, exceptional and pedestrian. That was and remains a big part of its appeal.  The question of “Can machines be ‘truly creative’?” is not that interesting, but the questions of “Can they be wise, honest, caring?” are more important if we’re going to be welcoming [AI] into our lives as advisors and assistants. Is that emphasis on novelty and utility a part of why Silicon Valley likes to think of itself as the new nexus for creativity? Absolutely. The two criteria go together. In techno-solutionist, hypercapitalist milieus like Silicon Valley, novelty isn’t any good if it’s not useful (or at least marketable), and utility isn’t any good (or marketable) unless it’s also novel. That’s why they’re often dismissive of boring-but-important things like craft, infrastructure, maintenance, and incremental improvement, and why they support art—which is traditionally defined by its resistance to utility—only insofar as it’s useful as inspiration for practical technologies. At the same time, Silicon Valley loves to wrap itself in “creativity” because of all the artsy and individualist connotations. It has very self-consciously tried to distance itself from the image of the buttoned-down engineer working for a large R&D lab of a brick-and-mortar manufacturing corporation and instead raise up the idea of a rebellious counterculture type tinkering in a garage making weightless products and experiences. That, I think, has saved it from a lot of public scrutiny. Up until recently, we’ve tended to think of creativity as a human trait, maybe with a few exceptions from the rest of the animal world. Is AI changing that? When people started defining creativity in the ’50s, the threat of computers automating white-collar work was already underway. They were basically saying, okay, rational and analytical thinking is no longer ours alone. What can we do that the computers can never do? And the assumption was that humans alone could be “truly creative.” For a long time, computers didn’t do much to really press the issue on what that actually meant. Now they’re pressing the issue. Can they do art and poetry? Yes. Can they generate novel products that also make sense or work? Sure. I think that’s by design. The kinds of LLMs that Silicon Valley companies have put forward are meant to appear “creative” in those conventional senses. Now, whether or not their products are meaningful or wise in a deeper sense, that’s another question. If we’re talking about art, I happen to think embodiment is an important element. Nerve endings, hormones, social instincts, morality, intellectual honesty—those are not things essential to “creativity” necessarily, but they are essential to putting things out into the world that are good, and maybe even beautiful in a certain antiquated sense. That’s why I think the question of “Can machines be ‘truly creative’?” is not that interesting, but the questions of “Can they be wise, honest, caring?” are more important if we’re going to be welcoming them into our lives as advisors and assistants.  This interview is based on two conversations and has been edited and condensed for clarity. Bryan Gardiner is a writer based in Oakland, California.

Americans don’t agree on much these days. Yet even at a time when consensus reality seems to be on the verge of collapse, there remains at least one quintessentially modern value we can all still get behind: creativity. 

We teach it, measure it, envy it, cultivate it, and endlessly worry about its death. And why wouldn’t we? Most of us are taught from a young age that creativity is the key to everything from finding personal fulfillment to achieving career success to solving the world’s thorniest problems. Over the years, we’ve built creative industries, creative spaces, and creative cities and populated them with an entire class of people known simply as “creatives.” We read thousands of books and articles each year that teach us how to unleash, unlock, foster, boost, and hack our own personal creativity. Then we read even more to learn how to manage and protect this precious resource. 

Given how much we obsess over it, the concept of creativity can feel like something that has always existed, a thing philosophers and artists have pondered and debated throughout the ages. While it’s a reasonable assumption, it’s one that turns out to be very wrong. As Samuel Franklin explains in his recent book, The Cult of Creativity, the first known written use of creativity didn’t actually occur until 1875, “making it an infant as far as words go.” What’s more, he writes, before about 1950, “there were approximately zero articles, books, essays, treatises, odes, classes, encyclopedia entries, or anything of the sort dealing explicitly with the subject of ‘creativity.’”

This raises some obvious questions. How exactly did we go from never talking about creativity to always talking about it? What, if anything, distinguishes creativity from other, older words, like ingenuity, cleverness, imagination, and artistry? Maybe most important: How did everyone from kindergarten teachers to mayors, CEOs, designers, engineers, activists, and starving artists come to believe that creativity isn’t just good—personally, socially, economically—but the answer to all life’s problems?

Thankfully, Franklin offers some potential answers in his book. A historian and design researcher at the Delft University of Technology in the Netherlands, he argues that the concept of creativity as we now know it emerged during the post–World War II era in America as a kind of cultural salve—a way to ease the tensions and anxieties caused by increasing conformity, bureaucracy, and suburbanization.

“Typically defined as a kind of trait or process vaguely associated with artists and geniuses but theoretically possessed by anyone and applicable to any field, [creativity] provided a way to unleash individualism within order,” he writes, “and revive the spirit of the lone inventor within the maze of the modern corporation.”

Brainstorming, a new method for encouraging creative thinking, swept corporate America in the 1950s. A response to pressure for new products and new ways of marketing them, as well as a panic over conformity, it inspired passionate debate about whether true creativity should be an individual affair or could be systematized for corporate use.
INSTITUTE OF PERSONALITY AND SOCIAL RESEARCH, UNIVERSITY OF CALIFORNIA, BERKELEY/THE MONACELLI PRESS

I spoke to Franklin about why we continue to be so fascinated by creativity, how Silicon Valley became the supposed epicenter of it, and what role, if any, technologies like AI might have in reshaping our relationship with it. 

I’m curious what your personal relationship to creativity was growing up. What made you want to write a book about it?

Like a lot of kids, I grew up thinking that creativity was this inherently good thing. For me—and I imagine for a lot of other people who, like me, weren’t particularly athletic or good at math and science—being creative meant you at least had some future in this world, even if it wasn’t clear what that future would entail. By the time I got into college and beyond, the conventional wisdom among the TED Talk register of thinkers—people like Daniel Pink and Richard Florida—was that creativity was actually the most important trait to have for the future. Basically, the creative people were going to inherit the Earth, and society desperately needed them if we were going to solve all of these compounding problems in the world. 

On the one hand, as someone who liked to think of himself as creative, it was hard not to be flattered by this. On the other hand, it all seemed overhyped to me. What was being sold as the triumph of the creative class wasn’t actually resulting in a more inclusive or creative world order. What’s more, some of the values embedded in what I call the cult of creativity seemed increasingly problematic—specifically, the focus on self-­realization, doing what you love, and following your passion. Don’t get me wrong—it’s a beautiful vision, and I saw it work out for some people. But I also started to feel like it was just a cover for what was, economically speaking, a pretty bad turn of events for many people.  

Staff members at the University of California’s Institute of Personality Assessment and Research simulate a situational procedure involving group interaction, called the Bingo Test. Researchers of the 1950s hoped to learn how factors in people’s lives and environments shaped their creative aptitude.
INSTITUTE OF PERSONALITY AND SOCIAL RESEARCH, UNIVERSITY OF CALIFORNIA, BERKELEY/THE MONACELLI PRESS

Nowadays, it’s quite common to bash the “follow your passion,” “hustle culture” idea. But back when I started this project, the whole move-fast-and-break-things, disrupter, innovation-economy stuff was very much unquestioned. In a way, the idea for the book came from recognizing that creativity was playing this really interesting role in connecting two worlds: this world of innovation and entrepreneurship and this more soulful, bohemian side of our culture. I wanted to better understand the history of that relationship.

When did you start thinking about creativity as a kind of cult—one that we’re all a part of? 

Similar to something like the “cult of domesticity,” it was a way of describing a historical moment in which an idea or value system achieves a kind of broad, uncritical acceptance. I was finding that everyone was selling stuff based on the idea that it boosted your creativity, whether it was a new office layout, a new kind of urban design, or the “Try these five simple tricks” type of thing. 

You start to realize that nobody is bothering to ask, “Hey, uh, why do we all need to be creative again? What even is this thing, creativity?” It had become this unimpeachable value that no one, regardless of what side of the political spectrum they fell on, would even think to question. That, to me, was really unusual, and I think it signaled that something interesting was happening.

Your book highlights midcentury efforts by psychologists to turn creativity into a quantifiable mental trait and the “creative person” into an identifiable type. How did that play out? 

The short answer is: not very well. To study anything, you of course need to agree on what it is you’re looking at. Ultimately, I think these groups of psychologists were frustrated in their attempts to come up with scientific criteria that defined a creative person. One technique was to go find people who were already eminent in fields that were deemed creative—writers like Truman Capote and Norman Mailer, architects like Louis Kahn and Eero Saarinen—and just give them a battery of cognitive and psychoanalytic tests and then write up the results. This was mostly done by an outfit called the Institute of Personality Assessment and Research (IPAR) at Berkeley. Frank Barron and Don MacKinnon were the two biggest researchers in that group.

Another way psychologists went about it was to say, all right, that’s not going to be practical for coming up with a good scientific standard. We need numbers, and lots and lots of people to certify these creative criteria. This group of psychologists theorized that something called “divergent thinking” was a major component of creative accomplishment. You’ve heard of the brick test, where you’re asked to come up with many creative uses for a brick in a given amount of time? They basically gave a version of that test to Army officers, schoolchildren, rank-and-file engineers at General Electric, all kinds of people. It’s tests like those that ultimately became stand-ins for what it means to be “creative.”

Are they still used? 

When you see a headline about AI making people more creative, or actually being more creative than humans, the tests they are basing that assertion on are almost always some version of a divergent thinking test. It’s highly problematic for a number of reasons. Chief among them is the fact that these tests have never been shown to have predictive value—that’s to say, a third grader, a 21-year-old, or a 35-year-old who does really well on divergent thinking tests doesn’t seem to have any greater likelihood of being successful in creative pursuits. The whole point of developing these tests in the first place was to both identify and predict creative people. None of them have been shown to do that. 

Reading your book, I was struck by how vague and, at times, contradictory the concept of “creativity” was from the beginning. You characterize that as “a feature, not a bug.” How so?

Ask any creativity expert today what they mean by “creativity,” and they’ll tell you it’s the ability to generate something new and useful. That something could be an idea, a product, an academic paper—whatever. But the focus on novelty has remained an aspect of creativity from the beginning. It’s also what distinguishes it from other similar words, like imagination or cleverness. But you’re right: Creativity is a flexible enough concept to be used in all sorts of ways and to mean all sorts of things, many of them contradictory. I think I write in the book that the term may not be precise, but that it’s vague in precise and meaningful ways. It can be both playful and practical, artsy and technological, exceptional and pedestrian. That was and remains a big part of its appeal. 

The question of “Can machines be ‘truly creative’?” is not that interesting, but the questions of “Can they be wise, honest, caring?” are more important if we’re going to be welcoming [AI] into our lives as advisors and assistants.

Is that emphasis on novelty and utility a part of why Silicon Valley likes to think of itself as the new nexus for creativity?

Absolutely. The two criteria go together. In techno-solutionist, hypercapitalist milieus like Silicon Valley, novelty isn’t any good if it’s not useful (or at least marketable), and utility isn’t any good (or marketable) unless it’s also novel. That’s why they’re often dismissive of boring-but-important things like craft, infrastructure, maintenance, and incremental improvement, and why they support art—which is traditionally defined by its resistance to utility—only insofar as it’s useful as inspiration for practical technologies.

At the same time, Silicon Valley loves to wrap itself in “creativity” because of all the artsy and individualist connotations. It has very self-consciously tried to distance itself from the image of the buttoned-down engineer working for a large R&D lab of a brick-and-mortar manufacturing corporation and instead raise up the idea of a rebellious counterculture type tinkering in a garage making weightless products and experiences. That, I think, has saved it from a lot of public scrutiny.

Up until recently, we’ve tended to think of creativity as a human trait, maybe with a few exceptions from the rest of the animal world. Is AI changing that?

When people started defining creativity in the ’50s, the threat of computers automating white-collar work was already underway. They were basically saying, okay, rational and analytical thinking is no longer ours alone. What can we do that the computers can never do? And the assumption was that humans alone could be “truly creative.” For a long time, computers didn’t do much to really press the issue on what that actually meant. Now they’re pressing the issue. Can they do art and poetry? Yes. Can they generate novel products that also make sense or work? Sure.

I think that’s by design. The kinds of LLMs that Silicon Valley companies have put forward are meant to appear “creative” in those conventional senses. Now, whether or not their products are meaningful or wise in a deeper sense, that’s another question. If we’re talking about art, I happen to think embodiment is an important element. Nerve endings, hormones, social instincts, morality, intellectual honesty—those are not things essential to “creativity” necessarily, but they are essential to putting things out into the world that are good, and maybe even beautiful in a certain antiquated sense. That’s why I think the question of “Can machines be ‘truly creative’?” is not that interesting, but the questions of “Can they be wise, honest, caring?” are more important if we’re going to be welcoming them into our lives as advisors and assistants. 

This interview is based on two conversations and has been edited and condensed for clarity.

Bryan Gardiner is a writer based in Oakland, California.

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Congress votes to rescind California vehicle emissions waiver

Dive Brief: The U.S. Senate passed three joint resolutions May 22 nullifying California’s ability to set emissions standards for passenger cars, light duty vehicles and trucks that are stricter than national standards set by the U.S. Environmental Protection Agency. Auto and petroleum industry lobbyists targeted California’s Advanced Clean Car II regulations, adopted in 2022, which require all new passenger cars, trucks and SUVs sold in the state to be zero-emission vehicles by the 2035 model year. Federal law set in 1990 allows 17 additional states and the District of Columbia to follow California’s regulations. California Gov. Gavin Newsom, a Democrat, announced the state’s intention to file a lawsuit blocking the congressional resolutions, which await the signature of President Donald Trump to become law. Dive Insight: California’s ability to set its own vehicle emissions standards stem from the 1967 Air Quality Act, passed at a time when smog and poor air quality often permeated the Los Angeles basin. While air quality in California has improved over the years, experts fear a setback from the Senate’s action. “Public health could potentially suffer as a consequence,” said Michael Kleeman, a professor at the University of California, Davis, Department of Civil and Environmental Engineering. “This is, plain and simple, a vote against clean air to breathe,” said Aaron Kressig, transportation electrification manager at Western Resource Advocates, in an emailed statement. He warned of potential lost days at school or work and premature deaths.    “Over 150 million people in the United States are already exposed to unhealthy levels of air pollution,” Steven Higashide, director of the Clean Transportation Program at the Union of Concerned Scientists, said in an emailed statement. “The standards are based on the best available science, and were finalized with extensive public input.”  Along with public health concerns, the debate around California’s

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Cisco bolsters DNS security package

The software can block domains associated with phishing, malware, botnets, and other high-risk categories such as cryptomining or new domains that haven’t been reported previously. It can also create custom block and allow lists and offers the ability to pinpoint compromised systems using real-time security activity reports, Brunetto wrote. According to Cisco, many organizations leave DNS resolution to their ISP. “But the growth of direct enterprise internet connections and remote work make DNS optimization for threat defense, privacy, compliance, and performance ever more important,” Cisco stated. “Along with core security hygiene, like a patching program, strong DNS-layer security is the leading cost-effective way to improve security posture. It blocks threats before they even reach your firewall, dramatically reducing the alert pressure your security team manages.” “Unlike other Secure Service Edge (SSE) solutions that have added basic DNS security in a ‘checkbox’ attempt to meet market demand, Cisco Secure Access – DNS Defense embeds strong security into its global network of 50+ DNS data centers,” Brunetto wrote. “Among all SSE solutions, only Cisco’s features a recursive DNS architecture that ensures low-latency, fast DNS resolution, and seamless failover.”

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HPE Aruba unveils raft of new switches for data center, campus modernization

And in large-scale enterprise environments embracing collapsed-core designs, the switch acts as a high-performance aggregation layer. It consolidates services, simplifies network architecture, and enforces security policies natively, reducing complexity and operational cost, Gray said. In addition, the switch offers the agility and security required at colocation facilities and edge sites. Its integrated Layer 4 stateful security and automation-ready platform enable rapid deployment while maintaining robust control and visibility over distributed infrastructure, Gray said. The CX 10040 significantly expands the capacity it can provide and the roles it can serve for enterprise customers, according to one industry analyst. “From the enterprise side, this expands on the feature set and capabilities of the original 10000, giving customers the ability to run additional services directly in the network,” said Alan Weckel, co-founder and analyst with The 650 Group. “It helps drive a lower TCO and provide a more secure network.”  Aimed as a VMware alternative Gray noted that HPE Aruba is combining its recently announced Morpheus VM Essentials plug-in package, which offers a hypervisor-based package aimed at hybrid cloud virtualization environments, with the CX 10040 to deliver a meaningful alternative to Broadcom’s VMware package. “If customers want to get out of the business of having to buy VM cloud or Cloud Foundation stuff and all of that, they can replace the distributed firewall, microsegmentation and lots of the capabilities found in the old VMware NSX [networking software] and the CX 10k, and Morpheus can easily replace that functionality [such as VM orchestration, automation and policy management],” Gray said. The 650 Group’s Weckel weighed in on the idea of the CX 10040 as a VMware alternative:

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Indian startup Refroid launches India’s first data center CDUs

They use heat exchangers and pumps to regulate the flow and temperature of fluid delivered to equipment for cooling, while isolating the technology cooling system loop from facility systems. The technology addresses limitations of traditional air cooling, which industry experts say cannot adequately handle the heat generated by modern AI processors and high-density computing applications. Strategic significance for India Industry analysts view the development as a critical milestone for India’s data center ecosystem. “India generates 20% of global data, yet contributes only 3% to global data center capacity. This imbalance is not merely spatial — it’s systemic,” said Sanchit Vir Gogia, chief analyst and CEO at Greyhound Research. “The emergence of indigenously developed CDUs signals a strategic pivot. Domestic CDU innovation is a defining moment in India’s transition from data centre host to technology co-creator.” Neil Shah, VP for research and partner at Counterpoint Research, noted that major international players like Schneider, Vertiv, Asetek, Liquidstack, and Zutacore have been driving most CDU deployments in Indian enterprises and data centers. “Having a local indigenous CDU tech and supplier designed with Indian weather, infrastructure and costs in mind expands options for domestic data center demand,” he said. AI driving data center cooling revolution India’s data center capacity reached approximately 1,255 MW between January and September 2024 and was projected to expand to around 1,600 MW by the end of 2024, according to CBRE India’s 2024 Data Center Market Update. Multiple market research firms have projected the India data center market to grow from about $5.7 billion in 2024 to $12 billion by 2030. Bhavaraju cited aggressive projections for the sector’s expansion, with AI workloads expected to account for 30% of total workloads by 2030. “All of them need liquid cooling,” he said, noting that “today’s latest GPU servers – GB200 from Nvidia

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Platform approach gains steam among network teams

Revisting the platform vs. point solutions debate The dilemma of whether to deploy an assortment of best-of-breed products from multiple vendors or go with a unified platform of “good enough” tools from a single vendor has vexed IT execs forever. Today, the pendulum is swinging toward the platform approach for three key reasons. First, complexity, driven by the increasingly distributed nature of enterprise networks, has emerged as a top challenge facing IT execs. Second, the lines between networking and security are blurring, particularly as organizations deploy zero trust network access (ZTNA). And third, to reap the benefits of AIOps, generative AI and agentic AI, organizations need a unified data store. “The era of enterprise connectivity platforms is upon us,” says IDC analyst Brandon Butler. “Organizations are increasingly adopting platform-based approaches to their enterprise connectivity infrastructure to overcome complexity and unlock new business value. When enhanced by AI, enterprise platforms can increase productivity, enrich end-user experiences, enhance security, and ultimately drive new opportunities for innovation.” In IDC’s Worldwide AI in Networking Special Report, 78% of survey respondents agreed or strongly agreed with the statement: “I am moving to an AI-powered platform approach for networking.” Gartner predicts that 70% of enterprises will select a broad platform for new multi-cloud networking software deployments by 2027, an increase from 10% in early 2024. The breakdown of silos between network and security operations will be driven by organizations implementing zero-trust principles as well as the adoption of AI and AIOps. “In the future, enterprise networks will be increasingly automated, AI-assisted and more tightly integrated with security across LAN, data center and WAN domains,” according to Gartner’s 2025 Strategic Roadmap for Enterprise Networking. While all of the major networking vendors have announced cloud-based platforms, it’s still relatively early days. For example, Cisco announced a general framework for Cisco

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Oracle to spend $40B on Nvidia chips for OpenAI data center in Texas

OpenAI has also expanded Stargate internationally, with plans for a UAE data center announced during Trump’s recent Gulf tour. The Abu Dhabi facility is planned as a 10-square-mile campus with 5 gigawatts of power. Gogia said OpenAI’s selection of Oracle “is not just about raw compute, but about access to geographically distributed, enterprise-grade infrastructure that complements its ambition to serve diverse regulatory environments and availability zones.” Power demands create infrastructure dilemma The facility’s power requirements raise serious questions about AI’s sustainability. Gogia noted that the 1.2-gigawatt demand — “on par with a nuclear facility” — highlights “the energy unsustainability of today’s hyperscale AI ambitions.” Shah warned that the power envelope keeps expanding. “As AI scales up and so does the necessary compute infrastructure needs exponentially, the power envelope is also consistently rising,” he said. “The key question is how much is enough? Today it’s 1.2GW, tomorrow it would need even more.” This escalating demand could burden Texas’s infrastructure, potentially requiring billions in new power grid investments that “will eventually put burden on the tax-paying residents,” Shah noted. Alternatively, projects like Stargate may need to “build their own separate scalable power plant.” What this means for enterprises The scale of these facilities explains why many organizations are shifting toward leased AI computing rather than building their own capabilities. The capital requirements and operational complexity are beyond what most enterprises can handle independently.

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New Intel Xeon 6 CPUs unveiled; one powers rival Nvidia’s DGX B300

He added that his read is that “Intel recognizes that Nvidia is far and away the leader in the market for AI GPUs and is seeking to hitch itself to that wagon.” Roberts said, “basically, Intel, which has struggled tremendously and has turned over its CEO amidst a stock slide, needs to refocus to where it thinks it can win. That’s not competing directly with Nvidia but trying to use this partnership to re-secure its foothold in the data center and squeeze out rivals like AMD for the data center x86 market. In other words, I see this announcement as confirmation that Intel is looking to regroup, and pick fights it thinks it can win. “ He also predicted, “we can expect competition to heat up in this space as Intel takes on AMD’s Epyc lineup in a push to simplify and get back to basics.” Matt Kimball, vice president and principal analyst, who focuses on datacenter compute and storage at Moor Insights & Strategy, had a much different view about the announcement. The selection of the Intel sixth generation Xeon CPU, the 6776P, to support Nvidia’s DGX B300 is, he said, “important, as it validates Intel as a strong choice for the AI market. In the big picture, this isn’t about volumes or revenue, rather it’s about validating a strategy Intel has had for the last couple of generations — delivering accelerated performance across critical workloads.”  Kimball said that, In particular, there are a “couple things that I would think helped make Xeon the chosen CPU.”

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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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