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Why AI hardware needs to be open

When OpenAI acquired Io to create “the coolest piece of tech that the world will have ever seen,” it confirmed what industry experts have long been saying: Hardware is the new frontier for AI. AI will no longer just be an abstract thing in the cloud far away. It’s coming for our homes, our rooms, our beds, our bodies.  That should worry us. Once again, the future of technology is being engineered in secret by a handful of people and delivered to the rest of us as a sealed, seamless, perfect device. When technology is designed in secrecy and sold to us as a black box, we are reduced to consumers. We wait for updates. We adapt to features. We don’t shape the tools; they shape us.  This is a problem. And not just for tinkerers and technologists, but for all of us. We are living through a crisis of disempowerment. Children are more anxious than ever; the former US surgeon general described a loneliness epidemic; people are increasingly worried about AI eroding education. The beautiful devices we use have been correlated with many of these trends. Now AI—arguably the most powerful technology of our era—is moving off the screen and into physical space.  The timing is not a coincidence. Hardware is having a renaissance. Every major tech company is investing in physical interfaces for AI. Startups are raising capital to build robots, glasses, wearables that are going to track our every move. The form factor of AI is the next battlefield. Do we really want our future mediated entirely through interfaces we can’t open, code we can’t see, and decisions we can’t influence?  This moment creates an existential opening, a chance to do things differently. Because away from the self-centeredness of Silicon Valley, a quiet, grounded sense of resistance is reactivating. I’m calling it the revenge of the makers.  In 2007, as the iPhone emerged, the maker movement was taking shape. This subculture advocates for learning-through-making in social environments like hackerspaces and libraries. DIY and open hardware enthusiasts gathered in person at Maker Faires—large events where people of all ages tinkered and shared their inventions in 3D printing, robotics, electronics, and more. Motivated by fun, self-fulfillment, and shared learning, the movement birthed companies like MakerBot, Raspberry Pi, Arduino, and (my own education startup) littleBits from garages and kitchen tables. I myself wanted to challenge the notion that technology had to be intimidating or inaccessible, creating modular electronic building blocks designed to put the power of invention in the hands of everyone. By definition, the maker movement is humble and it is consistent. Makers do not believe in the cult of individual genius; we believe in collective genius. We believe that creativity is universally distributed (not exclusively bestowed), that inventing is better together, and that we should make open products so people can observe, learn, and create—basically, the polar opposite of what Jony Ive and Sam Altman are building. But over time, the momentum faded. The movement was dismissed by the tech and investment industry as niche and hobbyist, and starting in 2018, pressures on the hardware venture market (followed by covid) made people retreat from social spaces to spend more time behind screens.  Now it’s mounting a powerful second act, joined by a wave of AI open-source enthusiasts. This time around the stakes are higher, and we need to give it the support it never had. In 2024 the AI leader Hugging Face developed an open-source platform for AI robots, which already has 3,500+ robot data sets and draws thousands of participants from every continent to join giant hackathons. Raspberry Pi went public on the London Stock Exchange for $700 million. After a hiatus, Maker Faire came back; the most recent one had nearly 30,000 attendees, with kinetic sculptures, flaming octopuses, and DIY robot bands, and this year there will be over 100 Maker Faires around the world. Just last week, DIY.org relaunched its app. In March, my friend Roya Mahboob, founder of the Afghan Girls Robotics Team, released a movie about the team to incredible reviews. People love the idea that making is the ultimate form of human empowerment and expression. All the while, a core set of people have continued influencing millions through maker organizations like FabLabs and Adafruit. Studies show that hands-on creativity reduces anxiety, combats loneliness, and boosts cognitive function. The act of making grounds us, connects us to others, and reminds us that we are capable of shaping the world with our own hands.  I’m not proposing to reject AI hardware but to reject the idea that innovation must be proprietary, elite, and closed. I’m proposing to fund and build the open alternative. That means putting our investment, time, and purchases towards robot built in community labs, AI models trained in the open, tools made transparent and hackable. That world isn’t just more inclusive—it’s more innovative. It’s also more fun.  This is not nostalgia. This is about fighting for the kind of future we want: A future of openness and joy, not of conformity and consumption. One where technology invites participation, not passivity. Where children grow up not just knowing how to swipe, but how to build. Where creativity is a shared endeavor, not the mythical province of lone geniuses in glass towers. In his Io announcement video, Altman said, “We are literally on the brink of a new generation of technology that can make us our better selves.” It reminded me of the movie Mountainhead, where four tech moguls tell themselves they are saving the world while the world is burning. I don’t think the iPhone made us our better selves. In fact, you’ve never seen me run faster than when I’m trying to snatch an iPhone out of my three-year-old’s hands. So yes, I’m watching what Sam Altman and Jony Ive will unveil. But I’m far more excited by what’s happening in basements, in classrooms, on workbenches. Because the real iPhone moment isn’t a new product we wait for. It’s the moment you realize you can build it yourself. And best of all? You  can’t doomscroll when you’re holding a soldering iron. Ayah Bdeir is a leader in the maker movement, a champion of open source AI, and founder of littleBits, the hardware platform that teaches STEAM to kids through hands-on invention. A graduate of the MIT Media Lab, she was selected as one of the BBC’s 100 Most Influential Women, and her inventions have been acquired by the Museum of Modern Art.

When OpenAI acquired Io to create “the coolest piece of tech that the world will have ever seen,” it confirmed what industry experts have long been saying: Hardware is the new frontier for AI. AI will no longer just be an abstract thing in the cloud far away. It’s coming for our homes, our rooms, our beds, our bodies. 

That should worry us.

Once again, the future of technology is being engineered in secret by a handful of people and delivered to the rest of us as a sealed, seamless, perfect device. When technology is designed in secrecy and sold to us as a black box, we are reduced to consumers. We wait for updates. We adapt to features. We don’t shape the tools; they shape us. 

This is a problem. And not just for tinkerers and technologists, but for all of us.

We are living through a crisis of disempowerment. Children are more anxious than ever; the former US surgeon general described a loneliness epidemic; people are increasingly worried about AI eroding education. The beautiful devices we use have been correlated with many of these trends. Now AI—arguably the most powerful technology of our era—is moving off the screen and into physical space. 

The timing is not a coincidence. Hardware is having a renaissance. Every major tech company is investing in physical interfaces for AI. Startups are raising capital to build robots, glasses, wearables that are going to track our every move. The form factor of AI is the next battlefield. Do we really want our future mediated entirely through interfaces we can’t open, code we can’t see, and decisions we can’t influence? 

This moment creates an existential opening, a chance to do things differently. Because away from the self-centeredness of Silicon Valley, a quiet, grounded sense of resistance is reactivating. I’m calling it the revenge of the makers. 

In 2007, as the iPhone emerged, the maker movement was taking shape. This subculture advocates for learning-through-making in social environments like hackerspaces and libraries. DIY and open hardware enthusiasts gathered in person at Maker Faires—large events where people of all ages tinkered and shared their inventions in 3D printing, robotics, electronics, and more. Motivated by fun, self-fulfillment, and shared learning, the movement birthed companies like MakerBot, Raspberry Pi, Arduino, and (my own education startup) littleBits from garages and kitchen tables. I myself wanted to challenge the notion that technology had to be intimidating or inaccessible, creating modular electronic building blocks designed to put the power of invention in the hands of everyone.

By definition, the maker movement is humble and it is consistent. Makers do not believe in the cult of individual genius; we believe in collective genius. We believe that creativity is universally distributed (not exclusively bestowed), that inventing is better together, and that we should make open products so people can observe, learn, and create—basically, the polar opposite of what Jony Ive and Sam Altman are building.

But over time, the momentum faded. The movement was dismissed by the tech and investment industry as niche and hobbyist, and starting in 2018, pressures on the hardware venture market (followed by covid) made people retreat from social spaces to spend more time behind screens. 

Now it’s mounting a powerful second act, joined by a wave of AI open-source enthusiasts. This time around the stakes are higher, and we need to give it the support it never had.

In 2024 the AI leader Hugging Face developed an open-source platform for AI robots, which already has 3,500+ robot data sets and draws thousands of participants from every continent to join giant hackathons. Raspberry Pi went public on the London Stock Exchange for $700 million. After a hiatus, Maker Faire came back; the most recent one had nearly 30,000 attendees, with kinetic sculptures, flaming octopuses, and DIY robot bands, and this year there will be over 100 Maker Faires around the world. Just last week, DIY.org relaunched its app. In March, my friend Roya Mahboob, founder of the Afghan Girls Robotics Team, released a movie about the team to incredible reviews. People love the idea that making is the ultimate form of human empowerment and expression. All the while, a core set of people have continued influencing millions through maker organizations like FabLabs and Adafruit.

Studies show that hands-on creativity reduces anxiety, combats loneliness, and boosts cognitive function. The act of making grounds us, connects us to others, and reminds us that we are capable of shaping the world with our own hands. 

I’m not proposing to reject AI hardware but to reject the idea that innovation must be proprietary, elite, and closed. I’m proposing to fund and build the open alternative. That means putting our investment, time, and purchases towards robot built in community labs, AI models trained in the open, tools made transparent and hackable. That world isn’t just more inclusive—it’s more innovative. It’s also more fun. 

This is not nostalgia. This is about fighting for the kind of future we want: A future of openness and joy, not of conformity and consumption. One where technology invites participation, not passivity. Where children grow up not just knowing how to swipe, but how to build. Where creativity is a shared endeavor, not the mythical province of lone geniuses in glass towers.

In his Io announcement video, Altman said, “We are literally on the brink of a new generation of technology that can make us our better selves.” It reminded me of the movie Mountainhead, where four tech moguls tell themselves they are saving the world while the world is burning. I don’t think the iPhone made us our better selves. In fact, you’ve never seen me run faster than when I’m trying to snatch an iPhone out of my three-year-old’s hands.

So yes, I’m watching what Sam Altman and Jony Ive will unveil. But I’m far more excited by what’s happening in basements, in classrooms, on workbenches. Because the real iPhone moment isn’t a new product we wait for. It’s the moment you realize you can build it yourself. And best of all? You  can’t doomscroll when you’re holding a soldering iron.

Ayah Bdeir is a leader in the maker movement, a champion of open source AI, and founder of littleBits, the hardware platform that teaches STEAM to kids through hands-on invention. A graduate of the MIT Media Lab, she was selected as one of the BBC’s 100 Most Influential Women, and her inventions have been acquired by the Museum of Modern Art.

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Essential commands for Linux server management

Any Linux systems administrator needs to be proficient with a wide range of commands for user management, file handling, system monitoring, networking, security and more. This article covers a range of commands that are essential for managing a Linux server. Keep in mind that some commands will depend on the

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Trump Revokes Biden Memo on Columbia Basin Protection

President Donald Trump has rescinded a memorandum issued by his predecessor to safeguard salmon, steelhead and other native fish populations in the Columbia River Basin. The memo, signed by Joe Biden September 2023, “placed concerns about climate change above the Nation’s interests in reliable energy resources”, the White House said in an online statement. “The MOU required the Federal government to spend millions of dollars and comply with 36 pages of onerous commitments to dam operations on the Lower Snake River”, the presidential office said. “Dam breaching would have resulted in reduced water supply to farmers, eliminated several shipping channels, had devastating impacts to agriculture, increased energy costs, and eliminated recreational opportunities throughout the region.   “The dam breaches would have eliminated over 3,000 megawatts of secure and reliable hydroelectric generating capacity – which is enough generation to power 2.5 million American homes”. Biden’s memo, meant to honor U.S. “trust and treaty responsibilities” to tribal nations and enforce safeguards under the Pacific Northwest Electric Power Planning and Conservation Act, directed all agencies with applicable authority to review their programs affecting native fish in the basin. The memo also called for the formation of an intergovernmental partnership involving tribal nations and the states of Idaho, Montana, Oregon and Washington. In December 2023 the Biden administration signed an agreement establishing a 10-year partnership with tribes, conservation groups, Oregon and Washington to restore wild fish populations, including a federal investment of over $1 billion. The agreement also enabled a 10-year break from decades-long litigation against the federal government’s operation of dams in the Pacific Northwest. Trump, through a presidential memorandum, has now directed the secretaries of energy, interior and commerce, as well as the assistant secretary of the Army for Civil Works, “to withdraw from agreements stemming from Biden’s misguided executive action, including the

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Senate Finance Committee reduces House IRA cuts, but few changes for wind and solar

Dive Brief: The Senate Finance Committee on Monday released its version of the budget bill the House passed in May, offering gentler cuts to the Inflation Reduction Act but still slashing tax incentives, especially those for wind and solar energy. The bill allows transferability for the full life of certain IRA energy tax credits, breaking with the House, which proposed ending transferability for 45Q, 45Z and 45X tax credits after 2027. The Senate proposal is particularly tough on residential solar and residential batteries, proposing that the 30% 25D tax credit for those items be phased out just 180 days after President Donald Trump signs the budget into law. Dive Insight: The Senate proposal removes the House’s tough requirement that projects must break ground within 60 days of the bill’s signing and then be placed in service by the end of 2028 to qualify for technology-neutral clean electricity production and investment tax credits. The Senate version stipulates that eligible technologies such as nuclear, geothermal and hydropower can claim the 45Y and 48E tax credits as long as they begin construction by 2033. However, it subjects wind and solar energy to different rules. Wind and solar projects would be able to qualify for 60% of these credits if they break ground by 2026, 20% if they break ground by 2027, and nothing after that. “For wind and solar, you have particularly large-scale projects that are very much in development,” said Harry Godfrey, who leads Advanced Energy United’s federal policy team. “They’re in interconnection. They are in permitting processes that have pilot agreements, but they are likely not to go to construction until ’27 or ’28, so this effectively kills those projects.” Godfrey said the legislation’s leasing prohibition on third-party wind and solar projects, along with the abrupt termination of 25D, hits the residential solar

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NRC speeds timeline for Dow/X-energy reactor permit review

Dive Brief: The U.S. Nuclear Regulatory Commission could approve construction of X-energy’s first commercial small modular reactor deployment by the end of 2026, the company said Monday. The 18-month review timeline would be significantly faster than the 36 months NRC says it takes to review a typical construction permit application and the 30 months X-energy advised in March. The accelerated timeline is due in part to the “completeness and quality of the application, and the effectiveness of pre-application engagements” since 2018, X-energy said. The four-reactor, 320-MWe plant would provide heat and power for Dow’s UCC Seadrift petrochemical plant on the Texas Gulf Coast, replacing a fossil-fuel cogeneration plant. Dow “does not expect to make a final investment decision on the project before 2028,” Dow Media Relations Director Sarah Young said in an email. Dive Insight: A final investment decision in or after 2028 would likely come as the NRC reviewed the project’s operating license application, the second of two steps in the Part 50 licensing process Dow is pursuing. In March, Dow and X-energy said construction could begin “once the permit is received and upon Dow confirming the ability to deliver the project while achieving its financial return targets,” which depend on the cost of energy produced at the plant being “competitive with other alternatives for firm, clean energy … net of all subsidies,” they said. A “clear, well-defined regulatory pathway” is helpful for X-energy as it continues work on its Xe-100 reactor design, fuel fabrication, supply chain and workforce development, all of which are “critical to the timely completion of the project,” CEO J. Clay Sell said in an email. X-energy subsidiary TRISO-X is building a fuel fabrication facility in Tennessee to supply the Seadrift plant and subsequent deployments, Sell said. In April, the U.S. Department of Energy said

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Khamenei Tells US that Iran Won’t Surrender to Israel

Iran’s Supreme Leader Ayatollah Ali Khamenei said his country won’t surrender to Israel after US President Donald Trump called for the Islamic Republic’s capitulation amid growing speculation that Washington could enter the conflict.  “The Americans should know that the Iranian nation is not one to surrender,” Khamenei said in a statement published on his official website, Khamenei.ir. He warned that if the US joined Israel’s military offensive, it would see “irreparable damage.” Khamenei also said he opposed an “imposed peace,” suggesting he would not engage in any US or Israel-led efforts to force Iran into accepting a ceasefire. Khamenei’s latest comments, which were originally scheduled to be televised, come a day after Trump said he knows where the supreme leader is “hiding” and also called for Iran’s surrender. On Tuesday, Trump and his national security team had a meeting that lasted more than hour, according to people familiar with the matter. Trump spoke with Israeli Prime Minister Benjamin Netanyahu afterward, a White House official said. No further official comments were made. Israel started its military strikes on Iran last Friday and has hit scores of targets in residential and commercial areas of the capital Tehran as well as nuclear facilities, gas fields and oil refineries.  In response Iran has fired hundreds of missiles at Israel, most of them targeting Tel Aviv. So far, at least 224 Iranians have been killed by Israel’s attacks and 24 Israelis have been killed by Iran’s strikes, according to government figures from both countries. The White House has said Trump will meet Pakistan’s army chief on Wednesday. The South Asian country – a key ally of Iran – has expressed a willingness to play a role as a mediator between the US and Iran. Pakistan’s Foreign Minister Ishaq Dar said Monday Iran is open to resuming talks

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NERC upgrades MISO reliability risk after ‘data mismatch’ discovered

After finding a “data mismatch,” the North American Electric Reliability Corp. on Tuesday said the Midcontinent Independent System Operator’s reliability risk wasn’t as bad as reported by the grid watchdog in a December assessment. “When reanalyzed with the corrected data, the MISO footprint was reclassified as an ‘elevated risk’ over the next few years, shifting to ‘high risk’ in the 2028–2031 timeframe, depending on new resource additions/retirements,” the reliablity watchdog said in a statement. Elevated risk means an area meets resource adequacy criteria but under extreme weather conditions remains likely to experience a shortfall in reserves, NERC said. In December NERC published its Long-Term Reliability Assessment, concluding that more than half of North America faces a risk of energy shortfalls in the next five to 10 years. While many areas were classified at an “elevated” risk, the report warned MISO faced a “high risk” beginning this year, with energy shortfalls in some areas possible during normal peak conditions. But at a technical conference on resource adequacy challenges, held earlier this month by the Federal Energy Regulatory Commission, MISO’s market monitor cast doubt on those conclusions. “I’d love to work with NERC to figure out where they got their numbers from, because I don’t think they’re accurate,” David Patton, president of Potomac Economics, said at the June 5 conference. According to Patton, NERC understated MISO’s capacity for demand response, behind-the-meter generation and firm capacity imports by more than 8 GW. And it considered possible power plant retirements that have not occurred, he said. “Following an in-depth review, NERC found that MISO submitted mismatched data, which overstated the near-term energy shortfall risk,” the reliability organization said.  The grid operator is exploring the cause for the mismatched data, it said. “We are in close contact with NERC and will provide an update as we learn

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AI is coming for grid decision making. Here’s why governance can’t be an afterthought.

Brandon N. Owens is the founder AIxEnergy, an independent thought leadership platform. I have spent the past two decades analyzing energy systems — across corridors, markets and control rooms. If there is one pattern that repeats, it’s this: technology moves faster than governance. Today, artificial intelligence is on the cusp of reshaping how we forecast demand, dispatch energy, manage outages and allocate investment across the grid. But while the technology races ahead, the frameworks to guide it have barely begun to form. What we’re witnessing is not just digital transformation. It is cognitive infrastructure — a system that anticipates, learns and optimizes. In some control centers, AI is already being used to balance distributed energy, identify faults and forecast system stress. In others, it is guiding major capital decisions based on probabilistic scenario modeling. And soon, these systems may be making ethical decisions — without ever being trained in ethics. The risk is not some science-fiction singularity. It is something far more practical: optimization without deliberation. Imagine an AI model designed to restore power after an outage. If it is trained solely to maximize economic productivity, it may prioritize large warehouses over nursing homes — not out of malice, but because that’s what the objective function rewards. Or consider forecasting algorithms that perpetuate underinvestment in low-income neighborhoods because historical usage was low — not because demand is low, but because access has been limited. These are not hypothetical edge cases. They are quietly becoming part of real-world grid operations — often buried deep within optimization engines, procurement models and DER orchestration platforms. The problem isn’t that AI is malfunctioning. The problem is that it’s working exactly as designed — and we haven’t designed it to align with public values. The industry has been here before. For much of the 20th

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Can Intel cut its way to profit with factory layoffs?

Matt Kimball, principal analyst at Moor Insights & Strategy, said, “While I’m sure tariffs have some impact on Intel’s layoffs, this is actually pretty simple — these layoffs are largely due to the financial challenges Intel is facing in terms of declining revenues.” The move, he said, “aligns with what the company had announced some time back, to bring expenses in line with revenues. While it is painful, I am confident that Intel will be able to meet these demands, as being able to produce quality chips in a timely fashion is critical to their comeback in the market.”  Intel, said Kimball, “started its turnaround a few years back when ex-CEO Pat Gelsinger announced its five nodes in four years plan. While this was an impressive vision to articulate, its purpose was to rebuild trust with customers, and to rebuild an execution discipline. I think the company has largely succeeded, but of course the results trail a bit.” Asked if a combination of layoffs and the moving around of jobs will affect the cost of importing chips, Kimball predicted it will likely not have an impact: “Intel (like any responsible company) is extremely focused on cost and supply chain management. They have this down to a science and it is so critical to margins. Also, while I don’t have insights, I would expect Intel is employing AI and/or analytics to help drive supply chain and manufacturing optimization.” The company’s number one job, he said, “is to deliver the highest quality chips to its customers — from the client to the data center. I have every confidence it will not put this mandate at risk as it considers where/how to make the appropriate resourcing decisions. I think everybody who has been through corporate restructuring (I’ve been through too many to count)

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Intel appears stuck between ‘a rock and a hard place’

Intel, said Kimball, “started its turnaround a few years back when ex-CEO Pat Gelsinger announced its five nodes in four years plan. While this was an impressive vision to articulate, its purpose was to rebuild trust with customers, and to rebuild an execution discipline. I think the company has largely succeeded, but of course the results trail a bit.” Asked if a combination of layoffs and the moving around of jobs will affect the cost of importing chips, Kimball predicted it will likely not have an impact: “Intel (like any responsible company) is extremely focused on cost and supply chain management. They have this down to a science and it is so critical to margins. Also, while I don’t have insights, I would expect Intel is employing AI and/or analytics to help drive supply chain and manufacturing optimization.” The company’s number one job, he said, “is to deliver the highest quality chips to its customers — from the client to the data center. I have every confidence it will not put this mandate at risk as it considers where/how to make the appropriate resourcing decisions. I think everybody who has been through corporate restructuring (I’ve been through too many to count) realizes that, when planning for these, ensuring the resilience of these mission critical functions is priority one.”  Added Bickley, “trimming the workforce, delaying construction of the US fab plants, and flattening the decision structure of the organization are prudent moves meant to buy time in the hopes that their new chip designs and foundry processes attract new business.”

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Next-gen AI chips will draw 15,000W each, redefining power, cooling, and data center design

“Dublin imposed a 2023 moratorium on new data centers, Frankfurt has no new capacity expected before 2030, and Singapore has just 7.2 MW available,” said Kasthuri Jagadeesan, Research Director at Everest Group, highlighting the dire situation. Electricity: the new bottleneck in AI RoI As AI modules push infrastructure to its limits, electricity is becoming a critical driver of return on investment. “Electricity has shifted from a line item in operational overhead to the defining factor in AI project feasibility,” Gogia noted. “Electricity costs now constitute between 40–60% of total Opex in modern AI infrastructure, both cloud and on-prem.” Enterprises are now forced to rethink deployment strategies—balancing control, compliance, and location-specific power rates. Cloud hyperscalers may gain further advantage due to better PUE, renewable access, and energy procurement models. “A single 15,000-watt module running continuously can cost up to $20,000 annually in electricity alone, excluding cooling,” said Manish Rawat, analyst at TechInsights. “That cost structure forces enterprises to evaluate location, usage models, and platform efficiency like never before.” The silicon arms race meets the power ceiling AI chip innovation is hitting new milestones, but the cost of that performance is no longer just measured in dollars or FLOPS — it’s in kilowatts. The KAIST TeraLab roadmap demonstrates that power and heat are becoming dominant factors in compute system design. The geography of AI, as several experts warn, is shifting. Power-abundant regions such as the Nordics, the Midwest US, and the Gulf states are becoming magnets for data center investments. Regions with limited grid capacity face a growing risk of becoming “AI deserts.”

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Edge reality check: What we’ve learned about scaling secure, smart infrastructure

Enterprises are pushing cloud resources back to the edge after years of centralization. Even as major incumbents such as Google, Microsoft, and AWS pull more enterprise workloads into massive, centralized hyperscalers, use cases at the edge increasingly require nearby infrastructure—not a long hop to a centralized data center—to take advantage of the torrents of real-time data generated by IoT devices, sensor networks, smart vehicles, and a panoply of newly connected hardware. Not long ago, the enterprise edge was a physical one. The central data center was typically located in or very near the organization’s headquarters. When organizations sought to expand their reach, they wanted to establish secure, speedy connections to other office locations, such as branches, providing them with fast and reliable access to centralized computing resources. Vendors initially sold MPLS, WAN optimization, and SD-WAN as “branch office solutions,” after all. Lesson one: Understand your legacy before locking in your future The networking model that connects centralized cloud resources to the edge via some combination of SD-WAN, MPLS, or 4G reflects a legacy HQ-branch design. However, for use cases such as facial recognition, gaming, or video streaming, old problems are new again. Latency, middle-mile congestion, and the high cost of bandwidth all undermine these real-time edge use cases.

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Cisco capitalizes on Isovalent buy, unveils new load balancer

The customer deploys the Isovalent Load Balancer control plane via automation and configures the desired number of virtual load-balancer appliances, Graf said. “The control plane automatically deploys virtual load-balancing appliances via the virtualization or Kubernetes platform. The load-balancing layer is self-healing and supports auto-scaling, which means that I can replace unhealthy instances and scale out as needed. The load balancer supports powerful L3-L7 load balancing with enterprise capabilities,” he said. Depending on the infrastructure the load balancer is deployed into, the operator will deploy the load balancer using familiar deployment methods. In a data center, this will be done using a standard virtualization automation installation such as Terraform or Ansible. In the public cloud, the load balancer is deployed as a public cloud service. In Kubernetes and OpenShift, the load balancer is deployed as a Kubernetes Deployment/Operator, Graf said.  “In the future, the Isovalent Load Balancer will also be able to run on top of Cisco Nexus smart switches,” Graf said. “This means that the Isovalent Load Balancer can run in any environment, from data center, public cloud, to Kubernetes while providing a consistent load-balancing layer with a frictionless cloud-native developer experience.” Cisco has announced a variety of smart switches over the past couple of months on the vendor’s 4.8T capacity Silicon One chip. But the N9300, where Isovalent would run, includes a built-in programmable data processing unit (DPU) from AMD to offload complex data processing work and free up the switches for AI and large workload processing. For customers, the Isovalent Load Balancer provides consistent load balancing across infrastructure while being aligned with Kubernetes as the future for infrastructure. “A single load-balancing solution that can run in the data center, in public cloud, and modern Kubernetes environments. This removes operational complexity, lowers cost, while modernizing the load-balancing infrastructure in preparation

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Oracle’s struggle with capacity meant they made the difficult but responsible decisions

IDC President Crawford Del Prete agreed, and said that Oracle senior management made the right move, despite how difficult the situation is today. “Oracle is being incredibly responsible here. They don’t want to have a lot of idle capacity. That capacity does have a shelf life,” Del Prete said. CEO Katz “is trying to be extremely precise about how much capacity she puts on.” Del Prete said that, for the moment, Oracle’s capacity situation is unique to the company, and has not been a factor with key rivals AWS, Microsoft, and Google. During the investor call, Katz said that her team “made engineering decisions that were much different from the other hyperscalers and that were better suited to the needs of enterprise customers, resulting in lower costs to them and giving them deployment flexibility.” Oracle management certainly anticipated a flurry of orders, but Katz said that she chose to not pay for expanded capacity until she saw finalized “contracted noncancelable bookings.” She pointed to a huge capex line of $9.1 billion and said, “the vast majority of our capex investments are for revenue generating equipment that is going into data centers and not for land or buildings.”

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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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