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See stunning first images from the Vera C. Rubin Observatory

The first spectacular images taken by the Vera C. Rubin Observatory have been released for the world to peruse: a panoply of iridescent galaxies and shimmering nebulas. “This is the dawn of the Rubin Observatory,” says Meg Schwamb, a planetary scientist and astronomer at Queen’s University Belfast in Northern Ireland. Much has been written about the observatory’s grand promise: to revolutionize our understanding of the cosmos by revealing a once-hidden population of far-flung galaxies, erupting stars, interstellar objects, and elusive planets. And thanks to its unparalleled technical prowess, few doubted its ability to make good on that. But over the past decade, during its lengthy construction period, “everything’s been in the abstract,” says Schwamb. Today, that promise has become a staggeringly beautiful reality.  Rubin’s view of the universe is unlike any that preceded it—an expansive vision of the night sky replete with detail, including hazy envelopes of matter coursing around galaxies and star-paved bridges arching between them. “These images are truly stunning,” says Pedro Bernardinelli, an astronomer at the University of Washington. During its brief perusal of the night sky, Rubin even managed to spy more than 2,000 never-before-seen asteroids, demonstrating that it should be able to spotlight even the sneakiest denizens, and darkest corners, of our own solar system. Today’s reveal is a mere amuse-bouche compared with what’s to come: Rubin, funded by the US National Science Foundation and the Department of Energy, is set for at least 10 years of planned observations. But this moment, and these glorious inaugural images, are worth celebrating for what they represent: the culmination of over a decade of painstaking work.  “This is a direct demonstration that Rubin is no longer in the future,” says Bernardinelli. “It’s the present.” The observatory is named after the late Vera Rubin, an astronomer who uncovered strong evidence for dark matter, a mysterious and as-yet-undetected something that’s binding galaxies together more strongly than the gravity of ordinary, visible matter alone can explain. Trying to make sense of dark matter—and its equally mysterious, universe-stretching cousin, dubbed dark energy—is a monumental task, one that cannot be addressed by just one line of study or scrutiny of one type of cosmic object. That’s why Rubin was designed to document anything and everything that shifts or sparkles in the night sky. Sitting atop Chile’s Cerro Pachón mountain range, it boasts a 7,000-pound, 3,200-megapixel digital camera that can take detailed snapshots of a large patch of the night sky; a house-size cradle of mirrors that can drink up extremely distant and faint starlight; and a maze of joints and pistons that allow it to swivel about with incredible speed and precision. A multinational computer network permits its sky surveys to be largely automated, its images speedily processed, any new objects easily detected, and the relevant groups of astronomers quickly alerted. All that technical wizardry allows Rubin to take a picture of the entire visible night sky once every few days, filling in the shadowed gaps and unseen activity between galaxies. “The sky [isn’t] static. There are asteroids zipping by, and supernovas exploding,” says Yusra AlSayyad, Rubin’s overseer of image processing. By conducting a continuous survey over the next decade, the facility will create a three-dimensional movie of the universe’s ever-changing chaos that could help address all sorts of astronomic queries. What were the very first galaxies like? How did the Milky Way form? Are there planets hidden in our own solar system’s backyard? Rubin’s first glimpse of the firmament is predictably bursting with galaxies and stars. But the resolution, breadth, and depth of the images have taken astronomers aback. “I’m very impressed with these images. They’re really incredible,” says Christopher Conselice, an extragalactic astronomer at the University of Manchester in England. One shot, created from 678 individual exposures, showcases the Trifid and Lagoon nebulas—two oceans of luminescent gas and dust where stars are born. Others depict a tiny portion of Rubin’s view of the Virgo Cluster, a zoo of galaxies. Hues of blue are coming from relatively nearby whirlpools of stars, while red tints emanate from remarkably distant and primeval galaxies.  A small section of the Vera C. Rubin Observatory’s view of the Virgo Cluster. Three merging galaxies can be seen on the upper right. The view also includes two striking spiral galaxies (lower right), distant galaxies, and many Milky Way stars.NSF-DOE VERA C. RUBIN OBSERVATORY The rich detail in these images is already proving to be illuminating. “As galaxies merge and interact, the galaxies are pulling stars away from each other,” says Conselice. This behavior can be seen in plumes of diffuse light erupting from several galaxies, creating halos around them or illuminated bridges between them—records of these ancient galaxies’ pasts. Images like these are also likely to contain several supernovas, the explosive final moments of sizable stars. Not only do supernovas seed the cosmos with all the heavy elements that planets—and life—rely on, but they can also hint at how the universe has expanded over time.  Anais Möller, an astrophysicist at the Swinburne University of Technology in Melbourne, Australia, is a supernova hunter. “I search for exploding stars in very far away galaxies,” she says. Older sky surveys have found plenty, but they can lack context: You can see the explosion, but not what galaxy it’s from. Thanks to Rubin’s resolution—amply demonstrated by the Virgo Cluster set of images—astronomers can now “find where those exploding stars live,” says Möller. Another small section of the observatory’s view of the Virgo Cluster. The image includes many distant galaxies along with stars from our own Milky Way galaxy. NSF-DOE VERA C. RUBIN OBSERVATORY While taking these images of the distant universe, Rubin also discovered 2,104 asteroids flitting about in our own solar system—including seven whose orbits hew close to Earth’s own. This number may sound impressive, but it’s just par for the course for Rubin. In just a few months, it will find over a million new asteroids—doubling the current known tally. And over the course of its decadal survey, Rubin is projected to identify 89,000 near-Earth asteroids, 3.7 million asteroids in the belt between Mars and Jupiter, and 32,000 icy objects beyond Neptune.  Finding more than 2,000 previously hidden asteroids in just a few hours of observations, then, “wasn’t even hard” for Rubin, says Mario Jurić, an astronomer at the University of Washington. “The asteroids really popped out.” Rubin’s comprehensive inventorying of the solar system has two benefits. The first is scientific: All those lumps of rocks and ice are the remnants of the solar system’s formative days, which means astronomers can use them to understand how everything around us was pieced together.  The second benefit is security. Somewhere out there, there could be an asteroid on an Earthbound trajectory—one whose impact could devastate an entire city or even several countries. Engineers are working on defensive tech designed to either deflect or obliterate such asteroids, but if astronomers don’t know where they are, those defenses are useless. In quickly finding so many asteroids, Rubin has clearly shown that it will bolster Earth’s planetary defense capabilities like no other ground-based telescope. Altogether, Rubin’s debut has validated the hopes of countless astronomers: The observatory won’t just be an incremental improvement on what’s come before. “I think it’s a generational leap,” says Möller. It is a ruthlessly efficient, discovery-making behemoth—and a firehose of astronomic delights is about to inundate the scientific community. “It’s very scary,” says Möller. “But very exciting at the same time.” It’s going to be a very hectic decade. As Schwamb puts it, “The roller-coaster starts now.”

The first spectacular images taken by the Vera C. Rubin Observatory have been released for the world to peruse: a panoply of iridescent galaxies and shimmering nebulas. “This is the dawn of the Rubin Observatory,” says Meg Schwamb, a planetary scientist and astronomer at Queen’s University Belfast in Northern Ireland.

Much has been written about the observatory’s grand promise: to revolutionize our understanding of the cosmos by revealing a once-hidden population of far-flung galaxies, erupting stars, interstellar objects, and elusive planets. And thanks to its unparalleled technical prowess, few doubted its ability to make good on that. But over the past decade, during its lengthy construction period, “everything’s been in the abstract,” says Schwamb.

Today, that promise has become a staggeringly beautiful reality. 

Rubin’s view of the universe is unlike any that preceded it—an expansive vision of the night sky replete with detail, including hazy envelopes of matter coursing around galaxies and star-paved bridges arching between them. “These images are truly stunning,” says Pedro Bernardinelli, an astronomer at the University of Washington.

During its brief perusal of the night sky, Rubin even managed to spy more than 2,000 never-before-seen asteroids, demonstrating that it should be able to spotlight even the sneakiest denizens, and darkest corners, of our own solar system.

Today’s reveal is a mere amuse-bouche compared with what’s to come: Rubin, funded by the US National Science Foundation and the Department of Energy, is set for at least 10 years of planned observations. But this moment, and these glorious inaugural images, are worth celebrating for what they represent: the culmination of over a decade of painstaking work. 

“This is a direct demonstration that Rubin is no longer in the future,” says Bernardinelli. “It’s the present.”

The observatory is named after the late Vera Rubin, an astronomer who uncovered strong evidence for dark matter, a mysterious and as-yet-undetected something that’s binding galaxies together more strongly than the gravity of ordinary, visible matter alone can explain. Trying to make sense of dark matter—and its equally mysterious, universe-stretching cousin, dubbed dark energy—is a monumental task, one that cannot be addressed by just one line of study or scrutiny of one type of cosmic object.

That’s why Rubin was designed to document anything and everything that shifts or sparkles in the night sky. Sitting atop Chile’s Cerro Pachón mountain range, it boasts a 7,000-pound, 3,200-megapixel digital camera that can take detailed snapshots of a large patch of the night sky; a house-size cradle of mirrors that can drink up extremely distant and faint starlight; and a maze of joints and pistons that allow it to swivel about with incredible speed and precision. A multinational computer network permits its sky surveys to be largely automated, its images speedily processed, any new objects easily detected, and the relevant groups of astronomers quickly alerted.

All that technical wizardry allows Rubin to take a picture of the entire visible night sky once every few days, filling in the shadowed gaps and unseen activity between galaxies. “The sky [isn’t] static. There are asteroids zipping by, and supernovas exploding,” says Yusra AlSayyad, Rubin’s overseer of image processing. By conducting a continuous survey over the next decade, the facility will create a three-dimensional movie of the universe’s ever-changing chaos that could help address all sorts of astronomic queries. What were the very first galaxies like? How did the Milky Way form? Are there planets hidden in our own solar system’s backyard?

Rubin’s first glimpse of the firmament is predictably bursting with galaxies and stars. But the resolution, breadth, and depth of the images have taken astronomers aback. “I’m very impressed with these images. They’re really incredible,” says Christopher Conselice, an extragalactic astronomer at the University of Manchester in England.

One shot, created from 678 individual exposures, showcases the Trifid and Lagoon nebulas—two oceans of luminescent gas and dust where stars are born. Others depict a tiny portion of Rubin’s view of the Virgo Cluster, a zoo of galaxies. Hues of blue are coming from relatively nearby whirlpools of stars, while red tints emanate from remarkably distant and primeval galaxies. 

A small section of the Vera C. Rubin Observatory’s view of the Virgo Cluster. Three merging galaxies can be seen on the upper right. The view also includes two striking spiral galaxies (lower right), distant galaxies, and many Milky Way stars.
NSF-DOE VERA C. RUBIN OBSERVATORY

The rich detail in these images is already proving to be illuminating. “As galaxies merge and interact, the galaxies are pulling stars away from each other,” says Conselice. This behavior can be seen in plumes of diffuse light erupting from several galaxies, creating halos around them or illuminated bridges between them—records of these ancient galaxies’ pasts.

Images like these are also likely to contain several supernovas, the explosive final moments of sizable stars. Not only do supernovas seed the cosmos with all the heavy elements that planets—and life—rely on, but they can also hint at how the universe has expanded over time. 

Anais Möller, an astrophysicist at the Swinburne University of Technology in Melbourne, Australia, is a supernova hunter. “I search for exploding stars in very far away galaxies,” she says. Older sky surveys have found plenty, but they can lack context: You can see the explosion, but not what galaxy it’s from. Thanks to Rubin’s resolution—amply demonstrated by the Virgo Cluster set of images—astronomers can now “find where those exploding stars live,” says Möller.

Another small section of the observatory’s view of the Virgo Cluster. The image includes many distant galaxies along with stars from our own Milky Way galaxy.
NSF-DOE VERA C. RUBIN OBSERVATORY

While taking these images of the distant universe, Rubin also discovered 2,104 asteroids flitting about in our own solar system—including seven whose orbits hew close to Earth’s own. This number may sound impressive, but it’s just par for the course for Rubin. In just a few months, it will find over a million new asteroids—doubling the current known tally. And over the course of its decadal survey, Rubin is projected to identify 89,000 near-Earth asteroids, 3.7 million asteroids in the belt between Mars and Jupiter, and 32,000 icy objects beyond Neptune. 

Finding more than 2,000 previously hidden asteroids in just a few hours of observations, then, “wasn’t even hard” for Rubin, says Mario Jurić, an astronomer at the University of Washington. “The asteroids really popped out.”

Rubin’s comprehensive inventorying of the solar system has two benefits. The first is scientific: All those lumps of rocks and ice are the remnants of the solar system’s formative days, which means astronomers can use them to understand how everything around us was pieced together. 

The second benefit is security. Somewhere out there, there could be an asteroid on an Earthbound trajectory—one whose impact could devastate an entire city or even several countries. Engineers are working on defensive tech designed to either deflect or obliterate such asteroids, but if astronomers don’t know where they are, those defenses are useless. In quickly finding so many asteroids, Rubin has clearly shown that it will bolster Earth’s planetary defense capabilities like no other ground-based telescope.

Altogether, Rubin’s debut has validated the hopes of countless astronomers: The observatory won’t just be an incremental improvement on what’s come before. “I think it’s a generational leap,” says Möller. It is a ruthlessly efficient, discovery-making behemoth—and a firehose of astronomic delights is about to inundate the scientific community. “It’s very scary,” says Möller. “But very exciting at the same time.”

It’s going to be a very hectic decade. As Schwamb puts it, “The roller-coaster starts now.”

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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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