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VFXEXPRESS.COMThe Last of Us Season 2 — Behind the ScenesStep into the world of The Last of Us Season 2 as Max unveils an exclusive look at the making of its premiere episode. Featuring insights from stars Pedro Pascal and Bella Ramsey, along with creators Craig Mazin and Neil Druckmann, this behind-the-scenes special explores how the team continues to expand the post-apocalyptic universe. From emotional performances to detailed set design, every frame reflects the same raw intensity and care that made the first season unforgettable. Dive into the creative choices, storytelling evolution, and the technical craftsmanship that bring this gripping world to life. Season 2 promises deeper character arcs, haunting new locations, and the same heart-wrenching survival journey. The post The Last of Us Season 2 — Behind the Scenes appeared first on Vfxexpress.0 Kommentare 0 Anteile 18 Ansichten
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WWW.FASTCOMPANY.COMThese new EV chargers could have been installed quickly. Then came TrumpNear Atlanta, the diverse suburb of Morrow, Georgia, is an EV charging desert. If you live in an apartment in one neighborhood and own an electric car, you might have to drive 20 minutes to get to a public charger. That’s why a local green bank wanted to support a new charging station in the area. It should have been a simple project, beginning with a small group of six chargers. Then came Trump. “We’re talking about a project that could have been up and running by now,” says Reginald Parker, president of Freedmen Capital Foundation, a green bank in Georgia. “It had a month’s delay. Over the last month, prices have gone up. The market has changed tremendously. And that type of uncertainty for the project adds costs that small businesses, in general, are not ready for.” Exactly the type of project that the green bank wanted to support Thanks to the Inflation Reduction Act, the bipartisan bill that Congress passed in 2022, there was funding for the work. Last year, the first national green bank opened with $5 billion in funding from the IRA. The organization started creating a network of state and local green banks. (Despite the name, these aren’t typical banks with deposits. Instead, they’re institutions that make green loans for projects like community solar installations or green building retrofits.) Freedman Capital Foundation, named after a late-1800s bank established for formerly enslaved people, was chosen to be part of the network. The new charging station was exactly the type of project that the green bank wanted to support. “The communities that are EV charging deserts are the first and hardest hit by climate impacts,” Parker says. Helping residents switch to EVs can help cut emissions. It can also reduce air pollution and help people save money on fuel. “It also builds energy independence,” he says. “Oil and gas are derived from some foreign sources. Electricity is all domestic.” One part of the charger project had already been funded. A grant from the Department of Transportation helped cover the cost for the local utility to set up the electric infrastructure needed for the chargers. The small organization that will operate the charging station, called TABT, is paying to install the chargers. The last piece of the funding—the money to cover a loan for the equipment—came from the EPA’s Greenhouse Gas Reduction Fund, a program created by the IRA. Trump pauses IRA funds On his first day in office, Trump issued an executive order telling agencies to pause all funds under the IRA. At first, grantees under the EPA program could still access the money sitting in their accounts. But in February, Trump-appointed EPA administrator Lee Zeldin said that the EPA would revoke contracts for the fund. The agency made baseless accusations of fraud. It froze $20 billion in grants. Citibank, directed by the government, froze the money in the account of Coalition for Green Capital, the nonprofit running the national green bank. Freedmen Capital Foundation was able to get its funds from the nonprofit just before that account was frozen. But the EPA warned it not to move forward on projects. “Everything had to stop,” says Parker. At the same time, some of the EPA’s grantees, including the Coalition for Green Capital, sued to force Citibank to unfreeze the money. A federal judge blocked the freeze. Appeals are still underway, and the money at Citibank still isn’t accessible. But the first court order meant that Freedmen was able to begin using the money it already had. (Another piece of its funds, for technical assistance, got stuck in the freeze.) In March, the utility finished upgrading the electric infrastructure needed for the chargers. If the project had happened normally, TABT could have ordered the chargers in advance. Installation could have started right away; the process could have taken as little as a week, and the chargers could be in use now. But because of the delays from the EPA’s actions, nothing was ready to go. ‘Instead of making investments, we are wasting time and resources’ Freedmen Capital Foundation has been scrambling to finalize the loan for the project. Trump’s chaotic rollout of tariffs means that the cost of supplies for making EV chargers—from steel to electronics—will jump. “If we weren’t able to move within the next week or two, the owner would be subjected to higher prices,” Parker says. Despite the delays, the project is unusual in that it’s able to move forward. Most projects that were set to receive funding through the Greenhouse Gas Reduction Fund are now stuck in limbo, waiting for the next stage in a lawsuit. A judge may issue a preliminary injunction this week that allows organizations to access their money, though the government will immediately appeal and could try to claw the money back. “From solar energy in Arkansas to hydropower in Alaska, local projects that lower energy costs and support domestic manufacturing aren’t currently able to move forward, forcing communities to wait for the jobs and economic opportunity they’re counting on,” says Brooke Durham, a spokesperson for Climate United, a nonprofit that received a $6.97 billion Greenhouse Gas Reduction Fund grant that was frozen. “Instead of making investments and delivering on those promises, we are wasting time and resources fighting an unnecessary battle in court. This program isn’t about politics; it’s about saving money for hard-working Americans who are struggling to pay for groceries and keep the lights on.”0 Kommentare 0 Anteile 23 Ansichten
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WWW.YANKODESIGN.COMRunning Shoes-Inspired Handheld Cooling Mist Spray Keeps Runners Cool While MovingThe battle against heat during intense physical activity is one that every athlete knows all too well. While hydration remains the cornerstone of temperature regulation, managing external body heat presents an equally critical challenge that can’t be solved by water intake alone. Traditional methods like splashing water on your face require stopping mid-stride, a compromise few serious runners are willing to make when every second counts in training or competition. As global temperatures continue to rise, cooling mist sprays have emerged as a practical solution for athletes seeking relief without breaking stride. The science behind these products is straightforward yet effective: when fine water droplets contact your overheated skin, they quickly evaporate, drawing heat away from your body through the process of evaporative cooling. This physiological hack can significantly reduce perceived exertion and discomfort, potentially extending performance in challenging conditions. Designers: Seungyeol Yi, Suah Kim, Youngbeen Seo (Intenxiv Inc) Current cooling mist options, however, present a design problem for runners. Most portable sprays come in conventional bottle formats that prove awkward to grip while maintaining pace. The fumbling required to locate spray nozzles and operate mechanisms often disrupts rhythm and focus, precisely what athletes work so hard to maintain during training sessions and races. This gap between function and usability inspired a fresh approach to cooling technology. The new handheld cooling mist concept draws inspiration from performance running shoes, particularly those from On Running with their distinctive cloud-like cushioning. Rather than adopting the traditional bottle shape, this design features a soft, deformed square with a large opening near the bottom, creating the visual impression of a small, fluffy cloud in your hand. The metaphor extends beyond aesthetics to function, delivering a light, refreshing mist that mimics running through a cool morning fog. The exterior surface employs cushioned materials reminiscent of running shoe soles, providing a tactile experience that feels natural in an athlete’s grip. The operation couldn’t be simpler: a gentle squeeze on the top surface releases a fine cooling mist, eliminating the need to locate nozzles or buttons mid-stride. This intuitive design allows runners to maintain focus on their performance rather than fumbling with equipment when heat stress begins to build. Beyond its functional benefits, the concept’s sporty aesthetic speaks directly to its intended users. The form language borrows from athletic equipment rather than personal care products, signaling its purpose as performance gear rather than a cosmetic accessory. This deliberate design choice helps position the product within the athlete’s essential toolkit, alongside specialized footwear, moisture-wicking apparel, and performance-monitoring devices. The post Running Shoes-Inspired Handheld Cooling Mist Spray Keeps Runners Cool While Moving first appeared on Yanko Design.0 Kommentare 0 Anteile 23 Ansichten
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WWW.CREATIVEBLOQ.COM'Great brands retain a degree of mystery’: a day in the life of Julian KyanstonPropaganda’s founder discusses the key to building a brilliant brand.0 Kommentare 0 Anteile 14 Ansichten
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WWW.WIRED.COMSmishing Triad: The Scam Group Stealing the World’s RichesMillions of scam text messages are sent every month. The Chinese cybercriminals behind many of them are expanding their operations—and quickly innovating.0 Kommentare 0 Anteile 12 Ansichten
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WWW.NYTIMES.COMTrump Wants to Reverse Coal’s Long Decline. It Won’t be Easy.Coal has been displaced by cheap and plentiful natural gas and the rapid growth of wind and solar energy — forces that President Trump will struggle to do away with.0 Kommentare 0 Anteile 14 Ansichten
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WWW.COMPUTERWORLD.COMDiscover Financial Services exec: GenAI isn’t yet ready for prime timeAs generative AI (genAI) tools grow in adoption and sophistication, Fortune 500 companies are finding they can rely more on data to drive decisions and improve operations. For more than two years, Discover Financial Services — one of those Fortune 500 companies — has explored how it can use genAI to improve quality and create efficiencies. But in a heavily regulated industry like financial services, protecting sensitive customer data always comes first, which has hampered the arrival of more advanced use cases for genAI. Coupled with the arrival of agentic AI — a more autonomous version of genAI that can make independent decisions with far less human oversight — the combination can be the thing of nightmares. Computerworld spoke with Keith Toney, president of Credit and Decision Management at Discover Financial Services (DFS) and a member of the company’s executive committee, about what the company has been doing and what it’s learned. Toney, who also serves as co-president for all of Consumer Banking, has helped lead efforts to bring about enterprise-wide adoption of advanced decision science. After starting at Discover Financial Services in 2019 as the Chief Data Officer responsible for the enterprise technology organization, he joined the DFS Executive Committee the following year. With more than 25 years of experience in financial services, analytics, and the economics of risk pooling, Toney specializes in emerging technologies in big data, AI, machine learning, data visualization capabilities, data governance, and data security. He leads an area called decisions and analytics and reports directly to DFS’s CEO J. Michael Sheppard. The following are excerpts from the interview with Toney. srcset="https://b2b-contenthub.com/wp-content/uploads/2025/04/Keith-Toney-Headshot-2.jpg?quality=50&strip=all 1237w, https://b2b-contenthub.com/wp-content/uploads/2025/04/Keith-Toney-Headshot-2.jpg?resize=300%2C291&quality=50&strip=all 300w, https://b2b-contenthub.com/wp-content/uploads/2025/04/Keith-Toney-Headshot-2.jpg?resize=768%2C745&quality=50&strip=all 768w, https://b2b-contenthub.com/wp-content/uploads/2025/04/Keith-Toney-Headshot-2.jpg?resize=1024%2C993&quality=50&strip=all 1024w, https://b2b-contenthub.com/wp-content/uploads/2025/04/Keith-Toney-Headshot-2.jpg?resize=718%2C697&quality=50&strip=all 718w, https://b2b-contenthub.com/wp-content/uploads/2025/04/Keith-Toney-Headshot-2.jpg?resize=173%2C168&quality=50&strip=all 173w, https://b2b-contenthub.com/wp-content/uploads/2025/04/Keith-Toney-Headshot-2.jpg?resize=87%2C84&quality=50&strip=all 87w, https://b2b-contenthub.com/wp-content/uploads/2025/04/Keith-Toney-Headshot-2.jpg?resize=495%2C480&quality=50&strip=all 495w, https://b2b-contenthub.com/wp-content/uploads/2025/04/Keith-Toney-Headshot-2.jpg?resize=371%2C360&quality=50&strip=all 371w, https://b2b-contenthub.com/wp-content/uploads/2025/04/Keith-Toney-Headshot-2.jpg?resize=258%2C250&quality=50&strip=all 258w" width="1024" height="993" sizes="(max-width: 1024px) 100vw, 1024px">Keith Toney Discover Financial Services So, we’ve not spoken before, but I have spoken to Disover Financial Services about its use of AI. How have you been involved in that tech rollout? “I think you had a conversation with one of my direct reports a bit ago, Raghu Kulkarni, who is kind of the chief data scientist, but I lead this area. I have about 1,500 people in my organization, and we’re doing machine learning and analytics, data work and insight generation. “It’s probably best to describe it as both a horizontal and a vertical, which is a little bit funny and a little bit unique. Horizontal being that we do work all across the bank, all across the value chain, from brand and marketing all the way through to collections and recovery. So, if you think about the life cycle of a consumer with … lending products or banking products — that whole value chain— that whole horizontal, I have. “The vertical part, though, is also interesting. I hold business responsibility for things like credit, which is the primary thing that you do in lending — make underwriting or credit decision, that’s part of my responsibility. That includes all the machine learning models that make the decision on whether or not we’re going to give you a credit card or a personal loan or a home equity line of credit, or make decisions in the checking and deposit space, the credit fraud collection strategy, the digital and mobile teams and so forth. All those algorithms are all part of my responsibility. “The principle argument for all of that is that as a direct-to-consumer digital bank, so much of what we do is run off these algorithms. So, we decided to bring that together under a common leadership structure.” That’s exactly the challenges a lot of entities are having right now with genAI tools — integrating them with existing applications. Salesforce, for example, has infused AI into its software. And you might have your own instance of AI that you’ve created, and you want that to be able to speak to the AI in the your Salesforce platform. How did you prepare your infrastructure, your data, for the introduction of AI? “We’re not in the business of building a new big LLM. We’re, going to buy that from a vendor. But we’re tailoring them. We’re refining them. There’s a process of fine-tuning these models to have it interact within the data that’s within the company, and that data may not be organized for that purpose. When we were capturing it, we weren’t really thinking about tagging it and structuring it and organizing it in the way that makes it as accessible for these kind of tools to work. “So, we’re piloting several things. We do a lot of work alongside [our CIO] in making custom-fit models, working in certain kind of use cases. But we’re also using Salesforce and Microsoft Copilot. We’re a Microsoft shop. “We’re rolling out Copilot, and we’ve had to go through a lot of work to make sure we’ve been thoughtful about data classification, restricted data structures and so forth, so that we’re making it available to the larger part of the organization. At the same time, we’re ensuring we’re still protecting restricted and secure data.” Let’s talk about data classification, data structures, security, and setting up guardrails, because we know you can’t just set it and forget it with AI. What were some of the guardrails? What were some of the precautions you took? “So, we have a data classification scheme that has five or six levels to it. Basically, we’ve been rolling that out as an enterprise program for quite some time. “The most loose classification would be data that can be made available to the public. And then you have kind of internal and confidential data. Then you have restricted, and then restricted with supervisory information. We’re a highly regulated bank, and so we’re having a back and forth with a regulator all the time — someone in the Federal Reserve or the Office of the Comptroller, or FDIC. Those are our regulators. That’s, that’s highly classified, restricted data. So think about like that hierarchy — getting that classification structure rolled out so that all the all the data elements are essentially classified. And then looking at the directory structure, where data sits within the enterprise. “You’re probably familiar with SharePoint or OneDrive. These are Microsoft applications. But there’s others, whether you’re a Google shop or whatever. Data lives in these directory structures. Some of it is very structured data, some of it is unstructured data, like audio. We run a big call center, we record those calls. Those are audio files. That’s obviously unstructured data, but the file itself is cataloged and structured and gets tagged. And that contains sensitive, restricted data. “A lot of times we’re talking about [personally identifiable information]. So there’s a kind of a matrix of classifications and labels that lead to handling standards and what we want to make available inside of the AI environment. For example, if it’s a confidential document in one area, I don’t want Microsoft Copilot, which is kind of navigating across all of my infrastructure, to be able to go pick that up and make it available to someone who shouldn’t have access to that that document. It’s those kinds of challenges we’re facing with AI.” Have you gotten to the point where you feel comfortable rolling Copilot to all of your employees, where you still feel that that your data would be protected. “We are in the process of kind of rolling that out, and we’ve learned a lot. I think probably what you’re hearing from many folks in the industry, across all the industries, is [genAI] implementations have slowed, and it’s largely because of issues like this [navigating security, privacy and data strutures]. “And there are some areas where we’re very comfortable. We have the data in a container that we feel is super serious. There are some areas that we’ve left cordoned off, and we’re not exposing that to the application until we get further confidence on the classification scheme that there’s not data left to be discovered in those spaces and so forth. So as you can imagine, it’s just a very rational process of progressively exposing it and making it available. “So, some areas were much more comfortable. Some areas we’re still working on it.” What are some of the areas, if you can talk about them, that you’re less comfortable with? “Well, it’s a natural fallout of the description I gave you. You know all your documents in legal and compliance. We’re not necessarily mixing those with the broader implementation of Copilot, as an example. So, how you think about sensitive and highly confidential or restricted material, and then how that’s made available in the platform. We’re not a big Salesforce shop, but I think you have kind of the same issue in any platform that you want to make available. Do you have command of the restricted data, confidential data, and then things that are just like largely internal, or things that you would consider public? Where do you see the return on investment with genAI? “The top track, which I think is naive, is just around job elimination — the idea that AI is going to take over and replace jobs. I don’t feel like that will be the out-of-the-gate impact. There’s so much backlog of ideas and work and development in our business, and … in other kinds of businesses, as well. “It’s going to be some time before we get AI to the place where we’re making our existing employees so much more efficient. We’re attacking the backlog right now; adding more features and capabilities and other things to our products and services before we go to the place where we’re just looking to cut costs and reduce jobs. I just think that’s the reality of it. “I think efficiencies like that will come sooner or later, but you know, so much of the work that we do is technology, and technical. We’re using the tools to make developers more efficient and more effective in their job. But again, there’s such a backlog of work to do that that’s why I tend to challenge a little bit of the doomsday narrative — at least in the short term. For the next two or three years, that’s how I think about it.” It sounds like you think that genAI is going to help developers. Have you seen that already? And do you see at least replacing some of the lower-level developer or even mid-level developer jobs? “If I squint, I can see it. It is starting to happen. For example, if you write SQL, so just a query language against the database, it’s very easy now to have Copilot help you write that code, whereas you used to have to learn it in a different way, have a different depth of knowledge. Now, you’re able to execute code much faster, or get to working code much faster. And so you play that forward. It does seem like there’s some point in the future where that’s going to create less demand [for developers]. But in my opinion, it’s also accelerating those entry-level employees up the learning curve faster. “Job [up]-skilling is a really important piece of the conversation. I just think that some of this will naturally reach a different equilibrium in terms of the work. But again, there are so many interesting things to do improve the tech stack. Plus, obviously, we’ve got to get through the change management curve. A lot of these systems used to be somewhat more manual, or maybe based on machine learning. We’re now wanting to move them to a more of an artificial intelligence platform. “That’s not easy to do. These systems are complex. You have to be very thoughtful. And then, you have to consider that we’re in a highly regulated business. We have to be just super mindful of how it impacts consumer, and make sure that, like, we’re not putting in place something that will, you know, kind of miscalculate the kind of the outcome that you’re seeking.” Have you deployed any AI agents? “We have not. We still operate fully with a of human in the [AI] loop.” A big topic now is agentic AI — the combination of the large language models and process automation. So, the notion of having agents that can act based autonomously speaks to a great deal of potential efficiencies. Would that be something that interests you? “Yes. You can still have human supervision, but at a far lesser degree. The applications that we’re piloting and the things that we have in flight are mainly working with our human agents in the call center. These applications are largely acting as assistants that our human agents are still in command of and ultimately, the information that gets shared back with the customer, or that kind of gets shared into the process. “The AI implementations are creating acceleration of finding customer complaints or other things in the data. But we’re not yet comfortable with kind of a true agentic implementation. There’s still a lot of still a lot of tethering needed.” Tell me about your data visualization efforts. “Data visualization for us is primarily dashboarding and reporting around business performance, or consumer behavior, shopping behavior, and those kinds of things. “We’re looking for ways to see patterns in data that can help us and through visualization, take different actions. So we’re studying multivariate structures around fraud, for example. And fraudsters are constantly trying to circumvent the system to their advantage and compromise either the consumer or the system itself. So, we do a bit of data visualization and pattern recognition as part of an early warning system. If we see something that’s out of pattern, we ask if that’s a bad actor or a ring of bad actors that are kind of causing us some kind of a fraudulent issue.” So, AI is able to assist with you in that? “We’re using machine learning. So, when you say AI, if you mean large language models and generative AI, not so much — yet. We do use machine learning and other kind of graph database technologies and things that I put under the broad banner of AI — generative AI being a piece of that machine learning. “We’re exploring [genAI] for that. We’re trying to leverage the compute power that’s behind some of the generative AI and the large language work to see if we can use that to determine new patterns. One area that we’ve done a lot of work in that’s under the bigger banner up front is money laundering. We have a big responsibility to study all the transaction flow. “We need to know if there’s bad actors out there that [are] trying to launder money through the system. So we’ve been looking at AI, not only for pattern recognition in terms of anti-money laundering, but also in the support of the agents. “When we see a pattern, a lot of it then becomes research and documentation of those kind of suspected activity reports. That’s one case where we really think there’s some interesting applications of the generative AI.” Are there any other areas that you see a prominent use case for generative AI? “The biggest forefront for us on generative AI is really in the context of the call center experience and the customer experience and integrating that with the digital app and the website. Discover wins JD Power Awards for customer experience. And we think generative AI and those applications are going to be are going to be pretty powerful. I’ll tell you, though, what’s interesting is, from my perspective, there’s some areas where we don’t see it being useful in, like underwriting, credit and underwriting, which is under my responsibility. “We’re not seeing an application because of AI’s [problem with] hallucination. These are probabilistic models. They’re not deterministic. Therefore, you can ask it the same question twice, you can get a different answer. In a world where I am, if I’m underwriting to decide whether I’m going to give you a credit card, I can’t have it be — if I ask it twice — ‘Oh, I will give you one. Oh, I won’t give you one.’ “There’s some areas that clearly, depending on the sensitivity of the decision that you’re making and the implications of it, that you wouldn’t want to use generative AI. That credit underwriting one is a good example. Other things around like liquidity and trading and so forth, are other examples. “You need to understand how the [AI] models can ‘hallucinate’ and create two different answers if you ask it the same question twice. And that’s also why we think the human in the loop will stay important for some time in various scenarios.” How have you approached training your employees? What percentage of your workers have been trained on AI? “You can think of it as like concentric circles. We have a relatively small group of researchers who are super deep in generative AI, machine learning and all of that. And then we have a set of users that are in our product organization, and they’re thinking about how to leverage it. And then we have the general staff. “At the broadest level, training right now is on the usage of Copilot and some of the general tools associated with it. And then we’re training on data protection and those kinds of things. So we’re focused more on general consumption and the actual usage of the models and the development of applications, and they’re in there running the pilots. We have folks that are that are really deep in the technical mathematics of it, all the way out to folks that are general users. So we’ve had to kind of think about it in different layers.” Have you trained a large percentage of your users, or are you still in the process of figuring out who needs that training? “We’re still in the process of figuring that out. There’s an Advanced Analytic Resource Center or AARC. This is the thing that we did in downtown Chicago, where we’re taking early-in-career, out-of-college new grads and bringing them into the company through a structured training program around the tools and technologies we need, and then accelerating them through like a two-year development cycle. Then we place them in the business. That’s becoming one of the areas where we’re incubating knowledge around machine learning and generative AI.” Have you discovered where the greatest ROI in genAI may be? “In some sense it’s the classic Gartner Hype Cycle. We’re in the trough of disillusionment. I think we’ve been pretty sober about the implications of it, and we’ve been very deliberate. There’s certainly some companies that have really gone all in, but they’re in less regulated industries; they have the ability to do that in a bit more of a unconstrained way. “Given the nature of banking, and especially direct-to-consumer credit card lending and so forth, we just had to be really deliberate and thoughtful.” Where do you see the big areas that genAI and agentic AI will be of most use in the future — say two, three or five years down the road? “It’s a call center, and then the other parts of the customer experience. So, the blending of the mobile app, the mobile experience, the web experience, and then the call center experience. “I don’t think the call center experience is going to completely go away. Financial products are just too complicated, and people just need to talk to somebody to engage with that. So, first, I think it’s call center. Second is the full customer experience. And third, it’s the brand and marketing space. “Discover is a big brand, and we spend lots of money on marketing, advertising and so forth. And the content around brand and media is ripe for improvemnt with generated data.”0 Kommentare 0 Anteile 15 Ansichten
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WWW.TECHNOLOGYREVIEW.COMMeet the researchers testing the “Armageddon” approach to asteroid defenseOne day, in the near or far future, an asteroid about the length of a football stadium will find itself on a collision course with Earth. If we are lucky, it will land in the middle of the vast ocean, creating a good-size but innocuous tsunami, or in an uninhabited patch of desert. But if it has a city in its crosshairs, one of the worst natural disasters in modern times will unfold. As the asteroid steams through the atmosphere, it will begin to fragment—but the bulk of it will likely make it to the ground in just a few seconds, instantly turning anything solid into a fluid and excavating a huge impact crater in a heartbeat. A colossal blast wave, akin to one unleashed by a large nuclear weapon, will explode from the impact site in every direction. Homes dozens of miles away will fold like cardboard. Millions of people could die. Fortunately for all 8 billion of us, planetary defense—the science of preventing asteroid impacts—is a highly active field of research. Astronomers are watching the skies, constantly on the hunt for new near-Earth objects that might pose a threat. And others are actively working on developing ways to prevent a collision should we find an asteroid that seems likely to hit us. We already know that at least one method works: ramming the rock with an uncrewed spacecraft to push it away from Earth. In September 2022, NASA’s Double Asteroid Redirection Test, or DART, showed it could be done when a semiautonomous spacecraft the size of a small car, with solar panel wings, was smashed into an (innocuous) asteroid named Dimorphos at 14,000 miles per hour, successfully changing its orbit around a larger asteroid named Didymos. But there are circumstances in which giving an asteroid a physical shove might not be enough to protect the planet. If that’s the case, we could need another method, one that is notoriously difficult to test in real life: a nuclear explosion. Scientists have used computer simulations to explore this potential method of planetary defense. But in an ideal world, researchers would ground their models with cold, hard, practical data. Therein lies a challenge. Sending a nuclear weapon into space would violate international laws and risk inflaming political tensions. What’s more, it could do damage to Earth: A rocket malfunction could send radioactive debris into the atmosphere. Over the last few years, however, scientists have started to devise some creative ways around this experimental limitation. The effort began in 2023, with a team of scientists led by Nathan Moore, a physicist and chemical engineer at the Sandia National Laboratories in Albuquerque, New Mexico. Sandia is a semi-secretive site that serves as the engineering arm of America’s nuclear weapons program. And within that complex lies the Z Pulsed Power Facility, or Z machine, a cylindrical metallic labyrinth of warning signs and wiring. It’s capable of summoning enough energy to melt diamond. About 25,000 asteroids more than 460 feet long—a size range that starts with midsize “city killers” and goes up in impact from there—are thought to exist close to Earth. Just under half of them have been found. The researchers reckoned they could use the Z machine to re-create the x-ray blast of a nuclear weapon—the radiation that would be used to knock back an asteroid—on a very small and safe scale. It took a while to sort out the details. But by July 2023, Moore and his team were ready. They waited anxiously inside a control room, monitoring the thrumming contraption from afar. Inside the machine’s heart were two small pieces of rock, stand-ins for asteroids, and at the press of a button, a maelstrom of x-rays would thunder toward them. If they were knocked back by those x-rays, it would prove something that, until now, was purely theoretical: You can deflect an asteroid from Earth using a nuke. This experiment “had never been done before,” says Moore. But if it succeeded, its data would contribute to the safety of everyone on the planet. Would it work? Monoliths and rubble piles Asteroid impacts are a natural disaster like any other. You shouldn’t lose sleep over the prospect, but if we get unlucky, an errant space rock may rudely ring Earth’s doorbell. “The probability of an asteroid striking Earth during my lifetime is very small. But what if one did? What would we do about it?” says Moore. “I think that’s worth being curious about.” Forget about the gigantic asteroids you know from Hollywood blockbusters. Space rocks over two-thirds of a mile (about one kilometer) in diameter—those capable of imperiling civilization—are certainly out there, and some hew close to Earth’s own orbit. But because these asteroids are so elephantine, astronomers have found almost all of them already, and none pose an impact threat. Rather, it’s asteroids a size range down—those upwards of 460 feet (140 meters) long—that are of paramount concern. About 25,000 of those are thought to exist close to our planet, and just under half have been found. The day-to-day odds of an impact are extremely low, but even one of the smaller ones in that size range could do significant damage if it found Earth and hit a populated area—a capacity that has led astronomers to dub such midsize asteroids “city killers.” If we find a city killer that looks likely to hit Earth, we’ll need a way to stop it. That could be technology to break or “disrupt” the asteroid into fragments that will either miss the planet entirely or harmlessly ignite in the atmosphere. Or it could be something that can deflect the asteroid, pushing it onto a path that will no longer intersect with our blue marble. Because disruption could accidentally turn a big asteroid into multiple smaller, but still deadly, shards bound for Earth, it’s often considered to be a strategy of last resort. Deflection is seen as safer and more elegant. One way to achieve it is to deploy a spacecraft known as a kinetic impactor—a battering ram that collides with an asteroid and transfers its momentum to the rocky interloper, nudging it away from Earth. NASA’s DART mission demonstrated that this can work, but there are some important caveats: You need to deflect the asteroid years in advance to make sure it completely misses Earth, and asteroids that we spot too late—or that are too big—can’t be swatted away by just one DART-like mission. Instead, you’d need several kinetic impactors—maybe many of them—to hit one side of the asteroid perfectly each time in order to push it far enough to save our planet. That’s a tall order for orbital mechanics, and not something space agencies may be willing to gamble on. In that case, the best option might instead be to detonate a nuclear weapon next to the asteroid. This would irradiate one hemisphere of the asteroid in x-rays, which in a few millionths of a second would violently shatter and vaporize the rocky surface. The stream of debris spewing out of that surface and into space would act like a rocket, pushing the asteroid in the opposite direction. “There are scenarios where kinetic impact is insufficient, and we’d have to use a nuclear explosive device,” says Moore. MCKIBILLO This idea isn’t new. Several decades ago, Peter Schultz, a planetary geologist and impacts expert at Brown University, was giving a planetary defense talk at the Lawrence Livermore National Laboratory in California, another American lab focused on nuclear deterrence and nuclear physics research. Afterwards, he recalls, none other than Edward Teller, the father of the hydrogen bomb and a key member of the Manhattan Project, invited him into his office for a chat. “He wanted to do one of these near-Earth-asteroid flybys and wanted to test the nukes,” Schultz says. What, he wondered, would happen if you blasted an asteroid with a nuclear weapon’s x-rays? Could you forestall a spaceborne disaster using weapons of mass destruction? But Teller’s dream wasn’t fulfilled—and it’s unlikely to become a reality anytime soon. The United Nations’ 1967 Outer Space Treaty states that no nation can deploy or use nuclear weapons off-world (even if it’s not clear how long certain spacefaring nations will continue to adhere to that rule). Even raising the possibility of using nukes to defend the planet can be tricky. “There’re still many folks that don’t want to talk about it at all … even if that were the only option to prevent an impact,” says Megan Bruck Syal, a physicist and planetary defense researcher at Lawrence Livermore. Nuclear weapons have long been a sensitive subject, and with relations between several nuclear nations currently at a new nadir, anxiety over the subject is understandable. But in the US, there are groups of scientists who “recognize that we have a special responsibility as a spacefaring nation and as a nuclear-capable nation to look at this,” Syal says. “It isn’t our preference to use a nuclear explosive, of course. But we are still looking at it, in case it’s needed.” But how? Mostly, researchers have turned to the virtual world, using supercomputers at various US laboratories to simulate the asteroid-agitating physics of a nuclear blast. To put it mildly, “this is very hard,” says Mary Burkey, a physicist and planetary defense researcher at Lawrence Livermore. You cannot simply flick a switch on a computer and get immediate answers. “When a nuke goes off in space, there’s just x-ray light that’s coming out of it. It’s shining on the surface of your asteroid, and you’re tracking those little photons penetrating maybe a tiny little bit into the surface, and then somehow you have to take that micrometer worth of resolution and then propagate it out onto something that might be on the order of hundreds of meters wide, watching that shock wave propagate and then watching fragments spin off into space. That’s four different problems.” Mimicking the physics of x-ray rock annihilation with as much verisimilitude as possible is difficult work. But recent research using these high-fidelity simulations does suggest that nukes are an effective planetary defense tool for both disruption and deflection. The thing is, though, no two asteroids are alike; each is mechanically and geologically unique, meaning huge uncertainties remain. A more monolithic asteroid might respond in a straightforward way to a nuclear deflection campaign, whereas a rubble pile asteroid—a weakly bound fleet of boulders barely held together by their own gravity—might respond in a chaotic, uncontrollable way. Can you be sure the explosion wouldn’t accidentally shatter the asteroid, turning a cannonball into a hail of bullets still headed for Earth? Simulations can go a long way toward answering these questions, but they remain virtual re-creations of reality, with built-in assumptions. “Our models are only as good as the physics that we understand and that we put into them,” says Angela Stickle, a hypervelocity impact physicist at the Johns Hopkins University Applied Physics Laboratory in Maryland. To make sure the simulations are reproducing the correct physics and delivering realistic data, physical experiments are needed to ground them. Every firing of the Z machine carries the energy of more than 1,000 lightning bolts, and each shot lasts a few millionths of a second. Researchers studying kinetic impactors can get that sort of real-world data. Along with DART, they can use specialized cannons—like the Vertical Gun Range at NASA’s Ames Research Center in California—to fire all sorts of projectiles at meteorites. In doing so, they can find out how tough or fragile asteroid shards can be, effectively reproducing a kinetic impact mission on a small scale. Battle-testing nuke-based asteroid defense simulations is another matter. Re-creating the physics of these confrontations on a small scale was long considered to be exceedingly difficult. Fortunately, those keen on fighting asteroids are as persistent as they are creative—and several teams, including Moore’s at Sandia, think they have come up with a solution. X-ray scissors The prime mission of Sandia, like that of Lawrence Livermore, is to help maintain the nation’s nuclear weapons arsenal. “It’s a national security laboratory,” says Moore. “Planetary defense affects the entire planet,” he adds—making it, by default, a national security issue as well. And that logic, in part, persuaded the powers that be in July 2022 to try a brand-new kind of experiment. Moore took charge of the project in January 2023—and with the shot scheduled for the summer, he had only a few months to come up with the specific plan for the experiment. There was “lots of scribbling on my whiteboard, running computer simulations, and getting data to our engineers to design the test fixture for the several months it would take to get all the parts machined and assembled,” he says. Although there were previous and ongoing experiments that showered asteroid-like targets with x-rays, Moore and his team were frustrated by one aspect of them. Unlike actual asteroids floating freely in space, the micro-asteroids on Earth were fixed in place. To truly test whether x-rays could deflect asteroids, targets would have to be suspended in a vacuum—and it wasn’t immediately clear how that could be achieved. Generating the nuke-like x-rays was the easy part, because Sandia had the Z machine, a hulking mass of diodes, pipes, and wires interwoven with an assortment of walkways that circumnavigate a vacuum chamber at its core. When it’s powered up, electrical currents are channeled into capacitors—and, when commanded, blast that energy at a target or substance to create radiation and intense magnetic pressures. Flanked by klaxons and flashing lights, it’s an intimidating sight. “It’s the size of a building—about three stories tall,” says Moore. Every firing of the Z machine carries the energy of more than 1,000 lightning bolts, and each shot lasts a few millionths of a second: “You can’t even blink that fast.” The Z machine is named for the axis along which its energetic particles cascade, but the Z could easily stand for “Zeus.” The Z Pulsed Power Facility, or Z machine, at Sandia National Laboratories in Albuquerque, New Mexico, concentrates electricity into short bursts of intense energy that can be used to create x-rays and gamma rays and compress matter to high densities.RANDY MONTOYA/SANDIA NATIONAL LABORATORY The original purpose of the Z machine, whose first form was built half a century ago, was nuclear fusion research. But over time, it’s been tinkered with, upgraded, and used for all kinds of science. “The Z machine has been used to compress matter to the same densities [you’d find at] the centers of planets. And we can do experiments like that to better understand how planets form,” Moore says, as an example. And the machine’s preternatural energies could easily be used to generate x-rays—in this case, by electrifying and collapsing a cloud of argon gas. “The idea of studying asteroid deflection is completely different for us,” says Moore. And the machine “fires just once a day,” he adds, “so all the experiments are planned more than a year in advance.” In other words, the researchers had to be near certain their one experiment would work, or they would be in for a long wait to try again—if they were permitted a second attempt. For some time, they could not figure out how to suspend their micro-asteroids. But eventually, they found a solution: Two incredibly thin bits of aluminum foil would hold their targets in place within the Z machine’s vacuum chamber. When the x-ray blast hit them and the targets, the pieces of foil would be instantly vaporized, briefly leaving the targets suspended in the chamber and allowing them to be pushed back as if they were in space. “It’s like you wave your magic wand and it’s gone,” Moore says of the foil. He dubbed this technique “x-ray scissors.” In July 2023, after considerable planning, the team was ready. Within the Z machine’s vacuum chamber were two fingernail-size targets—a bit of quartz and some fused silica, both frequently found on real asteroids. Nearby, a pocket of argon gas swirled away. Satisfied that the gigantic gizmo was ready, everyone left and went to stand in the control room. For a moment, it was deathly quiet. Stand by. Fire. It was over before their ears could even register a metallic bang. A tempest of electricity shocked the argon gas cloud, causing it to implode; as it did, it transformed into a plasma and x-rays screamed out of it, racing toward the two targets in the chamber. The foil vanished, the surfaces of both targets erupted outward as supersonic sprays of debris, and the targets flew backward, away from the x-rays, at 160 miles per hour. Moore wasn’t there. “I was in Spain when the experiment was run, because I was celebrating my anniversary with my wife, and there was no way I was going to miss that,” he says. But just after the Z machine was fired, one of his colleagues sent him a very concise text: IT WORKED. “We knew right away it was a huge success,” says Moore. The implications were immediately clear. The experimental setup was complex, but they were trying to achieve something extremely fundamental: a real-world demonstration that a nuclear blast could make an object in space move. “We’re genuinely looking at this from the standpoint of ‘This is a technology that could save lives.’” Patrick King, a physicist at the Johns Hopkins University Applied Physics Laboratory, was impressed. Previously, pushing back objects using x-ray vaporization had been extremely difficult to demonstrate in the lab. “They were able to get a direct measurement of that momentum transfer,” he says, calling the x-ray scissors an “elegant” technique. Sandia’s work took many in the community by surprise. “The Z machine experiment was a bit of a newcomer for the planetary defense field,” says Burkey. But she notes that we can’t overinterpret the results. It isn’t clear, from the deflection of the very small and rudimentary asteroid-like targets, how much a genuine nuclear explosion would deflect an actual asteroid. As ever, more work is needed. King leads a team that is also working on this question. His NASA-funded project involves the Omega Laser Facility, a complex based at the University of Rochester in upstate New York. Omega can generate x-rays by firing powerful lasers at a target within a specialized chamber. Upon being irradiated, the target generates an x-ray flash, similar to the one produced during a nuclear explosion in space, which can then be used to bombard various objects—in this case, some Earth rocks acting as asteroid mimics, and (crucially) some bona fide meteoritic material too. King’s Omega experiments have tried to answer a basic question: “How much material actually gets removed from the surface?” says King. The amount of material that flies off the pseudo-asteroids, and the vigor with which it’s removed, will differ from target to target. The hope is that these results—which the team is still considering—will hint at how different types of asteroids will react to being nuked. Although experiments with Omega cannot produce the kickback seen in the Z machine, King’s team has used a more realistic and diverse series of targets and blasted them with x-rays hundreds of times. That, in turn, should clue us in to how effectively, or not, actual asteroids would be deflected by a nuclear explosion. “I wouldn’t say one [experiment] has definitive advantages over the other,” says King. “Like many things in science, each approach can yield insight along different ‘axes,’ if you will, and no experimental setup gives you the whole picture.” MCKIBILLO Experiments like Moore’s and King’s may sound technologically baroque—a bit like lightning-fast Rube Goldberg machines overseen by wizards. But they are likely the first in a long line of increasingly sophisticated tests. “We’ve just scratched the surface of what we can do,” Moore says. As with King’s experiments, Moore hopes to place a variety of materials in the Z machine, including targets that can stand in for the wetter, more fragile carbon-rich asteroids that astronomers commonly see in near-Earth space. “If we could get our hands on real asteroid material, we’d do it,” he says. And it’s expected that all this experimental data will be fed back into those nuke-versus-asteroid computer simulations, helping to verify the virtual results. Although these experiments are perfectly safe, planetary defenders remain fully cognizant of the taboo around merely discussing the use of nukes for any reason—even if that reason is potentially saving the world. “We’re genuinely looking at this from the standpoint of ‘This is a technology that could save lives,’” King says. Inevitably, Earth will be imperiled by a dangerous asteroid. And the hope is that when that day arrives, it can be dealt with using something other than a nuke. But comfort should be taken from the fact that scientists are researching this scenario, just in case it’s our only protection against the firmament. “We are your taxpayer dollars at work,” says Burkey. There’s still some way to go before they can be near certain that this asteroid-stopping technique will succeed. Their progress, though, belongs to everyone. “Ultimately,” says Moore, “we all win if we solve this problem.” Robin George Andrews is an award-winning science journalist based in London and the author, most recently, of How to Kill an Asteroid: The Real Science of Planetary Defense.0 Kommentare 0 Anteile 13 Ansichten