A review published in Virtual and Physical Prototyping explores the growing field of additively manufactured acoustic metamaterials (ACA-Meta), highlighting how 3D printing technologies enable novel designs for effective sound absorption across diverse applications. Authored by researchers from Khalifa University and Dassault Aviation, the paper classifies acoustic metamaterials into perforated, slotted, cellular, and hybrid types and investigates how additive manufacturing enhances their performance. Expanding acoustic control with 3D printing Additive manufacturing offers unique benefits for acoustic metamaterials, enabling precise control over geometry, material distribution, and internal architecture. This level of control allows researchers and engineers to tailor acoustic behavior at specific frequency ranges, while simultaneously optimizing for weight, mechanical strength, and structural complexity.  Traditional sound-absorbing materials, such as porous foams or fibrous panels, are often constrained by fixed properties and limited adaptability. In contrast, 3D printing allows designers to create resonant structures and internal cavities with sub-wavelength precision, an essential factor in manipulating how sound waves interact with matter. The review outlines how techniques such as Stereolithography (SLA), Selective Laser Melting (SLM), Fused Deposition Modeling (FDM), and Digital Light Processing (DLP) are being employed to fabricate a new generation of acoustic absorbers. These processes enable the construction of intricate geometries previously unattainable with conventional manufacturing, and allow for the fine-tuning of key parameters such as pore size, wall thickness, infill density, and material gradients. In doing so, additive manufacturing not only improves absorption efficiency but also broadens the usable frequency range of these metamaterials, making them more adaptable to specific environments and industrial requirements. ACA-Meta fabricated by various additive manufactured techniques: a) vat photopolymerization, b) powder bed fusion, c) binder jetting, d) extrusion, and e) material jetting. Image via V. Sekar et al., Virtual and Physical Prototyping. The paper categorizes these acoustic metamaterials into four structural families, each with distinctive mechanisms for managing sound waves. Perforated metamaterials absorb mid- to high-frequency noise by dissipating energy through arrays of micro-holes, often backed by air cavities to enhance low-frequency performance. Slotted designs employ labyrinthine or coiled channels to extend the acoustic path length, enabling effective attenuation at low frequencies within a compact footprint. Cellular structures, including periodic honeycombs, gyroids, and stochastic foams, are engineered to exhibit broadband performance through controlled porosity and internal resonance. Lastly, hybrid designs combine multiple features, such as perforated faces with embedded coiled cavities or layered cellular cores, to achieve tunable, wideband absorption across multiple acoustic regimes. Classification and sub classification of ACA-Meta. Image via V. Sekar et al., Virtual and Physical Prototyping. These classifications are not merely theoretical; each has been demonstrated through experimental validation, with performance metrics such as sound absorption coefficient (SAC) measured using impedance tubes and reverberation chambers. The paper emphasizes that even minor design modifications, like altering the angle of perforations or grading cell density, can have significant effects on absorption performance, reinforcing the value of additive manufacturing as both a prototyping and production tool in acoustic engineering. Simulation and experimental validation To quantify acoustic absorption, the study reviews both analytical models and experimental methods. Key parameters include the sound absorption coefficient (SAC), surface porosity, and sample orientation. Validation techniques such as impedance tube and reverberation room testing show that additively manufactured metamaterials can achieve or exceed the performance of traditional absorbers. The review also identifies future directions, including volumetric 3D printing, multi-material printing, and 4D printing using smart materials for tunable acoustic responses. These approaches promise scalable, reconfigurable absorbers that can adapt to environmental changes or user-defined inputs. Schematic representation and design parameters of ACA-Meta. Image via V. Sekar et al., Virtual and Physical Prototyping. Reshaping acoustic metamaterials Interest in the acoustic capabilities of 3D printing has grown significantly in recent years. In 2019, researchers at the University of Sussex demonstrated a 3D printed metamaterial capable of directing sound to a specific location without the use of headphones, an early example of how additive manufacturing could redefine personal audio delivery. More recently, the University of Strathclyde received £500,000 in funding to develop miniaturized acoustic systems using 3D printing, aiming to advance compact and high-performance devices for sensing and communication. Consumer audio brands have also embraced the technology; Campfire Audio, for instance, leveraged additive manufacturing to create earphones internal structure for their Supermoon series, optimizing both sound performance and fit. On a more experimental front, researchers have begun using sound itself as a medium for fabrication, as seen in a recent study on holographic Direct Sound Printing (DSP), which manipulates ultrasonic fields to solidify resin. Together, these developments underscore the growing convergence of 3D printing and acoustic innovation, a convergence that the reviewed paper situates within the emerging domain of engineered sound-absorbing metamaterials. Read the full article in Virtual and Physical Prototyping Subscribe to the 3D Printing Industry newsletter to keep up with the latest 3D printing news.You can also follow us onLinkedIn and subscribe to the 3D Printing Industry YouTube channel to access more exclusive content. At 3DPI, our mission is to deliver high-quality journalism, technical insight, and industry intelligence to professionals across the AM ecosystem.Help us shape the future of 3D printing industry news with our2025 reader survey. Feature image shows ACA-Meta fabricated by various additive manufactured techniques.

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. The data center boom in the desert In the high desert east of Reno, Nevada, construction crews are flattening the golden foothills of the Virginia Range, laying the foundations of a data center city.Google, Tract, Switch, EdgeCore, Novva, Vantage, and PowerHouse are all operating, building, or expanding huge facilities nearby. Meanwhile, Microsoft has acquired more than 225 acres of undeveloped property, and Apple is expanding its existing data center just across the Truckee River from the industrial park. The corporate race to amass computing resources to train and run artificial intelligence models and store information in the cloud has sparked a data center boom in the desert—and it’s just far enough away from Nevada’s communities to elude wide notice and, some fear, adequate scrutiny. Read the full story. —James Temple This story is part of Power Hungry: AI and our energy future—our new series shining a light on the energy demands and carbon costs of the artificial intelligence revolution. Check out the rest of the package here. A new atomic clock in space could help us measure elevations on Earth In 2003, engineers from Germany and Switzerland began building a bridge across the Rhine River simultaneously from both sides. Months into construction, they found that the two sides did not meet. The German side hovered 54 centimeters above the Swiss one. The misalignment happened because they measured elevation from sea level differently. To prevent such costly construction errors, in 2015 scientists in the International Association of Geodesy voted to adopt the International Height Reference Frame, or IHRF, a worldwide standard for elevation.Now, a decade after its adoption, scientists are looking to update the standard—by using the most precise clock ever to fly in space. Read the full story. —Sophia Chen Three takeaways about AI’s energy use and climate impacts —Casey CrownhartThis week, we published Power Hungry, a package all about AI and energy. At the center of this package is the most comprehensive look yet at AI’s growing power demand, if I do say so myself. This data-heavy story is the result of over six months of reporting by me and my colleague James O’Donnell (and the work of many others on our team). Over that time, with the help of leading researchers, we quantified the energy and emissions impacts of individual queries to AI models and tallied what it all adds up to, both right now and for the years ahead. There’s a lot of data to dig through, and I hope you’ll take the time to explore the whole story. But in the meantime, here are three of my biggest takeaways from working on this project. Read the full story.This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here. MIT Technology Review Narrated: Congress used to evaluate emerging technologies. Let’s do it again. Artificial intelligence comes with a shimmer and a sheen of magical thinking. And if we’re not careful, politicians, employers, and other decision-makers may accept at face value the idea that machines can and should replace human judgment and discretion. One way to combat that might be resurrecting the Office of Technology Assessment, a Congressional think tank that detected lies and tested tech until it was shuttered in 1995. This is our latest story to be turned into a MIT Technology Review Narrated podcast, which we’re publishing each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as it’s released. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 OpenAI is buying Jony Ive’s AI startupThe former Apple design guru will work with Sam Altman to design an entirely new range of devices. (NYT $)+ The deal is worth a whopping $6.5 billion. (Bloomberg $)+ Altman gave OpenAI staff a preview of its AI ‘companion’ devices. (WSJ $)+ AI products to date have failed to set the world alight. (The Atlantic $) 2 Microsoft has blocked employee emails containing ‘Gaza’ or ‘Palestine’Although the term ‘Israel’ does not trigger such a block. (The Verge)+ Protest group No Azure for Apartheid has accused the company of censorship. (Fortune $) 3 DOGE needs to do its work in secretThat’s what the Trump administration is claiming to the Supreme Court, at least. (Ars Technica)+ It’s trying to avoid being forced to hand over internal documents. (NYT $)+ DOGE’s tech takeover threatens the safety and stability of our critical data. (MIT Technology Review) 4 US banks are racing to embrace cryptocurrencyAhead of new stablecoin legislation. (The Information $)+ Attendees at Trump’s crypto dinner paid over $1 million for the privilege. (NBC News)+ Bitcoin has surged to an all-time peak yet again. (Reuters) 5 China is making huge technological leapsThanks to the billions it’s poured into narrowing the gap between it and the US. (WSJ $)+ Nvidia’s CEO has branded America’s chip curbs on China ‘a failure.’ (FT $)+ There can be no winners in a US-China AI arms race. (MIT Technology Review) 6 Disordered eating content is rife on TikTokBut a pocket of creators are dedicated to debunking the worst of it. (Wired $) 7 The US military is interested in the world’s largest aircraftThe gigantic WindRunner plane will have an 80-metre wingspan. (New Scientist $)+ Phase two of military AI has arrived. (MIT Technology Review) 8 How AI is shaking up animationNew tools are slashing the costs of creating episodes by up to 90%. (NYT $)+ Generative AI is reshaping South Korea’s webcomics industry. (MIT Technology Review) 9 Tesla’s Cybertruck is a flopSorry, Elon. (Fast Company $)+ The vehicles’ resale value is plummeting. (The Daily Beast) 10 Google’s new AI video generator loves this terrible jokeWhich appears to originate from a Reddit post. (404 Media)+ What happened when 20 comedians got AI to write their routines. (MIT Technology Review) Quote of the day “It feels like we are marching off a cliff.” —An unnamed software engineering vice president jokes that future developers conferences will be attended by the AI agents companies like Microsoft are racing to deploy, Semafor reports. One more thing What does GPT-3 “know” about me?One of the biggest stories in tech is the rise of large language models that produce text that reads like a human might have written it.These models’ power comes from being trained on troves of publicly available human-created text hoovered up from the internet. If you’ve posted anything even remotely personal in English on the internet, chances are your data might be part of some of the world’s most popular LLMs.Melissa Heikkilä, MIT Technology Review’s former AI reporter, wondered what data these models might have on her—and how it could be misused. So she put OpenAI’s GPT-3 to the test. Read about what she found. We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.) + Don’t shoot the messenger, but it seems like there’s a new pizza king in town ($)+ Ranked: every Final Destination film, from worst to best.+ Who knew that jelly could help to preserve coral reefs? Not I.+ A new generation of space archaeologists are beavering away to document our journeys to the stars.

This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology. The data center boom in the desert In the high desert east of Reno, Nevada, construction crews are flattening the golden foothills of the Virginia Range, laying the foundations of a data center city. Google, Tract, Switch, EdgeCore, Novva, Vantage, and PowerHouse are all operating, building, or expanding huge facilities nearby. Meanwhile, Microsoft has acquired more than 225 acres of undeveloped property, and Apple is expanding its existing data center just across the Truckee River from the industrial park.The corporate race to amass computing resources to train and run artificial intelligence models and store information in the cloud has sparked a data center boom in the desert—and it’s just far enough away from Nevada’s communities to elude wide notice and, some fear, adequate scrutiny. Read the full story. —James Temple This story is part of Power Hungry: AI and our energy future—our new series shining a light on the energy demands and carbon costs of the artificial intelligence revolution. Check out the rest of the package here. A new atomic clock in space could help us measure elevations on Earth In 2003, engineers from Germany and Switzerland began building a bridge across the Rhine River simultaneously from both sides. Months into construction, they found that the two sides did not meet. The German side hovered 54 centimeters above the Swiss one. The misalignment happened because they measured elevation from sea level differently. To prevent such costly construction errors, in 2015 scientists in the International Association of Geodesy voted to adopt the International Height Reference Frame, or IHRF, a worldwide standard for elevation. Now, a decade after its adoption, scientists are looking to update the standard—by using the most precise clock ever to fly in space. Read the full story. —Sophia Chen Three takeaways about AI’s energy use and climate impacts —Casey Crownhart This week, we published Power Hungry, a package all about AI and energy. At the center of this package is the most comprehensive look yet at AI’s growing power demand, if I do say so myself. This data-heavy story is the result of over six months of reporting by me and my colleague James O’Donnell (and the work of many others on our team). Over that time, with the help of leading researchers, we quantified the energy and emissions impacts of individual queries to AI models and tallied what it all adds up to, both right now and for the years ahead. There’s a lot of data to dig through, and I hope you’ll take the time to explore the whole story. But in the meantime, here are three of my biggest takeaways from working on this project. Read the full story.This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here. MIT Technology Review Narrated: Congress used to evaluate emerging technologies. Let’s do it again. Artificial intelligence comes with a shimmer and a sheen of magical thinking. And if we’re not careful, politicians, employers, and other decision-makers may accept at face value the idea that machines can and should replace human judgment and discretion. One way to combat that might be resurrecting the Office of Technology Assessment, a Congressional think tank that detected lies and tested tech until it was shuttered in 1995. This is our latest story to be turned into a MIT Technology Review Narrated podcast, which we’re publishing each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as it’s released. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 OpenAI is buying Jony Ive’s AI startup The former Apple design guru will work with Sam Altman to design an entirely new range of devices. (NYT $)+ The deal is worth a whopping $6.5 billion. (Bloomberg $)+ Altman gave OpenAI staff a preview of its AI ‘companion’ devices. (WSJ $)+ AI products to date have failed to set the world alight. (The Atlantic $)2 Microsoft has blocked employee emails containing ‘Gaza’ or ‘Palestine’ Although the term ‘Israel’ does not trigger such a block. (The Verge)+ Protest group No Azure for Apartheid has accused the company of censorship. (Fortune $) 3 DOGE needs to do its work in secret That’s what the Trump administration is claiming to the Supreme Court, at least. (Ars Technica)+ It’s trying to avoid being forced to hand over internal documents. (NYT $)+ DOGE’s tech takeover threatens the safety and stability of our critical data. (MIT Technology Review)4 US banks are racing to embrace cryptocurrency Ahead of new stablecoin legislation. (The Information $)+ Attendees at Trump’s crypto dinner paid over $1 million for the privilege. (NBC News)+ Bitcoin has surged to an all-time peak yet again. (Reuters)5 China is making huge technological leaps Thanks to the billions it’s poured into narrowing the gap between it and the US. (WSJ $)+ Nvidia’s CEO has branded America’s chip curbs on China ‘a failure.’ (FT $)+ There can be no winners in a US-China AI arms race. (MIT Technology Review)6 Disordered eating content is rife on TikTokBut a pocket of creators are dedicated to debunking the worst of it. (Wired $) 7 The US military is interested in the world’s largest aircraftThe gigantic WindRunner plane will have an 80-metre wingspan. (New Scientist $) + Phase two of military AI has arrived. (MIT Technology Review)8 How AI is shaking up animationNew tools are slashing the costs of creating episodes by up to 90%. (NYT $) + Generative AI is reshaping South Korea’s webcomics industry. (MIT Technology Review)9 Tesla’s Cybertruck is a flop Sorry, Elon. (Fast Company $)+ The vehicles’ resale value is plummeting. (The Daily Beast)10 Google’s new AI video generator loves this terrible joke Which appears to originate from a Reddit post. (404 Media)+ What happened when 20 comedians got AI to write their routines. (MIT Technology Review) Quote of the day “It feels like we are marching off a cliff.” —An unnamed software engineering vice president jokes that future developers conferences will be attended by the AI agents companies like Microsoft are racing to deploy, Semafor reports. One more thing What does GPT-3 “know” about me?One of the biggest stories in tech is the rise of large language models that produce text that reads like a human might have written it. These models’ power comes from being trained on troves of publicly available human-created text hoovered up from the internet. If you’ve posted anything even remotely personal in English on the internet, chances are your data might be part of some of the world’s most popular LLMs.Melissa Heikkilä, MIT Technology Review’s former AI reporter, wondered what data these models might have on her—and how it could be misused. So she put OpenAI’s GPT-3 to the test. Read about what she found.We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet 'em at me.) + Don’t shoot the messenger, but it seems like there’s a new pizza king in town 🍕 ($)+ Ranked: every Final Destination film, from worst to best.+ Who knew that jelly could help to preserve coral reefs? Not I.+ A new generation of space archaeologists are beavering away to document our journeys to the stars.

This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology. The data center boom in the desert In the high desert east of Reno, Nevada, construction crews are flattening the golden foothills of the Virginia Range, laying the foundations of a data center city. Google, Tract, Switch, EdgeCore, Novva, Vantage, and PowerHouse are all operating, building, or expanding huge facilities nearby. Meanwhile, Microsoft has acquired more than 225 acres of undeveloped property, and Apple is expanding its existing data center just across the Truckee River from the industrial park.The corporate race to amass computing resources to train and run artificial intelligence models and store information in the cloud has sparked a data center boom in the desert—and it’s just far enough away from Nevada’s communities to elude wide notice and, some fear, adequate scrutiny. Read the full story. —James Temple This story is part of Power Hungry: AI and our energy future—our new series shining a light on the energy demands and carbon costs of the artificial intelligence revolution. Check out the rest of the package here. A new atomic clock in space could help us measure elevations on Earth In 2003, engineers from Germany and Switzerland began building a bridge across the Rhine River simultaneously from both sides. Months into construction, they found that the two sides did not meet. The German side hovered 54 centimeters above the Swiss one. The misalignment happened because they measured elevation from sea level differently. To prevent such costly construction errors, in 2015 scientists in the International Association of Geodesy voted to adopt the International Height Reference Frame, or IHRF, a worldwide standard for elevation. Now, a decade after its adoption, scientists are looking to update the standard—by using the most precise clock ever to fly in space. Read the full story. —Sophia Chen Three takeaways about AI’s energy use and climate impacts —Casey Crownhart This week, we published Power Hungry, a package all about AI and energy. At the center of this package is the most comprehensive look yet at AI’s growing power demand, if I do say so myself. This data-heavy story is the result of over six months of reporting by me and my colleague James O’Donnell (and the work of many others on our team). Over that time, with the help of leading researchers, we quantified the energy and emissions impacts of individual queries to AI models and tallied what it all adds up to, both right now and for the years ahead. There’s a lot of data to dig through, and I hope you’ll take the time to explore the whole story. But in the meantime, here are three of my biggest takeaways from working on this project. Read the full story.This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here. MIT Technology Review Narrated: Congress used to evaluate emerging technologies. Let’s do it again. Artificial intelligence comes with a shimmer and a sheen of magical thinking. And if we’re not careful, politicians, employers, and other decision-makers may accept at face value the idea that machines can and should replace human judgment and discretion. One way to combat that might be resurrecting the Office of Technology Assessment, a Congressional think tank that detected lies and tested tech until it was shuttered in 1995. This is our latest story to be turned into a MIT Technology Review Narrated podcast, which we’re publishing each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as it’s released. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 OpenAI is buying Jony Ive’s AI startup The former Apple design guru will work with Sam Altman to design an entirely new range of devices. (NYT $)+ The deal is worth a whopping $6.5 billion. (Bloomberg $)+ Altman gave OpenAI staff a preview of its AI ‘companion’ devices. (WSJ $)+ AI products to date have failed to set the world alight. (The Atlantic $)2 Microsoft has blocked employee emails containing ‘Gaza’ or ‘Palestine’ Although the term ‘Israel’ does not trigger such a block. (The Verge)+ Protest group No Azure for Apartheid has accused the company of censorship. (Fortune $) 3 DOGE needs to do its work in secret That’s what the Trump administration is claiming to the Supreme Court, at least. (Ars Technica)+ It’s trying to avoid being forced to hand over internal documents. (NYT $)+ DOGE’s tech takeover threatens the safety and stability of our critical data. (MIT Technology Review)4 US banks are racing to embrace cryptocurrency Ahead of new stablecoin legislation. (The Information $)+ Attendees at Trump’s crypto dinner paid over $1 million for the privilege. (NBC News)+ Bitcoin has surged to an all-time peak yet again. (Reuters)5 China is making huge technological leaps Thanks to the billions it’s poured into narrowing the gap between it and the US. (WSJ $)+ Nvidia’s CEO has branded America’s chip curbs on China ‘a failure.’ (FT $)+ There can be no winners in a US-China AI arms race. (MIT Technology Review)6 Disordered eating content is rife on TikTokBut a pocket of creators are dedicated to debunking the worst of it. (Wired $) 7 The US military is interested in the world’s largest aircraftThe gigantic WindRunner plane will have an 80-metre wingspan. (New Scientist $) + Phase two of military AI has arrived. (MIT Technology Review)8 How AI is shaking up animationNew tools are slashing the costs of creating episodes by up to 90%. (NYT $) + Generative AI is reshaping South Korea’s webcomics industry. (MIT Technology Review)9 Tesla’s Cybertruck is a flop Sorry, Elon. (Fast Company $)+ The vehicles’ resale value is plummeting. (The Daily Beast)10 Google’s new AI video generator loves this terrible joke Which appears to originate from a Reddit post. (404 Media)+ What happened when 20 comedians got AI to write their routines. (MIT Technology Review) Quote of the day “It feels like we are marching off a cliff.” —An unnamed software engineering vice president jokes that future developers conferences will be attended by the AI agents companies like Microsoft are racing to deploy, Semafor reports. One more thing What does GPT-3 “know” about me?One of the biggest stories in tech is the rise of large language models that produce text that reads like a human might have written it. These models’ power comes from being trained on troves of publicly available human-created text hoovered up from the internet. If you’ve posted anything even remotely personal in English on the internet, chances are your data might be part of some of the world’s most popular LLMs.Melissa Heikkilä, MIT Technology Review’s former AI reporter, wondered what data these models might have on her—and how it could be misused. So she put OpenAI’s GPT-3 to the test. Read about what she found.We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet 'em at me.) + Don’t shoot the messenger, but it seems like there’s a new pizza king in town 🍕 ($)+ Ranked: every Final Destination film, from worst to best.+ Who knew that jelly could help to preserve coral reefs? Not I.+ A new generation of space archaeologists are beavering away to document our journeys to the stars.

Save this picture!VARID A VR-AR Toolkit for Inclusive Design.. Image © Foster + PartnersOver the last decade, architectural design has relied on 2D methods of representation, such as elevations, sections, and floor plans, paired with digital renderings of 3D models. While these tools are essential to convey geometry and intent, they remain limited by their two-dimensional format. Even the most realistic renderings, created through programs like SketchUp, Revit, or AutoCAD, still flatten space and distance the viewer from the lived experience of a project. Recently, architects have begun to explore immersive technologies as a way to bridge this gap between drawing and experience, offering new ways to inhabit and assess spatial proposals.What are AR, VR, and MR?Extended Reality (XR) can be classified into three main types: Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), each offering varying levels of immersion in digital environments. At one end of the spectrum, AR enhances the real world with digital content, while at the other, VR fully immerses the user in a completely virtual environment, blocking out the physical world. MR lies between these extremes but is essentially a more detailed classification of AR based on the type of display used. Their research proposes the following classification: Class 1 display refers to monitor-based systems, where users view the real world through a screen equipped with a camera that captures the environment and overlays digital information, such as in the Apple Vision Pro, which uses passthrough cameras. In contrast, Class 2 and 3 systems use head-mounted displays (HMDs) with see-through lenses that superimpose 3D models onto the user's view, like the Microsoft HoloLens. In 2020, Trimble combined the HoloLens with a hard hat, creating the Trimble XR10, which makes this technology usable in the construction site. For clarity, this text will refer to Class 1 systems as AR and Class 2 and 3 systems as MR moving forward. Related Article Using Augmented Reality In Bamboo Architecture Save this picture!How do Users Perceive Space?Architectural design is not only about defining space, but also about anticipating how people will perceive and move through it. The way users interpret a space depends not just on geometry, but also on intuition, their individual knowledge, and experiences. Kevin Lynch described this as a space's "legibility," or how easily it can be understood and organized mentally, while Ittelson (1978) emphasizes how users explore, categorize, and systematize spatial elements into a coherent whole. The user first explores an area to orient themselves and move around, then they will develop a taxonomy of the space elements to mentally organize it, and finally, they put everything together into a system that tells the brain why things are happening and how they relate to each other. Research suggests that immersive environments such as mixed reality can simulate this faithfully, allowing architects and clients alike to engage with a design not as an abstract plan, but as a place to walk through, observe, and interpret.Save this picture!Which One Improves Design Understanding: 2D Drawings or MR?Based on the above, a study made by the National Taiwan University in 2021 explored this topic by conducting an experiment where participants were brought to a room and were divided into two groups. The first would analyze an interior design proposal of the space using printed architectural drawings and colored renderings. The second group was asked to do the same but only used the explorable MR 3D model seen through an MR headset, in this case: The HoloLens. After the exploration was done, users would sit down, and researchers would ask questions about the space. For example, the general understanding of the elements in the architectural program, how well people perceive length and sizes of objects, perception and understanding of textures and materials, and knowledge of demolition or renovation of specific elements. A total of 42 people participated in the research, with an average age of 26 years, various ranges of architectural drawing understanding, and from diverse cultural backgrounds, including Africa, the Middle East, Asia, the Americas, and Europe. The results shed light on several topics for architects looking into implementing this technology in their work.Save this picture!First, the study suggests that MR technology allowed users to understand around 85% of the overall design proposal compared to 2D methods (which allowed participants to obtain only around 75% of the information). At the same time, they also concluded that MR does not fully replace 2D; in fact, it's about balance. Both MR and 2D are suitable for identifying spaces and general layout, identifying where activities can be performed, and identifying heights. However, 2D plans are especially good for specific measurements of the space (Length and width), understanding the demolition plan, and identifying countable elements in the design, like the number of lamps, switches, or sockets. On the other hand, MR was better for understanding how elements in the space interact with each other (Like if the columns were wrapped by a specific material). MR  was especially useful for quickly identifying the specific materials and textures of the design and visually understanding size in terms of width, and mentally perceiving certain properties of materials like roughness, smoothness, warmth, or coldness.Save this picture!How Can We Integrate MR into our Current Design Review Workflows?MR has the potential to facilitate inclusive and interdisciplinary collaboration by bridging the gap between technical and non-technical stakeholders. Clients or end users with limited experience in reading architectural drawings often struggle to visualize how a space will look or function. AR, especially through Mixed Reality headsets, can mitigate this by allowing them to engage with the space intuitively. Given the transparent property of the MR lenses, non-architect users can experience the spatial and material qualities of a design proposal directly on-site, making it easier to identify potential issues such as circulation conflicts, scale misinterpretations, or material inconsistencies. This allows them to give feedback that is grounded in their own perceptual experience rather than abstract interpretations. This can help to democratize the design review process and can lead to more informed, client-centered decisions. For architectural teams, combining MR with traditional tools might mean that their detailed technical evaluations (e.g., clearances, counts, and demolition plans) are complemented by a richer experiential understanding from the client, which can lead to more holistic and user-validated design outcomes.Save this picture!This article is part of the ArchDaily Topics: What Is Future Intelligence?, proudly presented by Gendo, an AI co-pilot for Architects. Our mission at Gendo is to help architects produce concept images 100X faster by focusing on the core of the design process. We have built a cutting edge AI tool in collaboration with architects from some of the most renowned firms such as Zaha Hadid, KPF and David Chipperfield.Every month we explore a topic in-depth through articles, interviews, news, and architecture projects. We invite you to learn more about our ArchDaily Topics. And, as always, at ArchDaily we welcome the contributions of our readers; if you want to submit an article or project, contact us.

Klarna said it used an AI doppelganger of CEO Sebastian Siemiatkowski to report its updated quarterly earnings. Klarna 2025-05-22T02:31:59Z Save Saved Read in app This story is available exclusively to Business Insider subscribers. Become an Insider and start reading now. Have an account? Klarna said it used an AI avatar of its CEO to report quarterly earnings in a YouTube video. Klarna brands itself as an AI company and has "streamlined" its workforce by 40% since 2022. Klarna's Q1 results show revenue growth but see a spike in net and credit losses. Buy now, pay later services company Klarna said it used an AI doppelganger of CEO Sebastian Siemiatkowski to report its quarterly earnings on Monday.The AI avatar appeared in a video on Klarna's official YouTube channel to deliver earnings highlights. It wore a brown jacket reminiscent of one in Siemiatkowski's corporate headshots, and aside from a lack of blinking and suspect"Our AI-first strategy is driving exceptional returns, we're outpacing competitors, our merchant network is scaling rapidly, and our next-gen products are reshaping money management for millions," a presumably human Siemiatkowski said in a press release.The move comes as Klarna, which last month put its IPO on ice due to economic uncertainty, tries to brand itself as an AI company. In the earnings press release, Klarna said it has "streamlined" its workforce by around 40% since 2022.In 2022, 800 employees were fired, while some were quietly offered an exit package last year after being placed into a "talent pool." In February 2024, Klarna announced that itsKlarna has recently ramped up partnerships with platforms like Walmart, eBay, and DoorDash, but consumer watchdogs have long been concerned about the potential for overspending under BNPL services. Under the Biden administration, theBNPL providers as credit card lenders, which required stricter protections around disclosures and disputes.The Federal Reserve found in 2024 that users of BNPL services are more likely to rely on high-interest financing tools and are more financially fragile.LendingTree, an online lending marketplace, also found in an April survey that 41% of BNPL users in the US paid late over the last 12 months, up from 34% a year ago.Klarna's latest Q1 results also show that an increasing number of people may not have been paying their loans. While revenue grew 13% year over year and it reached 100 million active users, Klarna also doubled its net losses from $47 million in Q1 2024 to $99 million in Q1 2025 — a 110% increase.During the May 19 earnings call, Klarna attributed the spike in losses to several one-off costs related to depreciation, share-based payments, and restructuring.Klarna's consumer credit losses have also jumped, which its Q1 financial report said is "driven by the accelerated expansion of Pay Later and Fair Financing products." Klarna's first quarter saw a 17% year-on-year increase in credit losses from $117 million to $136 million.Klarna did not immediately respond to requests for comment.

But the added value... Google has set its new Ultra plan at $50 more than any other top-tier AI subscription. While it boasts exclusive tools and integrations, much of the offering repackages features that are already available in other Google services. If competitors follow this lead, AI subscriptions could become significantly more expensive – without offering significantly more value. Google introduced its AI Ultra subscription at I/O 2025, calling it the most advanced option for users who want "the absolute best" of Google AI. Priced at $249.99 per month, it's $50 or more higher than top-tier plans from OpenAI ($200/mo) and Anthropic ($100/mo). New subscribers get a 50-percent discount for the first three months, making it temporarily cheaper than OpenAI. Google frames Ultra as a premium-tier product for creative professionals, developers, and academics who need extended access to its largest models and experimental tools, including the latest Gemini 2.5 Pro model. However, the pricing reflects more than just higher usage limits – it sets a new baseline for what AI companies may soon charge. For $250, Ultra includes access to Google's latest versions of Gemini, the new Deep Think mode in Gemini 2.5 Pro, and early access to the Veo 3 video model, which is quite impressive. It also unlocks high-resolution video generation in Flow, a cinematic video creation tool built around Veo, Imagen, and Gemini. The package offers top-tier usage limits across these tools and others like Whisk Animate and NotebookLM, with more enhancements promised later this year. Many of these features aren't exclusive to Ultra. Google is rolling out Flow to the $20-per-month AI Pro subscription with fewer capabilities. Some Gemini integrations, such as those in Gmail, Docs, and Chrome, are already free or included in lower tiers. So, Ultra subscribers are essentially paying to beta test features that will soon become standard. Google Ultra includes 30 terabytes of Google One cloud storage, a YouTube Premium subscription, and Project Mariner, a task manager handling up to 10 concurrent threads. While these add some value, they aren't AI-specific. YouTube Premium and extra storage are available separately, making this bundle feel more like padding than a core upgrade. For users primarily seeking AI capabilities, paying extra for external subscriptions they may not want or use offers limited additional value. // Related Stories Meanwhile, tools like Whisk and NotebookLM, framed as Ultra upgrades, are also available in basic forms elsewhere. Even Veo and Flow, which sound exclusive, are already seeing partial rollout to AI Pro users. The most meaningful perk may be higher usage caps, but the practical value of those limits remains unclear – a frustratingly common trait across the AI industry. If Google's Ultra tier catches on, it could nudge competitors like OpenAI to introduce similarly priced or bundled offerings – even if the functionality remains essentially identical. That would shift the market from a race to deliver the best AI to a race to monetize "premium" features, regardless of whether they provide real differentiation. Google may be positioning AI Ultra as an elite creative toolkit, but it may also be redefining "premium" as just more expensive.

The Linux Foundation and Meta are putting some numbers behind how open-source AI (OSAI) is driving innovation and adoption.The adoption of AI tools is pretty much everywhere now, with 94% of organisations surveyed already using them. And get this: within that crowd, 89% are tapping into open-source AI for some part of their tech backbone.A paper released this week by Meta and the Linux Foundation stitches together academic brainpower, industry frontline stories, and global survey data to showcase an ecosystem that’s buzzing thanks to being open and affordable.If there’s one thing that jumps off the page, it’s the money talk. Cost savings, folks, are a huge deal here. Unsurprisingly, two-thirds of businesses are saying that open source AI is just plain cheaper to get up and running compared to proprietary. So, it’s no shocker that almost half of them point to these savings as a big reason for going the open-source route.We’re not talking about trimming a few coins here and there. Researchers reckon companies would be shelling out 3.5 times more cash if open-source software simply vanished. As AI digs its heels deeper into everything we do, the financial muscle of open-source is only going to get stronger, potentially even overshadowing traditional open-source software’s impact.But this isn’t just about pinching pennies; it’s about unleashing brains. The report points out that AI can slash business unit costs by over 50%, which, as you can imagine, opens the door for revenue boosts. When open AI models are out there for cheap, or even free, it levels the playing field. Suddenly, developers and businesses of all sizes can jump in, play around, and rethink how they do things.Often it’s the smaller players, the agile startups and medium-sized businesses, that are diving headfirst into open-source AI more so than the big corporate giants. And since these are often the places where groundbreaking ideas and new products are born, it really hammers home how vital OSAI is for keeping the innovation engine chugging and helping those plucky, cutting-edge firms compete.And if you want a textbook example of how going open can turbocharge things, look no further than PyTorch. The report digs into how Meta’s decision to shift its heavyweight deep learning framework to an open governance model, under a non-profit, turned out to be a masterstroke.The report leans on a close look by Yue and Nagle (2024), who tracked what happened next. Once PyTorch flew the Meta nest, contributions from Meta itself “significantly decreased.” Sounds a bit off, right? But actually, it signalled a healthy move away from one company calling the shots.What really ramped up was input from “external companies, especially from the developers of complementary technology, such as chip manufacturers.” Meanwhile, the actual users, the developers building stuff with PyTorch, kept their engagement steady – “no change.”It’s a clear win. As the researchers put it, this kind of shift for major OSAI software “promotes broader participation and increased contributions and decreases the dominance of any single company.” It’s a powerful testament to what report authors Anna Hermansen and Cailean Osborne found: “engagement in open, collaborative activities is a better indicator of innovation than patents.”This isn’t just theory; it’s making waves in massive sectors. Take manufacturing. Open-source AI is set to be a game-changer there, mostly because its open code means you can bend it and shape it to fit. This flexibility allows AI to slot neatly into factory workflows, automating tasks and smoothing out order management. A 2023 McKinsey report, flagged in the study, even predicts AI could pump up to $290 billion extra into advanced manufacturing.Then there’s healthcare. In places like hospitals and local clinics, where every penny and every minute counts, free and flexible tools like open-source AI can literally be lifesavers. Imagine AI helping with diagnoses or flagging diseases early.McKinsey thinks the global healthcare sector could see up to a $260 billion boost in value once AI is really rolled out. A 2024 analysis even showed that open models in healthcare can go toe-to-toe with the proprietary ones—meaning hospitals can get tailored, privacy-friendly OSAI without skimping on performance.And it’s not just about the tech; it’s about the people. The report mentions that AI-related skills could see wages jump by up to 20%. That’s a big deal and really underlines why we need to be thinking about training and development for this new AI era.Hilary Carter, SVP of Research at The Linux Foundation, said: “The findings in this report make it clear: open-source AI is a catalyst for economic growth and opportunity. As adoption scales across sectors, we’re seeing measurable cost savings, increased productivity and rising demand for AI-related skills that can boost wages and career prospects.“Open-source AI is not only transforming how businesses operate—it’s reshaping how people work.”So, the takeaway? Open AI models are fast becoming the standard, the very foundation of future breakthroughs. They’re pushing growth and healthy competition by making powerful AI tools available without an eye-watering price tag.The Linux Foundation’s report isn’t just cheerleading; it’s laying out the hard numbers to show why open-source AI is absolutely crucial for a robust, stable, and forward-looking economy.Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.Explore other upcoming enterprise technology events and webinars powered by TechForge here.

May 20, 2025The Hacker NewsPenetration Testing / Risk Management In the newly released 2025 State of Pentesting Report, Pentera surveyed 500 CISOs from global enterprises (200 from within the USA) to understand the strategies, tactics, and tools they use to cope with the thousands of security alerts, the persisting breaches and the growing cyber risks they have to handle. The findings reveal a complex picture of progress, challenges, and a shifting mindset about how enterprises approach security testing. More Tools, More Data, More Protection… No Guarantees Over the past year, 45% of enterprises expanded their security technology stacks, with organizations now managing an average of 75 different security solutions​. Yet despite these layers of security tools, 67% of U.S. enterprises experienced a breach in the past 24 months​. The growing number of deployed tools has a few effects on the daily operation and the overall cyber posture of the organization. Although it seems obvious, the findings tell a clear story - more security tools do mean better security posture. However, there is no silver bullet. Among organizations with fewer than 50 security tools, 93% reported a breach. That percentage steadily declines as stack size increases, dropping to 61% among those using more than 100 tools. Alert Fatigue Is Real The flip side of larger security stacks is that CISOs and their teams must contend with a much larger influx of information. Enterprises managing over 75 security solutions now face an average of 2,000 alerts per week — double the volume compared to organizations with smaller stacks, and those with over 100 tools receive over 3000 (3x the alerts). This in turn, puts much more emphasis on effective prioritization, otherwise, critical threats may get buried in a sea of alerts. In this environment, where alert volumes are high and time to triage is short, organizations benefit most when they can frequently test for exploitable gaps, so they know which issues truly matter before threat actors find them first. Software-Based Pentesting Gains Ground Trust in software-based security testing is growing rapidly. Only 5-10 years ago, many enterprises would never have permitted automated tools to run pentests in their environments for fear of causing outages, but sentiment is changing. As CISOs continue to recognize the advantages of software in scaling adversarial testing and keeping pace with constantly changing IT environments, software-based pentesting is becoming the standard. Over half of enterprises now use these tools to support in-house testing, driven by trust in their reliability and the need for scalable, continuous validation strategies. Today, 50% of CISOs cite software-based pentesting solutions as their primary method for uncovering exploitable gaps​. Insurance Providers Become Unexpected Influencers Beyond internal management and Boards of Directors, a surprising new force is shaping security strategy: Cyber insurance providers. 59% of CISOs admitted that they have implemented at least one cybersecurity solution that they were not previously considering as a result of their cyber insurers. It's a clear sign that insurers aren't just pricing risk, they're actively prescribing how to reduce it, and reshaping enterprise security priorities in the process.​. Low Confidence in Government Support While governmental agencies like CISA (in the US) and ENISA (in the EU) play an important role in threat visibility and coordination, confidence in government cybersecurity support is surprisingly low. Only 14% of CISOs believe the government is adequately supporting the private sector's cyber challenges​, while 64% feel that government efforts, though acknowledged, are insufficient​. 22% believe that they cannot rely on the government at all for cybersecurity help. To benchmark your organization's pentesting practices, budgets, and priorities against other global enterprises, register for the webinar on May 27, 2025 where senior security analysts will discuss the key findings. Alternatively, get the full 2025 State of Pentesting Report and see all the insights for yourself!Note: This article was written and contributed by Jay Mar Tang, Field CISO at Pentera. Found this article interesting? This article is a contributed piece from one of our valued partners. Follow us on Twitter  and LinkedIn to read more exclusive content we post. SHARE    