DIGITAL LIFE

New remote access trojan threatens Android ecosystem

The European cybersecurity company ESET has issued a global alert about the discovery of a new remote access trojan that compromises the security of Android devices through advanced social engineering tactics. The threat stands out for its ability to collect sensitive data and capture all user activity remotely. Unlike conventional tools focused on stealing banking credentials, this code allows you to take complete remote control of the affected equipment.

What is BTMOB and why is it a concern...BTMOB is classified as a RAT (Remote Access Trojan). Among the features provided by its creators, a tool for creating malicious applications stands out, allowing cybercriminals to launch campaigns more quickly and efficiently.

As already mentioned in other WeLiveSecurity articles, Brazil is known for the high incidence of Trojan detections. However, due to characteristics of the local scenario, these detections tend to be concentrated on banking Trojans.

In general, Trojans are threats that disguise themselves as legitimate files or applications to deceive victims and infect their devices. In the case of banking Trojans, the focus is on stealing financial information. RATs, on the other hand, have a more comprehensive scope, allowing everything from the theft of different types of data to complete monitoring of the infected device.

Among the capabilities of this type of malware are keylogging, periodic screen capture, activity recording, file transfer, and hijacking of active sessions. In the specific case of BTMOB, the possibility of real-time screen transmission was also observed, in addition to direct interaction between cybercriminals and the compromised device.

How BTMOB is distributed...Several social engineering campaigns have been used to distribute BTMOB. Among them, phishing sites that impersonate well-known streaming services stand out, as well as fake cryptocurrency mining platforms.

Since it is a threat focused on Android devices, the campaigns observed in Brazil concentrate their efforts on creating malicious versions of popular applications. These apps are distributed through social engineering, frequently directing victims to fake app stores that mimic the appearance of the Google Play Store.

BTMOB was also identified as being offered as a service on a website hosted on the open web (surface web). The page is simple and directs interested parties, through clickable links, to contact the BTMOB operator via Telegram.

In addition, references to the tool were found on social networks. An account on platform X (formerly Twitter), for example, redirects interested parties to the same contact on Telegram. Other platforms, such as Instagram, also present content related to the dissemination of the malware.

Analyses conducted by two independent researchers, Johnk3r and Merl, also point to the spread of the threat in other countries. In one case identified in Argentina, cybercriminals used the impersonation of a government agency, the Agencia de Recaudación y Control Aduanero, to distribute the malware, increasing the credibility of the campaign and potentially increasing the number of victims.

“BTMOB shows how the smartphone can go from being just a target for fraud to becoming a control point for the attacker. When the user installs a fake application and grants critical permissions, they are potentially exposing not only their data, but all the activity they maintain on the device,” says Ricardo Neves, Communications Manager at ESET Brazil.

The infection process begins with redirecting victims to phishing pages that replicate the visual identity of legitimate services, such as streaming platforms or cryptocurrency mining systems. From these addresses, users access fake app stores designed to mimic official repositories, such as the Google Play Store, where they download malicious installation files in APK format.

Technical analysis conducted by the ESET research team indicates that the first detections of this remote access trojan occurred in Brazilian territory. Additionally, records shared by analyst Germán Fernández Bacian document the group's activity in Argentina, with the direct falsification of the official portal of the government agency ARCA. The potential for geographic expansion of this infrastructure remains high due to the flexibility of the distribution model.

Abuse of Accessibility Services elevates privileges in the system...Once the installation on the target device is complete, this remote access trojan immediately begins attempts to obtain elevated administrative permissions. The critical vector for consolidating the attack lies in the systematic abuse of the Android operating system's Accessibility Services. This legitimate feature, designed to support users with special needs, allows the malicious application to perform automated actions without requiring any additional interaction or consent from the mobile phone user.

The criminal ecosystem associated with this campaign operates under the Malware-as-a-Service (MaaS) model. The creators offer an automation tool that allows the generation of new variants of the APK file without requiring advanced programming knowledge. The marketing of the product includes structured sales channels and dedicated technical support services, factors that significantly accelerate the circulation of this remote access trojan in multiple markets.

FAQ – Frequently Asked Questions:

- What is a remote access trojan and what are the risks on Android?

A remote access trojan is a type of malware that allows cybercriminals to take complete control of a device remotely. On Android, this threat monitors activity and collects sensitive data through abusive administrative privileges.

- How does an Android device get infected by this code? 

The infection develops through social engineering schemes where the victim accesses fake links to known services. These portals direct the user to fake app stores, where a malicious APK file is downloaded.

-How does malware bypass system protections? 

The fraudulent application requests the activation of Android Accessibility Services. By obtaining this level of authorization, the code gains administrative privileges that enable the autonomous execution of commands and the collection of information without the user's knowledge.

Key points:

-Full remote control: The malicious code surpasses the functions of common banking trojans and allows remote management of the affected smartphone.

-Professional distribution: The threat operates as a commercial service with automatic APK generators and technical support channels for buyers.

-Accessibility abuse: Exploitation of Android Accessibility Services serves to automate actions and bypass system security restrictions.

-Use of fake repositories: Attackers accurately replicate the design of official stores and government portals to deceive victims.

mundophone

TECH

UB scientists invent ‘transient thermal barcodes’ to improve plastic recycling

arcode readers excel at quickly identifying groceries and other products. Could a similar idea work at industrial recycling facilities to make sorting different plastics quicker and more cost-effective?

The answer, according to a University at Buffalo research team, is yes.

Unlike traditional barcode scanners, which rely on optical sensors, the team is developing a system that creates “three-dimensional transient thermal barcodes” that could rapidly identify plastics moving on conveyor belts.

The work is described in a Nature Communications Engineering study posted according to the journal’s early access policy.

“Our goal was to develop a cost-effective, scalable and industrially relevant plastics sorting technique that addresses the key prevailing scientific gaps restricting the recycling of plastics,” says corresponding author Amit Goyal, PhD, SUNY Distinguished Professor and SUNY Empire Innovation Professor in the UB Department of Chemical and Biological Engineering.

Goyal directs the UB Initiative on Plastics Recycling and Innovation, which is designated as a New York State Center for Plastics Recycling Research and Innovation by the New York State Department of Environmental Conservation (DEC).

The system, he says, aims to “improve the quality of sorted plastics by reducing contamination and, hence, increasing the recycling of these materials to help enable a circular economy.” He adds that it “is estimated that one ton of recycled plastic saves 5.7 megawatts of electricity, 685 gallons of oil, and 30 cubic yards of landfill space.”

Plastic recycling rates remain low...Plastic waste generated by households and businesses are sent to material recovery facilities where plastic is separated from other wastes. This is often done by hand, which can result in false identification and poor quality of sorted bales.

Plastics are then separated into different types. Presently, there is a lack of cost-competitive and accurate techniques that can effectively identify plastic types by their resin codes.

Developing techniques – including near-infrared spectroscopy, Raman spectroscopy, laser-induced breakdown spectroscopy – suffer from one or more issues. These include poor sensitivity; subpar selectivity; slow speeds; inability to detect black plastics; or they cannot be operated in standoff mode (identifying plastics from a distance) that’s often required in material recovery facilities.

These limitations explain, in part, why plastic recycling rates remain relatively low worldwide.

Team employs ‘molecular fingerprint regime’...To overcome these challenges, the UB team sought to invent a technology that quickly captures the molecular signature of waste plastics from a distance. It also must have the potential to be easily retrofitted into existing sorting machinery.

The researchers started with a range of mid-infrared wavelengths, which they shine onto plastic items. (Mid-infrared is known as the “molecular fingerprint regime” because of the unique spectral peaks for all plastic types that exist in this part of the electromagnetic spectrum.)

As the plastic absorbs the light, molecular bonds within the plastic vibrate, generating temporary heat patterns that are measured by a thermal camera. These heat patterns, which reflect the unique molecular structure of each plastic, are essentially a “three-dimensional transient thermal barcode.”

Researchers used six mid-infrared wavelengths identify all six common types (PET, PP, PS, HDPE, LDPE, PVC) of plastic waste. Moreover, the technique can also identify black plastics (all black plastics are based on one of the six types of plastics but with significant carbon derivatives added).

Heat-based signatures rapidly distinguish between common commercial plastics; could help address global pollution

Researchers are fine-tuning the system...At this point, the system is not ready for industrial deployment. The research team is working on advancements – faster hardware to sort plastics on high-speed conveyor belts; cost-effective light sources that project multiple mid-infrared wavelengths simultaneously; and artificial intelligence-based software – to improve the technology.

Still, the study shows that the transient thermal barcode technique fundamentally works and provides early promise to improve plastics recycling efficiency. It could eventually help divert more plastic waste from landfills and the environment, where plastics break down and cause health problems among animals, plants and humans.

The study was led by the New York State Center for Plastics Recycling Research and Innovation at UB. Lead author Kunal Singh, PhD,  is a postdoctoral fellow mentored by Goyal and co-corresponding author Thomas Thundat, PhD, a SUNY Distinguished Professor at UB. All three authors are affiliated with the Department of Chemical and Biological Engineering in the School of Engineering and Applied Sciences at UB.

Singh’s work has been central to this invention and study, Thundat and Goyal say. They note he has “not only done outstanding scientific research but has also developed advanced, custom instrumentation” and that his “rigorous and meticulous work identified key shortcomings in our initial approach and provided elegant technical solutions.”

Singh says: "We hope to further develop the technique so that it can be transferred to industry.”

The New York State Center for Plastics Recycling Research and Innovation at UB provided funding for the research. The center is supported by a grant from New York State Environmental Protection Fund, which is administered by the DEC.

Researchers have invented a "Transient Thermal Barcode" (TTB) technique that identifies plastics from a distance using unique heat signatures to revolutionize industrial sorting and boost global recycling rates. Developed by a team at the University at Buffalo (UB), this non-contact approach bypasses the limitations of traditional sorting methods to rapidly and accurately separate consumer plastics by their specific resin codes.

How the Technology WorksThe system captures the molecular signatures of moving waste items through a quick optical and thermal process:

Mid-Infrared Illumination: A tunable mid-infrared laser shines onto the plastic item. This part of the light spectrum is considered the "molecular fingerprint regime".

Molecular Vibration: The plastic absorbs the light, forcing its specific molecular bonds to vibrate.

Thermal Mapping: The vibration causes localized heating, generating a temporary hotspot.

Barcode Creation: An infrared thermal camera records these unique, three-dimensional heat patterns. The heat signatures act as a digital barcode unique to that material.

Why this matters for the environment...Current recycling rates remain low due to human sorting errors and contamination in sorted plastic bales. By substituting human sorting with automated TTB systems, facilities can significantly reduce contamination.

According to data shared by the UB Initiative on Plastics Recycling and Innovation, scaling up this automated sorting efficiency has massive resource-saving potential:

5.7 megawatts of electricity saved per ton of recycled plastic.

685 gallons of oil conserved per ton.

30 cubic yards of landfill space saved per ton.

by Cory Nealon--buffalo.edu

TECH

From AI art to body scans: Midjourney unveils underwater body scanner

We’re building a bold new kind of machine to reimagine the foundations of healthcare and our relationships to our bodies.

We’ve dreamed of something as powerful as MRI, and as casual as a trip to the spa, and we’re unveiling a path to that - today.

One of the overarching themes of the 21st century will be the expanding reach of intelligence and what we choose to do with it. We talk to artificial intelligences every day - and increasingly we talk to them about our health.

Whether we’re talking to doctors or AIs, what we do with our health comes down to having data and an awareness of our bodies.

You want as much data as you can get about your health as quickly and as cheaply as possible. In other words, you want a technology optimized for getting as many “megabytes per second per dollar” of information about your body.

In an ideal and near-term future, we take this information and watch how it changes over time. We compare it to the general population, we talk to doctors, nutritionists, coaches, trainers, and AI friends. We become more aware of our health and we improve our lifestyles. We make smarter, more proactive, more frequent decisions. And we live longer, healthier lives, better lives.

The Midjourney Scanner...It starts by stepping into a shallow pool of golden light. You then begin to descend into the water. Your body passes through a ring of underwater sensors, each acting like a dolphin, using its echolocation. The sensors send ultrasonic sound waves through your body from every angle. With enough waves, and enough angles, we form an image of what's happening inside your body.

When you step into the water, you’re standing on top of a platform. The platform is connected to rails and begins to descend into the water - an elevator gently lowering you at around 2 inches, or 5 centimeters, per second.

As you descend you pass through a ring made of half a million tiny squares each the size of a fine grain of sand, and each capable of acting as both a tiny speaker and a tiny microphone.

Each square creates ultrasonic waves and records the ripples back at millions of times per second. Together they act as both a choir and an audience - producing terabytes of data each second. If we converted that data into HD internet video you’d need to watch 500 hours of footage for every 1 second of scan data.

The sheer number of mechanical elements, the inconceivable volume of data, and the computational power required for this to all come together is one reason why no such machine was ever made - until now.

As you descend into the water, hundreds of thousands of tiny elements take turns, sending out waves, listening together, compressing and then streaming data to a massive cluster where thousands of computers split the task.

The major computational task is figuring out how to change waves into images. Basically - as waves travel through the water and your body they change shape. The shape of these waves changes whenever there is a change in density or stiffness (i.e., going from water to skin to fat to muscle to bone). By looking at how the shapes of all the waves change, we reconstruct a detailed map or ‘image’ which basically lets us figure out what’s in there.

All of these images come together to cover a 3D map of your body, down to a fraction of a millimeter, that looks a lot like today's MRIs but at nearly a hundred times the speed.

Midjourney is embarking on a new business model: a body ultrasonic scanner. Known for turning text prompts into AI-generated images, the company has now revealed its next project: the Midjourney Scanner, a medical machine that can scan your entire body in under 60 seconds. The project name, Midjourney Medical, has nothing to do with any of the company's previous ventures. 

How does it work? You step onto a platform and get submerged in water at about two inches per second. As you descend, your body passes through a ring of half a million tiny elements (each one the size of a sand grain) that fire ultrasonic waves at you from every angle and record what bounces back. Midjourney compares the experience to being surrounded by half a million tiny dolphins using echolocation all at the same time.

As a result, you get a detailed 3D map of your body, with an accuracy of a fraction of a millimeter, similar to an MRI, but produced at nearly a hundred times the speed. Midjourney aims to scan the whole body in less than 60 seconds, much less than the 60 to 90 minutes that a full-body MRI takes. Moreover, the scanner will use custom silicon to enable much better image quality.

Midjourney is building this project in collaboration with Butterfly Network, an ultrasound device maker. Over the next year, the technology will be refined, and, when ready, will be introduced in spas. The first one is planned to open in San Francisco. From there, the plan is to get FDA approval, expand to other cities in 2028, and reach 50,000 scanners worldwide by 2031.

"Midjourney Medical," which is developing a full-body ultrasonic scanner. It functions by submerging the user in a shallow tank and utilizing over 350,000 tiny sensors to create a 3D medical map in just 60 seconds without using radiation.

The scanner operates on a technology known as Ultrasonic CT (USCT) and relies on hardware components created by ultrasound company Butterfly Network.

The Process: You step onto a platform, lower yourself into a shallow, glowing pool of water, and pass through a ring of sensors that send ultrasonic waves through your body.

The Speed & Quality: The company claims the imaging quality rivals that of a clinical MRI, while the process takes only 60 seconds.

The Business Model: Rather than hospital settings, Midjourney plans to build a network of luxury wellness spas equipped with saunas and cold plunges.

Long-Term Ambition: Midjourney aims to deploy 50,000 scanners worldwide by 2031, with the capacity to conduct one billion scans per month, ultimately creating a massive dataset for preventative AI health tracking.

mundophone

TECH

Samsung rides the wave of TSMC

Samsung's chip manufacturing business is experiencing a golden moment. After a first quarter of 2026 with record-breaking operating profits, the South Korean manufacturer is preparing to host even more heavyweights in the technology industry, desperately seeking a viable alternative.

The reason behind this mass migration is simple: TSMC can't keep up. The explosion in demand for artificial intelligence and high-performance chips has completely exhausted the production capacity of the Taiwanese giant, forcing companies to rapidly diversify their supply lines.

To avoid being held hostage by bottlenecks in the supply chain, technology companies like Google and AMD are turning to Samsung. It's the classic case of "not putting all your eggs in one basket," and the South Korean brand is capitalizing on this competitive crisis in an exemplary way.

With TSMC practically at full capacity, the list of clients adopting the "dual-sourcing" strategy (splitting orders between two foundries) continues to grow. AMD, for example, is already in negotiations for Samsung to manufacture its future processors starting in 2028.

If you thought Google would be left out, think again. The search giant is deepening ties for the production of next-generation Axion processors and has already asked Samsung to take over some of the critical Tensor Processing Units (TPUs) intended for heavy artificial intelligence tasks.

As you might expect, this diversification movement isn't limited to the most obvious technologies. Even the automotive industry is preparing for shortages, securing its space on the South Korean brand's assembly lines:

-Tesla: You've already confirmed that your next AI6 chip will be entirely manufactured at Samsung's facilities in Texas.

-BYD: The world's largest electric vehicle manufacturer is in advanced discussions for the production of its autonomous driving chips.

-Groq: The well-known AI startup backed by NVIDIA already uses Samsung's foundry and is expected to maintain the partnership for future versions of its specialized chips.

The chip market is narrowing...Looking coldly at the current market, the reality is that there are only three names capable of manufacturing truly advanced semiconductors: TSMC, Samsung, and Intel. Since Intel's external manufacturing division is still in its infancy, Samsung naturally assumes the status of a major and unique alternative to TSMC's dominance.

It's undeniable that TSMC still holds the crown in producing the world's most advanced chips. However, this chronic inability to meet rampant demand is proving costly in the long run, opening the door for the South Korean company to gain momentum that seemed almost impossible just a short time ago.

It remains to be seen whether Samsung will be able to maintain this breakneck pace and convince these companies to stay on its side, even when the storm passes. For now, it's at least curious to observe how the competitive crisis ended up being the best news the brand's executives could receive this year.

Water and talent shortages...The scarcity of water and skilled labor in Taiwan has left TSMC worried, potentially jeopardizing the production of advanced chips for generative artificial intelligence solutions. The warning was given on Friday (12) by the company's CEO, CC Wei.

The Asian country has experienced several periods of drought in recent years, even imposing consumption controls in 2021, when it faced one of the worst droughts in its history. Therefore, the head of the world's largest chip manufacturer has not yet completely ruled out hiring water trucks to keep its factories running.

Addressing the issue during the inauguration of a science park in Pingtung, the executive said that the President of Taiwan, Lai Ching-te, presented plans to solve the water shortage problem. One of the ideas is to interconnect the island's reservoirs, which have refilled with recent rains.

When the project is completed, water distribution throughout the country will become more efficient, guaranteeing access even during crises, including for industries;

“In that case, in the future I will no longer need to say that land, water or electricity may be lacking,” declared Wei;

He was referring to the historical “five bottlenecks” of the local industry, which are water, energy, land, labor and talent;

The last two themes were also cited by the CEO of TSMC, who stated that he suffers from a lack of specialized professionals to hire.

On this, the Taiwanese president revealed that the government is trying to attract and retain foreign talent, especially for the technology sector. The strategy includes making the work authorization processes in the country less bureaucratic.

Even in the face of these difficulties, the head of the semiconductor manufacturer reiterated that the company will maintain its main research, development and manufacturing centers in the country. It is worth remembering that TSMC invested US$ 165 billion in the construction of a complex in Arizona (United States).

The high water consumption related to AI also generates concern among other technology giants, such as Google. Learn about the plans of the Mountain View company to make the use of water resources more efficient.

mundophone

TECH

In game theory, generalists sometimes win out over specialists, finds research

Whether you're playing poker against a single opponent or find yourself in a bidding war over a home purchase with another prospective buyer, you are operating under conditions of imperfect information. You know what cards you're holding in the poker game, and you also know how much above the home's asking price you can afford, but you don't know your opponent's hand in the card game or how high the other home buyer is willing to go.

A paper co-authored by MIT researchers and presented in April at the International Conference on Learning Representations in Rio De Janeiro won't tell you what to do in these situations, specifically. But it does offer new insights into so-called imperfect-information games that involve two contestants facing off in a "zero-sum" competition, where one player's gain means the other player's loss.

MIT researchers on the project include Sobhan Mohammadpour, a PhD student in MIT's Department of Electrical Engineering and Computer Science (EECS) and the Laboratory for Information and Decision Systems (LIDS); and Gabriele Farina, an assistant professor in EECS and a principal investigator at LIDS. Additional co-authors include Max Rudolph of the University of Texas at Austin (UT), Nathan Lichtlé of the University of California at Berkeley (UCB), Alexandre Bayen of UCB, J. Zico Kolter of Carnegie Mellon University (CMU), Amy X. Zhang of UT; Eugene Vinitsky of New York University; and Samuel Sokota of CMU.

The focus of the new work is on algorithms that could be used to train neural networks to participate in imperfect-information games. The assumption, long held in the field, was that algorithms grounded in principles of game theory would, in this setting, clearly outcompete a general-purpose variety of algorithms called policy gradient methods, which came into use for decision-making in the 1990s.

The term "policy" in this context basically means strategy, whereas "gradient" refers to a path that leads in the direction of greatest change—to the top (or bottom) of a hill, for example. Policy gradient methods are being used to train neural networks to make decisions that move—in small, sequential steps—toward a particular goal (like reaching a summit, metaphorically speaking), with continual adjustments and course corrections made along the way to bring the agent closer to the intended destination.

Although strategic games were not on the original agenda when policy gradient methods were conceived in the early 1990s, the authors of the new paper still wondered how this class of algorithms might fare in two-player games. These methods become more complicated to analyze in multi-agent settings, according to Farina.

"There is still a direction you can move in to improve your circumstances, but, because of the other player's actions, that direction can constantly change over the course of the game. And those shifts can be rapid," says Farina.

"It had been pretty much taken for granted that specialized game-theoretic algorithms were the right approach for this setting," says Sokota. "Our study showed that policy gradient methods can work better than these specialized algorithms, and that the specialized algorithms may not work as well as people thought—which raises an interesting sociological question about why this went unnoticed for so long. Part of the answer is that the field hadn't done the engineering work required to rigorously evaluate the algorithms, so it was hard to tell what worked and what didn't."

Consequently, a major contribution of this work has been to provide an even-handed way of appraising different algorithms that can teach agents—i.e., neural networks—how to compete in imperfect-information games.

"We're taking a different approach," notes Rudolph. "Unlike many of the papers published in this field, we're not proposing a new algorithm that can beat out other algorithms. We're proposing a benchmark that can assess these algorithms."

Simply put, a benchmark consists of software designed to rate the performance of algorithms. "What we're offering are testing grounds, or playing grounds, where people can take their algorithms, train them for a specific task, and see how well they do," says Farina.

The group calculates a player's performance in terms of a concept called exploitability, which measures how well a player does against the "worst-case adversary," Sokota explains. "In a game like poker, this opponent wouldn't know what my hand is, but would know how I would behave for any given hand." Achieving a zero on this scale implies perfect play, whereas a high exploitability score indicates far-from-optimal play.

Five games were played in experiments carried out by the team: two versions of Phantom Tic-Tac-Toe, in which players can't see what their opponent has done, along with two imperfect-information variants of a board game called Hex, and another game of deception called Liar's Dice.

The biggest challenge faced by the researchers was getting the exploitability measure to work on games of this size, which may include as many as 30 billion states. A "state" in this case is not just all the possible board positions, but also encompasses the entire history of the game, including every step and misstep along the way.

"It's like looking into a dark room that's filled with objects you can't see," says Mohammadpour. "Somehow, you need to figure out where these objects are and exactly how they got there." Previous researchers, Mohammadpour adds, have typically used exploitability for games that are 100,000 times smaller than the ones analyzed in their study.

In the experiments carried out on these five games, neural networks trained with policy gradient algorithms got better (lower) exploitability scores than networks trained on game theory-based algorithms. In head-to-head competitions, which took place in the next round, the policy gradient-trained networks again beat their game theory-trained opponents.

"Those results were reassuring," Rudolph says, "because they give us more confidence in our benchmarking approach."

The team has made their benchmarking software freely available and convenient to use.

"You don't need a supercomputer," Mohammadpour says. "You can run it on an ordinary laptop. And all you have to do is add a single line of code to a commonly used collection of benchmarking software called OpenSpiel."

Although their experiments involved some fairly obscure games, Farina would like to put this work into a broader context.

"Keep in mind that the term 'game' really applies to any multi-agent strategic interaction," he says. "So the lessons we learn from this research are by no means limited to recreational games."

Vinitsky agrees. "Hidden information is a very important property of the world," he says. "It pervades a range of things—including military operations, trading scenarios, and negotiations—all of which are carried out under conditions of hidden information. The idea that we can improve on these games suggests that we can also do better in these other settings as well."

Ian Gemp—a computer scientist and game theory expert at Google DeepMind who was not involved in this study—finds these results encouraging.

"This work serves as a compelling reminder," he says, "that modernizing classical tools [like policy gradient methods] remains a highly productive path for solving complex strategic problems."

Provided by Massachusetts Institute of Technology 

TECH

Redesigned high-NA lithography optical system aims to overcome challenges in semiconductor chipmaking

From data centers powering next-generation AI to vital medical technology, cars, and the mobile device or computer you're probably reading this on, semiconductor-based computer chips are essential to modern life.

As technology advances and power consumption increases, scientists are hoping to create ever-smaller computer chips, requiring delicate chip designs on the individual nanometer (nm) scale. Methods such as extreme ultraviolet (EUV) lithography are providing new paths to these smaller chips, but they come with major physics, engineering and financial challenges, limiting current application and scalability.

Published in the Journal of Micro/Nanopatterning, Materials, and Metrology, Professor Tsumoru Shintake of the Okinawa Institute of Science and Technology (OIST) has proposed a radical redesign of the illumination systems and projectors used in high numerical aperture (high-NA) EUV lithography.

Simulations suggest that his design could eliminate troublesome optical (so-called "mask 3D") effects, enhance resolution and enable the manufacture of smaller computer chips at lower cost than current EUV methods.

This diagram shows Shintake's proposed high-NA EUV lithography projector design. The collector mirrors in the illumination system have a simpler design to bring short wavelengths of light from the EUV source to the photomask. The two sets of mirrors in the projector increase numerical aperture. The circuit pattern on the photomask is projected onto the wafer, followed by chemical etching that produces dense nanometer lines on the silicon surface. This process is carried out on more than 20 layers of wafer that are stacked to ultimately produce a functional chip. Credit: Tsumoru Shintake, OIST

Shintake says, "Current EUV lithography systems cost hundreds of millions of euros per machine. My new design should achieve fine, 2–3 nm scale details, in a much cheaper way compared to today's state-of-the-art machines."

He highlights the downstream applications of these smaller semiconductor chips in the context of growing AI demands.

"The International Energy Agency predicts that data center electricity consumption will double by 2030 due to demand from energy-intensive applications like AI agents. However, the higher density of features on high-NA-produced chips means signals should travel shorter distances, minimizing energy loss. This can reduce power cost per computation," explains Shintake.

"These denser chips should also release less heat, lowering power required for cooling. Such improvements could have significant impacts for data center energy usage."

What is EUV lithography? Understanding semiconductor chip synthesis...In EUV lithography, light with an extremely short wavelength (13.5 nm) is generated and guided through an illumination system, where it strikes a reflective photomask that contains a template of the circuit pattern. The reflected light pattern then passes through a projector, which uses a series of mirrors to shrink and focus the image onto a silicon wafer. The pattern is then etched onto the wafer through further processing.

To print a higher density of circuit components, researchers are turning to high-NA EUV lithography. NA is linked to the range of angles at which an optical system can accept or emit light. A higher NA captures a wider angle of light, enabling the lens to resolve finer details. In theory, the resolution limit (the smallest detail that can be resolved) is inversely proportional to NA, so a higher NA provides finer printing capability for semiconductor chips.

Professor Shintake examines a premade, commercial silicon wafer. He stands behind a prototype of his last design for in-line, EUV lithography. Efforts are underway to make a prototype for his current in-line design for high-NA EUV lithography. Credit: Andrew Scott, OIST

In the early days of EUV lithography research in the 1990s, scientists explored optical designs for high-NA lithography that were similar to Shintake's, in which the photomask, projector and wafer were aligned. While these in-line configurations were attractively simple, researchers were unable to find solutions to distortions, blurring and other optical errors that occurred, particularly as the NA increased.

To address these challenges, Shintake first investigated whether a simple pair of mirrors—one concave and one convex—could serve as the projector. His design eventually evolved into a two-stage configuration, with a concave-convex mirror pair in each stage.

While initially unsuccessful, Shintake soon realized that multiple reflections between carefully arranged mirrors could potentially cancel out optical defects while maintaining high NA. After spending many months running calculations on OpTaliX, an optical simulation system, he determined the ideal curvature and positioning of the mirrors needed to achieve high NA while preserving image quality.

A step toward scalable semiconductor production...As with every research project, there are some limitations. The simulations assume that mirrors will be 100% reflective and defect-free, and moving from simulation to real-world implementation will require expert engineering. Building a physical prototype is Shintake's next step, and his team has now started developing EUV hardware, with the aim of producing lower-cost, high-performance EUV lithography.

"This design can make high-NA technology much simpler and cheaper to produce, opening new possibilities for semiconductor manufacturing. We should be able to create machines that are a quarter of the cost of those currently on the market," concludes Shintake.

"By achieving finer designs, we can make higher-density memory and more efficient logic chips. This technology may have transformative impacts on society, powering data centers and the future of AI, and making electronics faster, more energy-efficient and potentially cheaper to run."

Provided by Okinawa Institute of Science and Technology

DIGITAL LIFE

Google Chrome and the dictatorship of ads: the end of the line for traditional Ad Blockers

If you're one of those users who can't live without a clean internet free of annoying ads, we have bad news. Google has finally decided to deliver the coup de grâce to the traditional ad blockers we use daily in its browser.

The controversial transition to the new Manifest V3 architecture has been announced for years, but now the company has begun ruthlessly disabling extensions based on the old system. This means your browsing experience is about to change drastically.

The official justification from the search giant focuses on the privacy and security of the entire ecosystem, but the tech community has little doubt. For most experts, the real reason for this move is to shield and protect its billion-dollar online advertising empire.

To understand the magnitude of this resource cut, Manifest V3 fundamentally changes how extensions interact with your browser. By drastically limiting network rules and dynamic filtering, powerful and complex blockers, such as the famous uBlock Origin, simply cease to operate at their full potential.

It's frustrating, to say the least, to see Google using the pretext of security to crush tools that users legitimately installed to protect their own privacy. With this change to the codebase, the effective interception of network requests – the real magic behind blocking aggressive ads on YouTube or Twitch – becomes an almost impossible task to accomplish in Chrome.

What Google took away and why it took it...The technical change is the replacement of Chrome’s webRequest API with the declarativeNetRequest API.

Under the old system, extensions like uBlock Origin could watch your browser’s traffic as it happened, see an ad or tracker trying to load, and block it on the spot before it ever reached your screen.

Under the new system, extensions have to hand Google a pre-written list of things to block and Chrome decides whether to follow those instructions. The lists are capped at a fixed number of rules, and the extension can’t react to anything that isn’t already on the list.

uBlock Origin’s developer, Raymond Hill, has been clear that a Manifest V3 version cannot replicate the original’s full capabilities. A stripped-down version called uBlock Origin Lite exists for MV3, but it handles only a fraction of the filter lists, the community-maintained databases of known ads and trackers, that the original supported.

It also can’t perform cosmetic filtering, the process of hiding ad containers and promotional elements that remain on a page even after the ad itself is blocked. Without it, you get blank boxes where ads used to be, or sponsored content that looks native to the page. For more than 40 million Chrome users who relied on the original, the replacement is a downgrade by design.

Google engineer Devlin Cronin confirmed the timeline in a Chromium code review commit, a logged change to Chrome’s underlying source code that other developers can inspect, writing that “MV2 extensions are no longer allowed in any supported version of Chrome, and we are removing support for them and the associated functionality. We won’t be able to provide / maintain this functionality indefinitely due to the complexity and tech debt, as well as the security risks it entails (we’ve actually found a number of bugs that are specific to MV2 lately). Of course, other browsers can continue supporting these if they so desire.”

Cronin’s sign-off, that “other browsers can continue supporting these if they so desire,” suggests the removal as a Chrome-specific choice. It isn’t. Google controls 65% of the desktop browser market and the MV2 code being stripped from Chromium, the open-source project that Chrome and many other browsers are built on top of, affects every browser that shares that foundation.

Google justifies the migration on security grounds and there’s some substance to the argument. The old webRequest API gives extensions deep access to every network request a browser makes, from images and page loads to login credentials, and the extension sees the data before Chrome acts on it.

A compromised or malicious extension with that access can read your passwords as you type them, redirect you to fake websites, or slip harmful code into pages you trust.

The declarativeNetRequest API is designed to prevent exactly this kind of attack by restricting extensions to predefined rule sets. Instead of giving an extension free rein over your browser traffic, Chrome only lets it submit a list of instructions in advance and handles the blocking itself. That narrows the ways a bad actor can exploit an extension because the extension never gets to touch your data directly.

But Google generated roughly $239.5 billion in advertising revenue in 2025, and content blockers directly reduce the number of ads users see. The MV3 restrictions don’t ban ad blocking entirely. They cap how many rules an extension can use and eliminate dynamic blocking, the ability to recognize and stop new ad formats and trackers as they appear in real time.

Ad companies constantly change how they deliver ads, rotating domains and disguising tracking scripts, and the old extensions could keep up with that. The new ones can only block what’s already on a list that was written before the ad loaded. The result is ad blockers that work against yesterday’s ads but struggle against the ones that adapt daily.

The same company that built Chrome and sells the ads it displays also wrote the rules governing what ad blockers can do inside it. Whether those incentives shaped MV3’s design is the most obvious question in the room, and Google has never given a convincing answer.

Microsoft Edge and Opera, both built on Google’s Chromium engine, are expected to follow suit because the MV2 code being removed is shared across all Chromium-based browsers. Maintaining it independently would require significant engineering resources that most of those browsers are unlikely to commit.

Brave, also Chromium-based, supports MV2 but also sidesteps the problem by building its own ad-blocking engine directly into the browser, bypassing the extension framework entirely.

Firefox, which runs on its own engine, continues to support Manifest V2 and uBlock Origin without restriction. Mozilla implemented its own version of Manifest V3 but kept the old webRequest API working alongside it, so extensions that need real-time traffic access can still use it. That proves security improvements and effective content blocking can coexist. Google chose not to make them coexist.

What you can do...For Chrome users who want effective content blocking, the options are leaving Chrome or accepting reduced protection.

Firefox supports uBlock Origin in full and shows no signs of changing that. Brave blocks ads natively. Both are free and work well, and switching takes about ten minutes.

You can also install uBlock Origin Lite on Chrome and accept that it blocks less, adapts more slowly to new threats and can’t match the original. Or you can do nothing, and Chrome 150 will disable the extension through a routine update and show you a notification that it’s no longer supported.

Your current alternatives and solutions...With the forced deactivation of Manifest V2 in the stable version of Chrome, you can't simply ignore the problem. You'll have to make some firm decisions about the software you use to browse the internet if you want to keep your sanity intact and your screen free of visual distractions.

The transition requires you to take immediate action to avoid being inundated with intrusive advertising. Fortunately, the development community hasn't thrown in the towel and has already begun preparing concrete answers and alternative paths to mitigate this genuine technological headache.

To help you navigate this new and grim reality, we've compiled the main options available to you to circumvent these severe restrictions:

Install uBlock Origin Lite, a version officially adapted to Manifest V3, although considerably less effective on video platforms.

Transfer to tools like AdGuard or Blockify, which have already been rewritten from scratch and optimized for this new imposed architecture.

Switch to Brave, which offers a robust native shield against ads without relying on external extensions at all.

Adopt Firefox as your main browser, as Mozilla has already promised to maintain continuous and lifetime support for the full version of uBlock Origin.

Regardless of the path you choose, it's clear that Google's absolute dominance over the Chromium engine has given it total power to dictate the rules in its favor. Now we must wait patiently to see if this controversial stance will ultimately motivate a significant exodus of users to rival, more open and free ecosystems.