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Someone has created the website “is AI profitable anymore?” to answer the question of our time in real time

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There is a website called “Is AI Profitable Yet?” whose sole mission is to answer one of the most important—and most uncomfortable—questions of today’s technology industry: does artificial intelligence make money anymore? The visual response It is absolutely forceful: The short answer is a priori a big NO, but be careful, because that answer is in a certain sense misleading. The graph effectively shows how the companies that are building frontier models are burning money like there’s no tomorrowand they all spend much more than they earn. The four that appear with long red bars (expenses) and very short green bars (income) are precisely the companies that are betting almost everything on the future of AI. Amazon, Alphabet, Microsoft and Meta They have not stopped increasing their capex (capital expenditures) in recent years, and that logically means that their accounts are in the red. In fact, the announcements of these “hyperscalers” in their latest financial results have not only failed to soften that capex, but have driven it even further. The combined capex of these technology companies by 2026 is expected to amount to $725 billion, 25% of all world military spending. But the message of “everyone is losing money” is dangerous, because what all these companies are doing is investing in your future although when doing so they are running out of cash flow. There are two clear examples that can alert us. Companies are spending so much on AI infrastructure that they are running out of cash flow. It’s a dangerous bet. Source: Financial Times. The first is Amazon, which did not stop losing (investing) money for years and then became the giant it is today. The second, Uber, a company to which the same thing happened: it lost (invested) money for a decade, and although it does not have the size or success of Amazon, today it is an absolute world leader in its segment. That leaves us with a clear message: Not being profitable by investing in your future is not the same as not being clear about the economic model.. And all these companies are very clear about the economic model of AI: it is to invest today to earn (a lot) tomorrow. Nvidia is the big winner, but not the only one The great irony of AI is that for now the big business does not seem to be in AI, but in selling infrastructure to those who try to do business with it. It is the same thing that happened during the gold rush in the mid-19th century in California: Those who amassed stable fortunes were not the miners who searched for goldbut those who provided them with services and tools. There are several well-known examples: Levi Strauss saw the need of tough clothing, Samuel Brannan bought all the shovels, picks and pans he could in the area, and Henry Wells and William Fargo founded the famous postal and financial services company that allowed money and supplies to be sent safely to gold seekers. Nvidia is basically doing that: (making and) selling shovels. This has caused absolutely extraordinary growth in the stock market, and in the last three years it has become the most valuable company in the world and has not stopped breaking market capitalization records. Here it must be clarified that the estimates on that website are striking, but they do not mean that these companies are in any way bankrupt. Google/Alphabet continues to make billions of dollars every quarter, and the same goes for its rivals. All those red bars don’t mean that AI is smoke: just that we’re footing the bill for the experiment. One that could go wrong, of course, but one that could also go really, really right. The phrase that best sums up this “AI fever” is what Mark Zuckerberg said a few months ago: “We’re going to invest aggressively. Even if we lost a couple hundred billion dollars it would be a bummer, but it’s better than being left behind in the race for superintelligence.” Neither Zuckerberg nor his rivals seem upset about losing $200 billion right off the bat. They certainly do not seem to wrinkle despite the fact that at the moment there is a reality on the market: AI already works technically, but What it doesn’t do is function economically. for those who invest in frontier models. Here, however, there are a couple of notable notes. The first, the fact of Anthropic apparently expects to end the quarter making moneysomething unusual and promising. The second, that this website only shows Nvidia as the winner of this AI race, but that company is by no means the only one that has managed to make gold with this technological fever. The growth of stock market memory manufacturers is extraordinary. In just one year they have multiplied their market capitalizations by up to 11. Source: Reuters. In fact, we are seeing how a large number of technology companies have grown extraordinary in recent months thanks to the demand for hardware and components such as memories. Micron. SK Hynix and Samsung are the big beneficiaries of this situation, but they are not the only ones either. These days we have seen how PC manufacturers barely grow in income from those PCs, but they are doing it with the servers. There are more winners. There are photolithography equipment manufacturers such as ASML or Applied Materials, but also electrical, liquid cooling, networking, storage companies, and of course companies specialized in data center construction. This website answers the question in a very limited way, because the AI ​​segment is not only the one in which OpenAI, Anthropic, Microsoft, xAI or Google operate. What is happening is simply that the big business of AI is currently not where everyone thinks. AI is being very profitable. The problem is that perhaps we are looking in the wrong place. In Xataka | The problem is not spending a lot of tokens, it’s that most of them are being wasted

The nuclear explosion that changed the world also created a material that exists nowhere else in the known universe

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On July 16, 1945, the first detonation of an atomic bomb—known as the trinity test— changed the course of history and left an indelible mark on the New Mexico desert. The explosion of the plutonium device released energy equivalent to 21 kilotons of TNT, enough to vaporize the 30-meter test tower, the kilometers of copper cables connecting the recording instruments, and the desert sand itself. All this material, carried by the immense fireball, rained down in the form of molten glassy fragments, creating a unique form of matter known today as trinite. The vast majority of this trinite is a classic green color, but there is a much rarer variant called “red trinite,” whose color is attributed to the presence of copper oxide formed when transmission lines vaporized in the explosion. It is precisely inside this rare variant where scientists have discovered unprecedented crystalline structures. The violent conditions of the detonation subjected the materials to temperatures of around 1,500 °C and extreme pressures of 5 to 8 gigapascals. The matter vaporized, mixed, and cooled so extremely quickly—in a matter of seconds—that the atoms did not have time to organize themselves into stable structures, forging forms of matter that had never existed on our planet. An unprecedented find. Almost 80 years after that first nuclear explosion, an international research team led by Luca Bindi, a geologist at the University of Florence, has managed to identify a new material hidden in these samples. As the research explainsit is a “clathrate”: a cage-shaped chemical network that traps other atoms inside. This new crystal is built with 12- and 14-sided silicon cages that enclose atoms of calcium, copper, and small amounts of iron. It represents the first time that the presence of a clathrate among the solid products of a nuclear explosion has been crystallographically confirmed. That this discovery comes now, in 2026, is no coincidence. Samples of red trinitite are extremely rare and difficult to obtain, and only recent advances in mining techniques x-ray diffraction At a nanoscopic scale, they have made it possible to identify such tiny structures within metallic microdroplets embedded in glass. The technology simply was not up to par with the material before. The quasicrystal that arrived first. The story becomes even more fascinating because this discovery joins another monumental find made by the same team in 2021: the identification of a quasicrystal in the same little red trinity. Unlike ordinary crystals—such as salt or quartz, which have a precisely repeating atomic pattern—quasicrystals break the rules of classical crystallography. Its atoms are ordered, but without periodically repeating themselves, which generates symmetries that are prohibited in a conventional crystal. The one found at Trinity exhibits five-fold icosahedral symmetry and is composed of silicon, copper, calcium and iron. It is not only the quasicrystal created by the oldest known human being: has the incredible property that its exact moment of creation was indelibly recorded in historical records. The decisive role of copper. The most elegant thing about the new study is the mechanism that explains why two such different structures were formed in the same explosion. The key was the concentration of copper available during cooling. In the microzones where copper levels were low —about 10 to 11%— conditions allowed the clathrate cage structure to stabilize. Where there was more copper, that same structure collapsed and the atoms rearranged themselves in the forbidden geometry of the quasicrystal. Two radically different destinies, separated by a microscopic difference in chemical composition, at the same time and in the same place. The power of natural laboratories. Discovering these architectures on a microscopic scale is revolutionary because, as Terry C. Wallace explainsdirector emeritus of Los Alamos National Laboratory and co-author of the quasicrystal research, these structures require extreme environments that rarely exist on Earth: colossal shocks, temperatures and pressures, comparable only to the hypervelocity impacts of meteorites or nuclear detonations themselves. Destructive events that, paradoxically, act as laboratories capable of producing what no conventional laboratory can replicate. A tool for global security. Beyond materials science, this type of research has direct applications in the field of nuclear nonproliferation. Understanding the design of other countries’ nuclear weapons programs is an enormous forensic challenge. Scientists often track radioactive gases and waste in test areas, but those signatures inevitably decay over time. The crystals formed at the site of the explosion, on the other hand, are practically eternal. The red trinitite samples still preserve radioactive isotopes that allow variables such as the exact distance to the hypocenter of the explosion to be calculated with great precision. Wallace sums it up clearly: If science can establish a precise thermodynamic explanation for how these crystals form, a complete picture of the bomb and the materials used could be obtained, giving the world a new tool to monitor illicit nuclear explosions. A timestamp that cannot be falsified or deleted. The paradoxical legacy of Trinity. The study of trinitite demonstrates how matter is capable of reorganizing itself in astonishing ways under unimaginably hostile conditions. It is an almost poetic paradox that an event designed for destruction has left, 80 years later, a hidden legacy of microscopic geometric perfection that is useful today for the human future. This discovery is not only a window into the creation of cutting-edge energy materials and technologies, but it functions as a compass for future research. As the experts conclude in his academic publicationexamine the remains of other extreme and fleeting natural phenomena, such as fulgurites forged by lightning strikes or rocks subjected to meteorite craters, could continue to reveal unusual configurations of matter. Even today, hidden beneath the scars of destruction, structures await that continue to challenge our fundamental understanding of the universe. Image | PNAS and Unsplash Xataka | Europe throws away 16 billion a year in electronic waste. Spain has just turned on the first oven in Europe to recover them

The waiting list for a liver transplant can be eternal, so they have created a solution: inject yourself with a miniature one

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The National Transplant Organization of Spain makes it clear: The liver is one of the most requested organs on the transplant list, only behind the kidney. Only in the Spanish state in 2025 there were 310 people waiting and that Spain It is a world power in transplants. There are not enough donated and compatible organs to arrive in time for all those people who need them. This historical gap that no country has managed to close is a double tragedy: for the sick person, who waits without guarantees, and for the health system, which cannot offer them another way out. Liver transplant remains the only cure for certain conditions, and the path to it is full of obstacles: surgical complexity, compatibility problems, the exclusion of patients too fragile for surgery or lifelong immunosuppression. Even when an organ arrives on time, not everyone can receive it. Until now, there was no alternative. That could be about to change. The invention. An MIT research team led by Sangeeta Bhatia has developed “satellite livers”, a type of mini-livers capable of assuming the functions of the diseased liver without having to remove it. One is inside, its cells form a stable structure, connect to the person’s blood vessels and begin to produce proteins that the damaged liver can no longer make. They do not replace the entire organ, but they relieve it of its functions. They are actually small grafts of functional liver tissue that are administered via a syringe guided by ultrasound, that is, without surgery: minimal invasibility. Why is it important. Because it addresses the two big problems for those who need a liver: the shortage of available organs and those who cannot face a transplant operation. If you can have surgery, they act as a bridge until they find a suitable organ. And if you can’t, these mini livers cover the liver functions that your liver can’t do. In this way, satellite livers increase the spectrum of treatable patients. From a more general point of view, this invention is a milestone in liver tissue engineering: science has been trying to replicate the nearly 500 functions performed by the human liver for more than a decade. And if implemented in the different health systems, its impact is direct: according to the American Association for the Study of Liver Diseases (AASLD)chronic liver disease is the 12th leading cause of death in the United States and rising. Context. Although the liver is an organ with a remarkable regenerative capacity, it does not work miracles: when it exceeds a certain threshold of damage, regeneration is not enough and only the transplant remains. Since the 90s, medical science has been trying to transplant isolated hepatocytes, but the results were poor. Bhatia is not new to this either: has been there for more than 25 years investigating bioartificial liver models, which has served as a basis for understanding what conditions hepatocytes need to remain functional outside the liver. This MIT work is precisely the practical application of all this knowledge. How it works. The research team developed the idea of ​​turning these cells into an injectable along with hydrogel microspheres and fibroblasts. The spheres are intended to enable this route of administration by ensuring uniformity. Fibroblasts act as a support, helping hepatocytes survive and promoting the growth of new vessels into the tissue. Without blood supply, those cells would have their hours numbered. In the team’s experiments in mice, new vessels formed next to hepatocytes, allowing them to receive nutrients and function normally. In these rodents, the cells remained viable and secreting proteins during the eight weeks of the study. Yes, but. Although the results are tremendously promising, it is a preclinical study done in mice and the leap to humans is enormous. The human liver contains between 100,000 and 130,000 million hepatocytes and replicating a sufficient functional mass with injected cells is a challenge that this study has not yet addressed. Even assuming that we extrapolate this finding as is to humans, immunosuppressants would still need to be used. And it is not a minor problem: the fact that the immune system attacks weakened patients increases the risk of infections, tumors and kidney damage. In Xataka | The “silent” liver epidemic: we have a problem that escapes analysis and that science is already seeking to stop In Xataka | Fatty liver advances silently, but science has found unexpected allies: coffee and green tea Cover | Elen Sher and Magnificent

Toyota has created the city of the future and it is full of AI and cameras that protect you. It’s also a privacy nightmare

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At the foot of Mount Fuji, Toyota he has been building a city for years entire designed from scratch to test their future inventions. It’s called Woven City, and it already has its first inhabitants. And although the city does not lack one bit of technology, living there also involves making certain concessions in terms of privacy. Below these lines we tell you all the details. Why does this exist? At CES 2020, then-Toyota CEO Akio Toyoda advertisement that the company was going to build a laboratory city on the land of a former factory in Susono, in the Japanese prefecture of Shizuoka. The idea was not to create just another corporate campus, but to build a real urban environment where engineers, researchers and residents would coexist and test advanced mobility, robotics, artificial intelligence and sustainability technologies. The project, developed under the subsidiary Woven by Toyota, has cost about 10 billion dollars, according to they count from Ars Technica, and its first inhabitants arrived just a few months ago. In detail. Woven City has, at the moment, about 100 hand-selected residents, who they internally call Weavers. They are Toyota employees and people chosen for their technological profile. They live in Japandi-style apartments (fusion between Nordic and Japanese) equipped with domestic robotics and health monitoring systems. The city is powered by rooftop solar panels and hydrogen fuel cells, and its streets are designed in three categories based on vehicle speed: expressways, personal mobility zones, and pedestrian-only areas. When completed, the total area will be about 294,000 square meters, although only about 10% of the planned space is operational right now. What is proven there. Residents act as beta testers for a diverse list of projects: from AI karaoke systems that choose songs based on mood to an air conditioning system capable of eliminating 95% of pollen from the environment, something relevant in a country where half of the population suffers from allergies. Delivery robots, tricycles or, as point the middle, the Guide Mobi, an autonomous vehicle that acts as a digital towboat to take cars out of the garage and take them to their owners without the driver having to move. According to they count From Ars Technica, 98% of residents have given permission for a robot with cameras to operate within their own homes. Here comes the problem. For all of this to work, Woven City is full of cameras. Many. According to the mediumyou could count up to eight cameras at a single intersection, and dozens more spread across the roofs of buildings, common spaces, and even the small cafeteria there. All that network of images feeds what Toyota calls the AI ​​Vision Engine, an artificial intelligence system designed to monitor, catalog and report on activity in the city. The system can identify people and follow them from camera to camera based on their clothing, without using facial recognition. They used it in a demo to detect potential thefts in a business. What Toyota says. The company says it has its own consent management system called Data Fabric, which allows residents to decide what data they share and what they don’t. “We allow Weavers to select what they want to share or not. Whether they don’t want to share anything or if they want to share everything is up to each individual,” explained John Absmeier, CTO of Woven City, told Ars Technica. The data, according to Toyota, is not sold to third parties. “At least for now,” they added in the media report. Between the lines. That 98% of the residents have accepted practically all the privacy conditions does not say as much about trust in Toyota as it does about the profile of the people who live there: they are selected technicians, who know perfectly well what they are agreeing to and who have come precisely to participate in the experiment. Kota Oishi, CEO of Woven City, recognized Japanese citizens, like Europeans, are especially sensitive to privacy and demand to know exactly what their data will be used for. The leap between this group of controlled volunteers and the implementation of similar technology in a real city with millions of ordinary people would be enormous, and questions about mass surveillance inevitable. The other big bet: a Own AI. While all this is happening on the streets, Toyota is working in parallel to not depend on the large technological giants in terms of artificial intelligence. Daisuke Toyoda, son of President Akio Toyoda and head of the Woven City project, counted on an interview in April to Automotive News that developing AI internally is key to protecting jobs and the company’s industrial knowledge. “If you only work with the biggest or best companies abroad, you run the risk of becoming a mere user,” he said. Toyota sees AI not as a tool to cut staff, but to digitize the knowledge of its best workers and raise the level of the rest. One of the most striking projects of this line is an AI clone of Akio Toyoda himself (even with his voice, his way of speaking and his philosophy) that is already used internally to train managers. And now what. Woven City is still in its infancy: only 10% built, 100 residents and many robots that “don’t do much yet,” according to counted the middle. The objective is reach 2,000 inhabitants when all phases are complete. Toyota does not expect it to be profitable in the short term; understands it as a long-term technological incubator to test its technology in more open, but controlled spaces. Cover image | toyota In Xataka | Chinese manufacturers no longer know what more innovations to incorporate into their cars, so they have added a toilet to one

Someone has created an AI that knows nothing about what happened after 1930, and it has more use than it seems

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One of the problems with language models is that there is a cut-off date in the training data, that is, the model does not know current events that go beyond that date. Rapier In certain sectors it can be a serious problemis precisely the objective of Talkie-1930, a language model trained solely on texts from before 1930. If you’ve ever wondered what it would be like to talk to someone from the past, there’s an AI for that. A vintage language model. This is how These LLMs have been baptized who are trained with historical content. Talkie-1930 is a model with 13 billion parameters that does not have access to modern information nor can it consult the Internet, but has only been trained with books, newspapers and other texts from before 1930. To explore the model, the researchers had Claude converse with the model, evaluating his responses. The model showed great knowledge of the world, with many historical details of the time, and a great ability to imitate the style of Victorian authors such as Dickens, although somewhat limited in more satirical formats. More than a cultural experiment. Talkie is the closest thing to talking to someone educated in the early 20th century. This turns the model into a window that allows us to explore the mentality and culture of a past time and learn how society, politics or daily life were described back then. But beyond curiosity, Talkie-1930 also functions as a “control subject” to better study the functioning of AI and achieve important advances. Predicting the future. By being “frozen” in 1930, Talkie makes it possible to better measure how far a model can extrapolate and predict the future from historical patterns alone, without cheating with later data. To test this anticipatory capacity, the researchers showed up to 5,000 descriptions of subsequent historical events, taken from the “On this day” section of the New York Times, and measured the model’s degree of surprise. The result was that the model showed more surprise in the decades after the data cutoff, especially in the 1950s and 1960s, but then its degree of surprise stabilized. According to the researchers, this suggests that predictive performance improves as the time horizon becomes longer, but they point out that it will be necessary to train older models to be able to measure it well. Invention. Demis Hassabis, CEO of Google DeepMind, raised a very interesting question at a conference recently: if an AI with a limit of knowledge until 1911 could reach the theory of relativity that Einstein discovered in 1915. In this sense, models like Talkie-1930 are a very interesting tool to observe its ability to generate new ideas that can lead to discoveries. No pollution. Is one of the problems that the models have trained with large corpuses of current data, in which the evaluation data itself usually also sneaks in and ends up causing their capabilities to be overestimated. With vintage models there is no contamination and that allows you to carry out very specific experiments, such as seeing if you are able to learn to program without having any prior computer knowledge. Talkie-1930 is open source and is available on Github. Image | Xataka In Xataka | A macro experiment has tried to find out if we differentiate real images from those generated by AI. The answer is not optimistic

The chip industry has its own Lego black market. ASML created it by accident

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Rick Lenssen works as a data analyst at the Dutch company ASML and builds Lego models on the weekends. It could have remained there, a mere hobby shared with his children if the company that employs him did not design and manufacture the lithography machines necessary to produce microchips, one of the key elements of current technology and one of the key suppliers of TSMC, Samsung or Intel. Now, his Lego designs imitating the original machines reach four-digit figures on eBay. 380 million in 851 pieces. It appeared in the ASML online store at the end of November 2024: a Lego model called TWINSCAN EXE:5000, measured 35 centimeters long and cost $227.95. It reproduced the high numerical aperture extreme ultraviolet (High-NA EUV) lithography machine that the company delivered to Intel in late 2023 and that allows chips to be printed from its 2 nanometer node. The actual equipment weighs 165 tons, has more than 100,000 parts and had to be transported in three Boeing 747s. The Lego set reproduced it in the style of the popular toy brand, it included a purple ray that represented ultraviolet light and a minifigure with the full clean room suit that technicians wear. The product sheet, perhaps anticipating what was to come, already warned that multiple orders from the same customer would be cancelled. Brick Lenssen. This is the nickname given to Rick Lenssen, a 39-year-old company employee who became interested in Legos. by chanceafter taking his children to a toy fair in the Netherlands. His first personal project was an exact replica of the ASML campus in Veldhoven: two years of work, 2,500 euros out of his pocket and 25,000 pieces, with details as obsessive as the peregrine falcon that nests on a roof of the complex, accompanied by a pigeon that, according to him, acts as food. He designed everything first on the computer and assembled it in the attic of his house. Where do I put this. Lenssen then encountered a drama that will be familiar to any Lego fan: what to do once you finish building the set. He offered it to the campus itself, but they didn’t want it. Lenssen wrote to ASML’s CEO on a Friday night, and within hours he wrote back saying he loved the set. To get the model out of the attic, it had to be dismantled piece by piece (like the real ASML machines), and company workers loaded it into a van. Today it is the first thing visitors see when they arrive at the company’s reception. It’s official. The jump to merchandising officer arrived later, with a model of the skyline of the campus in charge of promoting an internal app, and then the two models of machines. He was not the first: Jeroen Ottens, an ASML engineer who had worked at Lego, I had modeled a previous version. The cheapest model in the current range, the TWINSCAN NXE:3400C, at $166.70, was not born as a commercial product either: it started as internal training tool before becoming a special edition open to the public. It took Lenssen a few weeks to design the current two sets, one with a 61-page instruction manual. Your only compensation is a copy of each model. Employees only. The sales policy is one unit per person and verified ASML email is mandatory. For weeks, some fans managed to place orders bypassing that restriction due to a security hole in networks, and measures had to be taken: in December 2024 ASML began canceling orders from buyers without an actual corporate email. The EXE:5000 file even disappeared and can only be consulted today through the Wayback Machine. The same corporate email restriction covers the rest of the merchandising of the company, yes, much less coveted: sweaters, mugs, pins and Christmas decorations. eBay fever. Of course, speculation was not long in coming, as It usually happens with Lego sets that disappear from the market. Individual sets of those designed by Lenssen have been seen for $600, while the complete collection reaches $4,500. Before closing that section of the store, ASML sold 1,355 units of the latest model (there are 44,000 company employees, possibly not all of them interested in building with toy blocks). Although the comparison is absurd, only six of the real machine have been sold. In Xataka | The great fear of the US is that ASML’s UVP machines will continue to arrive in China. So he is going to intensify his trade war

Someone has created the first complete advanced malware by vibecoding with AI. It’s called Voidlink and it leaves an important question

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For a long time, develop malware advanced seemed reserved for actors with experience, time and considerable technical capacity, especially in an environment in which operating systems and many platforms have been tightening their defenses. But the table is changing. What we have seen in recent years is that artificial intelligence not only serves to summarize texts or answer questions, it can also very visibly accelerate the software creation when given precise instructions. And that leaves us facing a reality that is difficult to ignore: the same tool that simplifies legitimate tasks can also reduce part of the effort necessary to create malicious code. That change begins to take concrete form with VoidLink. In his analysisCheck Point presents it as one of the strongest evidence so far of advanced malware developed largely with the help of AI. There is, however, an important nuance in the investigation itself: the company assures that it detected it at an early stage, that it was not deployed against victims and that it was not used in active attacks. But that is precisely why the discovery is so revealing, because it allowed access to development materials that rarely come to light. How VoidLink was built and why it changes the dashboard VoidLink was not, at least on paper, a minor piece or a rudimentary experiment. The cybersecurity firm describes it as a malware framework for Linux with a modular architecture, designed to maintain stealthy and prolonged access in cloud environments. In his analysis he mentions components such as eBPF and LKM rootkits, as well as specific modules for cloud enumeration and subsequent activities in container environments. That level of maturity is just what separates it from other previous cases associated with simpler code. One of the most striking twists in the case is who seems to have been behind it. Check Point explains that, due to its internal structure and the pace of evolution observed, VoidLink gave the impression of having come from a large team, with different profiles and a fairly defined work plan. But the evidence collected by the firm points to something very different: a single actor who, according to the investigation, would have had AI support during different phases of development. There is also another relevant element: that actor would not be a rookie, but rather someone with a solid technical base and previous experience in cybersecurity. The most revealing part of the case is how the project would have been built. The firm describes a working method based on what it calls Spec Driven Development that works as follows: You define what you want to build This idea is translated into architecture, tasks, sprints and delivery criteria The implementation is delegated to the model. In the exposed materials, development plans, technical documentation, coding standards, deployment and testing guides appeared, as well as an organization by teams and phases that supports this model. One of the recovered artifacts, dated December 4, 2025, further suggests that VoidLink had already reached a functional phase in less than a week and exceeded the 88,000 lines of code. That is precisely what separates VoidLink from other precedents. Check Point maintains that this is the strongest evidence of malware created almost entirely with the help of AI. “This is the first confirmed case of advanced AI-generated malware, created with the speed, structure and sophistication of an entire engineering organization,” claims the company. The question now is how far malicious actors can go with these types of techniques. Images | Xataka with Nano Banana | Check Point In Xataka | The Booking hack is a little more disturbing: “Tracking phishing” attacks are here to stay

In 2013, Amazon created a Kindle so good it has proven to last forever. And now he has decided that it must end

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Amazon has announced that, starting May 20, 2026, Kindle devices released in 2012 will no longer have access to the Kindle Store. You will still be able to access the books downloaded on the devices, taking into account that we should not factory reset the Kindle. If we do, we will not be able to register it in our Amazon account. Goodbye to old Kindles. If you have an early Kindle, starting in May you won’t be able to download books from the official Amazon store or register them as new devices when you restore them. Specifically, these are the affected models. Kindle 1st Gen (2007) Kindle DX and DX Graphite (2009 and 2010) Kindle Keyboard (2010) Kindle 4 (2011) Kindle Touch (2011) Kindle 5 (2012) Kindle Paperwhite 1st Gen (2012) Kindle Fire 1st Gen (2011) Kindle Fire 2nd Gen (2012) Kindle Fire HD 7 (2012) Kindle Fire HD 8.9 (2012) Amazon is sending an email to affected users, offering a 20% discount on new Kindle devices and credit compensation for purchasing new books. Likewise, all the purchases we have made on the old device will be available if we log in to the new one with the same account. It’s not the first time. Amazon has long wanted to have tight control over the installation of books on its Kindles. One of its most recent updates ended with a star function: being able to send books to the device via USB. In the same way, Users were required to keep their Kindle updated to access the store. In practice, this meant limiting features—such as downloading books outside of the Kindle Store—to push users to install those more restrictive versions if they wanted to retain access. Almost a paperweight. A book reader to which we cannot download more books is not very useful. A questionable decision considering that this type of device is born to have a useful life only limited by its hardware – that the screen ends up saying enough, which is difficult with electronic ink or that we are left without a battery replacement. Amazon has decided to end the life cycle of a product that still had a war left to fight. Not because the hardware has stopped working, but because maintaining its compatibility no longer fits with your business model or your current ecosystem. In Xataka | We enter book month with sales on Kindle: you can now buy the eReader for less than 100 euros

In 1994, a programmer created a “temporary” interface for Windows. Three decades later he is still with us

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Windows is one step away from turning 40 years old. The first version of the operating system appeared in November 1985and since then it has not stopped evolving. However, Microsoft tends to take a long time to update some components of its products. With Windows 10, for example, it released a renewed user interface, but it was not until years after its launch that it began to get rid of some icons from the Windows 95 era. Now, in Windows 11is renewing programs like paint and Notepad. Regardless of how modern Windows 11 may feel, and all the new features that come with its updates, the system still retains some elements that we could classify as historical. Among them we find the utility to format disks. WINDOWS 10: 9 VERY USEFUL and LITTLE KNOWN TRICKS Currently, if you wanted to format a storage drive from Windows 11 you would find a pop-up window practically identical to the one you could find decades ago. In fact, we know exactly who created it. The format drives dialog in Windows 10 A former Microsoft programmer named Dave Plummer recently shared an some interesting facts about this part of the operating system. The now entrepreneur says he created the Format dialog box one rainy morning from the end of 1994. He says that they were migrating millions of lines of user interface code from Windows 95 to Windows NT, and that the formatting section was very different between systems, so it was necessary to create a new user interface. And Plummer took on this task. The programmer did not think of doing a definitive job, but of providing a temporary solution with the help of a sheet, a pen, Visual C++ 2.0 and the Resource Editor. “It wasn’t elegant, but it would do until the elegant user interface arrived,” he says in the message. Plummer also set the 32GB limit for the format of FAT volumes that morning. It is curious, because FAT is capable of working with larger volumes, although to create volumes with this capacity it is necessary to use the command line. The disk formatting utility interface appeared in Windows NT-based operating systems, such as Windows 2000 and Windows XPand it has been with us ever since. Throughout this time it has basically been a temporary solution created in 1994. Images | Windows | Genbeta In Xataka | Intel is hunting and capturing new customers. His next goal: convince Elon Musk and make chips for Tesla

In 1967, a war veteran believed that moving around a computer could be easier. So he created the first mouse

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Things were clear from minute one. When Douglas Engelbarthead of the Augmentation Research Center (ARC), at Stanford, wanted to interview a new recruit, gave him a pencil attached to a brick and then asked him to write his name on a piece of paper. Difficult, right?, joked Engelbart, a doctor in electrical engineering and a pioneer in computer development. Well, people would encounter the same problems, he explained to the candidates, if they were not able to offer them more agile and simple tools to use computers. He wasn’t talking just to talk. Engelbart, together with one of his colleagues, also an engineer William Englishwas the father of the first mouse computer in the 1960s. Only that one was not called a mouse, but XY Position Indicator for a Display System; and its design was quite different from the modern peripherals that we use today. To begin with, it was made of wood and had a pair of metal wheels. This is your story. Make it easy for people: “Click” In the early 1960s, Engelbart, a World War II veteran, recent PhD and with just a couple of years of experience at the Stanford Research Institute —today known as SRI— had a clear idea: he wanted accessible technology. And simple. In 1945, while serving in the US Navy, he had read an article by the inventor Vannevar Bush who encouraged scientists to bring knowledge to the streets and he was determined to transfer that slogan to his own field. The golden opportunity came when the Department of Defense, through DARPAgave him the necessary support to set up his own center in the SRI, the ARC. There he had nearly fifty people working for him and efforts were focused on answering a question: What would the future of computer communication be like? At that time, computing had been in development for decades; IBM had manufactured the IBM 650 and the team was convinced of the enormous potential of the sector. The question was how to use it and prevent the systems from being as unwieldy as a pencil stuck to a brick. At that time the most popular devices for pointing on a screen were optical pencilsa system similar to that used in military radars. Since 1961 Engelbart, however, ruminated on an alternative. To make interaction with computers more efficient: install a pair of small wheels across a table so that the user could operate the screen cursor with them. One would rotate horizontally and the other vertically and its operation would be very similar to that of the planimeter commonly used by surveyors, geographers and architects. The idea had been recorded in his notebook, but already in the 1960s, with the financial backing of DARPA, his own team and extra help from NASAEngelbart was able to delve into it. The veteran and his colleagues gathered the best signaling equipment that existed and made a kind of brainstorming which left half a dozen proposals for working with monitors, some of the most curious, such as a joystick or a light pen. Perhaps the most striking of all was a mechanism that was fixed under the table and operated with the knee. A prototype nicknamed “mouse” Also included among that amalgam was a small device manufactured by Bill English after reviewing his notes from the beginning of the decade with Engelbart. The prototype basically consisted of a carved redwood block which included two wheels crimped at the bottom and a button at the top. Your name: XY Position Indicator for a Display System. Its appearance, compact and with a cable protruding, However, it ended up earning him the nickname “mouse.”. It was so comfortable that it prevailed over the rest of the laboratory’s alternatives and the team included it as a standard piece in their research. The SRI applied for the mouse patent in 1967 and received it in 1970. Engelbart and his companions did not stop there. They continued looking for a “companion” for the mouse, another device that the user could operate with their free hand and could use to enter commands and text. After several tests they opted for a device similar to a telephone with five keys. They also carried out tests to perfect the mouse design as much as possible. “We did a lot of experiments to see how many buttons it should have. We tried up to five. We decided on three. That’s all we could fit in. Now, the three-button mouse has become standard, except for the Mac,” Engelbart himself recalled in 2004, in an interview with Wired. With all this material and the rest of the inventions developed by his team, the war veteran decided to put on a gala performance. One like a beast. In 1968 they organized known as “mother of all demos”a historic conference held in San Francisco in which Engelbart showed all the functions they had developed over the last few years. “For 90 minutes, the stunned audience of more than a thousand professionals witnessed many of the features of modern computing for the first time: live video conferencing, document sharing, word processing, windows, and a strange pointing device jokingly referred to as “the mouse“The elements of the screen were linked to others through associative links or hypertexts,” explains the Computer History Museum. “People were amazed. In one hour, it defined the era of modern computing,” English commented to New York Times in 1996. Shortly after that historic achievement, however, the team began to lose its drive. Some staff questioned the lab’s drift, DARPA cut its funding, and other research centers began to emerge, such as the Xerox in Palo Alto (PARC). Result? Many of Engelbart’s employees sought new destinations. With them went the very concept of the mouse. The device, with a trackball, ended up being incorporated into the Xerox Alto computer and in 1983 Apple marketed it with its computer Lisa. After a while –as you remember Washington Post— Steve Jobs’ company was behind almost half of … Read more

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