companies

There is a company proving that AI can be the perfect interviewer for companies. His name is Orbio and he is from Madrid

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AIs have started doing job interviews, and the interviewees are leaving them horrified. It is a palpable reality in a segment that is experiencing its particular revolution, and that is where it comes in. Orbiuma Madrid startup that has jumped on that wave. And he has done it in a big way. How it all started. In 2025 three entrepreneurs (in the image, from left to right, Nacho Travesí (CRO), Sergi Bastardas (CEO) and Antonio Melé (CTO)) decided to solve a clear problem that they detected in the industry: the “human infrastructure” to manage the companies’ workers was not efficient enough. To solve this, they created Orbio, a startup that precisely helps manage workforces thanks to the use of AI agents. 18 million euros. This Monday, the company announced that it has closed a Series A financing round of 21 million dollars (almost 18.2 million euros). The financing was led by Dawn Capital, but other investment companies such as Visionaries VC, Plus Partners and Enzo Ventures have also participated. This round adds to the one that was made in September of last year, and in which they raised 6.5 million euros. Assault on the US. This injection of capital will allow this technology company to triple its team of engineers in Madrid, but the intention is to also open an office in New York to compete head to head with other native platforms created in Silicon Valley. Robotic interviewers. The fundamental pillar of the platform created by Orbio are the language models that, according to the company, have been polished to maintain fluid and technically rigorous conversations with job candidates. Those “robotic interviews” with AI agents They can be done through both voice and text channels. There is another differential detail in these processes: Orbio’s AI questions, for example, about the candidate’s experience, evaluates their skills and resolves doubts about the position in real time. The promise: eliminate biases from human interviewers and screen thousands of applicants in record time. A platform for those “frontline” workers. Orbio’s technological solution it is not thought to interview professionals who want to occupy traditional office positions (known as white collar), but is aimed at that mass market of frontline workers. Sectors such as delivery, logistics distribution centers or restaurant chains often suffer from very high staff turnover rates that exhaust the resources of HR departments. Orbio not only automates the interview process: it is capable of collecting documents, verifying backgrounds, and facilitating the onboarding process. The idea: cover job demand in hours or a few days instead of weeks. But. Of course, the automation of these processes It dehumanizes them and generates a clear ethical and social debate about the current situation of the labor market. That a machine ends up “scoring” you after these interviews is disturbing, and above all it means that you give up things like intuition and empathy in the personnel selection process. At Orbio they argue that this filtering precisely allows Human Resources managers to dedicate their time exclusively to the final phases of the process, treating the preselected candidates individually with much greater attention. If AI solves a problem, reward. The investment round is the validation of an idea that is beginning to gain strength: there are companies that are taking advantage of AI to propose solutions to real problems. In this, as in other cases, due to the efficiency of its use, something that is crucial in massive processes such as choosing candidates for a job, but also in the field of customer service, where AI is also infiltrating in leaps and bounds. The Madrid startup has been able to identify a bottleneck, and of course its technological solution has already attracted several business clients. In Xataka | Chargebacks are the silent hemorrhage of e-commerce. A Catalan startup is making money by covering it

The latest trick for AI companies to appear less artificial is to use classic fonts. It’s the arrival of ‘Tasteslop’

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It has rained a lot since the Will Smith who had a hard time eating spaghetti and the AI videos we have nowwith the potential for us to swallow them if we don’t pay attention. More curious is that, not so long ago, AIs were useless when it came to representing letters in an image, but they have improved so much that they have even converted a specific font into something that denotes that a text has been made with AI: the serif font. And it is a huge problem. Suspicious typography. AI is in everything. In recent days, non-E3 has been held, the week in which different video game companies present their new products for the coming months, and many players were on the lookout. Many video game companies have found in AI a quick way out to speed up development (and fire employees along the way) and it seems that they are in a competition to see if they can sneak it in. Titles like the new ‘Stellar Blade 2’ or ‘1666 Amsterdam’ (with AI assets when they declare themselves as a “team of craftsmen”) are two examples. Others classify it as a “carcinogenic” technology. AI is in everything and, as they point out in this article from Wired, also in typography. The improvement of this technology when it comes to representing texts is so notable that AI companies are training them to use a specific typeface: certain varieties of sarif or sarifa (depending on the program you use to edit texts). In fact, writer and designer Keya Vadgama has noticed so many companies using the typeface that he has coined the term “the serif renaissance” to describe the phenomenon. Why sarif? This font is very interesting because it has “thanks” or “punchlines”. The serif fonts are some like Times, Georgia or Courier, while then there are the sans-serif fonts, which are the ones that would not have those endings. The endings are the decorations that copyists used to use in books and it is a warmer and more human source and, precisely, that is the key. Vagama explains that “it’s not that hard to guess why native AI companies are attracted to serif fonts.” According to his thesis, it is because AI is a cold technology, soulless and incapable of creating, but a font with those endings in the letters brings that soulless creation of AI closer to the warmth of human calligraphy. “It connotes a very human and fluid way of making letter shapes,” notes Vadgama. ‘Tasteslop‘. And since everything on the Internet must have a name, this trend has been framed within a term that already existed and in which it fits perfectly: ‘tasteslop‘. What that means is that it’s something with that aesthetic that wants to look sophisticated and curated, but is actually a collage of superficial design decisions that are simply guided by templates and generative models, not by deeper criteria. Visually it is curated, it is powerful, it is elegant, but the problem is that it is still a machine posing as a human. It is replicable with a prompt. And we are talking about simple text, yes, but also about an intention that shows that, in the world of marketing, there is no stitch without a thread and the objective is to leave the cold sans-serif typography aside to opt for a more human and warm one that, subconsciously, causes us less rejection. The answer. Claude, Manus, Runway or Perplexity, among others, use serif typography and, after asking, Wired received a response from a Perplexity representative who pointed out that why wouldn’t they have a human design… if Perplexity is for people. The curious case of Anthropic. The logo is sans-serif, it has sans-serif fonts, but also serif Implications for the designer. If AI is already taking this space (too) to simulate that it is not a machine, but something created by a human, now is the time for designers (again) to have to move to find a new space. We are already seeing that, if someone creates an image and it is very perfect, there are comments on networks like “that’s AI.” Or the more ‘Bro’ version of “hey Grok, is that AI?” And it is a problem because artists and designers are seeing how a technology that has plundered their work is imitating them perfectly in many aspects. As models absorb that serif font boom and AI learns from AI and its aesthetics, humans will be the ones who have to adapt to find a new visual code that indicates that there is craftsmanship there. It is to carry the battlefield art/prompt to fonts, something that would seem absurd until not long ago, but we are already seeing that it is giving something to talk about. Especially when the AI ​​is already asked to make images with text that appear human in aesthetics and less tech. I wish they used Comic Sans. The identification problem. In the background there is something much more serious: how we separate the wheat from the chaff, the slop from the artisanal. Trying to achieve enough perfection to confuse us is something we are constantly seeing in AIs. In the generation of images, fingers and letters were the clues we had left to know if something was human or not, but they are overcoming the limitations by leaps and bounds. The United States Department of State, for example, went from a sans-serif font to a Times New Roman with those serifs in the letters, and there are already those who have raised an eyebrow. Are communications made in images with AI? Well, it is not known, but this adds another complication: separating what is made with AI and what is not. In this image, if we draw a line from a point in the figure to the same point reflected in the mirror, we see that the lines do not converge at a single point either. We will have to study a degree … Read more

companies operated by AI agents

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Artificial intelligence has ceased to be a distant promise and has become a force that is already reorganizing companies, infrastructure, jobs, science and economic power. What we have seen so far is probably only part of the change, but it is enough to put governments before a difficult decision: regulating too soon can curb innovationdoing nothing can open up risks that are difficult to contain. In that middle ground, full of uncertainty, many countries are looking for their place with the tools they have. That decision, however, is not made from the same starting point throughout the planet. Cutting-edge AI requires a combination that is difficult to replicate: abundant capitalaccess to chips, data centers, specialized talent, companies capable of scaling global products and enough energy to sustain that infrastructure. The United States and China play a good part of that game from the center of the board. Argentina, on the other hand, does not have that same technological, financial and industrial scale, so its room for maneuver necessarily lies elsewhere. Argentina does not seem to be trying to build its own OpenAI from scratch, nor compete with the great powers for the most sophisticated layer of AI. What is beginning to take shape is another strategy: turning the country into a attractive place for projectsinfrastructures and new business forms linked to this technology can be installed with fewer obstacles. This includes pieces that are less spectacular than a frontier model, but very relevant for this economy: energy, land, incentives, procedures, societies and operating rules. Argentina’s formula to enter the world of AI The vision of the Argentine president was condensed in an opinion piece published in the Financial Times. Milei argued there that AI needs room to develop before becoming trapped by rules he considers premature, and linked that idea to the history of limited liability in modern capitalism. From that framework, he proposed a figure for companies operated by AI agents or robots, accompanied by a reduced corporate tax and attractive rules for shareholders. As we can see, the approach combines deregulation, corporate engineering and an open call for investment. The legal support is in a bill of the Argentine National Executive Branchdated May 29, 2026, which reforms the General Companies Law. The key is not just that you mention AI, but where you place it: within the framework that regulates how companies are born, operate and respond. The text introduces a figure called Automated Societydesigned for companies that develop their purpose through autonomous algorithmic systems or artificial intelligence agents. That is, the proposal brings AI to the societal field, not only to the technological debate. Article 14 defines this figure quite clearly. “The Company of any of the types provided for in this law that develops its corporate purpose, through autonomous algorithmic systems or artificial intelligence agents, without requiring workers in a dependency relationship or human resources for its ordinary operation, will be considered an Automated Company.” The automation declaration, however, must be expressly stated in the statute and the name must include the expression “Automated.” The project also attempts to resolve an unavoidable question: what happens if these systems cause damage. His initial response is in article 14 itself, where it is established that “the automated society responds with its assets against third parties for damages caused by their autonomous algorithmic systems or artificial intelligence agents.” The formula maintains the problem within a well-known logic of corporate law: the company is responsible, not the algorithm as if it were a person. On paper, therefore, automation does not eliminate responsibility, but rather channels it through society. The question is whether this answer is enough for all the scenarios that can be opened. The same project allows the partners to freely set the amount of share capital, so that the assets available to respond to third parties can become a decisive piece. It also remains to be seen how the decision chain would be tested when autonomous systems, third-party providers, shareholders, administrators and potential beneficial owners are involved. In a traditional company it can already be difficult to rebuild responsibilities; In a society operated by AI agents, that task can become considerably more complex. The discussion does not end with liability for damages. The project combines strong statutory autonomy, limits on the capacity of registries to condition what is provided by law, Public registry files without accounting or economic information and room for the internal relations of certain companies to be subject to foreign law, although without affecting third parties or matters excluded by the text itself. Taken separately, those elements can be explained as business agility tools. Read together, they can also make Argentina an especially attractive place for external actors seeking to operate with less friction. Milei does not mention Stargate Argentina in his opinion article, but the announcement helps to understand the type of country that the Government wants to project. OpenAI and Sur Energy presented it as a possible large AI infrastructure in Argentina, with very ambitious communication around investment, energy and computing capacity, just the pieces that any economy needs to enter this new technological phase. Even so, caution is mandatory: what we have documented is a letter of intent to explore the project. As far as we have been able to verify, there is no definitive location, date of construction, or construction started. The measure of this bet will not be in how striking the legal figure is, but in its effects. Such a reform can open up economic activity and attract projects that perhaps would not come with a more rigid framework. But it can also remain a formal advantage if most of the value is decided, financed and is exploited outside the country. The point, therefore, is not only how many companies are created or how many advertisements are accumulated, but how much real profit ends up staying in Argentina. Milei’s bet, therefore, is not only played in the text of a corporate reform. The stakes are something more difficult … Read more

gain ground among American companies

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Not so long ago, the idea of ​​an American company directly paying a Chinese company like DeepSeek to use artificial intelligence would have sounded, at the very least, unlikely. Not because there was a lack of alternative models, but because the enterprise AI board seemed dominated by the big names of Silicon Valley and by a growing concern around data, security and technological dependency. But the expense is starting to weigh. And when a technology becomes expensive to maintain at scale, some companies begin to look beyond the usual vendors. The data. The specific sign appears in Ramp’s monthly lista New York-based company that processes business expenses and sorts the software providers its customers purchase for the first time. In June 2026, DeepSeek ranked first in that ranking. The data was also collected by SCMPwhich introduced it as part of a move by some US companies toward more affordable AI options over alternatives like OpenAI and Anthropic. What Ramp measures. The nuance is important, because this ranking does not say that DeepSeek has surpassed OpenAI or Anthropic in total enterprise use. As we say, Ramp classifies the suppliers that its clients buy for the first time, which serves to detect early signs of interest, but not to automatically convert them into consolidated market share. In other words, DeepSeek appears as a trending provider within that spending universe, not as the new leader of enterprise AI in the United States. It’s not just open source. Ramp’s precision is relevant because it separates two very different scenarios: using an open source model within the infrastructure itself or contracting DeepSeek directly as a provider. In this case, Kharazian assures that the spending data points to the latter and summarizes it like this: “Companies are sending and receiving data directly through DeepSeek.” That nuance explains why the movement attracts so much attention. We are not just talking about companies testing Chinese technology in isolation, but about direct payments and use of the service. The underlying explanation is in the cost. Kharazian notes that companies are adopting more disciplined management of AI spending and that he expected more interest in open models or cheaper options from OpenAI, Anthropic and Google. What he did not expect, he explains, was that American companies would end up using DeepSeek. Therefore, the Chinese service remains part of a business conversation marked by invoices that are increasingly difficult to ignore. Proportion matters. DeepSeek now appears high on the monthly list of trending providers, but its previous figures within the Ramp AI Index show that we are still talking about a small phenomenon. According to Kharazian, the Chinese company went from 0.3% enterprise adoption in January 2025 to 0.1% shortly after, and in April 2026 it was still around that level. In that same index, Anthropic and OpenAI concentrated 34.4% and 32.3%, respectively. The reasonable reading, therefore, is not that DeepSeek has caught up with the leaders, but that it has re-entered the radar of some American companies. The complete photograph. According to the firm, companies are not only looking towards Chinese models, but also towards open models and model inference and deployment platforms such as Fireworks AI, fal AI and DeepInfra. In any case, the message for Silicon Valley is clear: some American companies are willing to look at alternatives that recently seemed much more difficult to imagine. Images | Xataka with Nano Banana In Xataka | France has been determined to rob Spain of its position as a data center power in Europe

Computer companies didn’t make money on computers. What they are doing is making money thanks to AI servers

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On Friday, May 29, Dell shares they grew 39% suddenly. Since becoming a publicly traded company seven years ago, Dell has never had a rise like that. At first glance, this growth would seem strange, but the company has discovered that with stagnant PCs, the focus had to change. Nothing has gone wrong with that turn of the helm, but other traditional PC manufacturers have also taken advantage of the opportunity. The PC is dead, long live the server. In recent years the PC segment has been struggling with low margins and sales that have slowly been slowing down. Manufacturers were totally tied to that situation, but some have taken advantage of the opportunity that AI offered them. Dell and Lenovo rub their hands. Dell published its financial results and they were spectacular: 88% year-on-year growth thanks to the fact that its revenue in the server segment has risen 757%. Not only that, its guidance for this year has improved as well, further boosting confidence in the company’s near-term future. Lenovo also had a fantastic quarter: May was its best month on the stock market since 1999, doubling the value of your shares thanks again to that fever for hardware dedicated to AI. AI as a shield against inflation. The entire sector is experiencing a paradoxical situation: the cost of components such as DRAM memories or SSD units is absolutely shotbut companies are earning more than ever. Dell has tripled its net profit to $3.44 billion, allowing it to offset those costs through almost daily price increases. Lenovo has managed to maintain its margins because once again the market is willing to pay whatever it takes for servers and AI infrastructure. Beyond hyperscalers. One might think that to have resources in the age of AI it would be necessary to turn to hyperscalers (Amazon, Microsoft, Google), but Dell and Lenovo have shown that their experience in servers has managed to offer an alternative for all types of clients. Jeff Clarke, chief operating officer at Dell, explained that the need for AI hardware is so enormous that this segment continues to break sales records. The PC is no longer the protagonist. Although Dell’s Client Solutions division—which includes its revenue from PC and laptop sales—grew a more than decent 17%, that figure pales in comparison to the 181% growth of its infrastructure division. Lenovo follows a similar line: its shares rose 22% last Friday after confirming that its AI revenues manage to offset the weakness of the traditional PC business. The focus changes. Something similar happens with HPE, the company that spun off from HP to focus on the business segment. Its server business hasn’t grown as much, but they already have contracted orders worth $5 billion and that guarantees a promising second quarter. Other consumer products makers are also migrating to AI infrastructure: Foxconn has absolute trust in which the demand for these components will continue to be exceptional in the coming months, and the same happens with Quanta Computer, which continues to see how its servers do not stop growing in importance in revenue for the company: They were already 80% of the total in the first quarter of 2026. Image | Dell In Xataka | For some people there is something much better than having a PC at home: having a server rack

six companies, hundreds of millions of dollars and 25 missions to conquer the South Pole

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NASA has already launched phase 1 of construction of your moon base. They have not yet taken a new batch of humans to the Moon, but it is important to prepare the ground, which is why this Tuesday they announced the first steps they are taking to do so. And, as it could not be otherwise, it all starts with million-dollar hires. 6 companies in total. At the moment, NASA has invested hundreds of millions of dollars in hiring six companies that will be in charge of developing the technologies necessary to launch the first phase of the lunar base. The companies in question are Blue Origin, Astrobotic, Intuitive Machines, Astrolab, Lunar Outpost and Firefly Aerospace. In general, in this first phase of construction of the lunar base it is expected to explore the south polar region, test various technologies and prepare surface operations. All of this will be carried out through 25 missions that will include 21 moon landings. Moon Base 1. To begin with, the first three missions are expected to launch this year. The first, Moon Base 1, will be carried out by Blue Origin. Jeff Bezos’ company will take its lander to the Moon Blue Moon Mark 1the “brother” of the Blue Moon Mark 2 that is preparing to become the human landing system for the Artemis missions. As payload will include the Stereoscopic Cameras for Lunar Plume-Surface Studies to study how thrusters interact with the lunar surface, and the Laser Retroreflective Array, which helps spacecraft in orbit determine a more precise location using reflected laser light. The mission will take place in autumn 2026 if all goes well. Since it will be the first to land in the Shackleton crater, where the base is to be built, it will also be in charge of checking the viability of lunar landings near the lunar base. Moon Base 2. The second mission, which will also travel to the Moon at the end of 2026, will be carried out by Astrobotic. It will send its Griffin lander to the Moon, loaded with 500 kg of instrumentation, including a rover to study the surface on which the base will be built and mature the mobility systems for future manned vehicles. Moon Base 3. The third mission to be sent in 2026 has been granted to Intuitive Machines. This company will take its Nova-C Trinity lunar module there, which will be in charge of studying lunar eddies and the behavior of materials under extreme conditions. Furthermore, this mission will not be 100% private, as it will include payloads from the European Space Agency and the Korean Institute of Astronomy and Space Sciences. Some of the models that NASA showed during the press conference Boogies to move around the Moon. So that future astronauts who travel to the lunar base can move around it, they want to take two manned lunar vehicles there. Said so that we can all understand each other, two boogie-type strollers, designed to move around the lunar surface, both with and without a crew. Its development has been entrusted to the companies Astrolab and Lunar Outpost, also as part of this first phase. Delimitation drones. The company Firefly Aerospace has been entrusted with taking the 4 Moonfall drones to the Moon, whose main mission will be to inspect the area in search of the best landing places for the astronauts. Although they will also have a much more peculiar mission. As explained At NASA’s press conference, its executive director of the lunar base program, Carlos García-Galan, these drones will also be stationed in the corners to delimit the perimeter of the lunar base. Next phases. This first phase will last until 2029. Then the next phase will begin, which will end in 2032. In this, the permanent infrastructure of the lunar base will begin to be built, including electrical installation. From then on, it will only be necessary to refine more and more details and little by little receive the astronauts of the Artemis missions of the future. Without a doubt, this is the beginning of a new era of space exploration. Image | POT In Xataka | We knew there was water on the Moon, but not why some craters were empty. Finally we have the answer

To no one’s surprise, companies that lay off employees for AI are not seeing the benefits they expected.

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We have been hearing for years that artificial intelligence was going to transform the labor market as we know it. Apparently, companies that bet heavily on automation would gain productivity, save costs and leave the competition behind. And yes, many technology companies they have taken that path: dismiss employees to finance your leap into AI. A new report from the consulting firm Gartner has just poured cold water on that strategy. The research, based on surveys of managers of large organizations with income exceeding $1 billion annually, reveals that staff cuts They are not producing the economic benefits that many expected. The most striking thing is that the figures are practically the same among the companies that They fire and those who don’t. Gartner numbers. The consulting firm found that around 80% of large companies that are implementing autonomous AI technologies have reduced their workforce to a greater or lesser extent. As and as highlighted Fortunethese personnel cuts in some cases affected up to 20% of employees. However, when analysts looked at who was obtaining better economic results, the data indicated that there was no appreciable difference in the return on investment of those companies that had laid off a good part of their workers and those that had kept them on staff. As Helen Poitevin, distinguished vice president and analyst at Gartner, noted, “There is no connection or correlation between those achieving ROI and layoffs.” The substitution fallacy. According to the authors of the report, the logic that has dictated the strategy of many technology companies is that, if AI can do the work that was previously done by a human, dispensing with that human will reduce costs, and that savings automatically becomes profit. The problem is that this equation is not being fulfilled. Gartner notes that companies that opted for workforce cuts to use AI ended up at the same point as those that did not. Poitevin warned that this approach could be “very damaging in a broader sense,” noting that some organizations that cut staff were forced to rehire employees shortly after. Amplify people, not replace them. Gartner data revealed that the companies that are achieving the best results are those that They don’t use AI to replace peoplebut rather they incorporate AI into production processes so that their employees perform more. In fact, one of the risks posed by the strategy of replacing personnel with AI is that the company stops investing in the medium term in improving its operations and loses productive capacity. The report notes that companies that use AI as a co-pilot for their workers tend to invest in training programs, create new roles to oversee the implementation of AI and redesign workflows, making their employees increasingly autonomous and productive. The future of work: transformation, not apocalypse. Gartner projects that by 2029 the number of jobs created thanks to AI will exceed those lost, thus coinciding with other previous analyzes such as that of the World Economic Fundwhich point towards a shift in labor profiles, not towards a balance of net job destruction. Between 2023 and 2029, approximately 6 million jobs will be automated worldwide, a small proportion of the nearly 2 billion jobs available globally. Still, the impact of AI is real. Gartner estimates that about 32 million workers a year will see their jobs automated. The author of the report assured that AI “is not causing a workplace apocalypse, but it is unleashing chaos and changing the way people work.” In Xataka |“They blame AI for layoffs they would do anyway”: Sam Altman confirms that AI has been used as an excuse to lay off Image | Unsplash (Raj Rana)

It already has permission to sell its H200 GPU to 10 Chinese companies

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Alibaba, Tencent, ByteDance and JD.com are four of the ten Chinese companies that already have access to the GPU for artificial intelligence (AI) NVIDIA H200. According to Reutersthe US Department of Commerce, which is the institution that grants or denies export licenses, has authorized at least ten Chinese companies and several distributors, including Lenovo and Foxconn, to acquire Nvidia’s second most powerful AI chip. This news comes almost two months after the US Government confirmed which was going to allow the company led by Jensen Huang to deliver its H200 chip to its Chinese customers. Nvidia announced in mid-March during its annual developer conference that the US and Chinese Administrations had unlocked the sale of this GPU in the nation led by Xi Jinping. However, so far not a single delivery has been made. In practice, the blockade continues despite the March announcement. In all likelihood this is why Jensen Huang has joined the White House delegation participating in a summit with Chinese President Xi Jinping this week. Nvidia is caught between the opposing interests of the US and China, and Huang is going to try to recover a market, the Chinese one, valued at 50 billion dollars in 2026 and which has come to represent 13% of its income. Now the problem is the Chinese Government Earlier this May, Jensen Huang confirmed that he is currently Its market share in China is 0%. Nvidia has not sold its AI chips in this country for several months because US regulations require Chinese buyers to demonstrate that they have implemented sufficient security procedures and that they will not use the GPUs for military purposes. In addition, Nvidia must also certify that it has sufficient inventory in the US. And all this bureaucracy is not being resolved quickly at all. Currently the greatest reluctance to sell Nvidia chips in China comes from Beijing However, currently the greatest reluctance to sell Nvidia chips in China comes from Beijing. The Chinese Government wants to promote developing your own GPUs for AI at any price, which in October 2024 led him to send a recommendation to Chinese AI companies in which he asked them to use chips produced in China as much as possible. Ten months later this recommendation became a requirement. And the Chinese Government is already forcing state-owned data centers throughout the country to use at least 50% Chinese integrated circuits in their servers. The Administration led by Xi Jinping has made this decision because it can afford it. And it is that It already has three very clear alternatives to Nvidia: Cambricon Technologies, Huawei and Moore Threads. On the other hand, in the US there is also a pressure group that opposes the sale of advanced US AI chips in China. Chris McGuire, senior fellow on China and emerging technologies at the Council on Foreign Relations, holds that “any deal that allows Nvidia to sell more chips to China means fewer Nvidia chips for US companies and a minor US advantage over China in AI“. Besides, McGuire argues that “it is surprising that President Trump continues to allow himself to be convinced to put Nvidia’s interests before those of America.” Image | Nvidia More information | Reuters In Xataka | The US remains committed to stopping China. Now it has targeted the second largest Chinese chip manufacturer

Two companies have teamed up to put their own space garbage truck into orbit

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As the space race advancesso does the generation of debris, which includes everything from fragments of parts to discarded phases of rockets or complete ships that lost their orbit. This space debris accumulates, generating more and more risks. It is clear that it must be managed in some way, but all the hypotheses proposed have been left in the air. Now, however, two private companies have proposed the development of a kind of space garbage truck, which can lead the process to become operational and repeatable. Just like that truck that passes by your window every morning, they also hope to achieve frequency and efficiency with their waste removal service. The truck and the garbage can. The two companies that have proposed this service are the American Portal Space System and the Australian Paladin Space. The first has developed Starbust, a maneuverable and resupply ship that works like a garbage truck. The operator or garbage dump would be Paladin’s contribution, a payload called Triton. This is responsible for both obtaining images of space debris and classifying and collecting the debris. While the experimental proposals that have been made so far would collect one or very few objects, this combo would collect many more in a single mission. A regular service. Both companies have assured that they are working at a good pace, so they hope to make a first launch at the end of 2026. If all goes well, they would begin doing more regular missions from 2027. It would be a repeatable and well-organized service, which would try to keep at bay the space debris debris that, logically, will continue to be generated. More and more space junk. It is currently estimated that there are more than 130 million pieces of space debris in low Earth orbit. It is a figure that may possibly increase, due to something known as Kessler syndrome. The term refers to a kind of domino effect whereby, if a piece of space debris hits a satellite, for example, even more debris will be generated, which will continue to collide with each other, increasing in number more and more rapidly. The risks. Space debris is dangerous for many reasons, all of them largely related to impacts. To begin with, they can affect artificial objects that are also in orbit, such as satellites. Furthermore, if the impact occurs on manned facilities, such as the International Space Station, or spacecraft, the lives of the astronauts would be put at risk. And we cannot leave aside the risk posed by space debris when it deorbits and returns to Earth. Normally, most of the pieces disintegrate when crossing the atmosphere and do not even reach the Earth’s surface. However, debris may remain capable of causing material or personal damage. In fact, in 2022 a study was published which pointed out that, in the subsequent 10 years, the risk of a piece of space debris falling on a human being is 10%. It is worth launching as many cosmic garbage trucks into space as possible. We will avoid many problems if they work as expected. Cover image | Paladin Space In Xataka | SpaceX has made sending things to space very cheap. The problem is that now space is full of things

The countdown begins for companies to cut their working hours

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May 1 was celebrated as Labor Day, but Mexico did much more than that on that day full of symbolism: it began its path towards reduction of working hours of 40 hours with the entry into force of the law regulating the length of the day labor. The change promoted by President Claudia Sheinbaum’s party does not represent a sudden change, but with the entry into force of the reform secondary working day opens an adaptation process for companies to modify the organization of their working hours to the new regulations. From 48 to 40 hours in four steps. Mexico part of one of the work days longest in the world according to dOECD data. The current legal limit is 48 hours per week, a ceiling that has not moved since 1917. However, the reform seeks to lower it in stages until it reaches 40 hours per week: on January 1, 2027 the maximum limit will be 46 hours; It will drop to 44 hours a week in 2028, to 42 in 2029 and, finally, it will be set at 40 hours a week by 2030. Every year, two hours less. The first step expires on January 1, 2027, which leaves companies room until that date to reorganize shifts, contracts and processes. All this without the workers see their salaries or benefits reduced current, something that itself Federal Labor Law expressly prohibits. The duties that the reform brings. The publication of the labor reform Mexican not only activated the calendar. The new legislation establishes as an employer’s obligation to keep an electronic record of the working day, which in Mexico is popularly known as a time clock. That obligation comes into force on January 1, 2027 and It is not a simple procedure. The Ministry of Labor and Social Security (STPS) will have access to this data to verify that the working hours are truly respected. Penalties for not having the registration in order they are already set and range between 29,327 and 586,550 pesos (between 1,431 euros and 28,624 euros at the exchange rate), equivalent to between 250 and 5,000 times the Unit of Measurement and Update. In addition, the STPS must develop mechanisms to collect and evaluate data on how the reduction in working hours is applied. Most companies have not yet moved. The diagnosis of the real state of preparation of companies is not encouraging. The data from a study from EY published by Yucatan Diary with 165 companies in Mexico reveals that 72.7% are in what the analysts themselves call “tactical paralysis”: they know the details of the change of day, they have followed it closely, but they have not yet taken any concrete steps towards its application. Only 18% of companies consider that they are really prepared to apply the new labor regulations. As explained Yeshua Gómez, associate partner of People Advisory Services at EY México to Expansion“companies are not waiting because they do not understand the reform. They are waiting because they do not know how much it will cost them to implement it.” 85% identify cost as the main obstacle to starting to take action, while 71% recognize that they regularly depend on overtime to sustain their daily operations. For these companies, the challenge is not to spend 48 to 46 hours on paper, but to do it from real days that already frequently exceed the 48-hour limit. More limited working hours, but with more overtime. The reform has also modified the definition of the working day, establishing the daytime workday at a maximum of eight hours, the nighttime workday at seven hours, and the mixed workday could reach seven and a half hours. The only (and important) exception to this rule is that the day could be extended due to extraordinary circumstances. This overtime, on the other hand, is also gradually extended: up to 9 hours during 2026 and 2027, 10 hours in 2028, 11 hours for 2029 and a maximum of 12 hours for 2030. The objective is that the transition to the change in working hours does not suddenly hit the sectors most dependent on extra work, and to offer them tools to optimize the working day of their employees, even if it is at the cost of pay up to three times more expensive every extra hour. In Xataka | Mexico has an ambitious plan to be the tenth economy in the world and that involves technology: semiconductors Image | Unsplash (Jesus Herrera, Kaden Taylor)

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