companies

The US has decided to shoot itself in the foot and destroy one of the best AI companies in the country

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Dario Amodei, CEO of Anthropic, published a few hours ago a statement in which he announced something unusual: the Department of Defense (DoD) has confirmed that “we have been designated as a risk to the national security supply chain” of the United States. This agency thus fulfills the threat it posed a few days ago and automatically turns Anthropic, one of the best AI companies in the country (if not the best) into a pariah company. What implications does that have? Many and all of them huge. I veto Anthropic. This designation prohibits Anthropic from doing business or developing projects for the US military. That is already serious, but it is not just the Pentagon, for example, that will not do it: any company that works with the Pentagon is also prohibited from using Anthropic’s AI services for any government project. We are facing a decision whose collateral effects could be terrible for Anthropic. The loss of revenue could be massive, and if other federal agencies follow the Pentagon’s lead, Anthropic could have a hard time defending its viability against its competitors. That designation is not immediate, and there will be a transition period six months for DoD to migrate to other vendors (like OpenAI). It had never been done with a national company. The ban on Anthropic is absolutely extraordinary, and that designation as a “supply chain risk” was a measure historically reserved for foreign adversaries like Huawei. By applying this label to an American company, the DoD severs its commercial ties and marks the company with a stigma, a kind of “scarlet letter” that could scare away global investors and partners. ethical shock. The core of the conflict is not technical, but moral. Anthropic was born as a spin-off from OpenAI with the aim of avoid existential risks in the development of AI models, and the company has always positioned itself as a great defender of alignment with human values. Its CEO, Dario Amodei, insisted that its AI could not be used for mass surveillance or for the development of lethal autonomous weaponsbut that has collided head-on with the US government and military establishments, which wanted practically total access without restrictions, except those imposed by the US Constitution and laws. to the courts. Amodei has explained in its statement that it will fight the decision in court. His argument, he explains, is that statute 10 USC 3252 It is a tool of protection, not punishment. The defense will need to focus on showing that the Department of Defense did not use the least restrictive means to ensure security. If they succeed, they could invalidate the designation, although the reputational damage has already been done. The dilemma of sovereignty. Can a private company be above the Government? The Pentagon argues that no supplier can slip through the chain of command, and one thing is certain here: for an AI to have usage clauses that limit military operations is to cede national sovereignty to a private algorithm and the terms of service of a board of directors and a CEO who have not been democratically elected. The threat of extreme interventionism. This unusual measure could end up setting a precedent. If the government punishes companies that ask uncomfortable questions or place limits on the use of their technology, AI innovation could change its philosophy. Companies that want to survive would have to do so without questioning the orders out of pure fear of bankruptcy and bankruptcy. Transition period. There is, however, a period of six months granted for the transition and that seems to make it clear that the Pentagon still depends on Anthropic technology for current operations, as demonstrated by the kidnapping of Nicolás Maduro or the current intelligence analysis of the conflict in Iran. It remains to be seen how events will evolve, but the outlook for Anthropic is certainly worrying. And for the rest of the companies too, if indeed justice rules in favor of the Department of Defense. Image | Anthropic | Xataka with Freepik In Xataka | Anthropic has become the Apple of our era and OpenAI our Microsoft: a story of love and hate

NVIDIA is going to spend $4 billion on photonics companies. He is preparing for what is coming

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NVIDIA does not provide stitches without thread. At the end of August 2025, the company led by Jensen Huang announced that in 2026 their platforms artificial intelligence next generation (AI) will use photonic interconnections to achieve higher transfer speeds between GPU clusters. This announcement came during the conference specializing in semiconductor engineering and high-performance computing ‘Hot Chips’, which was held in Palo Alto (California), and was just the prelude to what was to come. And this same week NVIDIA has revealed that is going to invest 2,000 million dollars in Lumentum, and the same amount in Coherent. These two companies have something very important in common: they are specialized in developing photonic technologies. Shortly after NVIDIA confirmed its interest in them, the shares of these two companies rose 5 and 9% respectively. And the company led by Jensen Huang has committed to purchasing products from Lumentum and Coherent for several billion dollars, and also to use their advanced laser solutions and optical networking technologies. Photonics is the support that cutting-edge semiconductors need Most IC designers and manufacturers are working on the development of silicon photonics. Douglas Yu, a TSMC executive with responsibility for systems integration, explained in September 2023 very clearly what disruptive capacity this technology has: “If we manage to implement a good integration system for silicon photonics, we will unleash a new paradigm. We will probably place ourselves at the beginning of a new era.” Silicon photonics is a discipline that in the field in question seeks to develop the technology of this chemical element to optimize the transformation of electrical signals into light pulses. The most obvious field of application of this innovation is implementing high performance links which, on paper, can be used both to resolve communications between several chips and to optimize the transfer of information between several machines. In AI clusters, thousands of GPUs must work in unison, so it is essential to connect them using high-performance links The advanced packaging technologies used by leading semiconductor manufacturers, such as TSMC, Intel or Samsung, can greatly benefit from a very high-performance inter-chip communication mechanism. And large data centers where it is necessary to connect a large number of machines, too. However, there is one discipline in particular that has an overwhelming future projection and that would benefit greatly from building on the advantages offered by silicon photonics: AI. This is precisely NVIDIA’s bet. In AI clusters, thousands of GPUs must work in unison, so it is essential to connect them using high-performance links. It is possible to solve this challenge using traditional copper cables or optical modules, but both of these solutions introduce into the infrastructure very important inefficiencies. The most problematic are energy loss and bottlenecks. Data transfer can consume up to 30 watts per port, which increases energy dissipation as heat and increases the likelihood of failure. Additionally, latency limits the scalability of clusters as the number of GPUs in data centers increases. To resolve these inefficiencies, NVIDIA will integrate the optical components required for photonic interconnections into the same switching chip package. This technology is known as CPO (Co-Packaged Optics) and manages to reduce power consumption to only 9 watts per port. Additionally, it minimizes signal loss and improves data integrity. Looks really good. NVIDIA has confirmed that it will integrate CPO technology into its Quantum-X InfiniBand and Spectrum-X Ethernet interconnect platforms during 2026. However, there is something important that is worth not overlooking: CPO is not going to be an extra. When it arrives, it will be established as a structural requirement of the next generation of AI data centers in a clear attempt to increase the competitiveness of NVIDIA’s AI hardware platforms. Image | Generated by Xataka with Gemini More information | Reuters In Xataka | Intel and TSMC lead the photonic chip revolution. Their problem is that China has just gotten fully involved in this war

Sam Altman says he’s terrified of a world where AI companies believe themselves to be more powerful than the government. It’s just what you’re building

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Sam Altman sat down over the weekend before his audience at X to answer questions about the agreement that OpenAI has just signed with the United States War Department. What came out of that session was a beautiful involuntary x-ray of the biggest contradiction in the sector at the moment. Why is it important. The CEO of OpenAI said he is terrified of “a world where AI companies act as if they have more power than the government.” The phrase sounds good, it is marketinian and seeks to elevate OpenAI’s position as a powerful but very responsible and honest group. The problem is the context in which he pronounces it: hours before OpenAI signed that agreement, The US government labeled Anthropic, its direct rival, a “supply chain risk” for refusing to sign under those same conditions. Altman went to put out the fire just as someone accused him of setting it. Between the lines. Altman’s speech rests on a premise that must be monitored: that a democratically elected government must always prevail over unelected private companies. It is a philosophically reasonable position, but he applies it selectively. Altman acknowledged that the deal “was rushed and the picture is not good,” and that OpenAI moved quickly to “de-escalate” tension between the Pentagon and industry. In other words, your company made a unilateral strategic decision about how the entire AI industry should relate to the military establishment. That doesn’t exactly sound like institutional deference. The contrast. Anthropic opted for something different: requiring explicit safeguards against the use of its AI for mass surveillance or autonomous weapons. But the government penalized her. OpenAI accepted a more ambiguous formula (“for all legal uses”) and won the contract. Various OpenAI employees signed a letter supporting Anthropic’s position. Claude became the most downloaded free application in the App Store that weekend from Apple, precisely surpassing ChatGPT. The market also has opinions. Yes, but. It’s fair to admit that Altman’s position has some internal logic: If AI is going to be integrated into military systems anyway, it may be preferable that it do so under negotiated conditions rather than under coercion. And he’s right about one thing: The labeling of Anthropic as a supply chain risk, a tool intended for hostile foreign suppliers, applied to an American AI security company is, in his own words, “an extremely frightening precedent.” The big question. Who really decides how AI is used in military contexts? The companies that build it, the governments that hire it, or the engineers who design it and who are increasingly organized to influence those decisions? Altman says he believes in the democratic process. But OpenAI negotiated privately, signed privately, and made only a fraction of the contract public. Democratic transparency starts there. In Xataka | Anthropic has become the Apple of our era and OpenAI our Microsoft: a story of love and hate Featured image | Xataka

We have been talking about “day 996” in Chinese companies for years. The reality is more complex: “day 323”

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In China there are more than 1.4 billion people and nearly a quarter of its active population works in the public sector, a work universe so enormous that any generalization usually falls short. Thus, between global topics and everyday realities, the distance may be greater than it seems. The myth exported from 996. It we have counted on more than one occasion, but just because something is repeated many times does not mean that it is the norm. We have been hearing for so long that China applies infamous day 996 (working from 9:00 am to 9:00 pm, six days a week), that the concept itself has ended up becoming a symbol of a supposed superhuman work ethic, although in its origin it was a criticism to an abusive model within the technology sector and never a general rule. On paper, Chinese law sets weeks five days and 40 hoursalthough its application is irregular and the official unions lack real power, and although there are sectors such as migrant work or the platform economy where the hours are hard and the scarce rights. In any case, they said in a Foreign Policy report that 996 has prospered in the West because fits the fear It calls for China to “work harder” and surpass its rivals, but that narrative simplifies to the point of dehumanizing those 1.4 billion people. Furthermore, it hides a much more diverse reality. The inheritance of work as ideology. The truth is that Chinese work culture was not born with the technologies of Shenzhen, but with a tradition marked by Maoism and heritage. of Soviet Stakhanovismone where productive sacrifice was glorified and consolidated the social weight of the danwei or work unit. In that sense, he remembered the analyst James Palmer that was not until 1995 when the two-day weekend was formalized, and for decades employment was not only a source of income, but also the core of identity, housing and social network. that past explains the coexistence of intense practices with other deeply bureaucratic ones, where political obedience and compliance with quotas weigh as much as real efficiency. The silent reality of 323. As we said at the beginning, beyond from the myth of 996a significant part of Chinese employment (around 23% of the active population) is concentrated in the public sector, where an informal pattern predominates summarize as 323: three hours of work in the morning, a break of two or even three hours to eat and napand another three hours in the afternoon. That long interruption is, in fact, almost sacred and has withstood reform attemptswith offices that dim lights or enable spaces to rest, in a routine that surprises those who expect constant hyperproductivity. The pace can be lax in quiet times and frenetic at the end of the year to meet administrative objectives, often accompanied by creative accounting adjustments. Bureaucracy, patronage and ghost jobs. They recalled in FP that 323 coexists with less visible practices such as fictitious jobs granted by patronage, from positions where hardly any work is done to positions “without presence” that serve to reward loyalty or avoid formal requirements. In that environment, flexibility and frustration coexist: an office may close during a long break, but also show leniency in the face of formal delays. And when the political leadership hardens the toneas happened with the anti-corruption campaign started in 2013 or with extraordinary demands such as imposed on teachers to register vaccinations in 2022, the intensity increases and many of the amenities temporarily disappear. Mandatory socialization and discipline. Furthermore, it must be taken into account that official work life includes banquets, toast and collective meetings that reinforce hierarchies and informal networks, rituals that can become a burden rather than a privilege and that were briefly contents by disciplinary campaigns before eventually returning. That sway between everyday laxity and political pressure explains why 323 makes sense within the system: it does not respond to an ethic of leisure, but to an administration that alternates phases of low demand with bursts of mobilization. Put clearly: in front of the story simplistic 996reality is more contradictory and less hyperbolic, a fragmented work culture where the working day depends as much on the sector and the political climate as on individual will. Image | International Labor Organization ILO In Xataka | China promised them very happy with day 996. Until they realized that it was a shot in the foot In Xataka | China became famous for its eternal work hours. The solution has been to throw the employees out on time.

There are people using AI to plan murders. The question is what AI companies are doing about it

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On February 10, an 18-year-old girl shot and killed her mother and brother. Then he went to the institute and murdered seven more people, finally committing suicide. The disturbing thing is that the author had talked about it with ChatGPT and OpenAI had the opportunity to notify the police, but chose not to. What has happened? They count in the Wall Street Journal that, in June of last year, OpenAI’s automated system detected several messages that a user had sent to ChatGPT describing scenarios of armed violence. For some employees they were very worrying because they could end in real violence, so there was an internal debate about whether to notify the Canadian authorities. They finally closed his account, but they didn’t notify anyone. Now Canadian authorities have summoned them to ask for explanations. There is more. He Tumbler Ridge shooting It is not the only case in which AI has been used to plan a crime. At the beginning of 2025, a man parked a Cybertruck full of explosives in front of a hotel in Las Vegas with the intention of detonating it (although in the end the only victim was himself). Days before, the author I had asked ChatGPT how to do it. In this case, the chatbot did not detect any concerning messages, but we know this because OpenAI searched through its messages after the fact. In Seoul, a woman was jailed for the alleged murder of two people due to benzodiazepine poisoning. The investigation revealed that the accused had gone to ChatGPT to find out what the dangerous dose was and what happened if it was mixed with alcohol. The messages in this case are not that alarming and could arise out of genuine doubt, but it is another example of ChatGPT being used in the commission of a crime. Why is it important. Artificial intelligences have become a kind of confessional to which we tell all kinds of secrets, even the darkest. There are those who consider that AI is a friendhis psychologist or even his lover. In this sense, it is not strange for someone to tell ChatGPT that they are going to kill their family or want to detonate a car full of explosives. What is worrying, and where we should focus, is what companies are doing about it. At the moment, it seems not enough. Are they obligated? Confessing to your psychologist or psychiatrist that you want to hurt someone is one of the reasons why you not only can, but should break your relationship. professional secret and alert the authorities. However, no matter how much we use chatbots as psychologists, at the moment there is no law that forces AI companies to report these types of interactions, but it is an internal decision. The obligation, therefore, is not legal, but ethical. How to make a homemade bomb. Cases like that of the Tumbler Ridge shooter are not something that has begun to happen with the arrival of AI chatbots. Instructions for creating homemade bombs have been around for decades. bringing the authorities to their heads, Even before the use of the Internet became popular, manuals of this type were circulating. The same thing happens with the suicide cases; You don’t need to ask ChatGPT, we can Google it or write in a forum. In statements to New York Timesa former OpenAI employee highlights an important nuance: with a chatbot you don’t usually do a simple search, but rather you can have a longer conversation where the intentions are clearer. In this sense, it may be easier to detect cases like the Tumbler Ridge shooter, but there may also be many false positives due to users who are writing fictional stories or using AI as role-playing. Complicated. In Xataka | Investing in data centers for AI is insane, and it’s going to get worse. much worse Cover image | Pexels, Unsplash

Germany wanted to see if working four days a week was efficient. 70% of companies think so

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The four-day work week started in Germany as an experiment to search for the maximum productivity of companies without having an impact on an exhausted workforce and without the ability to reconcile family life. Two years after the start of this test, the data confirms that for the companies that participated it was not a simple test, but rather it has materialized in a change in the way of working that many companies have decided to consolidate. Now the monitoring report prepared by researchers from the University of Münster together with the consulting firm 4 Day Week Global. It analyzes what happened after the pilot test that began in 2024 and what subsequent effects it has had. The main conclusion is that around 70% of the companies that participated in that test continue to apply some model of reduction of working hours a year later. A known formula and a varied sample. The original four-day week project in Germany was built around to the 100-80-100 model: 100% of salary, 80% of time and 100% of productivity. This model of reduction of working hours is the same one that was carried out in Valencia in 2023, Portugal either United Kingdom. In the initial phase, 45 companies from different sectors participated, dedicated to manufacturing, insurance, technology, media, commerce or education. Furthermore, to be as representative as possible of the German industrial fabric, companies of different sizes were chosen: from micro-businesses with 1 to 9 employees, to large companies with more than 250 employees. The first data already gave clues. Researchers have been collecting data from participating companies and their employees since day one. A few months after starting the test, the companies were delighted with the results, to the point that in preliminary results73% said they would not return to the traditional five-day week. The new report provides the perspective that time gives and whether that initial impetus has been consolidated. Two years after the start of the test, seven out of ten companies that participated in the test not only maintain the four-day workdaybut they have integrated it into their normal operation. More than four days: flexible reduction of working time. One of the most interesting findings from the monitoring is that the four-day workweek model has evolved and every organization has implemented it adapting it to your needs. Not all companies have opted for a Monday to Thursday work week. Around 22% of the participating companies have adapted the initial scheme towards more flexible formulas: reduction of annual hours, alternate weeks or internal adjustments according to workload. The report itself speaks less of a “four-day week” and more of “reduction of work time“. The label matters less than the redesign of the work day and the elimination of superfluous tasks, fewer unnecessary meetings and greater autonomy of the teams. No impact on profits or productivity. In business terms, the German test has been a success since, despite having maintained 80% of the initial day, there have been no drops in either the level of profits or in productivity or slightly improved with respect to the starting point. That is, they have managed to do the same thing in less time. What it did have a strong impact on was the well-being of employees, where 90% reported improvements in the balance between personal and professional life. As a result of this improvement, employees reported feeling less stress and greater commitment to the company. 38% of companies indicated that sick leave and absenteeism of their employees had been reduced, while 56% claimed to have detected no changes. Lights and shadows in the reduction of working hours. Progress was also observed in job satisfaction and in the perception of the company as an attractive place to work. The study indicates that 87% of companies detected improvements in talent retention. For their part, 75% claimed that their companies now had a greater capacity to attract talent in selection processes. This, in a scenario of labor shortagerepresents a competitive advantage. However, as happened in other tests of the four-day work week, not all companies have followed the same evolution. About 30% stopped applying the initial scheme or returned to the traditional five-day week. The main reasons were operational, difficulties in coordinate with your clientswork peaks that are difficult to absorb or inflexible internal structures. In Xataka | Employees in Spain clear up doubts: working fewer days is better than working fewer hours, according to a survey In Xataka | Spain already has its first municipality with a four-day work week. It is not in Madrid or Barcelona, ​​but in a corner of Cádiz Image | Unsplash (Gonzalo Leon Jasin, Josue Isai Ramos Figueroa)

Anthropic just accused DeepSeek and other Chinese companies of “distilling” Claude

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For months we have talked about the race between the United States and China to dominate artificial intelligence as if it were only a question of who trains the most powerful model or launches the next version first. But the pulse begins to move to another, more delicate area: that of the rules of the game. When one laboratory accuses another of extracting capabilities from its system to accelerate its own development, the discussion goes beyond the technical. That’s exactly what Anthropic just did by denounce “distillation” campaigns against his model Claude. The complaint. In a text published this Monday, the company claims to have detected “industrial-scale campaigns” aimed at extracting Claude’s capabilities. According to their version, the activities attributed to DeepSeekMoonshot and MiniMax reportedly involved more than 16 million queries, question and answer interactions, and were channeled through approximately 24,000 fraudulent accounts, in violation of their terms of service and regional access restrictions. The race and the suspicion. The announcement by the firm led by Darío Amodei occurs in a context of growing tension around the progress of Chinese AI. Let us remember that DeepSeek altered the Silicon Valley landscape a year ago with the launch of R1, a competitive model that was presented as Developed at a fraction of the cost of American alternatives. The impact was immediate on the markets and revived the political debate in Washington about the technological advantage over China. Distilling is not always cheating. Anthropic itself recognizes that distillation is a common technique in the sector. It consists, in simple terms, of training a less capable model using the responses generated by a more powerful one, something that large laboratories use to create smaller, cheaper versions of their own systems. The problem, according to the company, appears when this practice is used to “acquire powerful capabilities from other laboratories in a fraction of the time and at a fraction of the cost” that developing them independently would entail. In that case, distillation would cease to be an internal optimization and would become, always according to Anthropic, a way of taking advantage of the work of others. Recognizable pattern. The three laboratories would have used fraudulent accounts and proxy services to access Claude on a large scale while trying to avoid detection systems. The company details infrastructures, what it calls “hydra cluster”, extensive networks of accounts that distribute traffic between its API and third-party cloud platforms, so that when one account was blocked, another took its place. Anthropic maintains that what differentiated these activities from normal use was not an isolated query, but rather the massive and coordinated repetition of requests aimed at extracting very specific capabilities from the model. Three campaigns. Although Anthropic presents the campaigns as part of the same dynamic, it distinguishes relevant nuances. DeepSeek would have focused its more than 150,000 queries on extracting reasoning capabilities and generating safe alternatives to politically sensitive questions. Moonshot, with more than 3.4 million queries, would have been oriented towards the development of agents capable of using tools and manipulating computing environments. MiniMax would concentrate the largest volume, more than 13 million queries, and according to Anthropic’s account, it reacted in a matter of hours to the launch of a new system, redirecting its traffic to try to extract capabilities from its most recent system. A geopolitical issue. The company states that illicitly distilled models may lose safeguards that seek to prevent state or non-state actors from using AI for purposes such as the development of biological weapons or disinformation campaigns. It also argues that distillation undermines export controls by allowing foreign laboratories to close the gap in other ways, while at the same time recognizing that executing these large-scale extractions requires access to advanced chips, thus reinforcing the logic of restricting their availability while, at the same time, remembering that the risk would grow if these capabilities end up being integrated into military, intelligence or surveillance systems. Images | Xataka with Nano Banana Pro In Xataka | Seedance is the greatest brutality we have seen generating video. And it has an uncomfortable message: it has surpassed Sora and Veo without NVIDIA chips

Companies are not just letting go of their youngest workers. They are making them CEO

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The business fabric in the US is experiencing one of its most turbulent periods. Not only because of the coming to power of Donald Trump and his upstart tariff policiesbut because of the challenge in management and governance models that poses to AI. OK to what was published by The Wall Street Journalthe US is experiencing a generational change at the head of the main listed companies. In 2025 alone, one in nine CEOs at the 1,500 largest companies in the S&P 1500 will be replaced, the highest rate since records began in 2010. The demands of AI they are retiring the CEOs more experienced. Relay record at the top. According to data revealed by a study from the consulting firm Spencer Stuart, 168 people debuted as CEO in large listed companies. In more than 80% of these appointments, the new managers lacked previous experience leading companies of that category, although 60% of those appointments were promotions. Furthermore, two-thirds of these incorporations had also not served on boards of directors before. That is to say, its greatest value It was not his experience, but his youth. The trend continues strongly during the first two months of 2026. Top-tier companies such as Walmart, Procter & Gamble, Lululemon, Disney, PayPal and HP have made changes in his highest executive position. This pace marks a great experiment in leadership by large companies in the face of unstable markets, where the pressure to obtain immediate results accelerates the departures of veterans. Younger and younger leaders. The average age of new CEOs dropped to 54 years in 2025, which is almost two years less than the record in 2024, thus confirming that this is a trend that has been occurring for some years. Although only 3% of managers in large companies are under 40 years old, 64% are between 50 and 59 years old, and only 12% are over 60 years old. Some examples are found in recent replacements like disneyin which Josh D’Amaro, 55, took the replacement of Bob Iger 75 years old. This replacement reflects a commitment to fresh talent, but with a deep knowledge of the companies they are going to lead, but without experience in decision-making. The life cycle of a CEO. Spencer Stuart analysts found that CEOs of large companies have “a useful lifespan” at the helm. During the first year in office, the new CEO begins the “honeymoon effect” and his companies outperform the S&P 500 by 10% on average. However, in the second year of office, 73% experience a drop in returns of an average of 21%. Between the third and fifth years at the helm, a reinvention of leadership occurs, which precedes a stagnation between the sixth and ninth years. Beginning in the tenth year, stable leadership is established. The majority cannot taste that stability since, after the third year, 25% have already left the position. 50% do not reach the sixth year as CEO. The average duration of active CEOs is 7.1 years, and 86% of departures are voluntary and agreed upon with the board of directors. Only 9% of CEO changes in the S&P 500 group of companies have been forced removals. It should be noted that only 16% of new appointments to senior management positions they have been womenwhich represents a bittersweet historical record. In Xataka | The average salary of Ibex 35 managers has grown by 172% in two decades: the purchasing power of its employees, not so much Image | Unsplash (Bruce Mars)

China is clear about who should lead the advances of its best AI and robotics companies: Generation Z

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Those who now enter the labor market find themselves with a rival that is difficult to beat: they have no agreement or need for rest or fulfillment. In addition, it does the tasks of junior profiles quite well: artificial intelligence is limiting the landing of Generation Z in the offices. in the United States, we have seen it in the UK and also in the Big Four that make up the Madrid skyline. Replacing those who start working with AI has been revealed as the West’s formula to boost productivity… from the point of view of the bosses. If you have to fight with her and validate her, not so much anymore. But it is by no means the only way, nor does it happen to everyone. In fact, China is betting just the opposite: it is turning Generation Z and millennials into heads of areas as strategic as robotics or artificial intelligence itself. They are not just any young people: they are true galacticos, their best assets. Give me someone young. As collect TechAsiaa trend is emerging in China: that of hiring millennials and young people from generation Z for positions with high-level technical profiles in large AI and robotics companies. The best example is Vinces Yao Shunyu: at 28 years old he has already been at OpenAI. A couple of months ago he returned to his native China to become the chief scientist of Tencent. He now reports directly to the CEO. Shunyu’s is just the tip of the iceberg of this new organizational strategy of Chinese companies. There are other cases, such as that of Luo Jianlan, formerly of Google since a year the chief scientist of AgiBot. Or of Dong Haochief scientist at PrimeBot after earning his PhD at Imperial College. By the way, OpenAI and Meta have copied the recipe: the first with Polish Jakub Pachocki and the second, with the Chinese Zhao Shengjia. They are scientists, but they could just as well be professional footballers: none of them are over 35 years old. Why is it important. When thinking about a boss within a modern business structure of a certain size, it is inevitable that team management, meetings and bureaucracy come to mind. However, this strategy of Chinese big tech is deliberately different from what we have in the West and is based on three reasons that SMCP explains: Institutional separation of research vs. product. A chief scientist looks to the future, he does not manage human teams or budgets. Competitive advantage in a saturated market, allowing you to build your own technologies without depending on third parties. If you have the best at home, you don’t have to ask for permission or sign abroad. The top youth asset. AI is evolving by leaps and bounds and with this movement, China is ensuring that it has those who have been at ground zero of the great milestones of recent years: elite universities or laboratories of renowned institutions such as OpenAI, Google or Princeton. China is a world source of engineers. That China is a country of engineers is no secret: it is a plan that has been underway for 4o years. In fact, now he has opted to go one step further and accelerate doctorates. The Chinese labor market is already showing signs of some saturationwhich has also brought diversification, changing routes to avoid even setting foot in the university in its new bet on FP. In any case, having an army of almost six million engineering professionals gives you an advantage with AI. And it has more than enough: it has engineers to export. Without going any further, the vast majority of signings of the Meta superintelligence team from last year they are Chinese. But young engineers who stay at home have an opportunity beyond joining a leading company in the sector: leading it. Disclaimer: a chief scientist is not a CTO. It is worth remembering a difference between positions that are often confused: a chief scientist is not the director of technology. While the first profile investigates, explores and plans in the medium and long term without touching products or marketing, the second manages teams, designs architecture and meets business objectives. Confuse both profiles or mix them, as the SMCP remembers what Alibaba or Baidu did, ends up subordinating science to the urgency of the market. In any case, it is a fragile position in a company that is not clear why it is needed. In Xataka | China looks at VET: why more and more generation Z students prefer trades over university degrees In Xataka | If Spain wants to imitate China and be a “country of engineers”, this map reveals the extent to which it has a problem Cover | and Hyundai Motor Group and cottonbro studio

Spanish companies have hired again in 2026. The problem is that there is no one to hire

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Spanish companies start 2026 wanting to expand their workforce, but they face a big problem: they cannot find enough qualified candidates for your vacancies. According to the data of the ‘Labor Market Guide 2026‘ prepared by the consulting firm Hays, companies are ready to grow and hire more staff. However, the labor market has changed and professionals are already they don’t want to give up to their current jobs. Companies step up. The Hays study reflects that 81% of Spanish companies plan to increase their workforce during 2026. The economic growth trend drives the expansion objectives of Spanish companies and, to carry it out, new vacancies have been opened. This growth in job offers is especially noticeable in dynamic sectors such as technology, professional services and industry. However, the big obstacle quickly appears: there are not enough professionals with the necessary training to fill those vacancies. 93% of the companies consulted for the Hays study claim to have serious difficulties in find qualified profilesa percentage that reaches a historical record and is paralyzing many hiring plans. Talent shortage vs. little training. The lack of qualified professionals has become an insurmountable wall in the hiring processes for new vacancies. 85% of companies claim to have launched internal training programs to develop capabilities of its employees. Only 18% of participants openly admit that they are not investing enough in closing this skills gap that holds them back so much. From the employees’ side, the perception is different. Only 48% of employees are aware that training is being carried out in their company to improve their training. This disconnection between what companies promise and what workers see aggravates the situation, making it more difficult to attract and train talent. Qualified external talent is not found, but neither are resources allocated to train the talent that is already on staff. Less job rotation. Unlike what happened years ago, in 2026 professionals have prioritized stability and growth within their company, instead of jumping to another offer. This change in mentality represents a change with respect to the years 2022 and 2023 in which the labor market had high mobility and the workers they changed jobs frequently in search of better working conditions. Even so, 62% of workers feel that their salary does not reflect all the effort that they put in day by day, but that dissatisfaction is not enough to push them to movesince they value stability and personal balance more. Christopher Dottie, regional managing director of Hays for Southern and Western Europe, puts it in clear words: “companies continue to look for talent, while talent continues to look for stability.” Better salary and flexible working hours: keys to attracting talent. To break this inertia and attract available talent, 72% of companies plan salary increases in 2026, with increases of 7% in areas such as customer service, administration and finance, and 6% in the technology sector to meet salary expectations what candidates demand. Furthermore, the flexible days They are imposed as a key piece in attracting talent, although many companies still resist implementing them despite the fact that the vast majority of employees consider them essential for their well-being. In fact, this ability to adapt to demands for flexibility and offer teleworking options is what is tipping the balance. between the public and private sectors. In Xataka | The employment paradox in Spain: we have the highest unemployment in the EU and also the lowest number of job vacancies Image | Unsplash (Beatriz Cattel)

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