engineers

“They are hiring more engineers”

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Are you a software engineer and afraid of getting fired because of AI? Well don’t have it. At least, that is the position of a very interested party in the conversation around artificial intelligence. At this point, the name of Jensen Huang It will not be foreign to you. This is the CEO of Nvidia, a company that has gone from leading the GPU segment for playing video games for two decades to leave that market for focus on AI platforms. We cannot say that they are doing badly, of course, and within the strategy we have a Jensen who has become one of the most important ‘evangelists’ in the segment of the artificial intelligence. Within the framework of the Computex 2026 fair held in Taipei and in which PC manufacturers show their new products, Jensen commented that it is foolish to be afraid that an AI will replace us at work. The logic is that this AI will generate more jobsbut there is a question hanging over that argument: what kind of jobs. Because, if the optimism of all companies focused on the development and popularization of AI is one side of the coin, the other is that of lYoung people who cannot access jobs. And that of the companies themselves firing employees to replace them with… an AI. Jensen Huang is on a mission At Computex, Huang feels at home. Taiwan is home to some of the world’s most important technology companies not so much for their products. There we have giants like Asus, BenQ, Foxconn or Acer (among many others known to gamers). But, above all, we have TSMC. TSMC is the engine of the chip industry and Nvidia its current best client after overtaking Appleand Huang, furthermore, is a rockstar in Taiwan. During his time at the fair, Huang presented his new platform RTX Spark Superchip and a new chip to compete against Intel and AMD in the field of CPUs, but it has also taken advantage of the speaker to demonstrate again your opinion on the future of AI and work. The CEO consider that AI is something positive for both GDP and everyone’s profits, but also pointed out that it is “nonsense” to think that artificial intelligence is leading to people being fired from companies in the profile of software engineers. “The number of software engineers is actually increasing. People talk about AI reducing jobs, but it’s complete nonsense: it’s leading to more software engineers being hired” – Jensen Huang Huang is very vocal on this topic and has spent 2026 taking advantage of any interview, podcast or visit to universities and events to preach about the benefits of AI and the positive relationship between technology and employment. He has gone so far as to say that “AI creates jobs” and that it is the United States’ best opportunity to reindustrialize, pointing out that blaming AI for the very numerous layoffs in industries such as technology and video games is a “too lazy” practice. Now, as in every story, there is part that is true and part that is not so true. On the one hand, Huang is very interested the narrative that AI is a job creator. As we say, it is one of the parties most interested in technology continuing to advance because we are already seeing that it is a sector that moves a lot (a lot) of money and Nvidia is one of those that is taking advantage thanks to both its products and its commercial vision. On the other hand, the reindustrialization discourse is correct. The United States is seeking that reindustrializationthis flowering of the business fabric based on technology and, to this end, it is looking not only for part of its companies to move the industry from Asia to the US, but also to attract giants like the South Korean companies. Samsung and SK Hynix…and the coveted TSMC. Does data kill story? Huang’s argument makes sense. AI creates jobs. What it doesn’t say out loud is what type of job. Because engineers or those who have careers related to the development of AI Yes, it is “easy” to get into jobs related to AI, but the rest, and profiles without much experience, find it increasingly difficult. Technology companies are getting rid of juniorswhich are replaced by AI while those jobs are taken over by developers. AND jobs are opening in record numbers of more than 67,000 offers in engineering and 7,300 in product, but the fine print is that it is almost impossible for young recent graduates to apply for one of these positions due to the high degree of specialization that companies demand. And they are not only the requirements, but the technologies themselves who are citing AI efficiency as a driver for laying off their human workforce. Amazon with 16,000 employees and Microsoft with 15,000 are two examples. Heavyweights like Dario Amodei (CEO of Anthropic) point out that AI could eliminate approximately half of entry-level jobs and there are studies that link AI with almost 55,000 layoffs in the US in 2025 alone. For Huang, all of this is “ridiculous“because it won’t be AI that will make us lose our jobs: it will be because there will be someone who uses AI better than you. Furthermore, according to himAI has created 500,000 jobs in the last two years. And, in the background, we have two currents. On the one hand, the AI ​​optimists. On the other hand, a generation Z that is actively resisting adopting artificial intelligence in their daily lives and, especially at work. Because, compared to those who think that AI is a positive network for humanity because it gives opportunities that favor young people, there are some young people who they can’t find work once they graduate, they are thrown into a disconcerting work scenario and they are starring in a curious soundtrack in recent weeks. That of the boos to the AI ​​evangelists in universities. In Xataka | Companies are … Read more

The engineers who worked at FSD do not trust their own creation

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Elon Musk has been ensuring for a decade that full autonomous driving is just around the corner. Although the company has advanced in its driving assistance systems, a Reuters investigation reveals something worrying. Several people who worked on this project have denounced that the technology continues to suffer from basic and dangerous errors, and they confess that they would not get into a Tesla autonomous car for the world. what has happened. In this investigation, Reuters had the testimonies of nine “data taggers”—the people who train that Tesl AI system—as well as a software engineer who worked on the project. According to them, vehicles with these systems collide with animals, ignore the presence of school buses or accelerate in construction zones. One of the team’s veterans summed up everything in one sentence: “we have all seen the FSD fail.” Beware of public demos. Tesla has already launched robotaxi pilot programs in cities like Austin (Texas). Musk claims that his software is a generalized system that can be adapted to any city without high-precision maps, but these interviewees indicate that the operational reality is different. The trick. Tesla staff spent months recording videos and mapping the area of ​​Austin where the tests were to take place, and they spent hundreds of hours labeling curbs or road markings just to avoid problems during the demonstrations. According to these former employees, this level of intervention is unaffordable on a global scale. Comparing pears with apples. To maintain that the FSD system is up to ten times safer than human driving, Tesla uses a methodology criticized by experts. For example, he compares his cars (4.1 years old on average, modern safety systems) with the average American car, which is almost 13 years old. Phil Koopman, a professor at Carnegie Mellon University, explained that “It’s like saying my jet plane is faster than a World War II bomber.” The data reveals that if only accidents with airbag deployment are compared, Tesla’s advantage would not be 10 to 1, but 3 to 1, and even that figure is questionable. The controversial “Mad Max” mode. Internal videos have shown Tesla cars driving at speeds much higher than those allowed after the introduction of certain aggressive driving modes like the so-called “Mad Max”. Some of the employees who participated in the investigation reported cars traveling at almost 100 km/h in zones limited to 40 km/h. This aggressive driving is often treated as a low priority problem by its engineers, despite the risk it poses to road safety in these urban environments. Investigations in progress. The National Highway Traffic Safety Administration (NHTSA) currently has four open investigations into FSD and Autopilot. These cases include situations in which Tesla vehicles ignored red traffic lights or they turned directly into oncoming traffic. Fatal accidents that occurred are also being investigated in low visibility conditions —fog, sun glare—, and where the Tesla sensors, which are focused entirely on the use of cameras, have turned out to be insufficient. Where are the robotaxis? Almost a year after its launch in Austin, Tesla’s fleet of robotaxis it’s still tinyand consists of about 50 vehicles. It is also limited to very specific areas, and in cities like Dallas or Houston, users have complained that the cars do not drop them off at their exact destination. Besides, many of these vehicles They still have human drivers in the passenger seat who are there to avoid problems. It’s a reasonable practice, but it destroys the promise of full unattended autonomy that these vehicles offer. In Xataka | Elon Musk has come up with two names for Tesla’s self-driving taxi. And legally you can’t put any on it

We thought AI was laying off engineers. In reality, it has pilloried another profile: middle management.

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We’ve been hearing for several years that AI was going to change work as we know it. What perhaps no one anticipated is that the first mass casualty They would not be factory operators or data analysts, but the layer of professionals that holds together the structure of any company: middle management. The phenomenon is already leaving a trail of layoffs with the successive restructurings that the big technology companies have been applying for the last year. Departments are reduced by the implementation of AI and become increasingly autonomous in decision-making, so the intermediate step that united everything becomes unnecessary. The profile that worries the most. Middle managers have been acting as a transmission belt between the management that dictates strategies and the teams that execute them for decades. The function of these positions was to collect data, synthesize it, transfer decisions and coordinate day-to-day operations. That intermediary job is exactly the role that AI is automating most easily, making middle managers the most important link. likely to be fired in that chain because it is not related to either decision-making or their execution. The pressure on this intermediate profile has been building for some time and the data confirms it. By the end of 2025, job offers for middle managers in the US were 42% lower to the maximum recorded three years earlier, according to Revelio Labs. The consulting firm Gartner calculated that by 2026 one in five companies will use AI to eliminate more than half of their middle management positions. Companies are applying it. Just a few weeks ago, Block, the payments company founded by Jack Dorsey, announced the dismissal of 40% of its staff and presented a new organizational model in which AI assumes the role of a link between teams. In one later blog postDorsey and councilor Roelof Botha explained this move: “There is no need for a permanent layer of middle management.” Brian Armstrong picked up Dorsey’s baton in your ad of dismissal for 14% of the Coinbase workforce, specifying that the intermediate positions were going to disappear as such and that they were now going to contribute by “getting their hands dirty with their teams.” What is lost when a link disappears. In statements to GuardianFreeland Abbott, former CTO of Square, warned that “AI cannot provide team motivation, human connection, and support the way a person can,” removing the human component from middle management in companies. Furthermore, the elimination of this role could mean another obstacle in promotion options for junior employees, who usually find those opportunities by starting to manage the work of other junior employees as they gain experience. According to the study By Anastassia Fedyk, a professor at the Haas School of Business at the University of California, Berkeley, as AI tools allow more work to be shifted from managers to their subordinates, these structural changes could become permanent. Rehire middle management. Matthew Bidwell, professor of management at the Wharton School of the University of Pennsylvania, assured on his podcast on the labor market that there are precedents of companies that tried eliminate intermediate hierarchies and they ended up turning back. According to their analysis, middle managers are in an especially vulnerable position in restructurings because it is more difficult for them to demonstrate their value to management. Far from putting an end to the “productive” positions held by engineers and administrators, AI seems to have opened the door and the piece that is being most affected to the point of placing it as a species at risk of extinction are middle managers. Above all, after his post-pandemic proliferation. In Xataka | Generation Z is avoiding promotions to mid-level positions: too much stress and too little reward Image | Unsplash (Austin Distel)

an all-stars of engineers from Porsche, BMW and Lamborghini

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It is not easy to build a car brand from scratch. In fact, if you appreciate advice on how to go broke, put all your money into trying to build one. Over the decades, the number of companies that have succeeded in the automotive industry from nothing, completely from scratch, are absolutely exceptional. The electric car has been a breakthrough which has facilitated the entry of new players, such as Tesla, and despite everything, many have failed along the way. Let’s think about Fisker, Dyson, Apple… All of them were projects that were developed with more or less effort but that they have not finished curdling. And to start a new company you need a lot of money. You have to design a car, have access to the factory and the corresponding machinery, distribute the cars and offer after-sales service. And, above all, gaining the trust of the general public, key when it comes to trusting a brand without references, without a story behind it and a brand that has to prove to be solvent enough to get ahead. That opportunity offered by the electric car, as we said, has been taken advantage of by China. For years they have built a supply chain and invested huge amounts of money in researching how to get the best out of this technology. And to do this they have not hesitated to absorb the knowledge of European manufacturers. He all-stars from Xiaomi is a good example. Learning from the classics In its learning to position itself as the market leader in electric cars, China has not hesitated to rely on European knowledge. In the early 2000s, European manufacturers thought that the Chinese state was laying out a red carpet for them to produce their cars on its soil. They did it with one condition: that manufacturers ally with a local company. In this way, the engineers assimilated the knowledge coming from outside and were able to apply it in entirely Chinese companies, already outside the European orbit. He result We have seen it years later. The Chinese customer now prefers the purchase of a locally developed car because it better adapts to their demands and they consider them more advanced than Western ones. The gap, even, has forced Volkswagen to look for engineers in China in order to better understand the market and produce specific vehicles for said market. In the opposite direction, Chinese firms have armed themselves with Western talent to bring their cars closer to the European and American aesthetic standards. We have seen historical designers like Wolfgang Egger, who designed the beautiful Alfa Romeo 8C Competizione, carry out the Yangwang U9, BYD’s supercar. Or Walter de Silva, who built his career in the arms of the Volkswagen Group, designing cars for the BAIC group. But design has not been the only rock on which Chinese manufacturers are building their new house. And Xiaomi is an example of this. Just as Volkswagen has hired Chinese engineers to be able to approach the Asian market, Xiaomi is aware that it has to adapt to European tastes so that their cars find sufficient support outside their borders. A decision that is summarized in a photograph. In it we find the design and research and development team that will lay the foundations of the product that we will see in Europe. Click on the image to go to the original tweet As seen in the image in the post, Xiaomi has built a kind of all-stars of German engineering. And there are such relevant figures in his team that they have directed the teams that have produced cars of the caliber of the Porsche 911 GT3 RS, the Mercedes S-Class or the BMW i8, among others. Where Xiaomi Much emphasis has been placed on design. Jean-Arthur Madelaine He was part of the team that created the Mercedes-Benz Vision GT Concept, a prototype created for the Gran Turismo 6, but his most relevant positions have been as head of interiors for Citroën first and Polestar later. He now heads the Xiaomi electric design team in the plant that the company opened in Germany last year. Julien Cueffwho is in charge of the interiors, worked for Mercedes but has been in the orbit of Chinese manufacturers such as Nio or Lotus for years. Fabian Schmölz-Obermeierdedicated to the exterior appearance of cars, has worked for Porsche and Lamborghini. In this last company he was the person most responsible for the exterior design of a car like the Temerario. But beyond the design, the company has looked for prominent heads in the market to guarantee the good performance of its cars. Simon Schmitt is an engineer specialized in aerodynamics who has been part of the BMW racing team. From the same company they have arrived Claus-Dieter Grollfor the development of the dynamics of their cars, and Kai Langerwho worked for 22 years at BMW and was design director of the Bavarian company’s electric range to lead the team focused on user experience. These names are just a handful of examples. The company seems aware that it needs to get closer to the European public in its expansion strategy outside of China. And in recent years we have seen very good competitors arrive from China but also how some of these cars had not adapted to the tastes and demands of the European public. In Xataka we have counted the case of firms like Omoda/Jaecoo, which have tweaked their cars in record time to make them harder and leave aside dynamics supported by suspensions that are too soft. A good part of the Chinese market needs to delve deeper, for example, into driving assistance systems, which are clearly not tuned for European roads and our way of driving, with narrower lanes. But Chinese manufacturers are demonstrating enormous adaptability. Stellantis assures that Leapmotor vehicles are tuned in Italy To suit our tastes, BYD aims to produce a purely European vehicle with its Hungarian factory. At Ebro they assure … Read more

in DeepMind they use Claude, the rest of Google engineers want to and cannot

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Things are hectic at Google. In recent months, some DeepMind engineers have had access to Claude Code and Anthropic models, but in many other parts of the company this tool, which is currently considered the best on the market, has been banned. This has caused strong internal tensions in the company, and is also a sign of something worrying: Google’s AI cannot compete with Anthropic’s at the moment. what has happened. Steve Yegge is a software industry veteran who worked for years at Google. Last week posted a viral tweet in which he explained that after speaking with a current manager, he was concerned about the adoption of AI tools in this company. “The bottom line is that Google engineers have about the same adoption of AI as John Deere, the tractor company,” he said. Or what is the same: one of the most cutting-edge technology companies in the world was being anything but cutting-edge in its use of AI. Demis Hassabis gets angry (and a lot). Recent Nobel laureate Demis Hassabis, head of DeepMind, criticized Yegge’s tweet and told him to stop spreading nonsense. “This publication is totally false and is simply clickbait,” he said. Yegge returns to the fray. The engineer spoke in the following days with more current Google employees and discovered more things that he told in another long tweet. According to their conversations, the internal adoption of AI at Google follows a conventional pattern: 20% reject it, 60% use it in a basic way, and 20% take advantage of it intensively. Either you let me use Claude Code or I’m out of here.. But there was something else: some engineers are prohibited from using Claude Code because it is a competing product, but the vast majority do not have access to those tools because the company wants them to use Google’s tools — that is, the Gemini models in Gemini CLI, its alternative to Claude Code. According to Yeggewhen they tried to force DeepMind engineers to stop using Claude Code and Anthropic models, they refused to stop using the tool and threatened to leave the company. Internal sources of the company confirmed the data published by Yegge in a published news on Business Insider. Sergey Brin gets going. This week, The Information public that Sergey Brin has sent an internal memo to DeepMind engineers and researchers and confirms what was already being said. “To win the final sprint, we must urgently close the gap in agentic execution and turn our models into world-class developers,” the Google co-founder wrote. According to this data, an “assault team” has been created with the direct participation of Brin himself and DeepMind’s CTO, Koray Kavukcuoglu. That statement makes it clear that Gemini is below Claude in capabilities, because otherwise there would be no talk of “closing the gap.” Google and fragmentation. It’s not just that Claude Opus and Claude Code are now better than Gemini and Gemini CLI. Es que además esto ha dejado claro que en empresas tan grandes como Google la fragmentación operativa puede llegar a ser un problema grave. That some can use something that others cannot, and that worse tools are forced just because they are their own, can end up generating internal tensions, as has happened. That is what Google now seems to want to remedy so that all its employees row together. Another victory for Anthropic. All this controversy does nothing but favor Anthopic, which has managed to take the lead in this race – rather marathon – of AI. That the engineers at the prestigious DeepMind prefer their AI platform to Google’s own is an unequivocal sign that today Anthropic is ahead for AI experts. Image | Alex Dudar In Xataka | The tech industry is spending billions of dollars on GPUs for AI. 95% are inactive

Apple is two years behind its competitors. So he’s sending 200 engineers to an “AI camp.”

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When we talk about AI Big Tech, there is one name missing: Apple. There are many “the wolf is coming” in this matter of artificial intelligencewith companies that are creating ‘hype’ with models that they consider very dangerous and, above all, with artificial general intelligence. However, the “the wolf is coming” par excellence in AI is the new Siri and Apple Intelligence. Apple is tired of being the last and has made the most radical decision two months before WWDC. Sending almost all Siri engineers to early summer camp. Issues. Apple has two approaches with AI. On the one hand, a more transparent one for the user that interconnects applications of your systems or that allows us to have advanced information about photos from our gallery. On the other hand, the avalanche of promises they made two years ago about Apple Intelligence. For a start, they were already late to the advertise your system a year and a half after the arrival of ChatGPT. To continue, there were functions that did not reach the devices, others that were delayed and even had to delete promotional videos that showed something totally false. This translated into an Apple that allied itself with OpenAI to integrate ChatGPT into Siri and, in January of this year, they teamed up with Google to put a huge band-aid: Apple’s next basic models will basically be Gemini. The user will not notice it – it would be a blow to the pride of those from Cupertino – but Google accounts will. The camp. If two years ago they were late, now they are running out of reaction time. This year we are seeing AI advancing day after day with both American and European and, above all, Chinese models. Apple must get in tune and, as they point out in The Informationhave made the decision to send 200 of Siri and Apple Intelligence engineers to a several-week “camp” focused on programming tools for AI. It is something that reflects the uncomfortable reality that Apple is experiencing right now. On devices they are doing well (even with a MacBook), are establishing themselves as one of the technological pillars of the United States and They have returned to work in Chinabut in the most important race in recent years, they are still behind. Therefore, it is urgent that the Siri team, which is earning such a bad reputation, gets its act together ahead of what could be one of Apple’s most momentous launches in years. And it’s not just sending developers to camp: it’s reformulating the company. The departure of John Giannandrea – one of the leaders of Apple’s AI strategy team – left a gap that has been filled by Craig Federighi, the company’s director of software engineering. Mike Rockwell, team leader of the VisionPronow leads the new Siri team. They are two Apple heavyweights who are very much on top of the AI ​​team, which makes clear the importance that Apple is giving to this issue. 60 stay at home. Obviously, the Apple Intelligence ‘laboratories’ are not going to be deserted these weeks. As The Information points out, about 60 members of the Siri development team will remain in their positions to continue shaping the new assistant and another 60 will be in charge of evaluating performance, ensuring that it meets the standards that Apple wants to implement. Because we are no longer talking only about the quality or functionality of the assistant and Apple Intelligence, but about the ambitious privacy goal. At the presentation of the softwareApple commented that it had built a cloud infrastructure specifically for AI with end-to-end encrypted data sending and that, when that was not possible, the data would be encrypted to obscure the user’s identity. According to the company, none of them would be visible even to its own workers. The new Siri, now it is. It is evident that Apple seeks to close the gap between its assistant and what the competition has – Google integrated Gemini into Assistant months ago – but they must also close that space between their reality and the ambition they showed when presenting Apple Intelligence. Either way, this year is expected to be the year of the new Siri. According to rumors, we will see during the first half of this yearbut we have been there for four and a half months and there is no trace. Now, everything indicates that Siri will be the star of Apple’s keynote at WWDC, the great software – and hardware, sometimes – event that will be held from June 8 to 12. Meanwhile, the world of AI continues to spin, and the most curious thing about all of this is what we mentioned at the beginning: Apple has no say. We’ll see if that new Siri manages to get them into the conversation. In Xataka | Customers demand that a human solve their problem. The surprising thing is that if humans serve them they think they are an AI

Jensen Huang believes he has found the perfect new bonus for software engineers. Not Stocks: AI Tokens

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The CEO of Nvidia has been converting the AI tokens at the center of all their public conversations. Jensen Huang’s latest idea links these tokens to the efficiency of engineers and how the best engineers in the world are recruited: in addition to a generous salary, offer them an amount equivalent to half their annual salary in AI tokens as part of the hiring package.​ Huang verbalized his proposal during the inaugural speech of the GTC 2026 conferenceNVIDIA’s largest annual event for developers. In a later interview, the Nvidia CEO detailed that engineers would earn “a few hundred thousand dollars a year as a base salary,” and the intention would be to give them “probably half of that, also, in tokens, so they can multiply your productivity times ten”.​ What Huang proposes already has a name: Tokenmaxxing. In one podcast appearance ‘All-InHuang said he would be on “high alert” if an engineer earning $500,000 didn’t spend at least $250,000 a year on tokens. “If that person said (that he has used tokens worth) $5,000, I would go completely crazy,” Huang stated. When asked if NVIDIA planned to spend $2 billion on tokens for its engineering team, as proposed, Huang responded: “We’re trying.”​ As and how they counted in The New York Timesthat has generated a phenomenon called “Tokenmaxxing“, with which engineers brag about the number of tokens they consume to try to improve the perception of their productivity: the more tokens you consume, the more productive you are. Tokens as bonuses are a trend in Silicon Valley. The CEO of NVIDIA is not the only one who thinks this way, and the use of tokens as an extra work benefit it’s soaking among investors in the sector. Tomasz Tunguz of Theory Ventures stated to Business Insider that “companies are incorporating AI inference as a fourth component of engineer compensation: salary, bonus, stock and tokens.” The interest of whoever sells the chips. The NVIDIA CEO encouraging everyone to spend more on tokens is not disinterested advice. Gergely Orosz, analyst at software engineeringhe pointed it out bluntly in a publication from AND he added an analogy that sums it up accurately: “It’s almost as if the CEO of Apple said, ‘If someone who makes $500,000 a year doesn’t spend at least $50,000 a year on in-app purchases on iOS, I’d be deeply alarmed.’ And yes, you would be, because that would reduce the revenue you generate.” Huang is the head of the company that manufactures the chips for AI on which most of the world’s artificial intelligence runs. Huang himself made it clear to his investors: “Without computing, there is no way to generate tokens. Without tokens, there is no way to grow revenue,” he declared, describing his data centers as “token factories” whose demand will only grow as AI agents proliferate.​ Do not confuse value with price. However, Huang has incurred a bias when arguing his idea: confusing value with price. Orosz formulated it clearly in a message in X : “The advice that engineers should use tools that make them more productive IS correct… except that the cost of tools should NOT be what we focus on. Some of the most useful tools are very cheap. Of course, vendors will focus on selling the most expensive and most profitable tools.” Productivity is not measured in tokens spent, but in results achieved. The right question for companies should not be whether their employees use more AI, but whether increased use of AI is rewarded. with greater productivity. In Xataka | Customers demand that a human solve their problem. The surprising thing is that if humans serve them they think they are an AI Image | NVIDIA, Unsplash (Arif Riyanto)

If Spain wants to imitate China and be a “country of engineers”, this map reveals the extent to which it has a problem

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An essential requirement for an energy and digital transition to occur in Spain is that there are enough engineers to cover demand. While it is true that there are more and more degrees that have the last name of engineering, the reality is that there are fewer and fewer professionals with the legal capacity to execute the transformation of the state, such as collects the Third Report from the Institute of Graduates in Engineering and Technical Engineers of Spain. In addition, the offer is being concentrated in specific communities. And that is a problem. Why is it important. Enabling engineering is that which grants legal powers for infrastructure and safety, for example what is behind ensuring that a bridge does not fall. With classic branches such as Civil, Mining or Naval Engineering decimated, Spain would lose autonomy and competitiveness by having to resort to imports to sign its essential projects. Jose Antonio Galdón, president of INGITE, deepen on the consequences of this fact: “On the students, who access Degrees with an Engineering denomination without a clear professional exit, and on society, which needs engineers with powers and responsibility to guarantee the safety, quality and sustainability of infrastructures and services.” On the other hand, the lack of complete supply in certain communities forces talent to emigrate, emptying technical capacity to regions that need engineering professionals to develop and establish their industry. Engineers are going to be needed. Two decades ago, those studying engineering represented 24% of the total number of university students and today that weight has fallen to 17%. as detailed by the COIGT. The engineering They are the ones that have lost the most students and also this one concentrates around computer engineering and emerging technological branches. Although the global female quota in engineering is 23%, it is precisely in these branches where it is most concentrated. On the other hand, Engineering such as Mining and Energy, Topography, Civil or Naval continue to decline and in some Autonomous Communities they already have less than 10 graduates. Although there are thousands of graduates each year, it is estimated that in Spain will have a deficit of 200,000 engineers in the next decade to meet demand. More engineering but less enabling. The IGNITE report confirms a phenomenon that has been registering for a long time in previous analyzes: Non-qualifying degrees, that is, those that do not allow the exercise of the regulated profession, have increased massively and now reach 53% of the total. On the other side of the scale, those enabling them are stagnating and even decreasing in some autonomous communities. The decline has been especially serious in places such as Asturias (-28.56%), Castilla y León (-28.79%) or Extremadura (-34.02%). The report makes a special mention: La Rioja. The small upstate community takes the cake with explosive 190% growth in engineering. But in small print: the fault lies with the non-qualifying degrees, which have grown by 431%, going from 433 to 2,289 enrolled. At the opposite extreme is Extremadura, which has the greatest drop in students, with 20.25% less. Engineering students from CCAA in Spain. INGITE Spain at two speeds. According to the reportthe Autonomous Communities that concentrate the largest number of engineering students and graduates are in Andalusia, Catalonia, the Valencian Community and the Community of Madrid. In addition to obviously because its population is larger, also because only Andalusia, Madrid and Catalonia have all the branches of engineering, revealing a territorial inequality in access to studies. The gap between public and private. The phenomenon of non-qualifying degrees is especially important in private universities, a type of center that grows out of control in the statealthough unevenly. Thus, while in the Balearic Islands, Castilla-La Mancha and Extremadura there is no this type of center and Galicia opened the first in 2022-2023, in Madrid there are 13 according to data from the Community itself. Since the 2015 – 2016 academic year, the autonomous communities where the number of degrees in private entities has grown the most has been Andalusia (from two to nine), Aragón (from three to nine) and La Rioja (from two to seven). In Xataka | If the question is which countries have the most workers with higher education, the answer is not Spain In Xataka | The university degree with the most job opportunities in 2025 looks into a great abyss: that of a future conditioned by AI Cover | INGITE

On the surface, the AI ​​talent war is about engineers and developers. It’s actually about plumbers and electricians.

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In recent months we have seen how some of the big big tech companies are opening their portfolio to hire the best AI talents: among the most voracious is goalbut the arrival of Jony Ive to OpenAI It was a flash signing. They may not have the resume of the former design director or make as many headlines, but the AI ​​talent war is also being played in another league: that of blue-collar technicians, such as the CEO of NVIDIA already predicted months ago and more recently, at the World Economic Forum from Davos. (Another) bottleneck for AI. Because for ChatGPT to have a new model or Nano Banana to level up, data centers are needed. And at the same time, huge quantities of electricity supplied by energy plants. We have already seen that data centers are proliferating like mushrooms (or at least, their planning, materializing them is another more arduous and slow story which leads some companies to consider ride them in space). So there are big tech that are being becoming energetic. But to assemble and maintain everything, you need electricians, plumbers or air conditioning technicians. And there are precisely not a few: the union that represents electricians in the United States and Canada mentions in a blog post of specific data center projects that can quadruple the current number of its members. Blue collar technicians wanted. The problem is that they are scarce: according to the United States Bureau of Labor Statisticsbetween now and 2034 there will be an average shortage of 81,000 electricians per year. Furthermore, demand in the next decade will increase by 9%, well above average. According to this McKinsey studyBy 2030, the United States will require 130,000 more electricians and 240,000 construction workers. The absence of professionals such as bricklayers, welders or plumbers also occurs in Europe, as collect the latest report of the European Employment Service. In Spain at the moment takes its toll on housing construction. There is no one to inherit the workshop anymore. Wired picks statements by the economist responsible for the American Builders Association, Anirban Basu, who tells how in the past workers passed on their skills to their offspring, but now they are encouraged to pursue university studies. The problem is that baby boomers are retiring, leaving a void that no one is filling. Dan Quinonez, its counterpart in the plumbing sector, comes to say the same: They are doing everything possible, but it is a structural problem that has no immediate solution. Data centers are not places for newbies. On the other hand, data centers are not just any job and it is not only because of the technical requirements, but because the deadlines are tight, leaving little room for delays or errors. This is crucial as it is normal for apprentices to be trained on the job. Incorporating workers quickly and safely is a challenge, as David Long tells of the National Association of Electrical Contractors. What Big Tech are doing. This reality does not go unnoticed by big technology companies and Google has already gone ahead: last spring advertisement that would make a financial injection to the Electrical Training Alliance, an organization that trains electricians with the goal of improving the skills of 100,000 active electricians and training 30,000 before 2030. The point is that AI also competes with other sectors: housing, hospitals, industries… the competition is fierce. But the companies behind it have an ace up their sleeve: those demands and tight deadlines usually translate into higher salaries and more overtime. As Charles White tells of the Association of Plumbing Contractors, this causes union workers to change companies in search of better conditions. Without going any further, Jensen Huang prediction offers with six-figure salaries. How long will the boom last? The installation of a data center is a finite project in time that, once completed, is limited to maintaining a small permanent maintenance team. Likewise, and although we are in a phase of AI expansion with enormous potential, sooner or later it will lose steam. At that time, we will see what will happen: of course, taking into account the needs in other sectors and the hole that the retiring generations are leaving, it seems that it will not cost them much to find another job. In Xataka | Spain is becoming a true Mecca for data centers. Uruguay has some lessons in this regard In Xataka | 30,000 jobs and many doubts. What we know (and what we don’t) about the Valencian “data valley” Cover | Sammyayot254, Jimmy Nilsson Masth and Xpda chaddavis.photography

China already has an army of 5.8 million engineers. His new plan involves accelerating doctorates

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China has a plan to win the technology race, one that began more than 40 years ago when decided to invest in training millions of engineers. We have seen it in the signings of the Meta superintelligence teamwhere the vast majority are Chinese. Chinese universities have a new plan to further accelerate the attainment of doctorates, one that puts aside theory to focus on practice. What is happening. They tell it in South China Morning Post. China is implementing a new policy that affects STEM students pursuing doctorates. The title PhD or ‘Doctor of Philosophy’ is the highest academic rank that can be obtained and until now required the development of a thesis. With this change, led by Harbin University of Technology, engineers can earn the PhD degree with the development of real products and systems. First case. The first student to achieve the PhD based on practical results was Wei Lianfeng last September. He graduated in 2008 and joined the China Nuclear Institute, where he worked for more than a decade until he decided to return to university to pursue his PhD, which he earned for his results in developing a vacuum laser welding system. To evaluate their work, the court that attended the oral defense included industry experts. Why is it important. The training of technical talent has been a priority for China for decades and more recently they have redoubled their efforts. In 2022, the government launched a program to promote STEM education especially in strategic areas such as semiconductors and quantum computing. Among the key points of the plan was close cooperation between companies and universities for joint training. This measure is the culmination of this strategy and the recognition that theoretical knowledge is not enough to compete in the technological race, especially with US blockades of key technologies. This allows China to solve the bottleneck in graduating higher-ranking engineers; It is not only about training more engineers, but about training them as soon as possible and with solutions that can be applied to the real world, instead of theses that are hundreds of pages long. STEM Power. The push to train engineers and scientists is part of a long-term government plan that began in the post-Mao era. And the plan is going from strength to strength. If we focus only on doctorates, according to data from 2023, China awarded 51,000 doctorates (PhD) in STEM careers, while the US was at 34,000. The projection at that time was that by 2025 the figure would rise to 77,000. In terms of total figures, In 2020, China was already the country that produced the most STEM graduates throughout the world with an abysmal difference: 3.57 million compared to the 2.55 million that India produced or the 822,000 in the United States. At the moment China already has 5.8 million graduates and it is estimated that more than 40% of all graduates choose a STEM career. Image | Joshua Hoehne in Unsplash In Xataka | Silicon Valley has a problem: its engineers are beginning to look to the other side of the Pacific. Specifically towards China

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