companies

An existential threat looms over several US chips companies. And China is just one of its problems

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Several US companies involved directly in the integrated circuit industry are suffering. Some of them, in fact, They are flirting with bankruptcy. In this context it is inevitable not to think of Intel and The difficult stage that crosses Currently, but from the company Led by Lip-Bu Tan We have spoken a lot in recent months. The companies in which we are going to investigate in this article are smaller, but, even so, they play a very important role in the US chips industry. The worst is happening is, without a doubt, Wolfspeed. And this company of Durham (North Carolina) It has officially declared in bankruptcy. Its specialty is the development and manufacture of silicon carbide (sic) and gallium nitride (GAN) semiconductors for high -power electronics applications, which positions them as extraordinarily attractive integrated circuits for the electric car industries, renewable energy, data centers, fast -charged infrastructure and aerospace and military industries. Robert Feurle, the general director of Wolfspeed, has declared That “after evaluating the options available to strengthen our balance and adjust our capital structure we have decided to take this strategic step (declare in bankruptcy and look for new financing routes) because we believe that it will place Wolfspeed in the best possible position for the future.” An interesting note before moving forward: Spain has launched The Godic project with the purpose of contributing to the independence of Europe of silicon carbide semiconductors from China and the US. China is not the only cause of the problems of American companies Wolfspeed is not at all the only company in the US chips industry that is in difficulties from a financial point of view. The American subsidiary of the Israeli company Tower Semiconductor, Globalfoundries, on semiconductor, Skywater Technology or Ayar Labs are some of the companies that are also facing economic difficulties. The competition from China is subjecting them to a pressure that does not cease to increase, but the competitiveness of Chinese companies is not the only factor that is putting in trouble some US chips companies. The competitiveness of Chinese companies is not the only factor that is putting in trouble some US chips companies Tariffs linked to Imports from China which has deployed US administration seeks to protect the business of US companies within your market. However, most of the companies that I have mentioned in the previous paragraph also sells their semiconductors outside the US. And the competitiveness of Chinese companies in other markets is very high due mainly to two crucial factors: their prices are moderate thanks to contained production costs and the quality of their products is comparable to that of their western and Asian competitors. In any case, the economic problems faced by some designers and manufacturers of American chips do not have their origin solely in China’s competition. Wolfspeed is at a very delicate moment because, beyond the pressure exerted on it, its Chinese competitors, The global demand of the high -power semiconductors it produces has fallen. In addition, during the last five years He has borrowed To be able to build new integrated circuit factories, and currently you cannot assume this economic burden. The panorama of other US companies that are dedicated to chips is not very different to the context with which Wolfspeed is dealingso it is possible that in the short or medium term other companies also enter in bankruptcy. Image | Xataka More information | GLOBALDATA In Xataka | The US is willing to do anything for advanced chips not to reach China. And Malaysia is an obstacle

Among generalist or specialist, companies already have their response

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He initial astonishment against chatgpt It was not only because of that magical feeling of seeing how character responded to character, pattern inherent to the LLMs that humanized them to some extent. The astonishment was because they knew everything. They explained quantum theory and wrote poetry, summarized novels and armed a business plan in seconds. They seemed capable of anything, such as the classic first row student who dazzled because he analyzed Blasco Ibáñez with the same precision with which he resolved a differential equation. The question, sooner or later, always comes: What is the use of? In it Deloitte technological trends report for 2025 A track appears: many companies that had opted for these generalist models – large, complex, difficult to refine – are beginning to look at smaller and specific options. Models trained with less data, but much more relevant. Specialists, no todologists. It is no accident: that initial enthusiasm with the Llm It is running with a reality: knowing everything is not always useful. And the world of business does not value wisdom, the margin is valued. As sometimes it happens, this is a more philosophical change. And he looks a lot like an old debate in companies: that of human specialists vs. generalists. The expert who has dedicated his life to a single field that dominates as anyone … … Faced with the broad, curious, adaptable profile, with tangential knowledge. David Epstein explored it well in a book that I loved it‘Amplitude‘. That title made a somewhat uncomfortable thesis fashionable: in a changing world, specialization can become a cage. But the AI, perhaps in a counterfit, is returning luster to the specialist profile. Because? Because in practice, Generalist models are vague. They try everything but refine a little. An AI that advises doctors, lawyers or engineers cannot be improvised. It needs rigor. Context. Know the terrain. And that does not give it, the approach gives. There is a slightly thinner reading here. The turn to specialized models allows greater efficiency, but also more control. The big models are in the hands of a few: OpenAi, Google, Anthropic, goal … are closed, opaque, often expensive. The smallest models can be open, trained at home, adaptable to concrete niches. They look more like tools than oracles. It also has labor implications: If a generalist can do “everything”, it is a diffuse threat. If there are many specific ones, they may not come so to replace people, but to expand them. A doctor with an AI adjusted to his specialty, an architect with an assistant who knows how to read plans, an –ejem– editor with a co -pilot specialized in his sector. It is not the same to compete with a universal AI as collaborating with a refined tool. And this connects with something more important: A new knowledge economy. For years, we were told that “knowing everything.” Be versatile, navigate between disciplines. Now, companies reward the located, technical, deep knowledge. We already know that IA transforms workbut perhaps also our ideas about knowledge. What is worth, what matters. And there comes the question. What kind of intelligence do we want to enhance? One who knows a bit of everything and monopolis attention? Or many humble intelligences, distributed, each focused on solving their own problems? Choosing between generalists or specialists is how we want to live with AI. And what knowledge model we prefer for the coming world. Outstanding image | Elen Sher and Patrick in Unspash In Xataka | Deep Research is not just a new AI function. It is the beginning of the end of intellectual work as we know it

Replacing workers with AI sounded spectacular. There are already companies backward

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That an AI takes away our work is A fear That is being realized. More and more companies that bet on replacing human employees with automated processes with AI. At the same time, the potential that the AI agents It seems almost unlimited. The reality is much more complex and there are already some companies that have had to give reverse in their plans. Yes, but to supervise her humans. There are many companies that have begun to draw a plan to replace their employees with AI, especially in the sector of the customer service. However, according to a survey of Gartner, 50% of companies are abandoning this path due to the challenges that the transition to a service managed only by AI is assuming. 95% of the executives surveyed claimed that they would bet on a hybrid approach combining AI and Human agents. In the words of Kathy Ross, director of the Gartner customer service: “IA offers significant potential to transform customer service, but it is not the panacea. The human touch remains irreplaceable in many interactions.” The Klarna case. Perhaps the most popular case of a company that has regretted betting on the AI ​​is that of Klarna. In February 2024, his CEO presumed that an AI was doing the work of the 700 employees who had just fired and also assured that he was receiving the same score from the clients. A year later, the quality of service offered by AI received many criticisms and had to back to hire human labor Ensure that customers can always talk to a human agent. Not so quickly. Although currently the agents of AI are not so reliable As Altman promisedit does not guarantee that they will not improve in the future. In addition, there are cases of other companies to replace humans for AI has gone well. Like the CEO of this Indian startup that He fired 90% of the template And a year later he states that it has been A success. And it is not the only one. Duolingo, for example, fired 10% of its translators to replace them with an AI. Other large companies such as UPS and Cisco They have followed similar paths. The case of IBM It is particular, since, although it has opted for AI, it has also had to hire more workers precisely to manage that AI. IA agents. With the generative AI in decelerationsince the end of last year there is another concept that has gained relevance, that of the AI agents. While chatbots can only attend one request at the same time, an AI agent is able to perform more complex tasks. For example, you could organize the holidays only to mention the dates and destiny. The promise of autonomy, the ability to handle several tasks at the same time and make decisions make the AI ​​agents A threat to many jobs. Unreliable. We can all make mistakes and in this it seems that AI agents are very human. The problem is that if an AF agent makes an error, he continues to repeat in successive tasks, making the error increasing And the final result is also wrong. We have also seen other uses of AI tools at work that have not fully went well, such as disastrous work interviews conducted with AI. A revealing experiment. A experiment carried out by researchers from the Carnegie Mellon University He suggested that they are still very green. They created a fictitious software company whose employees were AI agents. They used Google, OpenAi, Anthropic and Meta models, to which they assigned roles such as finance, administration or software engineering. The result was disastrous: they only managed to complete 24% of the tasks assigned to them. AI and labor market. The impact of AI on the labor market is undeniable. According to the last World Economic Forum Reportit is expected that by 2030 92 million jobs will be destroyed due to AI automation. But there is another face of the currency. At the same time, they will be created 170 million new positions And the AI ​​will be one of the job creation engines, something we have already seen with Salesforce’s case. Cover image | Pixabay In Xataka | The workers have stopped fear of AI as a machine to destroy jobs: software engineers do not think the same

Every year millions of packages are lost during shipments. So there are companies that are selling them to weight

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Only in the United States They lose or steal 1.7 million packages every day. In Spain the latest data from the TDI logistics group They revealed that more than two shipments were lost per minute. The curious thing is where at least part of them end: they are shown to weight. Millions of lost packages. According to They indicate to EFE From the employer of the logistics sector one, in Spain more than 3.3 million packages are sent per day, and the cases of loss involve a tiny fraction of 0.001% (about 3,300 per day). A simple error on the label or lack of centralized information can cause these problems, and that is where some companies recover them to resell them. Reversing weight. Services such as Crazy Day Factory, My Mystery Package, Merkandi, LotesDevolutions, or King Colis are dedicated exactly to the same thing: acquiring those lost packages to often resell them as part of surprise boxes that are sold to weight. As they point out in the confidentialin Kink Colis for example they establish a price of 1.99 euros per 100 grams in standard packages and 2.79 euros in the premium type. A lot of noise and few chollos? In King Colis FAQ, a French startup, they explain that buying this type of surprise packages can be very profitable, because one “can contradate state -of -the -art technological devices to clothing or accessories of recognized brands.” However, they also warn: “Not all lost packages necessarily contain treasures. There is a part of chance!” You don’t know what you buy. One acquires these packages to weight, but does not really know what he is buying. As they revealed in the nationalin stores such as my mystery package open ephemeral stores throughout the year in different municipalities to give out these packages, but there is a key requirement: the package cannot be opened until after buying it. And that implies risks. These lost packages are not checked and therefore can be damaged, be defective or have a much lower price than the buyer ends up. In Lotes Devolutions they explain that those products that put on sale – which are returns, not lost shipments – do not go through a previous check, which can end up causing a disappointing surprise effect. Packages are sold repaired without visible brands to eliminate commercial references, turning the purchase into a riddle … or a bet. The psychology of surprise. The surprise boxes such as those offered by all these businesses take advantage of known phenomena of human psychology. Several researchers published in June 2024 A study in which they revealed how the stimulus-organism-response (Sor) causes that impulsive purchase out of curiosity without intervening conscious thinking. We think quickly instead of thinking fast, as the Nobel Prize Daniel Kahneman in his famous’ stood out in depth.Think quickly, think slowly‘. Previous experience. In Xataka we were able to meet this type of business last year, when we went to an old warehouse on the outskirts of Madrid to try to locate some cholt between the chaos of Amazon returned products that a company put on sale. There was no surprise effect here and the proposal is something different, but the conclusion was already clear: we had no luck and after hours of search we went out empty. Finding chollos, whether by surprise or not, is not easy. Image | Chuttersnap In Xataka | The end of free online returns: Zara, Pull and Bear and more stores begin to collect them

Whole China is of exams. So AI companies are laying their chatbots so that students do not cheat

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In Spain the students recently passed By the Pau test (Before EBAU, EVAU or Selectivity), and now something similar is happening in China, where Chinese students face Gaokao (高考), the National Access to University Exam. And they do it with an almost obligatory novelty. Nothing to cheat with chatbots from AI. The most popular chatbots in China Like Qwenfrom Alibaba, have temporarily deactivated functions such as image recognition. They have done it precisely to prevent such characteristic from being used as a modern “chop” To help them during these tests. Impartiality in the tests. The same has happened with Yuanbao (Tencent) and Kimi (MoNshot), two other popular chatbots in China, which have also deactivated that image recognition characteristic. When trying to use this function, they indicate In Bloombergthe text “appears” to guarantee the impartiality of the university access tests, this function cannot be used during the test period. “ An exam in which the future is played. The Gaokao was held for the first time in 1952 as part of the reform of the then newly created People’s Republic of China. The access processes to universities changed during Mao Zedong’s mandate, but in 1977 Deng Xiaoping recovered them and have continued to be used until today. There are 16 provinces with personalized exams, but in all cases the conclusion is the same: these tests determine the immediate future of students In the academic aspect. Designed and printed in jail. Gaoako access tests are so important that they are designed under strict security by a small team of teachers. These professionals are sent to isolated site of Beijing as military facilities or prisonswhere they make the questions. They cannot leave those locations until the tests are performed, but it is also that most exams are printed within prisons and each “printing” is protected 24 hours a day by cameras and guards. Even its transport to the centers is done with security measures that one would expect in money transports from banking entities, for example. Everything to prevent the questions from leaking. Scratch note. Chatbots are presented as a spectacular help for these students, and students – and their parents – know it. The note of these exams determines whether the student may or may not access the best careers and university institutions, and that also depends on their future positions, salaries and even their social mobility. Competitiveness is also huge: More than 13 million students They are presented to these tests this year. To achieve better notes, all kinds of solutions are used, from particular teachers to these attempts to cheat. Of photo recognition, nothing. The tests have taken place from 7 to today, June 10. The Alibaba chatbots (Qwen) and bytedance (Doubao) offered the Image recognition for AI until last Monday. However, according to Bloomberg if a user asked for the solutions to a problem in a paper that was taken a photo, Qwen replied that the service was temporarily disabled. In Doubao the message indicated is that this request “did not meet the rules.” AI is fine to learn, but not for exams. In Beijing they launched recently A plan to integrate the teaching of AI at school. Although this type of discipline in classrooms is being tried, one thing is that they learn to use it and another very different that students take it to cheat in these tests. In fact a new set of standards Published by the Ministry of Education of China last month established that students should not use the content generated by the response in their duties or in the aforementioned exams. The objective: that they do not depend too much on artificial intelligence. Image | 绵 绵 In Xataka | The 100 best universities in the world excluding those of the US, exposed this graphic revealing

the 15,000 ninja companies that dominate key niches without anyone knowing them

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China not only manufactures giants such as Alibaba, Tencent or Tiktok. He has built meticulously An army of 14,600 “small giants” that dominate fundamental industrial sectors, but without making noise. Why is it important. While in the West we follow the track of BydXiaomi, Bytedance or Huaweithese specialized SMEs are those that control the pieces of the industrial puzzle. Sensors, aerospace components, specialized semiconductors: the niches where technological supremacy is really won or lost. The context. He “Little Giants” program He was born in 2015 as part of “Made in China 2025“Its objective: push highly specialized medium -sized companies to develop competitive advantages in specific sectors. A surgical model against the model of large state companies. There are 15,000 “small giants” with official certification. Almost 90% are in the manufacturing sector. More than 80% focus on emerging strategic industries such as integrated, robotic or aerospace circuits. And almost 5,000 work in AI AND CLEAN ENERGIES. That is happening. Each “little giant” receives state support to dominate a specific niche. Submarine cables, superconductor materials, quantum sensors, satellite systems … technologies that seem lower but vital for global supply chains. And for Chinese military development. Some examples: Leaderdrive: Specialized in precision harmonic reducing. Endovtec: Develop advanced endovascular devices. Phabuilder: Biotechnology to produce industrial materials. Acoinfo: Develop real -time industrial operating systems. Guizhou Anda: Battery materials, supplies Catl and Byd. WELION: solid state batteries of high energy density. JIASHIDA Robot: Domestic cleaning robots. It is no accident that The United States has already included many of these companies in their blacklist. They are the real threat: not the brands that anyone knows, but those that manufacture the components that make the world work. This “unique champions” strategy makes medium -sized companies practically monopolies into ultra -specialized sectors. Result: If you need a certain type of semiconductor or components, you have no alternative. And that company is subsidized, protected and backed by the Communist Party. Outstanding image | Acoinfo In Xataka | China has an ambitious plan to overcome the West in Technology. And he has already chosen his 18 companies to get it

We have been concerned about what companies with our data do. Brazil will allow money with them to win

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Brazil has just crossed a line that promises to change forever the relationship between its citizens and their personal digital information: digital wallets to moneture their data. Why is it important. The South American country has announced The first national program in the world which allows its citizens to own, manage and monetize their fingerprint. Brazil has decided to convert this information into economic assets for those who generate them instead of simply seeing how their citizens give data to technological ones. The initiative, administered by Dataprev – state technology company – in alliance with the Californian Drumwave, will create personal data savings accounts. Users may deposit the information generated by their daily activities and receive economic offers from companies interested in buying it. In detail. The system works like cookies of third partiesbut with a turn: instead of simply accept or reject, users can choose to make money. When they request a loan, for example, the contract data will be stored in their digital portfolio, and companies will be able to bid for them. “People don’t get anything from the data they share,” explains Brittany Kaiser, co -founder of Own Your Data Foundation and Drumwave advisor, according to the official statement. “Brazil has decided that its citizens must have property rights over their data.” The pilot starts with a small group of Brazilians who will use loan portfolios. After accepting an offer from a company, the payment is deposited in the portfolio and can be transferred immediately to a bank account. The context. This movement places Brazil ahead of the United States, where a similar initiative of the governor of California, Gavin Newsom, It was raised in 2019 But he never took off. If it is completely implemented, it will be the first public-private association that allows citizens-not to companies-to obtain a personal data market share. Yes, but. Some specialists in Brazilian data protection have expressed serious doubts. In a country where three out of ten people are functional illiteratesaccording to official data, there is a risk that vulnerable populations sell their data without understanding the consequences. “We will be asking for half of the country that you don’t know how Rest of World. “People in vulnerable situations will say yes, and that could be used against them.” The background. The Brazilian Congress works on a bill that would classify data as personal property, exceeding the current legislation that considers them an inalienable right. The new regulations would give people complete rights about their personal information, especially that generated “through the use and access of online platforms, applications, Marketplaceswebsites and connected devices “. And now what. If this is consolidated, Brazil will sit a precedent that other countries can follow. The proposal promises “a correction in the historical imbalance of the digital economy,” according to Rodrigo Assumpção, president of Datapre. The idea: transform personal data into assets for those who provide them. For companies such as Google, Meta or Amazon, accustomed to obtaining valuable data “simply” offering their platforms also for free, this proposal is an earthquake. For users it could be the first step towards a world where each clickeach search and each digital movement has a tangible market value. Outstanding image | Samuel Costa Melo and Campaign Creators in Unspash In Xataka | The AEPD already knows where the data of millions of freelancers who were on sale on the Internet have come from: the Chamber of Commerce

Four AI companies control how Half Mundo reasons. It is the greatest concentration of intellectual power in history

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While the public focus is concentrated in the possibility that the AI ​​will take our job ahead (Business Insider 21% of its template has just announced citing it as a cause, the CEO of Axios has published A text by the chungosAnthropic’s CEO has shouted “that comes the wolf” to justify that only they can save us), In the background something less visible is happening: We are giving our intellectual autonomy in favor of efficiency and comfort. It is not just that four companies –Openai, Google, Anthropic, Meta – are building the infrastructure with which millions of people resolve doubts and make decisions. They not only manage data: they also protect the way we link ideas. The Great Chinese of AI They are out of this equation for a simple reason: their still domestic approach without the international vocation of the Americans. Google (the search engine) was and is influential, but with it we have had to spin our own speech: Cotejar Fuentes, Weighing biases, assume contradictions. The generative AI instead serves a round response that It sounds coherent even when hallucin And that’s why he demands less surveillance. The result is that we are replacing the “internal process” with an external verdict covered with a technological aura that deter the replica. Whatever you say, Chatty. Delegate is too tempting. Save time and headaches. The problem is that we do not subcontract logistics, but criteria. We ask Chatgpt A professional strategy. TO Claude A curriculum. TO Gemini today’s interpretations. In doing so we accept without discussing the biases and empty of a trained model about texts that we will never see. It is an invisible assignment and, therefore, difficult to question. Never before so few hands had defined what questions can be asked and what answers sound reasonable. History has known infrastructure monopolies – electrity, internet, railways – but never one about reasoning patterns. Now another qualitatively appears: It operates on the symbolic plane, where narrative frames are defined through which we understand the world. Very subtle and very decisive. What previously implied a deliberation – read, contrast, imagine scenarios, weigh nuances – today becomes an instantaneous response, of definitive appearance. What to think about euthanasia? How to react to infidelity? What economic model is more fair? We no longer look for elements to think: we look for the correct answer The faster and more comfortable. And we accept as valid the one that sounds best, even if it ignores what does not fit in your narrative. Its effects will not be immediate, but predictable: a slow loss of variety in thought, of ideas out of the ordinary. Platforms have progressive consequences. Tiktok and Spotify, for example, They have made the songs last less and the chorus arrive before. What consequences will the LLMS within fifteen years? If we all consult models that converge towards average responses, intellectual eccentricity – culture rate for innovation – It will be increasingly weird. There is hardly a brake for AI, but perhaps at some point we have to decide how much reasoning we are willing to deliver before staying without it. Outstanding image | Xataka In Xataka | Deep Research is not just a new AI function. It is the beginning of the end of intellectual work as we know it

The great AI companies have declared a underground war to a pillar of education: human teachers

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We would all like to have a Keating Professor In our lives. One that made us get on the desks to see things from a different perspective and that he would teach us that the most important lesson he has for us is summarized in the words “Carpe Diem”. There are very few who approach that image, but all of them, bad or good, threatens them the same future as Other professions: Be replaced by an AI. Professor 24/7. The narrative of several AI companies is clear: the human teacher is a bottleneck. Each of them serves many students, their knowledge is limited and their finite availability. The AI, they assure those companies, proposes a remarkable alternative. Personalized professors 24/7 with infinite patience and access to all the knowledge of the world. There is a clear problem: that message devalues ​​the teacher’s function as a guide, mentor and catalyst for curiosity and reduces it to a mere transmitter of information. Continuous evaluations. Another of the pillars of the educational system – and one of the tasks that most consumes the teaching staff – is Student evaluation. The AI ​​promises to correct efficiently, massively and immediately, releasing the teacher for other tasks. But again in human evaluation there is much more than a mere correction of errors. The effort, the reasoning process, creativity, originality or even the personal context of the student are evaluated. Biases also pose a clear threat to these evaluations, in addition to promoting a model Based on the correct answer and not in the reflexive process. My school is OpenAi. So far schools, universities and other academic institutions are the guarantors of a theoretically coherent and quality curriculum. The approach of the companies of AI would be that of Become them In “Guardians of knowledge” deciding what is important to learn and how. The risk: lead to a fragmented education and dictated by the interests of the market, eroding the role of education as a pillar of society. Threat to humanities. The AI ​​also raises the irrelevance of memorization – it can already respond to all known knowledge – and bet on skills such as “Prompt Engineering“(know how to ask things to AI) or Technical subjects (Stem). That suggests a clear impact to matters of humanities and critical thinking that we do not apply directly. Fields such as philosophy, art or social skills, hardly quantifiable, would go to the background. The objective would not be as much to train and prepare workers for the technology industry. Goodbye to social investment. Companies that bet on that model have a clear objective: climb and be profitable. AI technology applied to education promises a lot of savings (less physical infrastructure, less teachers) and a highly scalable business. But also imposes a worrying revolution to one of the pillars of society. Bill Gates believes in the future of the teachers of AI. Among the experts who outline that idea is the figure of Bill Gates, co -founder of Microsoft. His commitment to the teachers of AI It was early: Chatgpt had been in the market for just five months when he said that “AIs will reach that capacity, to be as good tutors as any human being.” For him, this technology should also be a “leveling” for society. According to Gates “having access to a tutor is too expensive for most students, especially if that tutor adapts and remembers everything you have done and review your work.” Openai and Khan Academy have the same vision. A year ago the presentation of GPT-4O surprised among other things for that capacity offered by this AI model to talk directly to him. One of the OpenAI demos, carried out in collaboration with Khan Academyhe showed Sal Khan, his founder, contemplating how his son used the model to receive a geometry lesson. The interaction was impeccable and pointed to a future full of teachers of ia locked in our tablet, our mobile or our computer. Khan is of course interested, but it doesn’t hurt see your ted talk on “how AI could save (not destroy) education.” Schools converted into nurseries. Luis von ahn, Founder of Duolingothe poular application to learn languages, it also takes time turning towards the AI. A few days ago he participated in the podcast No priorsand there he commented how although there are very good teachers, “there are not many.” For him, education will change radically because “it is much more scalable to teach with which with teachers.” Even so pointed out That does not mean that teachers disappear: “You will continue to need people who take care of students”, but focused on a new role: “I don’t think schools disappear, because you need nurseries.” Image | Buena Vista Pictures In Xataka | Towards the end of duties: how chatgpt has been inserted in the center of the great debate on education

Japan’s commitment to lead the chips industry is held on these three companies

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For Japan, as for South Korea, Taiwan, China or the US, the semiconductor industry has a strategic character not only because of the deep beneficial impact it has on its economy, but also by the impulse that gives its technological capacity. This is the context in which the Japanese government announced in the middle of last November A public plan that will injected into companies that are dedicated to the design and manufacture of chips no less than 325,000 million dollars within ten years. In addition, it prepares additional 65,000 million that seek to support the activity of local companies. There is no doubt that it is a very strong and more ambitious bet even than those designed by the US, China or Europe. Only South Korea prepare an economic investment of a similar size. The first reactions of Japanese companies have not been waiting. “We are working with our clients to develop technologies that teach four generations in the future.” These words of Nobuto DoiVice President of Tokyo Electron, are a declaration of intentions. However, before moving forward in this article it is important that we briefly review where Japan comes from. At the end of the 80s this Asian country dominated the global industry of the integrated circuits with an indisputable forcefulness. Nec, Toshiba, Hitachi, Fujitsu, Mitsubishi, Matsushita and other Japanese companies They monopolized in 1988 Nothing less than 50% of the chips industry. However, today none of these companies is positioned among the leaders of a sector dominated with iron fist by Taiwanese, American, Chinese, South Korean and German companies. Tokyo Electron: Japanese Asml This company is one of The pillars of the Japanese industry of integrated circuits. It is dedicated to the design and manufacture of lithography and waking -up equipment, so its machines often live together in the TSMC, Intel, Samsung, Micron Technology or SK Hynix plants, among other companies, with the teams of the Dutch company ASML or the American Apply materials. Its importance for Japan is such that it is currently one of the Japanese companies that are being backed by subsidies approved by the Japanese government. The new Tokyo Electron plant in Oshu will be intended for the manufacture of advanced team deposition equipment and logistics In fact, it is building several buildings in the prefecture of Miyagi that will presumably be completed in 2025. The most ambitious project that will address in these facilities will consist of the design and manufacture of some some WAFSMA TEACHING BY PLASMA Very advanced. They are precisely the machines that Nobuto Doi speaks in the statement that I have included in the second paragraph of this article. These equipment are involved in the definition of the pattern that will later be transferred to the wafer. The Japanese company Hitachi also has plasma wafering engraving machines, but the singing voice in this particular market has tokyo electron. Apparently the engineers of this last company are working side by side with their clients to develop solutions that, according to doi, four generations ahead will be positioned. However, its plan goes beyond the facilities of the Prefecture of Miyagi. And it is that Tokyo Electron is also building a new plant in Oshu, in the prefecture of Iwate, which will be intended for the manufacture of advanced wafering deposition equipment and logistics. We can be sure: Tokyo Electron is the Japanese Asml. Without it, the ambitious plan pergeted by the Japanese government for its semiconductor industry would not be viable. Rapidus Corporation: The spearhead of Japan The company that is destined to compete from you to you with TSMC, Intel or Samsung in the chip production market is Rapidus corporation. In fact, it has been expressly created to replace Japan at the forefront of integrated circuits. This is a very young company. It was founded on August 10, 2022 by the Japanese government with an initial capital of 7,346 million yen (just under 46 million euros) contributed by, and here comes the interesting, Sony, Toyota, Nec, Softbank, Kioxia, Denso, Nippon Telegraph and Mufg Bank. The initial capital invested in the constitution of this company is not very bulky, but there is no doubt that the companies that participate in it have an indisputable relevance in the sectors of technology, automotive and telecommunications. Rapidus is currently putting a circuit manufacturing plant integrated in northern Japan, in the city of Chitose (Hokkaido), in which it plans to produce 2 Nm semiconductor. The first prototypes of these chips are already readybut large -scale manufacturing will not arrive at best until 2027. Rapidus is making a chip manufacturing plant in northern Japan in which it plans to produce 2 Nm semiconductors What is causing the new Rapidus factory to monopolize the looks of the semiconductor sector is that, according to Atsuyoshi Koike, which is the president of the company, it will be completely automated. Its purpose is to resort to robots and artificial intelligence (AI) to tune an automated production line that will be specialized in the manufacture of 2 nm chips for AI applications. Its plan consists, in short, to produce integrated circuits faster, with a lower and more quality cost. To manufacture these semiconductors, equipment of extreme ultraviolet lithography (UVE) produced by the Dutch company ASML, and practically all manufacturing processes are automatic. However, the tests of test and validation, interconnection and packaging of the chips are still largely carried out manually in most manufacturing plants. According to Rapidus, its automation technology of all these processes will allow you to reduce the delivery time of your chips by 66% compared to the times they usually offer TSMC and Samsung. JSR Corporation: The photor resistance monopoly is in his hands There is a Japanese company that is indisputably leader in its specialty. It is little known outside the scope of the semiconductors, and yet it is one of the bastions of Japan. Is called JSR Corporation and specialized in the production of photorers. The photolithography equipment designing and produces ASML … Read more

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