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17 years later, it has come out with 7,000 million dollars in the pocket

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For more than 17 years, the investment firm Berkshire Hathaway led by Warren Buffett and his partner Charlie Muger, maintained one of his most profitable bets in the automobile sector: Byd, the Chinese manufacturer of electric vehicles. According to He informed Reutersin recent months the veteran investor has been undone of their shares until they sell them all, such and as confirmed CNBC. The markets have reacted sinking the value of their shares by 3.4%. Warren Buffett always wins. In 2008, few investors were interested in the future of the electric car, Berkshire acquired 225 million shares of an unknown Chinese company called byd for about 230 million dollars. The equivalent of 10% of the company. Since then, the value of that investment has fired more than 4,500% until March 2024, confirming as one of the Many investment successes of the American billionaire. With this long -term operation, the veteran investor confirms its Good eye for profitability since the 230 million would have become about 7,000 million dollars, multiplying their money in just 17 years. The impact on the byd price. However, not everything is good news in Buffett’s withdrawal from Byd’s shareholders. The news caused An immediate reaction In the markets: the value of Byd’s shares fell 3.4% in the Hong Kong Stock Exchange, in what represents its largest setback in three weeks. At the stock level, the last months have been convulsive for the electric car manufacturer, which in July carried out a unfolding shares (Stock Split) After which his price fell 16%. To that scenario, the drop in the stock market that occurred after the news of the output of a “trust” investor such as Berkshire Hathaway, chaining up to 30% fall From its annual maximum registered in May. Tranquility is what is most sought. Berkshire Hathaway’s departure from Byd has been taking shape since 2022, when the electric car war began to give its first measures, but has stepped on the accelerator as the uncertainty that surrounds the electric vehicle market in China was growing. In the context of Overproduction of the factories Chinese, and the Freezo in demand of electric cars, a scenario opens where strong competition is deriving in A price war that threatens to erode the margins of the manufacturers. Several analysts suggest that this Perspective of instability It could have been a weight factor in Berkshire’s decision to completely liquidate his position in Byd. Byd reactions. On the other hand, from the Chinese manufacturer, the movement of the Buffett company has been responded with thanks to Berkshire Hathaway and its historical leaders. According The published by BloombergLi Yunfei, general director of brand and public relations at Byd, published a message on the Chinese social network Weibo: “We are grateful to Muger and Buffett for their recognition to Byd, and for their 17 years of investment, support and company. In investment in shares, buy and sell are normal practices,” he explained trying to calm the uncertainty of the shareholders for the departure of Buffet. This message reflects the symbolic importance that Buffett had as an early investor in ByD for almost two decades. In addition, Charlie Muger played a crucial role in the Initial decision to invest in bydwhen he recommended the operation with the president of Himalayas capital, li lu. In Xataka | In his effort for not leaving fortune, Warren Buffett made a unique decision: to deny a loan to his daughter Image | Flickr (Fortune Live Media), Byd

Tether is the great cover of the world of crypts. Aspires to value 500,000 million for doing something simplistic: save foreign money

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Tether Holdings SA is the company responsible for issuing and controlling the most important stablcoin in the world – also called “Tether” (USDT) -. And those responsible are in negotiations with investors for lift up to 20,000 million dollars. If that round becomes effective, Tether would become a company with an assessment of 500,000 million dollars, and the question is obvious: how can a company be worth so much that nobody has heard? What is Tether (USDT). Launched in 2014, Tether is a cryptocurrency With its own block chain. It is designed to facilitate the use of Fiat currencies (such as the dollar or the euro) digital. Tether is specifically A stablecoina cryptocurrency whose value is strongly linked to the US dollar, which makes its volatility virtually nil. One would think that it is much more interesting to operate with Bitcoins or Ethereum, but care: Tether is a giant for a much simpler reason than it seems. As big as Netflix. If this investment round is confirmed, Tether would be at the level of companies such as Netflix, the 18th company for market capitalization According to Companies Market Cap. Unlike other technological companies focused on future innovation, Tether is a company whose business model is strongly tied to current cash flow. Sources close to negotiations talk that this investment round could be “significantly lower”, so the estimated assessment could be much lower. Interest gains. This is Tether’s main source of income. For each USDT token, the company keeps an equivalent amount in reservations, and does so largely in assets that generate interest, such as US Treasury Bonds. Its current market value is 173,000 million dollars, and thanks to that you can invest those huge reserves and obtain mass profits. In fact Tether is currently one of the great debt holders of the United States government. Extraordinary benefit margin. The CEO of Tether, Paolo Ardoino, He has affirmed Recently the company has a 99%benefit margin. That means that their COESTE operations are incredibly low compared to their income. Tether Holdings Sa is an efficient money to make money. The reference stable. Its success is also based on having become the most popular stablcoin in the cryptodivsis market. Thus, while the current market assessment of Tether S of 173,000 million dollars, the following stablecoin in relevance is USDC, with an assessment of 74,000 million, less than half. But. Although the company has a privileged position and an apparently promising future, Tether He had problems in the past that also threaten their projection. Thus, in 2021 He had to pay A fine of 41 million dollars for a lawsuit for misrepresenting its reserves. The company has also been criticized for the opacity of its reserves: although it publishes quarterly reports, these are not audited by any of the Big Four (such as PWC or Deloitte), but by less recognized signatures. Regulation. The true Damocles sword for Tether is the regulatory tensions. That has left her out of the US market for years, but the company has moved a card hiring a former White House official and it seems that there is now a clear and favorable approach Bajo Trump. However, the US continues Approve laws that will force Tether to restructure its model to access that market. In Xataka | In 2011 a group of investors bought 80,000 bitcoins. They have been sold by 17,000,000% more expensive

Nvidia will invest 100,000 million dollars in OpenAI. Actually a single euro will not be spent

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Openai has signed a “strategic agreement” with Nvidia. According to this agreementNvidia “intends to invest up to 100,000 million dollars” in OpenAI gradually, but the truth is that this investment is misleading. Especially since Openai will spend those 100,000 million dollars to buy GPUS to Nvidia. Everything remains at home. What happened. These two companies have initiated the procedures to complete an agreement with a clear objective: create and display AI data centers With a joint gigantic computing capacity: 10 GW. The investment will be made gradually and will be completed “as each gigawatt” of computing capacity is installed in those Data centers. Nvidia will thus become a “computing partner and strategic connectivity” for the development plans of new data centers, says Openai. Millions of Gpus. According to Jensen Huang statementsCEO of Nvidia, that represents between four and five million gpus. Or what is the same: it is the number of units of their GPUS of ia that they expect to distribute this year, and “twice the ones we distributed last year.” The strategy “seller finances buyer”. This agreement is not a simple investment, but a strategic association in which the hardware provider invests a massive amount of money in its main client. In return that client undertakes create a mass infrastructure With supplier technology. It is nothing more than a closed cycle: Nvidia gives OpenAi money, and OpenAi uses it to buy Nvidia products. This sounds like a bubble. There is Several analysts that They speak How this remembers once again The bubble of the Puntocomwhere companies lent money to buy products from the other. That raises suspicions and questions about the long -term sustainability of these agreements. Companies becoming stronger among them. The circular agreement serves in fact to strengthen both companies and solidify their positions as dominant and indispensable actors in the AI ​​industry. In fact, this strategic alliance makes rivals like AMD or Intel very difficult. Nvidia is worth 170,000 million dollars more. The announcement caused immediate reactions in the NVIDIA assessment, whose shares increased almost 4%. The stock market capitalization of the company of Jensen Huan grew by 170,000 million dollars in that session and already touch the 4.5 billion dollars, and manages to distance itself even more from Microsoft, Apple or Google, which already exceed three billion. Long live Hype. Here once again there is a reinforcement of the speech of expectations and Hype. The confidence of these companies in the future of AI is patent, but they are interested and for now Openai’s income – no rivals – are well below spending They are doing in these technologies. Energy challenge. The plans to create infrastructure with 10 GW capacity are also astronomical. According to Some estimatesthose 10 gigawatts They are equivalent to the production of about 10 nuclear reactors, which normally provide a capacity of 1 GW per plant. A colossal cost. The current data centers range between very modest capabilities of 10 MW and other extraordinary 1 GW. Openai’s plans would leave those facilities very behind in computing capacity. In August Huang told investors to create a 1 GW data center is a cost of between 50,000 and 60,000 million dollars, of which about 35,000 are dedicated to Nvidia chips. With those figures, the total cost of those 10 GW of joint computing power would amount to more than 500,000 million dollars, a figure that – one—curiously— It coincides with that of the Project Stargate. Image | Flikr (Techcrunch) | Nvidia In Xataka | 5,000 “tokens” of my blog are being used to train an AI. I have not given my permission

Mark Zuckerberg doesn’t care to lose $ 200,000 million in AI. The real risk would not be betting on it, ensures

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“We are going to invest aggressively. Even if we lost a couple of hundreds of billions of dollars it would be an annoyancebut it is better than being left behind in the race for superintelligence. “Those words recently pronounced Mark Zuckerberg, Meta CEO. The founder of Facebook does not tend to shake his hand when making risky technological bets. He already knows what it is to lose them: Metaverso is being a failure for the moment, but even if he does not seem to want to leave that bet. The company continues to invest in it even though It is estimated which has already lost 45,000 million dollars in that project. But for him the commitment to AI, although it seems exorbitant, is almost mandatory strategically. In the interview In the Podcast Access The Meta CEO explained how In fact the Risk for a company as a goal would not be aggressive enough. In the recent Trump dinner With the great leaders of the technological segment in the US, Zuckerberg promised to invest at least 600,000 million dollars in the United States until 2028. Analysts believe that The numbers do not fit: It is estimated that Meta will invest about 80,000 million dollars in the US in the second half of 2025 (including all its expenses). That would make it necessary that from 2026 to 2028 he spent 520,000 million, but experts do not see it feasible and some They think than these comments They are more business marketing than anything else. But what is true is that both goal and other large technology companies are investing extraordinary amounts of money in this field. We already saw that Capex’s forecasts of some of them are huge in 2025 due to that commitment to AI data centers: Amazon: 100,000 Millions of dollars Microsoft: 80,000 Millions of dollars Google: 75,000 Millions of dollars Goal: 65,000 Millions of dollars Apple: 12,000 Millions of dollars Thus, Mark Zuckerberg is not too frightened to lose 200,000 million dollars in AI, but he also knows what is something like that. In April 2024 their financial results were so disastrous That their shares suddenly 19%, which was equivalent precisely to a drop in the stock market capitalization of 200,000 million dollars. Of course, Meta recovered. In that downturn the goal shares were just 500 dollars. Today and a half later, they are at maximum, $ 778. The company has stumbled in the past, but Zuckerberg has risen again and again AI bubble: “I think there is definitely the possibility, at least empirically, based on large infrastructure constructions of the past and how they led to bubbles.” And even so, Zuckerberg is clear that this is a critical moment for this technology and it is better to bet on the big not to do it and lose. For him going too slow can make you lose a privilege position, and that would be fatal because according to him “it will be the most important technology that will allow the greatest number of new products, innovation and creation of value in history.” In Xataka | Big Tech have buried thousands and billions in AI. They are earning money, but not thanks to the AI

Nvidia has paid 900 million for one

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Nvidia has signed a new talent from Ia. The news is not that, but the way in which he has signed it: to achieve “capture it” he has made an investment of more than 900 million dollars in the company he directed. It is a new hiring modality that allows “stealing talent” without current legislation being able to do much. What happened. According to CNBC dataNvidia has invested more than 900 million dollars in the AI ​​Hardware Startup Contractwhich manufactures connectivity components for AI servers. As part of that agreement, Nvidia has signed his CEO, Rochan Sancar, who will begin to work directly for the firm led by Jensen Huang. Clusters to power. Contractivity connectivity solutions – founded in 2019 – allow the company to connect more than 100,000 GPUS to put them to work within AI. These types of solutions can help Nvidia offer integrated systems that use their chips. Or what is the same: all this points to new “supernodos” of computing with thousands of Nvidia chips ready to be installed in large data centers. The firm already its GB200 NVL72 marketsfor example, but this agreement allows you to go more in that field. They already knew each other. In 2023 Nvidia already participated in a round of investment in which Undergraduate raised 125 million dollars. In 2024 another new 115 million round He made companies such as ARM, Samsung or Cisco participate. According to Pitchbook, after this round the contribute assessment was 600 million dollars: the investment made by NVIDIA is enormous considering that data. Big Tech invest fortunes to sign talent. This tactic is the same that used goal in June, when invested 14.3 billion dollars In the startup Scale AI and signed his new tsar of the Superintelligence Division, Alexandr Wang. Google did the same in July by announcing an agreement with Windsurf: would invest 2.4 billion dollars in itand incidentally, he would sign his CEO, Varun Mohan. Microsoft did the same With Inflection and Mustafa Suleyman In July 2024, and Amazon also He moved file At that time when signing managers of the STARTUP of the ADEPT. One way to avoid legal problems. Traditionally, these types of operations were carried out through the well -known “Acquihires”. A large company bought another and in many cases it did to get talent, not because of the product or service offered by the “victim.” These agreements have ended up suffering remarkable legal scrutiny, which has made large companies go to other forms of talent. These “pseudoinversiones” are nothing more than a mechanism to achieve that talent without being so exposed – at least, for the moment – to legal scrutiny. And a distortion of the startup market. These operations, however, pose an important problem for the global startup panorama. If a large company can go to methods like this to sign talent, change the dynamics and strategies of startup themselves. After the investment in Underground, the company should continue to be separated, but to what extent is this a undercover acquisition? More elements for the bubble of the AI. There is also a threat to the risk capital market. Big Tech are using their huge cash reserves to inflate startup assessments such as getting out. Not because of its market potential, but as a “hiring premium” covered by its founders. This can create a bubble and change the strategy of risk capital investors, which can now value talent more than long -term business viability. Image | Hillel Steinberg In Xataka | We still do not have the four -day week and there are already CEOS dreaming with the next level: work only three days

one million terabytes and 24,000 nvidia chips for a key mission

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In an increasingly digitized world and where artificial intelligence (AI) is transforming the way we work, investigate and relate, the supercomputing has established itself as the rod of measure technological power. It is a strategic resource that allows us to accelerate advances in science, innovation and defense. Not all super -taders play in the same league. Frontierof the United States Department of Energy, marked a milestone in 2022 by becoming the first to officially overcome the exaescala barrier, with 1,102 Exaflops in the Benchmark HPL. To that achievement they joined later The Captain and Auroraalso on American soil, consolidating its leadership position on paper. In the case of China, the information remains opaque, With very few public data about the status of their projects. Europe, however, just moved. Your first superorous to exaescala is already underway: Jupiter. Installed in the Jülich Supercomputing Centerin Germany, one of the most important advanced research poles of the continent. Jupiter is driven by the platform Nvidia Grace Hopper And Evidan xh3000 Bullsequana architecture is based on a liquid -refrigerated system designed to squeeze efficiency and performance. It is expected to reach up to 90 exaflops in artificial intelligence loads. Their applications will be diverse: from climatic research to neuroscience and quantum simulation, placing Europe in a new calculation capacity league. An inauguration with historical air September 5 The official inauguration ceremony in Jülich took placewith the presence of German authorities, European and leaders of the technology industry. German Chancellor Friedrich Merz presented him as a Pioneer project for Europe. “With Jupiter, Germany now has the fastest supercomputer in Europe and the fastest room in the world. Open completely new possibilities, from the training of AI models to scientific simulations.” In the Top500 list, Jupiter already appears as the fourth Most powerful supercomputer in the world, only behind the Captain, Frontier and Aurora in the United States. The European Union stands outIn addition, what works entirely with renewable energyby hiring green supply on the German network, and that its Rack Jedi leads the Green500 energy efficiency classification. The figures behind Jupiter To understand its magnitude, just review some technical data: 24,000 superchips nvidia gh200 grace hopper 51,000 network connections with infiniband quantum-2 technology Storage capacity close to an exabyte Modular installation with 50 specialized containers Maximum consumption of 17 MW, equivalent to about 11,000 homes A rack called Jedi leads the World Energy Efficiency Classification Why is it relevant to Europe Europe had been behind in the supercomputing career for years, with a landscape dominated by the United States. JUPITER offers researchers, companies and academic centers direct access to a top -level machine without depending on external resources. This means forming their own talent, consolidating experience in the management of these systems and reinforcing technological sovereignty at a time when artificial intelligence and calculation capacity have become strategic issues. Concrete applications The first projects already selected show how far a supercomputer of this category can go: Climate: The ECMWF works with a kilometer scale simulations, capable of representing extreme storms and feeding the Destination Earth project, whose objective is to build digital twins of the planet European: The Trustllm consortium trains language models in multiple European languages ​​for industrial and scientific applications Neuroscience: With the arbor simulator, neurons behavior will be modeled at the subcellular level, key to developing therapies against diseases such as Alzheimer’s Quantum: JUPITER aims to exceed the 50 -QBITS record in simulation, a relevant step towards quantum practical computing Astrophysics: The Max Planck Institute will use it to study cosmic reion, the period in which the first stars and galaxies emerged Particle physics: The University of Wuppertal will increase the resolution of its calculations on the Mon, which could open the door to new discoveries Video models: The University of Munich explores compression and dissemination architectures to advance applications that go from medicine to autonomous driving Multimodal models: The University of Lisbon Scale open and multilingual models, integrating different fields of science and automatic learning Access and future Researchers may request access to the system in calls that will be held twice a year. At the moment, there are already 30 projects underway. The expected useful life is at least six years, which guarantees continuity and stability in a land where technological cycles are increasingly fast. A strategic movement Jupiter is not just a technological achievement. It is a strategic commitment to provide Europe on their own capacity in an area where part of the future of artificial science and intelligence is played. With him, the continent finally has a tool that allows him compete at the highest levelwith energy efficiency and technological independence. Images | Nvidia | Jülich Supercomputing Center In Xataka | Alibaba has just demonstrated that Openai spends 78 million to do the same as them for $ 500,000

Alibaba has just demonstrated that Openai spends 78 million to do the same as them for $ 500,000

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There is a new star technique to train AI models super efficiently. It is at least what Alibaba seems to have demonstrated, that Friday presented His family of QWEN3-next models and did so presuming from spectacular efficiency that even Leave behind the one he achieved Deepseek R1. What happened. Alibaba Cloud, the Alibaba group’s cloud infrastructure division, presented a new generation of LLMS on Friday that described as “the future of efficient LLMs.” According to those responsible, these new models are 13 times smaller than the largest model that that company has launched, and that was presented just a week earlier. You can try QWen3-Next On the Alibaba website (Remember to choose it from the drop -down menu, in the upper left). QWen3-Next. This is what the models of this family are called, among which it stands out especially QWen3-Next-80b-A3Bwhich according to developers is up to 10 times faster than the QWEN3-32B model that was launched in April. The really remarkable thing is that it also manages to be much faster with a 90% reduction in training costs. $ 500,000 is nothing. According to AI Index Report From Stanford University, to train GPT-4 OpenAI invested $ 78 million in computation. Google was further spent on Gemini Ultra, and according to that study the figure amounted to 191 million dollars. It is estimated that QWEN3-Next has only cost $ 500,000 in that training phase. Better than its competitors. According to the benchmarks made By the artificial firm Analysis, QWen3-Next-80B-A3B has managed to overcome both the latest version of Deepseek R1 and Kimi-K2. Alibaba’s new reasoning model is not the best in global terms-GPT-5, Grok 4, Gemini 2.5 Pro Claude 4.1 Opus overcome it-but still achieves outstanding performance taking into account its training cost. How have you done it? Mixture of experts. These models make use of the Mixture of Expert architecture (MOE). With it, the model is “divided” into a kind of neuronal subnets that are the “experts” specialized in data subsets. Alibaba in this case increased the number of “experts”: while Depseek-V3 and Kimi-K2 make use of 256 and 384 experts, QWen3-Next-80b-A3B makes use of 512 experts, but only activates 10 at the same time. Hybrid attention. The key to that efficiency is in the so -called hybrid attention. Current models usually see their efficiency reduced if the input length is very long and have to “pay more attention” and that implies more computing. In Qwen3-Next-80b-A3B, a technique called “Gated Deltanet” is used that They developed and shared MIT and NVIDIA in March. GATED DELTANET. This technique improves the way in which the models pay attention when making certain adjustments to the input data. The technique determines what information retain and which can be discarded. That allows creating a precise and super -efficient cost mechanism. In fact, QWEN3-Next-80B-A3B is comparable to the most powerful Alibaba model, Qwern3-235B-A22B-Thinking-2507. Efficient and small models. The growing costs of training new models of AI begin to be worrisome, and that has made more and more efforts to create “small” language models that are cheaper to train, are more specialized and especially efficient. Last month Tencent presented models below 7,000 million parameters, and another startup called Z.AI published its GLM-4.5 Air model with only 12,000 million active parameters. Meanwhile, large models such as GPT-5 or Claude use many more parameters, which makes the necessary computation to use them much greater. In Xataka | If the question is which of the great technology is winning the AI ​​career, the answer is: None

Openai estimates that it will enter 200,000 million dollars in 2030. The figure, like everything in OpenAi, is extremely ambitious

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OpenAI has set a target of 200,000 million dollars for 2030, as reported The Information. Your own internal documents reveal that to achieve this you will need multiply by 13 your current income In less than five years. Why is it important. The company is burning billions per month and plans to spend 90,000 million only in R&D by 2030. This represents 45% of its projected income, well above the percentage allocated by large technological ones, which remain mostly between 15% and 30% of their gross benefit, not even their income. If Openai’s income is below the goal, that percentage will be even greater. The figures. Openai expects to move from 13,000 million income at 2024 to 200,000 million in 2030. Its R&D expenditure would be proportionally double that of the most successful technological technological ones, much more mature and settled. To achieve this, it basically depends on large companies continue to invest in generative. If there is A brake on investmenteven if that does not imply the burst of a bubble, OpenAi will have accounting problems. In addition, this projection rises up to only one semester. OpenAI has increased the expected billing by 2030 by the beginning of the year. The big question. Is a business model sustainable where almost half of the income – even the gross benefit – is destined for research and development? If business income does not rise as Openai projects, the company will have a serious problem. Yesterday it was announced Your agreement with Oracle committing to a huge investment level to which you can hardly face except that you change the screws, or to deliver a good part in kind (business use licenses), as Microsoft did with it paying in Azure credits. In Xataka | Baidu is no longer satisfied with being the Chinese Google. His new AI model also wants to turn it into China Openai Outstanding image | IlgmyzinXataka

Germany has discovered that a teacher saved a million euros. And what did he do as he was on 16 years

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The OECD He placed Germany in front of a mirror: that of the country developed where less hours work a year. Behind the figures (just 1,331 hours per year) There was a culture broth marked by economic deterioration and a nation that moves between two poles: lengthening the days or valuing life more outside of work. And in between, scandals that have reinforced the perception that labor laxity is unsustainable. The case of a low teacher since 2009 has lit the debate. An unusual case. In Wesel, North-Westphalia Rhine Since 2009sixteen years without reincorporating his post, but fully charging his salary, which over 16 years added around one million euros (between 5,000 and 6,000 euros per month). During all that time he presented monthly medical certificates, although he was never required an official recognition to accredit his status. The anomaly came to light when, after years of bureaucratic inertia, a new official detected irregularity In 2024 and ordered the medical review. When he was finally asked to undergo a medical examination, the teacher responded demanding her employer, claiming violation of rights, as she had done before in front of an attempt to transfer in 2017, but this time she lost the litigation. The Ministry of Education of Renania del Norte-Westfalia has described The issue of “serious failure within the Bezirksregierung of Düsseldorf” and has promised a “concessions” review of all internal procedures. Implications The teacher’s official granted her Extraordinary protectionincluding the right to leave indefinite with full salary, provided that it was properly accredited. However, local reports suggest that during their prolonged absence he reached Found a company Medical and exercising as a naturopath, activities that, if confirmed, would violate the obligations of prior notification and prohibition of parallel works during a decline. Not just that. He came to participate in entrepreneurship competitions, getting to obtain A 5,000 euros award for a cream of your invention. According to the labor lawyer Ralf DelgmannNot only infringed the regulations that require prior authorization for any secondary work, but would have done it while perceiving a medical leave, which feeds the suspicion that he was never really incapacitated. This could cost his pension, salary and even the condition of official. Even so, jurists warn That retrospectively demonstrating the absence of disease is practically impossible, so the recovery of wages already perceived is unlikely. A symptom of a major problem. The scandal, airy by the German presshas raised a debate about the rigidity and at the same time the vulnerability of the official statute. While private employees go on to collect reduced benefits After six weeks, officials keep the salary even for years, provided there is effective control. The case demonstrates how a Supervision vacuum prolonged allowed an anomaly to be consolidated for almost two decades. Although the Ministry insists that it is not a systemic problem, but about punctual negligence, public opinion perceive that confidence in the public function is committed by episodes of abuse like this. A long process. The media in Germany tell that the newly opened disciplinary procedure can Extend three or four yearstime during which both the actions of the teacher and the omissions of her administrative superiors will be investigated. Beyond its individual outcome, the case has become a symbol of control deficiencies in German administration, evidencing how a single poorly managed file can erode the credibility of an entire system. Plus: Beyond the judicial outcome, what remains in evidence is the urgency of rethink a casualty model That, in his eagerness to shield officials, he opens the door to abuses that end up being paid by society as a whole. Image | Pxhere In Xataka | The myth says that Germans work more than the Spaniards. The data tell a different thing In Xataka | Some researchers have analyzed the working day in Spain: the same thing that 40 years ago is worked, but in worse jobs

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