Tech

Chinese Big Tech can now buy Nvidia GPUs. The problem for Nvidia is that they don’t need it now

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The United States and China are immersed in a trade and technological war that has caught the line of fire to the AI ​​giant: Nvidia. The situation is that Nvidia must prioritize AI companies from the United States to guarantee the supremacy of this country, but as a company it would be interested in taking a bite out of the giant Chinese market. And the problem is twofold: it has not been able to do so for a long time due to trade vetoes, but now that it seems that it can sell its famous H200 to China, it turns out that China has turned the page. More or less. green light. Nvidia has gone from having a monopoly on AI GPUs in China to have a 0% quota. These are the words of the CEO, Jensen Huang, and the reason is the aforementioned trade restrictions between the powers that prevented Nvidia from selling its most powerful products to the Asian giant. Huang has spent months insisting on Donald Trump’s government to allow them to sell with a very clear logic: China is going to develop its alternatives and what better way to make a profit until then. The situation is gone relaxing at the end of last year and at the beginning of this to get to the point where we are now. According to Reutersthe US Department of Commerce already allows ten Chinese companies and distributors such as Foxconn and Lenovo acquire that long-awaited H200the company’s second most powerful AI chip. Good news for the company. Or they should be if it weren’t for the fact that the Chinese industry is going its own way looking home. Alibaba, ByteDance, JD.com and Tencent are the Chinese giants that can supposedly already buy H200. Up to 75,000 chips each, to be exact. However, it is noted that they have not yet made any shipments. Here there is a mix between very restrictive bureaucracy and, above all, that emphasis on national development. Tencent, for example, noted in September last year that they had no intention of producing AI chips, but that they were going to invest a lot of money in domestic partners. For example, they are in the process of adapting their infrastructure to be able to connect Huawei’s Ascend platform (particularly the Ascend 950 series) as the main training tool for large models. A few days ago, Tencent’s strategy director already pointed out that that strategy was still in place and that the company expects a significant increase in spending on AI GPUs designed in China. Manufacturing at home. Alibaba and Bytedance have a different approach. If Tencent is focusing on acquiring Huawei platforms, Alibaba and Bytedance are looking to create their own chips. Alibaba seeks to be the most powerful RISC-V chip created to date and it was reported that Bytedance wanted Samsung will manufacture its processor. In the end, whether buying from Huawei or developing the tool internally, the two approaches respond to the great national objective: that at least 50% of the data centers that belong to the State use at least 50% Chinese integrated circuits in their servers. That is one of the great Chinese technological impulses of recent years, one of the crucial points of the Five-Year Plan for the development of the country and, above all, the strategy that Nvidia had been warning the United States about for some time. The age of inference. Because this period of ostracism to which the US condemned China has served for the country to develop three very clear alternatives to Nvidia and encourage companies that are already working with models to develop their own hardware. This is important especially in the new AI framework we are entering, that of inference. Although the AI ​​will continue to train and GPUs will be needed for this, the next step is inference, the agentic era in which the processor or CPU is very important. AMD is moving there, same as Intel or ARMand precisely processors are something that Huawei is good at and in which the Chinese giants can shine as much as their American counterpart by developing chips tailored to their models and needs. Also, as pointed out in CNBChaving your own chips means you don’t have to fight with anyone else in a time when there is scarcity and, of course, if you don’t have to buy from an outsider, there is an improvement in the gross income margin. juicy cake. And this leaves Nvidia in that uncomfortable situation, one in which it wants to participate, but in which it seems that it is no longer needed as much as before. Because China is developing its chips for this new era of AI and Nvidia is running into a final boss called bureaucracy and the pressure groups of the ‘Make America Great Again‘. The first is due to the slowness of the export order processes, something that takes months when orders should be much more agile. The second are the aforementioned pressure groups that hold that any deals Nvidia makes with Chinese companies are less chips for American companies, something that should not be allowed. Meanwhile, Chinese companies are developing their alternatives and Huawei wants to flood the market with 750,000 chips this year, three times more than its shipments in 2025, and Nvidia is falling short of a $50 billion pie. In Xataka | The US has the best AI models. China has something else: AI too cheap to care about

Big Tech spent $725 billion on AI. Then they ran out of money in their pockets.

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This is non-stop. Big tech companies have already spent an irreverent amount of money in 2025 to not lose footing in the AI ​​race, but this year things are getting better. Together Amazon, Microsoft, Google and Meta have announced a capex of $725 billion, which represents an astonishing 77% growth over last year’s (also astonishing) figure of $410 billion. The numbers they are dizzyingbut they are having a worrying consequence. A lot of money saved. For years, Big Tech has been able to boast extraordinary accounting books in which revenues and profits have practically not stopped growing. They’ve built up exceptional cash flow, but now they’re taking advantage of all that money to fund an AI race that doesn’t seem to end at the moment. Cash flow plummets. The amount of investments is of such magnitude that all of these hyperscalers have encountered a problem: their cash flow—the available liquidity— has collapsedthey indicate in the Financial Times, and now it is at levels that we have not seen since 2014. Before, the average was to have 45,000 million dollars since the pandemic, but now that figure is expected to fall to 4,000 million in the third quarter of 2025. Source: Financial Times. Let’s see who spends more. Amazon leads this unique race for spend more than others. The company led by Andy Jassy foresees an investment of 200,000 million dollars in 2026, which will lead it to burn about 10,000 million of its cash flow this year. Meta will continue that same trend in the second half of the year, while Microsoft could enter negative territory in at least one quarter. Even Google, which remains positive, will post its lowest level of cash flow in a decade. Debt, new fuel for AI. To finance this deployment, both Alphabet and Meta have had to resort to massive debt issues and suspend their share buyback programs for the first time in almost a decade. Alphabet issued $48 billion in bonds recently (in February a partdoes some days other), while Meta sumo 55,000 million debt in just six months. Bet now to win later. This strategy marks a paradigm shift: it is no longer investing only with the income one has in cash, but Big Tech is mortgaging its future. The objective is what we have mentioned time and time again: not to lose step in a race where, as Zuckerberg said, staying behind is not an option. Disguising the beads. These companies fear Wall Street’s reaction to these movements, so they are moving billions of dollars in infrastructure but they are doing so outside of their conventional balance sheets. In the FT they explain how Big Tech are using special investment vehicles that allow them to attract external capital and hide debt. They are also more opaque about who will be impacted if the AI ​​does not meet expectations. The memory crisis is also having an impact: in such a way that Microsoft already has added 25 billion dollars to its investment needs this year just to be able to assume the increase in component prices. The danger of going with the flow. CEOs justify these moves by comparing them to what happened with cloud investment two decades ago, but analysts warn: investing when the competition invests is not always a strategic choice, but rather a forced response to staying out of the race. In Xataka | The chip crisis is leaving no stone unturned: motherboards seemed untouchable, but their time has come

Big tech had ambitious climate goals. Then the AI ​​came and started devouring them

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There was a time when technology seemed to have found a comfortable way to tell its climate future. The big companies talked about “clean energy”net zero emissions, increasingly efficient operations and commitments dated to 2030 or 2040. It was an attractive story because it coexisted with our daily use of the internet, services and applications. Generative AI, however, has complicated that picture: not only does it bring more smart services, it also requires more infrastructure, more electricity, and climate pressure that is much more difficult to square with the promises those same companies made just a few years ago. The most recent movement comes from Microsoft. Bloomberg has published that the company would be considering delaying or even abandoning one of its most ambitious energy goals, at a time when the race for AI requires increasingly more computing capacity. Tell OpenAI or Anthropic. This case does not appear in a vacuum: other large technology companies are also facing increasingly visible challenges to fit their climate commitments with the expansion of their data centers. The question is no longer just what they promised, but what happens when those promises collide with the actual scale of AI. The companies did not reach these commitments in a single way nor did they promise exactly the same thing. Some focused on the purchase of renewable energy, others on zero-carbon electricity, others on net-zero emissions, and others on eliminating more carbon than they generate. There were also different reasons for doing so: regulatory pressure, investor expectations, reputation and a fairly widespread conviction that digital infrastructure could grow. without triggering its climate impact. What interests us here is not to review all those promises, but to follow some of the most ambitious ones and see how they are holding up to the AI ​​race that is unfolding before our eyes. Climate promises in the face of expanding data centers As we say, the fundamental change is that many of these commitments were formulated before generative AI became an absolute priority for the industry. Until then, the growth of data centers was already a challenge, but it could be projected with a more gradual logic. The new race has altered that pace: training models, deploying them in massive products, and answering large-scale queries requires computing power that grows very quickly. What once seemed like a difficult but manageable roadmap now faces a different dynamic. Microsoft was one of the companies that formulated one of the most demanding goals. In July 2021 he announced his 100/100/0 commitment, a way of saying that by 2030 he wanted match 100% of your electricity consumption100% of the time, with zero-carbon energy purchases. The nuance matters: it was not just about offsetting annual consumption with renewables, but about getting closer to an hour-by-hour correspondence. Furthermore, the company proposed doing so in the same electrical networks from which it took that energy. Now that commitment is under obvious pressure. The aforementioned economic media indicated that the Redmond company is studying delaying or even abandoning it, according to anonymous sources with knowledge of the matter, while seeking to clear obstacles to powering its data centers. Microsoft has not confirmed that change and its director of sustainability, Melanie Nakagawa, maintained that the company remains committed to its environmental goals. He also left an insight that sets the tone for the official response: any adjustment would be part of a review of approach, not a change in long-term ambition. Google also set a powerful goal. In 2021, the Mountain View company set the goal to achieve net zero emissions across its operations and value chain by 2030, including its consumer hardware products. To achieve this, he proposed reduce 50% its absolute emissions compared to 2019, not only those generated directly by the company, but also those linked to its activity and its supply chain. What it could not reduce, according to its roadmap, it would compensate by removing carbon from the atmosphere through natural and technological solutions. The current situation shows how difficult it is to put this roadmap into practice. In its 2025 environmental reportGoogle points out that in 2024 its emissions were 11.5 million tons of CO2 equivalent. That is 11% more than the previous year and 51% above its 2019 base. The nuance is important: they did not increase 51% in one year, but rather compared to the starting point chosen by the company. The report itself also recognizes that integrating more AI into its products can complicate the reduction of emissions due to the greater demand for computing and technical infrastructure. Amazon also presented a high-ambition climate pledge. In September 2019the e-commerce giant announced together with Global Optimism The Climate Pledge, a commitment to achieve net zero carbon emissions by 2040ten years before the horizon set by the Paris Agreement. The company founded by Jeff Bezos became the first signatory of that initiative, which called for measuring and reporting emissions on a regular basis, applying decarbonization strategies and neutralizing remaining emissions with additional, quantifiable, real, permanent and socially beneficial compensations. Amazon’s situation shows that these promises already had gray areas even before AI was at the center of the debate. In September 2023, Data Center Dynamics published that the Science Based Targets initiative had removed the Amazon commitment from its panel and placed it in the “expired commitment” category. The reason, according to the media, was that both parties were unable to agree on a sufficiently significant emissions target. Amazon responded that the requirements had changed and that it would continue to look for credible third-party validators. In this sense, general photography goes in the same direction. The US Department of Energy estimates that the Data centers consumed around 4.4% of the country’s electricity in 2023 and could be between 6.7% and 12% in 2028. The International Energy Agency also projects a relevant leap on a global scale: from about 415 TWh in 2024 to about 945 TWh in 2030. Not all of this growth can be attributed solely to AI, … Read more

cost savings are becoming very expensive for big tech

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Large technology companies have been in a dynamic for months that is difficult to understand if the current technological context is not taken into account. Companies that, according to your tax results of the first quarter of 2026, record historic profits close to 80%they are cutting jobs at the same time. What is happening in their workforce has nothing to do with a financial crisis, but rather responds to a strategic decision regarding AI. According to the records from the portal Layoffs.fyiSo far in 2026, more than 92,000 employees in the technology sector they have lost their job throughout the world due to layoff rounds that the main technology companies have launched. The main argument for these layoffs is AIbut not because this technology is going to do the work that programmers used to do, but rather it responds to a restructuring of companies to lighten their workforce and focus only on developing AI. The measure is not coming cheap. The big bet of AI that must be paid. By chance (and the proximity to the presentation of their first quarter results) Microsoft and Meta announced, on the same day, layoffs that will affect more than 16,000 employees between the two. Meta will lay off 8,000 workers, 10% of its global workforce, and will leave another 6,000 vacancies unfilled. The goal of both companies is to improve efficiency and offset investment in artificial intelligence. Microsoft will face investments close to 145 billion dollars only in this fiscal year, thus adding to investments in AI what are they doing each and every one of the big technology companies. Maintaining that bet without margins suffering forces cuts, and personnel is the expense that investors like it less. Altogether, investments worth 700,000 million will be accumulated among all large technology companies during 2026. These estimates also include compensation expenses that are associated with these personnel cuts. Oracle, for example, reserved 2.1 billion dollars only for this game in your round of 30,000 layoffs. Microsoft launches a different formula: voluntary dismissal. Instead of announcing collective layoffs, Microsoft has chosen a path that the company had never used in its 51-year history: making voluntary exit offers to encourage its employees to leave by their own decision. Google already applied this formula of voluntary dismissals in its 2025 personnel cuts, not without the risk of losing its best employees by opening the exit door for them. This initiative is aimed at employees with a very specific profile who, in theory, would be more complicated to relocate to a new internal position within the framework of this workforce restructuring. In total, this offer has been made to 7% of its workforce in the US, more than 8,500 people. Amy Coleman, Microsoft’s chief people officer, announced the move in an internal memo. In that statement to which had access CNBCColeman wrote: “Our hope is that this program gives those eligible the option to take that next step on their own terms, with the company’s generous support.” Why an incentive instead of a layoff. Both voluntary departure and conventional dismissal have the same outcome: the workforce is reduced. However, as as highlighted to Fortune Domenique Camacho Moran, lawyer and partner at the Farrell Fritz law firm, specialized in labor law for Fortune 500 companies, traditional layoffs are legally more complex because they require evaluating the performance of each worker and argue his dismissal to avoid legal risks. “The voluntary exit option gives the employer the ability to say that it’s not that we don’t think you’re doing a good job, but that if you’re thinking it’s time to move on, I’m going to encourage you to do so because we need to downsize.” Incidentally, since it is an initiative of the employee, the company does not have to look for arguments for dismissal, which simplifies the process and avoids future legal claims. A risky bet for talent. However, as we already mentioned, the voluntary dismissal formula is risky since it leaves the decision in the hands of the employee. possibility of resigning. In a context of shortage of specialized talent (especially in AI), companies run the risk that their best swords will accept the incentive, paying a double cost for it. Last year, Google offered voluntary departures across several teams, including its search and advertising division. Vice President Nick Fox was blunt in his memo: “I want to be very clear: If you are excited about your job, energized by the opportunity ahead of you, and performing well, I really (really!) hope you don’t take it.” as collected CNBC. In Xataka | While technology companies dispense with juniors to replace them with AI, IBM is doing the opposite: catching bargains Image | Unsplash (Compagnons, Sam Torres)

The best tech deals on Amazon for less than 50 euros today, April 28

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April is coming to an end and if you are looking to renew or buy new technological devices for your home, Amazon is one of those stores where you can get very good deals. These are the best deals in technology for less than 50 euros that we found today, April 28, in this store. Tenda RX2L Pro – AX1500 WiFi 6 Router The price could vary. We earn commission from these links speaker system Logitech Z207 Bluetooth by 46.45 euros: with 3.5 mm input and 10 W of power. surveillance camera Reolink E1 Pro by 42.49 euros: Supports dual band WiFi. WiFi 6 router Tenda RX2L Pro by 29.99 euros: with WiFi 6 and five antennas. Smart humidifier Dreo by 49.99 euros– Compatible with Alexa and Google Assistant. wireless mouse Logitech Ergo M575S by 34.99 euros: with customizable buttons and trackball. Logitech Z207 Bluetooth Speaker System If you want to give your computer better sound, this Logitech Z207 Bluetooth speaker system is perfect now that it’s on sale. It has gone from costing 71.99 euros to 46.45 eurossince it has applied a 35% discount. This is a speaker system that you can pair to two Bluetooth devices or connect a device via the 3.5mm input. It pairs easily using the Bluetooth button and has an integrated headphone jack. The total power it offers is 10 W. Logitech Z207 Bluetooth PC Speaker System The price could vary. We earn commission from these links Reolink E1 Pro surveillance camera The time is approaching when getaways and departures from home are more continuous. If you are looking for a good option for have your home under control when you are awaythis Reolink surveillance camera is a good option. Its usual price is 49.99 euros, but now you can get it for 42.49 euros. This surveillance camera for indoors it offers a resolution of 2,880 x 1,616 pixels and is supports dual band WiFi. It has detection assisted by Artificial Intelligence and multiple storage options. Reolink E1 Pro 3K PT Indoor Camera The price could vary. We earn commission from these links Tenda RX2L Pro WiFi 6 Router If you want to have a good Internet connection at home, this Tenda RX2L Pro is a WiFi router that will come in handy. Its recommended price is 49.99 euros, but now it has a 40% discountbeing able to buy it for 29.99 euros. This router is equipped with WiFi 6 technology and offers dual-band speeds of up to 1,501 Mbps. It is equipped with five non-detachable antennas and technology beamformingwhich effectively improves signal transmission. Tenda RX2L Pro – AX1500 WiFi 6 Router The price could vary. We earn commission from these links Dreo Smart Humidifier It’s allergy time and maintain the best environment at home It is ideal to be able to cope with allergic rhinitis, for example, better at home. This one from Dreo has a recommended RRP of 59.99 euros, but now you can get it for 49.99 euros. This is a humidifier that you can control via app and voice commands, as it is compatible with Google Assistant and Alexa. It creates a mist three times larger than most humidifiers on the market and its four-liter tank offers up to 32 hours of mist. Dreo Smart Humidifier The price could vary. We earn commission from these links Logitech Ergo M575S Wireless Mouse With a 41% discountthis Logitech ergonomic mouse has gone from costing 58.99 euros (recommended RRP) to 34.99 euros. If there is something it stands out for, it is its cut shape, which keeps your hand relaxed for hours. From the firm they guarantee a 25% less muscle tension on the forearm using this mouse. In addition, it has three customizable buttons, so you can establish shortcuts that will save you time. Additionally, it comes with a wireless trackball. Logitech Ergo M575S wireless trackball mouse The price could vary. We earn commission from these links Some of the links in this article are affiliated and may provide a benefit to Xataka. In case of non-availability, offers may vary. Images | Logitech, Reolink, Dreame and Tenda In Xataka | The best mobile phones, we have tested them and here are their analyzes In Xataka | Best wireless headphones. Which one to buy and 21 models from 15 euros to 470 euros

Big Tech is pouring billions of dollars into GPUs for AI. 95% are inactive

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When the COVID-19 pandemic began, toilet paper and yeast They flew from the supermarket. Paper because it is a basic good, but yeast because everyone was going to make a lot of bread in his house. That was the forecast, but we would really have to see how many of us ended up making bread. Well, something similar is happening in the data centers at the moment. Hyperscalers have spent billions and billions of dollars on GPUs for AI and, according to one report, 95% are idle most of the time. And all because of the fear of being left out. Kubernetes. Before getting into the matter, there is a concept that must be landed on. It is the one of the kubernetes. It is a kind of “operating system” in data centers, the foreman who organizes and monitors all the software that is being used. Imagine that a data center is a supermarket, the shelves are the servers and the products are the apps. Example of a control panel What this foreman does is find the perfect shelf to place the product in the most optimal way possible. In addition, he is constantly monitoring all the shelves at all times with the aim of not missing anything and ensuring that the data flow is perfect. It is, in short, a software that manages many physical servers in a very optimized way and 24/7. What’s happening. That said, the 2026 State of Kubernetes Optimization Report prepared by Cast AI has just revealed something: the tremendous inefficiency of data centers. They have analyzed about 23,000 kubernetes clusters in giants such as AWS (Amazon), Azure (Microsoft) and GCP (Google) and have discovered that the average GPU utilization of these data centers is just 5%. This translates another way: 95% are inactive most of the time, which implies that these companies are paying to get 20 times more computing capacity than they really need. Right now you might be wondering if it was worth it. destroy the RAM and SSD marketmaking computers, mobile phones, consoles and practically everything more expensive. And it is a question that makes all the sense in the world, but there is another interesting fact. To worse. As we see in TechRadarthose responsible for Cast AI point out that it is “the third year that we published this report and the numbers are getting worse.” Specifically, we are talking about CPU usage falling from 10% last year to 8% currently, while memory usage fell from 23% to 20%. Oversized needs. Something that the report also points out is that, although the use of equipment drops compared to the previous year, hyperscalers continue buying as if the world was going to end. CPU overprovisioning, as they describe it, increased from 40% to 69%. In the case of memory, it went to 79%. FOMO. A few weeks ago, one of the leaders of SMIC, the large foundry in China, already pointed out that Big Tech was buying all the resources that they will need, or that they think they will need, during the next decade… but in just a couple of years. They are investing a fortune in creating wide highways when there are no cars or real demand, and from Cast AI they are pointing in that same direction. Hyperscalers are buying piecemeal due to fear of being left out. It is what is known as FOMO or fear of missing outsomething that applies to many scenarios, but here it has to do with not wanting to come last in the race that is moving many millions from one place to another. This hoarding instinct is fueling a cycle of component shortages that affects consumers, but also the industry itself. According to the report, it makes some sense to want to buy everything as soon as possible because delivery times are long, but they are precisely so because everyone is buying more capacity than they need. Math doesn’t work. In the analysis they also point out that there are clusters that do not have such bad performance and that there are some that are using 49% of their H200 or 30% of their H100, well above the aforementioned 5%, but it is not the norm. And beyond having exploded the components market, the consequence of having so much equipment idle is that they are losing money because they are not profitable. According to calculations, an unused CPU costs a few cents per hour, but an idle GPU costs several dollars. And therein lies another key to this whole matter. Amazon or Azure data centers serve to satisfy the demands of their own companies, but they also rent computing power to whoever needs it. And since having the GPUs stopped costs them money, in recent months it has been reported that the prices of those rentals are multiplying. When will it all end? Cast AI is not optimistic, since they claim that most hyperscalers prefer to assume the costs rather than change their habits for fear that this will take off one day and catch them on the wrong foot. The translation is that… I will never have my Steam Machinesince everyone is focused on making hardware for AI. Image | NVIDIA In Xataka | There are data centers being watched and guarded by robot dogs because apparently the future is already the present

Big Tech has entrusted the keys to its kingdom to NVIDIA. Now they want the keys back

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NVIDIA is no longer a gaming graphics card company: NVIDIA is a ubiquitous company. That means it is the baby at the baptism, the bride at the wedding and the cement of the manufacturing industry. artificial intelligence. Your hardware is in the most powerful data centers on the planethis software controls everything and your money invest in any company that has something to say in AI. Big Tech (and everyone) is blindly trusting NVIDIA and has been given the keys to the house, but something is changing. And now they want the keys back to regain control. All the spotlights. Microsoft, Amazon, Google and Meta have bought hundreds of thousands of NVIDIA GPUs to shape your AI aspirations. At some point many began to develop their own hardware, but in the end NVIDIA’s was everywhere and was the one that gave the most guarantees, so they “gave up.” Apple, curiously, opted for Amazon. And not just the big ones. OpenAI, Anthropic, Mistral or xAI are purely AI companies that They bet very heavily on NVIDIA from the beginning. Its hardware is the one that leads the way, the one that Western and Chinese companies want and the one that has such a brutal demand that it has elevated the company as the best client of TSMC and Samsung. amd. But no one likes to have all their eggs in one basket, and those same names are moving. From a position of absolute dominance, in a short time we can move to another in which the hardware market is much more diversified. AMD is NVIDIA’s great historical rival in the PC gaming segment (and in consoles), but although they were out of the conversation for a few years, they have returned with force. They have the hardware and are moving to get the same memory that NVIDIA has (and Samsung wins more than anyone else) and contracts as juicy as the one they achieved recently with Meta. The big rival also has deep pockets and is committed to taking a piece of the AI ​​pie. The Chinese threat. On the other side of the world we have China. We have said on numerous occasions that China is on to other things when we talk about AI. If the West pursues the AGI (with questionable claims like it’s already here), to China doesn’t care exactly. They want fast chips that allow them to create accessible and monetizable models in the short term. But they also have Huawei, the company that has become the spearhead of the Chinese technology industry thanks to its collaboration with foundries such as SMIC is allowing, in an unthinkable way due to vetoes, can develop advanced chips. The development of cutting-edge chips still needs to be achieved, but Huawei already has more powerful inference chips than NVIDIA’s H20, according to them, and a supercluster for training. Taking back control. Because in that term, “inference”, is where the current key is. AI training is important because it is what allows the model to then have the data and have a wardrobe to pull from, but inference is the final layer, which processes the user’s request to provide a response. There is not so much raw power needed, and that is what almost all the companies mentioned above are taking advantage of. Amazon, Google or Meta have programs in which they are actively researching or developing chips proper for inference. OpenAI has signed an agreement with Broadcom to supply chips and xAI along with other companies Musk also has its own chips and they plan to open factories. And in China things are no different with Cambricon wanting to be a local alternative to NVIDIA and giants like Alibaba either ByteDance getting into chip design. Groq. Given this, do you think NVIDIA is standing still? Among their hardware proposals, they have Groq, an inference accelerator that is designed for, next to Vera Rubinprocess a large amount of data at enormous speed. Groq was an unknown in the world of AI – until NVIDIA licensed it – and specialized from the beginning in that: chips with minimal latency for inference. The key is in the architecture of its chips and it was a piece that was missing from the NVIDIA catalog and shows that, although the rest want the keys back, the one that already had them may have made a backup copy to continue being the reference. Because they may all be preparing their chips, but while they arrive, NVIDIA is already there and, in fact, with Groq it seeks to sneak into theThe $50 billion pie: China. Problem for NVIDIA. But of course, that’s part of the story. The other is that NVIDIA also has all its eggs in one basket: that of AI. In the middle of last year we already mentioned that six customers represent 85% of all NVIDIA revenue in the previous quarter. It is an absolute nonsense that shows that, if there is a shift in technology, a puncture of the bubble or a new player that arrives strongly, the situation for NVIDIA may not be so favorable. The question is whether a regime change can come and everything will be allowed to collapse like a house of cards. The uncomfortable thing is that an absurd amount of money is being invested and it’s not something that can escalate forever. In Xataka | Jensen Huang believes we have reached the “coming of the AI ​​wolf.” It is perfect for feeding a Tamagotchi

We believed that AI was killing jobs in the tech industry. It is actually changing the rules of the game: Crossover 1×41

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It is possible that in the future AI will take away our jobs, but at the moment it is being taken away from very few. This was stated in a recent Anthropic study on the impact of AI on the labor market, and this is a perfect perch to present the debate that concerns us in Crossover 1×41. And it is a special edition because we have as a guest Jordi Arrufiof Talent Arena. This event, which is held within the framework of the Mobile World Congress in Barcelona, ​​is aimed at future developers and also senior profiles, and with it we had the opportunity to talk about how AI is changing the rules of the game for professionals in the sector. To begin, we must dispel myths. At least for now, because although there was a time that AI was going to replace programmers, what is being seen according to Arrufí is that The demand for technological talent is increasing. In fact, what is expected is that the impact of AI will cause this technology to begin to create jobs that we cannot even imagine. We also couldn’t imagine that with the rise of the Internet there would be frontend and backend developers or web designers: the same in this case. Many professionals may fear that future, and here the recommendation to be prepared for the future is that these professionals combine your technical capacity (‘hard skills’) with human capabilities (‘soft skills’) such as critical thinking, leadership or communication. The frenetic advancement of AI also makes the ability for continuous learning and adaptability key in these changing times. He vibe coding has changed the paradigm, and has opened this area even to users without basic programming knowledge. Plus there is something striking here. A real opportunity for current professionals and those to come, because if something is clearly taking off it is interest in technological sovereignty. Europe seeks to recover ground against the US and China through investments in chipsFor example. Public funding is especially critical to retaining talent and prevents professionals from emigrate for higher wages. We also had the opportunity to talk about another of the areas of greatest projection: robotics. It is expected a imminent adoption of humanoid robots in industry and in logistics processes. Domestic robots will take longer, no doubt, but what seems clear is that by 2035 the world will be dominated by AI agents and massive advances in fields such as biotechnology. This is not just about AI: It’s about talent, money and who adapts faster and in a more accurate way. On YouTube | Crossover In Xataka | A startup from Malaga is the most used European AI app in the world according to Andreessen Horowitz. It’s called Freepik

It is a nod to Chinese Big Tech and a message for NVIDIA

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Huawei has arrived at the Mobile World Congress with one objective: to show the world What good have these last five years been? of vetoes and sanctions. The company has just had the second best year in its history. It seemed impossible when The United States ostracized herbut this five years has served not only to regain the throne in the enormous Chinese market, but to build something: the idea that China’s technological evolution passes through its hands. As a result of this we have the advertisement at the Barcelona fair of a line of SuperPoD supercomputers with a single objective: that the Chinese Big Tech don’t have to depend from NVIDIA. Return. Huawei has been collaborating with SMIC -the great foundry of China- to create chips. Chips that feed both your consumer devices as other high-performance ones for large-scale computing. It is clearly difficult to do this without violating Western vetoes (for example, their mobile processors do not have 5G and are less powerful than those of Qualcomm or MediaTek), but they are making progress. The symbolic thing is that They have turned resilience into their best quality. If in 2020 they competed for the market with Samsung and Apple, achieving a profit of 129,000 yuan, in 2025 registered 127 billion dollars, something impressive if we take into account that, above all, They come from the local market. In this time, Huawei has positioned itself as a lifestyle brand that has consumer devices, but also home automation and even cars. But if there is a great frontier today, it is that of artificial intelligence. And Huawei knows that it was something that had to be attacked not only from the most local perspective, but by launching a global warning. SuperPoD. Because these supercomputers, really, are not new. The company presented them in mid-September last year with a more local focus, for China. And before looking at the products, you have to see what a SuperPoD is. These are high-performance clusters that bring together thousands of specialized AI chips. And those chips are not from NVIDIA, which dominates the global conversation in AI computing, but rather their own. It’s about your Ascendsome that have been developing for years and that China is waiting like May rain to break that hegemony of NVIDIA. The idea is the same as with other technological sectors of the Asian giant: not to depend on anyone else. They are the following: Atlas 950 SuperPoD– A cluster of up to 9,192 Ascend 950DT NPUs per system with up to 1,152 TB of unified memory. TaiShan 950 SuperPoD– First general-purpose computing SuperPoD with two models: 96 cores / 192 threads or 192 cores / 384 threads for, for example, massive virtualization or critical databases. Local ecosystem. Huawei’s approach is very interesting. The Ascend is not close to the power and sophistication of NVIDIA chips, nor to CUDA technology that has become the language of AI. However, if each chip individually cannot compete for the most demanding tasks, what Huawei has thought is that these chips be scalable. To do this, they have developed a connection technology with ultra-high bandwidth that allows all these chips to be connected to each other with the aim that, in practice, it behaves like a single logical computer. This connection technology has been named UnifiedBus and, in the statement, Huawei states that the idea is to “continue defending open source and open systems to accelerate developer innovation and the prosperity of ecosystems. That is something that resonates with the Government’s objective: that its companies such as Tencent, ByteDance, Alibaba or DeepSeek, which have run into the arms of the latest NVIDIA chips As soon as the ban was lifted, they developed their technologies using ‘made in China’ solutions. Ambition at the cost of sanction. All this comes in a tremendously turbulent context. China is betting a lot on artificial intelligence and robotics as pillars of the country’s technological roadmapbut NVIDIA still has the best product. There is analysis that expose that the best of Huawei is still five times less powerful than the best of NVIDIA, and the United States has just made it clear that investment in AI is one in national security. All the mess between Anthropic and the Pentagon has to do with how the United States demands that the AI ​​of its private companies belongs to the State because they claim that the AI ​​of Chinese companies belongs to China, and China will not hesitate to do whatever it wants with that AI. Because computing power is, and will be, at the core of the AI ​​race, Huawei has shown that it is doing everything it can to deliver the best tools. And Western sanctions have only helped China ‘wake up’ and begin to shape these technological solutions at an accelerated pace. NVIDIA was clear. It remains to be seen whether customers around the world will adopt Huawei’s SuperPoD systems as an alternative to NVIDIA, but what is already on the table is that something is happening. At least, in China. In the middle of last year, the CEO of NVIDIA pointed out that before the vetoes, NVIDIA had 95% of the market share in Chinabut currently it is only 50%. These vetoes did not stop China, but rather accelerated the development of its own industry to the point that the competition, now, is fierce. In fact, the manager recently pointed out that it was absurd for the US to try to stop China with vetoes and sanctions, since China would achieve technological sovereignty sooner or later and that the ideal would be to take an economic slice while they could… and make Chinese Big Tech dependent on NVIDIA technology. And there Huawei’s approach is very curious because yes, its chips may not be the most powerful, but they are mass scalable and adaptable to the needs of each of the companies. Images | HuaweiXataka In Xataka | Huawei no longer competes: it is building its own … Read more

All Big Tech are betting the money they have and the money they don’t have on the future of AI. All but one: Apple

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650 billion dollars. There it is nothing. That is the total amount that Google, Amazon, Meta and Microsoft are going to invest in data centers for AI. That amount of money is astonishing and is similar to the current GDP of countries like Argentina or Israel. But the curious thing is not only that: there is a Big Tech that is totally ignoring this fever to spend on AI as if there were no tomorrow. Apple against the current. The company led by Tim Cook is the only one of the group of large technology companies whose capex (planned capital expenditure) was reduced last quarter. Based on FactSet data compiled by SherwoodApple’s forecasts for that quarter were not to spend more, but attention, spend (quite a bit) less. The numbers don’t lie. According to the data provided by these companies, Amazon expects that in 2026 its capex reaches up to 200,000 million dollars. Google wants to go from 175,000 to 185,000 million. Meta estimates that the expense will be between 115,000 and the 135,000 million. And although Microsoft did not give a specific figure, it surely exceeds the $114 billion estimated by Wall Street. And Apple? Apple will not spend more, but 19% according to its latest estimates: about $12.7 billion. Amazon: +42% YoY (vs. previous year) Microsoft: +89% YoY Google: +95% YoY Goal: +48% YoY Apple: -19% YoY Cupertino goes from AI. While its competitors spent record sums last quarter (which ended December 31) on the purchase of material and properties linked to the AI ​​sector and data centers, Apple continues not to invest in this sector. It is something that makes it clear that the company seems to have definitively decided that this is not its war. Siri+Gemini is the best test. Confirmation of that “surrender” is in the recent announcement that Gemini will be the AI ​​on which the new version of Siri will be based. Apple’s new AI assistant is expected to hit the market this spring with at least some initial features, but the fact that it does so depends entirely on Google’s AI model makes it clear that Apple here prefers to delegate rather than invest to have its own foundational model. AI will be a commodity. Instead of participating in this costly war of language models, Apple is clear that AI is going to end up being a commodity, something that is going to become a basic standard technology like the PC, mobile phone or laptop is now. Model prices plummet as the capacity of those models grows, and benchmarks make it clear that no model is better than another for long. Apple as a gateway to AI. As usual, what Apple will do is take advantage of the fact that has the “gateway to AI. With 2.4 billion devices worldwide, it controls the most valuable distribution channel on the planet. It has the luxury of not making “the engine,” but rather acting as an avenue to bring AI to the masses. Here agreements like the one it has completed with Google are just the beginning. It doesn’t matter being late. It is something that is in the company’s DNA. He also did not want to fight the search engine battle, but it did not matter: he reached an agreement with Google, which has paid him billions of dollars for years to be able to put its search engine as the default engine on iPhones, iPads and Macs. Apple prefers that others pave the way and absorb the costs of early learning. Then she usually arrives with superior integration and a refined experience (iPod, iPhone) or directly with deals like the one she completed in the search engine space. AI will be invisible and ubiquitous. Apple’s goal doesn’t seem to be to offer its own chatbot on the web, but to make AI invisible and ubiquitous. It doesn’t matter which model runs behind it, but simply that this AI works transparently for the user. And it does so, of course, seamlessly integrated into Apple services and applications. Privacy by flag. And of course, with that vaunted commitment to privacy that Apple always boasts of. Its Private Cloud Compute is the best proof of this. By not relying on advertising (hello Google, hello OpenAI), it is able to offer advanced features without collecting massive data from users. But there is risk. Still, the strategy has a critical risk: if AI models become a commodity and end up creating technological monopolies, Apple could be permanently at the mercy of its suppliers. If these competitive advantages end up being consolidated in the model layer – the one controlled by OpenAI, Anthropic and Google – and not in the integration layer – which is Apple’s – the dependence on third parties will be a dangerous strategic weakness. Room for maneuver. Apple has annual benefits close to 100 billion dollars, which gives it an enviable financial position to wait for this “hype” cycle to cool down. It is clear that there is an AI bubble and that bubble will probably end up exploding and leaving many victims. If it does, one of those that will undoubtedly have room to maneuver to survive will be Apple. Image | Xataka with Freepik In Xataka | China does not have a spending problem with AI. What it has is a huge income gap compared to its main rival

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