He is tired of giving it away to Big Tech AI

Satya Nadella, the CEO of Microsoft, has been getting creative on Twitter. Through a message almost as long as the one that his colleague Asha Sharma, CEO of Xbox, took the opportunity to communicate the dismissal of 3,200 people just a week ago, Nadella has shared something that disturbs him: in the age of AI, information is power, and You don’t like others benefiting from your data. Nadella cites the phrase coined by Nobel Prize-winning economist Kenneth Arrow, whose paradox of the information market was that “the buyer does not know the value of that information until he has it, but by then he has acquired it, in effect, at no cost.” In Arrow’s formula, for the seller to convince the buyer of the value of the information, he or she must reveal enough of it to make the buyer interested. The problem is that at a certain point, the buyer will already know so much that they will not need to pay for that information. For Nadella, in the age of AI the problem is the other way around because it is the buyer of AI services who runs the risk of transferring knowledge valuable institutional, simply, to use artificial intelligence tools. For Nadella, companies are paying twice. “One with money, but another with something even more valuable: the personal and confidential knowledge that you must reveal for that intelligence to be useful.” According to the CEO, “the better you want the model to perform, the more knowledge of that type you will have to feed it.” That, precisely, is the problem. And this is what Nadella has dubbed the ‘Inverse Information Paradox’. The Inverse Paradox of Information Following Nadella’s reasoning, as a company gives more and more information to the owner of the artificial intelligence model, the asymmetry between both parties becomes increasingly skewed. You can imagine why: the seller learns more and more about your company as you use what you bought, while you learn very little about what the seller is learning in return. Did Nadella just describe what all companies do with search engines and services that traffic in our information? Maybe, but what the CEO is clear about is that, just as intellectual property patents solve one of the aspects of the Arrow paradox, since the inventor can reveal the idea without giving it away, the Inverse Information Paradox would need its own legal framework that protects companies that buy AI services. As? Well, that’s what we should see, since Nadella points out that models learn from the prompts that people write, the agents’ tools and, above all, the corrections that users make when a model makes a mistake. But Nadella goes further, stating that “When you consume intelligence, you are creating intelligenceand what you create should belong to you. This is your particular intelligence, the knowledge of time, place and circumstance, something that no one else can possess.” The message is tremendously ironic, but the reflection is useful and makes perfect sense: “if learning flows in only one direction, the economic value converges towards the owners of the learning infrastructure instead of towards the creators of knowledge.” Therefore, according to Nadella, “it is imperative that we distribute the learning infrastructure to be able to control that learning loop.” Advice for the age of AI (for companies, of course) In short, Nadella continues developing an idea in which what he explains is that the true competitive advantage of AI in the business environment does not lie in choosing the best model, but in owning its learning cycle. What if Microsoft ‘rents’ Claude either ChatGPTbut then it is Microsoft users who train that external model, that knowledge stays in Microsoft and don’t flow to Anthropic and OpenAI. At least free. Of course, and this would end up… Azurethe Microsoft cloud. Because the models belong to others, but if users access them through the Microsoft cloud, then Microsoft should keep all that valuable information, such as the corrections they make to the different models that have been used, remember, thanks to the Microsoft cloud. “If learning flows in only one direction, economic value converges towards the owners of the learning infrastructure rather than towards the creators of the knowledge” On the sidelines, in his very long message, the CEO of Microsoft proposes five points to ensure the company’s profits. Because, if in the era of the cloud companies accumulated data, in the era of AI they accumulate learning, and that learning should not escape if the following advice is followed: Control: create private evaluations, retain ownership of the company’s memory, comments and institutional context. Ability– Build proprietary learning environments within the confines of your own server to train or tune models without exposing company knowledge. Choice: decouple that from any individual model and be able to adapt to any AI model. Cost: thanks to that decision, you can bring together the context, models and efficient and profitable tasks without sacrificing quality. Capitalization: bringing together the four elements above to create a continuous learning loop that allows AI investors to multiply the value of the company. In the end, another thing that Nadella seeks is that there is no competition in the choice of models. Claude, GPT and Gemini are already good enough, so what companies that do not have equivalent models must do is compete to obtain all that knowledge of the learning loops, that does not escape from those companies and that, specifically, are built in Azure. Others have the models, Microsoft, Amazon and Google the servers. Now, not everyone agreesand both OpenAI and Anthropic they assure that their workflows and updates do not depend so much on those loops, but on other issues to keep frontier models evolving for customers who are not big whales like Microsoft. Because learning loops can work if you have Azure ready to provide the service, since the client does not care which model you use because there will always be a working model, but not all companies … Read more

South Korea had a tech king since 2000. The AI ​​fever just crowned another

When one talked about South Korean technology, the company that always came to mind was Samsung. The semiconductor giant and the mobile industry He seemed to be the undisputed leader of his countrybut that’s about to change. Sk Hynix is ​​the new darling of the South Korean technology industry, and it has achieved this driven by memory crisis. Surprise in sight. Since 2000, Samsung Electronics had maintained imperial dominance in the Asian country, and since then it has been the flagship of its economy. However, things have changedbecause its eternal rival, SK Hynix, has been one of the great beneficiaries of the memory crisis. Source: Reuters. Seen and unseen. Yesterday the company’s shares reached their all-time high, briefly surpassing in market capitalization to Samsung, a colossal milestone that makes clear the impact that AI has on the global economy. Memory chips were a good business before, but now they are the star technological product. In yesterday’s session, however, SK Hynix dropped 12.5% ​​in value, which made Samsung (which also fell significantly) regain that throne again in market capitalization…for now. Sk Hynix rises from the ashes. In 2002, the company (then called Hynix Semiconductor) was drowning in debt. It had executed an aggressive expansion plan that did not work well and was on the verge of being sold to Micron (the offer was announcedIn fact, although was rejected). Its shares, which went public in 1996 at a price of 20,000 won, fell to 135 won in 2003, which made it considered a company doomed to failure. After years of crossing the desert and suffering the cyclical crises in the RAM memory market, the rise of AI has transformed it into one of the most valuable chip manufacturers on the planet, competing head-to-head with Samsung or Micron. A goose that lays the golden eggs called HBM. The turning point came after a crucial strategic decision. In 2023 the semiconductor industry was in free fall in terms of prices, but at SK Hynix they decided not only to maintain, but to accelerate their investments in high bandwidth memory chips (High-Bandwidth Memory, or HBM). These memories are the most in demand in the field of GPUs aimed at data centers, and thanks to that commitment SK Hynix has taken 61% of the global HBM chip marketwell above the 17% that Samsung has. Of commoditynothing. The president of SK Group—parent of SK Hynix—, Chey Tae-won, indicated how historically memory had become a commodity. It made no difference to buy a module from SK Hynix, Samsung or Micron because they were almost clone and interchangeable chips. With HBM technology the story changed: it is a component so optimized and integrated with AI chips, that Nvidia’s dependence on these chips is enormous. Samsung defends its leadership. He surprise temporary has not gone down well with Samsung. Those responsible have indicated that market capitalization calculations should include preferred shares. If they are included, Samsung’s capitalization value would continue to be higher than that of SK Hynix. Samsung is currently the leader in this area, but the market trend seems to favor the theory that SK Hynix will end up being more valuable as long as this memory crisis continues. The threat to DRAM. The danger for Samsung not only comes from SK Hynix being the undisputed leader in HBM memories, but from the fact that it is also is growing noticeably in conventional DRAM memories. According to Bank of America estimates, SK Hynix will expand its wafer production by 38% between 2025 and 2028, while Samsung will only do it 17%. At SK Hynix they are putting everything on the table, and that is causing the (economic) gap between both companies, previously enormous, to practically no longer exist. In Xataka | The RAM memory trident already works on DDR6 technology. It will be for the hyperscalers, of course

Big Tech offers you up to 15 GB of free cloud storage. O2 Cloud makes them look ridiculous and gives 10 TB to its customers

O2 customers are in luck. The operator communicated yesterday a fantastic change in your offer – so far O2 Cloud offered 1 TB of cloud storage included in that plan. Now that capacity is expanded dramatically, with customers now able to access 10TB of cloud storage. It is something amazing if we compare this offer with the space offered by default by Google, Microsoft or Apple, but there are some drawbacks. 10 TB “free”. Years ago, Movistar created Movistar Cloud as an option to create backup copies of your files, and that was striking from the first moment because it also the service’s storage space was theoretically unlimited. O2 Cloud joined that offer some time later, and did so initially with 1 TB of free space (included in the plan) which is now multiplied by ten. If you only have an O2 mobile, you also have 10 TB. Until now this offer was valid for fiber users (whether they also had mobile lines or not), but now O2 offers O2 Cloud with 10 TB of storage included to any user of its services: if you have an O2 mobile line, with or without fiber, you have 10 TB of O2 Cloud for free, included in the plan. Apps for Android and iOS. The service is intended to be a “Dropbox” or “iCloud” that constantly backs up your photos and videos to O2’s cloud storage space. Just install the android app or that of iOSconfigure it by registering for the service and that’s it: we will have those copies for free as we are O2 customers. In the image, the O2 Cloud interface from the web browser. We can view the photos directly there, and the operation is surprisingly fluid. Also on Windows or Mac desktop. It is also possible to use O2 Cloud to save images, videos or documents from a personal computer. I have tested it on my Mac, and it is possible to download the desktop client so that it works in the background: everything you put in the “O2 Cloud” folder will automatically be synchronized with the operator’s cloud storage space. Integrated image editor. This service seems especially designed to safeguard the photos on our mobile phone so that if we lose it or it is stolen, they will remain safe. But it is also a great service for viewing them (it runs very smoothly) and even editing them: the integrated editor offers some basic filters (Sepia, Gray, etc.) and also a few editing tools that give more added value to the solution. The integrated editor is limited, but it can get us out of a quick fix. Customize folders or albums. From there, it is possible to access and download content from our devices, and in O2 Cloud we can also create personalized folders or albums to organize photos and documents based on their theme, location, etc. O2 makes Big Tech look ridiculous. The O2 Cloud service is surprisingly generous, especially when compared to what big technology companies offer. Google offers 15 GB of free storage when you create an account, while Apple and Microsoft offer 5 GB. If you want more, you have to pay, and that’s where subscriptions to paid plans like Google One/Workspace come in, Apple iCloud+or Microsoft 365/Family. We have made a small comparative table, and it is clear that those 10 TB of O2 Cloud are a true gift for the operator’s customers. Ability Monthly price o2 cloud 10TB Included with Fiber/Mobile plan Apple iCloud+ 6TB 29.99 euros Google One 5TB 21.99 euros Microsoft 365 Family 6TB (Up to 6 users, 1 TB per user) 13 euros Dropbox 3TB 12 euros But Big Tech offers other things. It is important to note that it is understandable that big technology companies are so stingy with the free space they offer to users: with hundreds (or thousands) of millions of customers, offering more capacity would force them to grow extraordinarily in resources in their data centers. But in addition, payment services such as Google One, iCloud+ or Microsoft 365 are rather “multiservice” because mix storage with productivity tools, security and, in some cases, AI plans. But if you only had iCloud for photos… However, many users are forced to contract Apple iCloud+ or Google One to maintain that backup of your photos in the clouds of these companies and “everything just works.” The O2 Cloud proposal presents a fantastic alternative for these users, because they get the same thing without paying extra: the plan they have with O2 would already serve to enjoy this service. The integration of those services will always be superior to that of O2 Cloud, of course, but for that basic backup use, the alternative seems extraordinary. What happens if I leave O2?. There is no permanence in O2, but logically if we go to another operator, we will lose access to O2 Cloud. The company gives 30 days to download the files if you unsubscribe before deleting them, which of course gives the option to recover all that data and save it, for example, on an external hard drive and then move it to another cloud service if we wish: there are no (unfortunately) tools or services that allow this “migration” from one cloud to another. Common Terms of Use. O2 Cloud has some terms of use and of privacy which are already common in this type of services. In O2 they explain for example that: “To manage some of the functions necessary to provide the service, we have contracted trusted suppliers who may have access to personal data, who will act as data processors and who will be contractually obliged to comply with their legal obligations as data processor, to maintain the confidentiality and secrecy of the information.” They also clarify that “some of the functions necessary to provide the service are contracted to data processors located outside the European Economic Area”, although they guarantee “an adequate level of protection of personal data”. The personal data … Read more

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

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.

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

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

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

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

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

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

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