bubble

If anyone was waiting for the AI ​​bubble to burst, NVIDIA’s results have a message: sit tight

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NVIDIA just published your results of the fourth quarter of its last fiscal year and has left Wall Street speechless. Revenues of $68.1 billion, a net profit that almost doubles that of the same period of the previous year, and a forecast for the following quarter that has far exceeded analysts’ expectations. And all this in a turbulent context where more efficient models and other alternatives are beginning to appear. The crash of DeepSeek is far away, and the demand for chips does not slow down. We tell you the numbers in detail. In case your position was not clear. Only a handful of companies in history have exceeded $100 billion in annual profit. Alphabet, Microsoft and Apple are in that club. NVIDIA has just joined them, with $120 billion in profits in the last twelve months, according to the report. The difference is speed: just three years ago, its annual profit was 4.4 billion. We can say with certainty that no technology company has ever grown so quickly on that scale. AI, and more AI. The engine that has driven these profits is its data center business, which generated $62.3 billion in the quarter, 71% more than a year ago. Within that segment, if we focus on their Blackwell chips, they have gone from entering 32.6 billion to 51.3 billion, while the networks (NVLink, Spectrum-X and InfiniBand) grow from 3,000 to 11,000 million. Gross margin is 75%, and earnings per share nearly double to $1.76 in GAAP terms (which is the official rulebook that companies follow to demonstrate transparent accounting). What Jensen Huang says. “Without computing, there is no way to generate tokens. Without tokens, there is no way to grow revenue.”, counted directly the CEO of NVIDIA in the meeting with investors. Their thesis is that in the new AI economy, computing power directly equates to revenue for their customers. That is why the large cloud service providers (Google, Amazon, Microsoft, Meta) continue increasing your capex budgetswhich together will exceed 500,000 million dollars in 2026 to build AI data centers. And NVIDIA is the main beneficiary of that expense. What DeepSeek has not broken, but accelerated. At the beginning of 2025, the emergence of the Chinese DeepSeek model generated an unprecedented tremor in the markets, leaving a simple question in our minds: if AI becomes more efficient, why do we need so many chips? The answer from NVIDIA’s results is that efficiency does not reduce infrastructure demand, it multiplies it. Every improvement in inference efficiency lowers the cost per token, encouraging more companies to deploy more AI applications, which in turn requires more compute. It’s like Jevons’ paradox, but applied to AI: efficiency expands the market instead of contracting it. Agentic AI as the next catalyst. On the same call with investors and analysts, Huang stood out that “enterprise adoption of agents is skyrocketing.” AI agentsthese systems that make decisions and execute tasks autonomously, require many more inference cycles than chatbots. They are the next step in the AI ​​value chain, and NVIDIA is once again in a privileged position. Colette Kress, CFO of the company, confirmed In addition, the first samples of Vera Rubin, the next generation of chips that will arrive later this year, have already been sent. China and the competition. Not everything is green. NVIDIA acknowledged that its forecast for the next quarter ($78 billion) does not include computing revenue in China. The company has generated just about $60 million from H20 chips since the Trump administration reapproved some sales in August 2025, according to SEC filings, and has yet to earn revenue from the most recently approved H200. Regulatory uncertainty with Beijing remains a small China in Huang’s shoe. In parallel, competitors such as AMD, Broadcom or Google’s own custom chips (TPUs) are gaining ground. But the NVIDIA CEO remains focused on his vision. And according to pointed at the meeting: “Every company depends on software, and all software will depend on AI.” As long as this is fulfilled, everything indicates that NVIDIA will continue selling the blades and picks. Cover image | NVIDIA In Xataka | NVIDIA was founded by three engineers, but only Jensen Huang remains CEO: “I wish I had kept some shares”

OpenAI’s biggest fear is not that the bubble will burst. It’s just that I do it ahead of time

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Sam Altman has admitted in an internal memo published by The Information that Google is catching up technologically with Gemini 3. That’s a real problem for OpenAI, but OpenAI’s real concern isn’t that. It’s just that he needs the party to last long enough to give him time to build his own infrastructure. Why is it important. OpenAI plans to burn more than $100 billion in the coming years pursuing AGI. But it is completely dependent on Microsoft for servers, NVIDIA for chips, and external investors for financing. Google, on the other hand, already has its own TPUs and generates 70 billion in free cash flow per year thanks to Search, YouTube and Google Cloud. If the music stops early, one survives and the other doesn’t. The paradox of timing. OpenAI faces a very peculiar race against time: If investment in AI slows in 2026 or 2027, it will have spent tens of billions but will not have completed its own infrastructure. You will remain tied to expensive suppliers. You will not be able to compete on costs with Google. Staying halfway is the worst possible scenario. Instead, if the bubble lasts until 2030 or beyond, OpenAI will probably have reached the threshold of self-sufficiency. It will have its own chips, its own data centers, economies of scale. It will be able to survive even when the investment tap is turned off. It’s like building a bridge: it doesn’t matter how much you’ve spent a lot. If you only get halfway, it’s of no use. The absence of moat. OpenAI cannot protect itself with sustainable technological advantage. In AI there are no defensive moats (moats) real. Every time OpenAI or any other lab makes a breakthrough, the rest replicate it within months. The only sustainable advantage OpenAI has left is cost. If you control your infrastructure, you can offer prices that no one else can match. If you do not control it, you become a dispensable intermediary between the end customer and whoever does have the chips and servers. The context of the memo. The document published by The Information reveals that Altman anticipated turbulence after the launch of Gemini 3. Google’s new model stands out precisely in the areas that generate the most revenue for OpenAI: automation of web design and programming. Altman acknowledged to his team that “Google has been doing an excellent job lately” and warned that he expects “the environment to be tough for a while.” But he urged them to stay focused on “achieving superintelligence”, admitting this would mean being left “temporarily behind in the current regime”. The figures. OpenAI went from almost non-existent revenue in 2022 to projecting 13 billion this year. It is one of the fastest business growth in history. But it plans to earn 200 billion in 2030. To achieve this, it will need to multiply its current income by 13 in less than five years. Meanwhile, it plans to spend $90 billion on R&D alone through 2030. That represents 45% of its projected revenue. Large technology companies allocate between 15% and 30% of their gross profit to research, not their total income. If OpenAI falls short of its billing goal, that percentage will be even higher. Yes, but. Google has structural advantages that are difficult to overcome: Generates a huge cash flow thanks to consolidated and very profitable products. You can afford to burn money on AI for years without too much trouble. And it already has its own infrastructure after a decade developing TPUs. OpenAI, on the other hand, lives off external funding. His recent agreement with Oracle to design data center components in the United States is an attempt to build that self-sufficiency. Altman presented it as “a step to ensure that the core technologies of the AI ​​era are built here.” At stake. OpenAI’s technological advantage over rivals such as Google and Anthropic has narrowed. Investors have sunk more than $60 billion into OpenAI, recently valuing it at $500 billion, betting that it will continue to dominate the market for AI that creates content and reasons like humans. That bet falters. Anthropic, founded four years ago by former OpenAI employees, is skyrocketing its valuation and aiming to generate more revenue than its former home selling AI to developers and companies. Their models specialize in generating computer code. And ChatGPT is still far ahead of Gemini in usage and revenue, but the gap is narrowing. Between the lines. Altman concluded his memo by acknowledging the pressure: “It sucks that we have to do so many hard things at the same time: the best research lab, the best AI infrastructure company, and the best AI platform/product company. But it’s our destiny in life. And I wouldn’t trade positions with any other company.” The question is not whether OpenAI can technically compete with Google. It’s whether you can hold on financially long enough to stop depending on others. Featured image | Xataka In Xataka | There is a generation working for free as a documentarian of their own life: they are not influencers but they act as if they were.

The AI ​​bubble is so obvious that not even Sundar Pichai or Satya Nadella make an effort to deny it

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The thing about bubbles is that we are certain that there is one only when they burst. And with all this artificial intelligence, is talking a lot about whether or not there is one around this technology. Of course there are indicators that set off alarm bells, but the curious thing is that we would not have believed that two of the greatest exponents in contributing to the development of this technology would maintain reservations. And Sundar Pichai, for Google, and Satya Nadella, for Microsoft, have not made much effort to deny the doubts. Irrationality. Pichai declared to the BBC in an interview he noted “elements of irrationality” in the current AI market and warned that no company, including Google, will be immune if the bubble bursts. His words are especially striking because they come at a time when Alphabet shares have doubled in seven months, reaching a market capitalization of $3.5 trillion. The CEO compared the situation with the Internet bubble of the late 90s, recognizing that although there was excessive investment that ended in bankruptcies and layoffs, today no one questions the profound impact of the Internet. “I hope AI is the same. I think it’s both rational and there are elements of irrationality in a time like this,” he explained. When the numbers don’t add up. Skepticism is based on concrete data. OpenAI, Google’s most visible competitor in this field, has committed to spending $1.4 trillion in infrastructure for eight years while it expects to generate just $13 billion in revenue this year. Just like share In the Ars Technica media, Sam Altman himself, CEO of OpenAI, acknowledged to journalists in August that investors are “overly enthusiastic” about AI models and that “someone” will lose an “incredible amount of money.” Microsoft also shows the cards. For his part, Satya Nadella has been equally forthright about the current limitations of the sector. At the beginning of the year already pointed out to claim that a milestone has been achieved in AGI (general artificial intelligence) is “just hacking the tests without meaning”, downplaying the benchmarks that so much marketing generates. According to Nadella, the true metric of AI success should be reflected in countries’ gross domestic product: “When we say ‘this is like the industrial revolution,’ we should have that kind of growth that caused the industrial revolution,” he explained, referring to increases of 5-10% in GDP. That growth has not yet come. Jensen Huang says exactly the opposite. While Pichai and Nadella talk about irrationality, NVIDIA founder and CEO Jensen Huang has presented spectacular results in the third quarter and settled the debate in his own way. “There has been a lot of talk about an AI bubble. From our perspective, we see something very different,” he commented. NVIDIA reported revenue of $57 billion in its latest quarter, up 62% from a year earlier, with net profits of $32 billion. Its data center business has generated $51.2 billion, a record boosted by the sale of its Blackwell chips. According to Huang, sales of these GPUs are “skyrocketing” and cloud chips are out of stock. NVIDIA also projects a fourth quarter with revenues of $65 billion. AI still doesn’t make money. NVIDIA does make money, a lot of money, but He does it by selling the shovels during the gold rush. The vast majority of companies that develop large language models are losing money spectacularly. OpenAI is the most obvious examplebut not the only one. Microsoft, Amazon, Meta and Google they are allocating tens of billions of dollars to build data centers dedicated to AI in a colossal bet whose profitability is not guaranteed. For Nadella, what AI needs is something equivalent what Excel and email meant for the PC, that is, an app that makes the majority of users understand how to use AI. At that time we saw that the PC took a long time to find its place, especially until it reached mass adoption that transformed real processes. There are chips but there is no energy to power them. In addition to the profitability problem, there is an immediate physical limitation. Nadella revealed recently that the biggest obstacle is not the lack of chips, but the energy needed to power them. “If you can’t do something like that (supply enough power), you’re going to have a bunch of chips sitting around in inventory that you can’t plug in. In fact, that’s my problem right now: It’s not that I don’t have a sufficient supply of chips: it’s actually the fact that I don’t have places to plug them in,” he admitted. Microsoft, Google and other big technology companies are resorting to drastic solutions such as building their own small nuclear power plants (SMR reactors) to supply their future data centers. ARM CEO Rene Haas noted that energy needs could triplea challenge that calls into question the sustainability of the current expansion. Of course we don’t know how things are going to end, but no one doubts that we’re going to have a good time with it. Cover image | Microsoft and Bloomberg In Xataka | Gemini 3 promises more quality and precision than ever in its responses. The question is whether we will really notice the difference

NVIDIA and OpenAI know that the AI ​​bubble can burst in their faces. His solution: let dad pay for the state

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Too big to fail or, in English, “too big to fail.” It is a theory of economics and finance which argues that certain corporations, especially banks, are so large and so interconnected that their failure would have catastrophic consequences for the global economy and therefore must be rescued by governments. The speech gained traction in the 2008 financial crisis and is beginning to sound again from the mouths of NVIDIA and OpenAI, no less. Government support. At an event of WSJSarah Friar, CFO of OpenAI, stated that the company will not go public in the short term (she says until at least 2027) and that its priority is growth and investment in R&D, above profitability. The most striking part of his speech was when he said that they hope that the government will support the financing of future agreements related to data centers. That OpenAI is burning astronomical amounts of money to lead the AI ​​race is something we have been discussing for a long timebut it is the first time that they directly appeal to the state to guarantee it. Shortly after, Friar collected cable in a post on LinkedIn: “OpenAI does not seek government support for our infrastructure commitments. I used the word ‘support’ and that confused the message,” but the seed was already planted. Depreciation. OpenAI is closing deals to secure computing capacity. We have seen it with his alliance with NVIDIAwith amdwith Broadcom and more recently with amazon. The complexity of the situation is that the depreciation rates of AI chips remain uncertain. As it says Washington Post’s Gerrit de Vynck in XOpenAI is going to need the best chips to be at the forefront of the AI ​​market, but financing this demand is not the same if the life cycle of the chips is seven years, as if it is only two years. The money is flowing, the question is for how long. In this uncertain scenario, government support would act as a safety net so that banks and private equity firms would feel more comfortable and continue releasing billions for OpenAI. China will win. NVIDIA is also appealing for government involvement in subtle ways. In a Financial Times event in London, Its CEO Jenshen Huang has warned that “China is going to win the AI ​​race.” Their arguments are that China has more flexible regulation and government subsidies for the energy your data centers needthat It is not little. This energy advantage allows China to compete even if they cannot buy NVIDIA’s most powerful chips. Huang doesn’t say it directly, but it is a clear wake-up call: either you subsidize the energy our data centers need or China will win. The fear. The question has been hanging over the air for a long time: Are we witnessing a new bubble? The investor Michael Burry thinks soand he is not just any investor, he was the one who made gold when the real estate bubble burst in 2008 (the movie ‘The Big Short’ is based on his story). The thing is, Burry just bet short against NVIDIA, which recently It was valued at 5 billion dollars. Fear of the bubble continues to grow, according to a Coatue report and the number of fund managers who believe we are in a bubble increased to 54% in October, up from 37% in July this year. 48% of the S&P 500 index corresponds to AI-related stocks. Fountain: Bianco Research Numbers. The fear is not at all unfounded and all you have to do is take a look at the numbers. Account Tomás Pueyo in Uncharted Territories that the economy should be in recession, but the numbers show the opposite and AI is behind this growth. The S&P 500 index is through the roof and 48% of this growth corresponds to AI-related stocks. The share price is far above what it was in the dotcom bustall with ridiculous benefits. And that’s not all, the economic growth of the United States in 2025 is due almost entirely to the construction of data centers for AI. According to the Economist Jason Furmanwithout taking data centers into account, the GDP of the United States would have grown only 0.1% in 2025. The creator of the newsletter Today in Tabs He gave a very graphic example: “Our economy could be reduced to three AI data centers in trench coats.” Tightrope. Returning to OpenAI, its financial director assured the Financial Times that it could be profitable simply by stopping investing too aggressively since it has a “very healthy” margin structure. The thing is, they can’t do it. OpenAI needs to achieve AGI, its great promise and the only thing that could justify this insane investment. If it fails, will cause a shock wave that can impact NVIDIA, AMD, Oracle… and end up dragging down the global economy. The competition tightens, Anthropic is eating the business market’s toast and Google is not only winning every time more users with Geminireached record revenue in the last quarterwhile OpenAI lost $11.5 billion in the same period. It doesn’t look good. Images | Wikipedia In Xataka | NVIDIA will invest 100 billion in OpenAI so that OpenAI buys chips from NVIDIA. And it’s a disturbing sign

Michael Burry just shorted NVIDIA. All good except because he was the one who predicted the 2008 real estate bubble

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Michael Burry, the well-known investor and fund manager who predicted the 2008 financial crisis, has recently shown his bearish positions against NVIDIA and Palantir just after launching on social networks a warning about excess optimism in the market. Warning which the Bloomberg media has qualified ‘cryptic’, for several reasons. The movements, made known in regulatory documents filed on Mondayhave reopened the debate on whether artificial intelligence is generating a speculative bubble. What exactly has Burry done. His investment fund, Scion Asset Management, has bought put options (puts) worth $186.5 million against NVIDIA and $912.1 million against Palantir, according to mandatory filings with the SEC. These options benefit if the stock price falls. Burry also took bullish positions (calls) in Pfizer and Halliburton, two stocks that have underperformed the market this year. Why does it matter? Burry is not just any investor. Its history is marked by having bet short against the US real estate market two years before the 2008 crashenduring criticism from his investors until Lehman Brothers went bankrupt and his fund multiplied its profits. His story inspired the film ‘The Big Bet‘. Having gained that fame, when Burry bets against something, the markets pay attention, although his track record is not infallible, as he has been wrong in the past with other bubble predictions. Click on the image to go to the post The context of their movements. Days before these positions became known, Burry broke two years of silence on social networks with a disturbing message: “Sometimes we see bubbles. Sometimes you can do something about it. Sometimes the only winning move is not to play,” accompanied by an image of his character in the film. On Monday night he posted again, this time sharing a Bloomberg chart about concerns about circular financing between OpenAI, NVIDIA and other AI companies. Market reactions. Palantir shares fell more than 10% following the news, even though the company had just raised its annual revenue guidance. NVIDIA also fell by up to 2.9%. Palantir CEO Alex Karp responded in an interview with CNBC calling the idea of ​​shorting against companies like Palantir and NVIDIA, which he says are doing “noble tasks,” “crazy.” The bubble debate. For months, many investors have expressed concern about whether the AI ​​boom is being artificially sustained. Ray Dalio, founder of Bridgewater Associates, warned recently told CNBC that “there are many things that look like bubbles,” although he clarified that bubbles do not usually burst until the Federal Reserve tightens its monetary policy. According to its “bubble indicator”, approximately 80% of market gains are concentrated in large AI-related technology companies. An important nuance. It’s not entirely clear whether Burry is betting directly on the downside or whether these options are part of a more complex strategy to protect other investments. And just as share Bloomberg, regulatory filings only reflect long positions, so if you were using these puts as a hedge for other investments, we wouldn’t know. The curious thing is that its first quarter presentation did include a note explaining that puts “could be used to cover long positions”, but the third quarter presentation does not say anything about it. Scion’s recent history. This is not the first time Burry has bet against NVIDIA. During the first trimester He has already liquidated almost his entire portfolio of listed shares and bought put options against the chipmaker. However, it has also achieved success: in the third quarter it closed positions in Alibaba (with a 36.5% profit), Estée Lauder (27%), ASML Holdings (45.7%) and Regeneron Pharmaceuticals (10.8%). Canary in the mine or false alarm? The question on Wall Street is whether Burry is once again detecting a bubble before anyone else or if he is wrong this time. NVIDIA is up 54% this year until reaching a capitalization of 5 billion dollarswhile Palantir has soared 173% thanks to its expansion in AI-related businesses. Valuations are high, but both companies continue to grow and expand their business. Be that as it may, if there is a bubble, we will find out in the worst possible way: when it bursts. Cover image | Solen Feyissa and ‘The Big Short’ In Xataka | The geopolitical irony that we are experiencing in the chip war has an unexpected beneficiary: Russia

If you thought the AI ​​bubble was worrying, it’s because we hadn’t entered its next phase: debt

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Big technology companies have issued $75 billion in bonds and loans between September and October 2025: Meta leads with 30,000 million. Followed by Oracle (18,000 million in bonds plus a loan of 38,000 million). And Broadcom (27 billion). The figure is equivalent to what these three companies used to borrow in an entire year. Why is it important. The shift from liquidity to debt marks a turning point in the AI ​​race. For years, these companies financed their infrastructure with cash flows, but now they are resorting to debt: Debt not linked to bonds has gone from 15% to 30% of its capital. The money trail. Oracle has closed the largest syndicated loan (a joint loan by several banks to a single client) in its history: 38 billion for data centers. Meta, for its part, is allocating its 30,000 million to campuses in Virginia and Oregon. And Broadcom uses them to strengthen its semiconductor division and its network equipment. The threat. Paying the interest on all this debt now consumes 15% of these companies’ operating profits, compared to 10% a year ago. And the cost of borrowing has risen: corporate bonds are near their most expensive levels since 2022. If the energy bill rises by 20% – a more than likely scenario given the stress on electrical networks – or if AI does not generate the expected revenue, these companies could see their credit rating reduced and trigger a chain crisis. Yes, but. Large investors continue to buy these bonds, attracted by returns of 6%. Money flows because official interest rates are at 3.75%so lending to these technology companies seems like a good deal. The problem is that any sudden change in rates can make these bonds lose value. And fast. At stake. Debt finances the AI ​​revolution, but also makes it more fragile and technology companies continue to increase their investment. If inflation returns or profits fail, the same debt that accelerates innovation could become a liability. Investors, meanwhile, continue to win; but they assume the risk of the storm. In Xataka | Apple is resisting the push for AI PCs because AI PCs have caused complete indifference Featured image | Towfiqu barbhuiya

When asked if AI is a bubble about to burst, big technology companies have just responded: hold my cap

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The AI ​​race is about computing power and data centers the size of entire cities. And that doesn’t exactly come cheap. Big Tech is spending indecent amounts of money so as not to be left behind in AI and the fear that everything is a bubble flies over the environment. That doesn’t seem to stop them. Microsoft, Google and Meta have announced that they are increasing their planned spending on AI. what’s happening. Microsoft, Google and Meta have just presented their results for the last quarter and there are two pieces of news. The good thing is that all three have managed to increase their income. The not-so-good news is that they have sent a message to their worried investors: they are going to spend even more money than they planned on data centers and AI infrastructure. More wood. That AI is a bonfire of money we already knew it. Now we know it’s going to get even bigger. Meta had planned that Capex (capital expenditures) for 2025 would be $66 billion. Now they just said that The total will be between 70 and 72,000 million. And not only that, next year it will be even bigger. For its part, Alphabet (Google) had planned a Capex of 75,000 million, but they confirm that They will spend between 91 and 93 billion dollars. Finally, Microsoft has not given the annual data, but in this quarter They have spent 34.9 billion dollars5,000 million more than planned. In 2026 they expect spending to be even higher. Planned CAPEX REVISED CAPEX goal 66 billion 70-72 billion +24% GOOGLE 75 billion 91-93 billion +23% microsoft 30,000 million (quarterly) 34.9 billion (quarterly) +23% Also more income. Don’t panic, or at least not too much. All three have achieved record profits in this period. Meta earned 51.24 billion, Google 102.3 billion and Microsoft 70.1 billion, an increase of 26%, 16% and 13% more than the same period last year. All three assume that the numbers will continue to grow, and that is precisely what Those who warn of a bubble are not so clear. It’s not AI, it’s the cloud. In the case of Microsoft and Alphabet, the main vector of revenue growth is their cloud business, a trend that It started in the previous quarter and has continued to increase. Google Cloud generated 34% more revenue thanks to growth in “core products, AI infrastructure, and generative AI solutions.” In the case of Microsoft, its cloud services brought in 26.8 billion, 33% more than last year. And I published it. Meta is building data centers like there’s no tomorrow, but it doesn’t have a cloud business. Mete has something else: Facebook and Instagram. Its income comes largely from advertising and Zuckerberg assures that the good numbers come precisely because They are applying AI to improve their advertising systems. Not so fast, Zuck. Although Meta is the one that has increased its income the most compared to last year (26%), its shares have fallen 8% after announcing that it would continue to increase spending on AI. It seems that investors have quite a few doubts about their latest decisions, such as spend a million to create your superintelligence team or the plan to spend $600 billion in data centers. Image | Pixabay In Xataka | OpenAI is burning money like there is no tomorrow. The question is how long can he last like this?

OpenAI is building the biggest house of cards in history. Its “circular financing” aggravates the threat of the AI ​​bubble

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Yesterday OpenAI and Broadcom announced a collaboration agreement that will see both companies design and deploy 10 GW of custom AI chips over the course of four years. It’s a new episode of that unusual strategy that OpenAI has carried out and which is summarized in an increasingly disturbing concept: that of circular financing. Multimillion-dollar agreements. In recent weeks we have seen how OpenAI has reached new agreements worth billions of dollars with large companies in the semiconductor sector. Thus, we have: Circular financing. All these advertisements respond to a unique circular financing strategy in which chip companies (the suppliers) not only sell their products to an AI startup (customer), but also invest capital in that startup, which in turn uses that capital to buy more products from its investor. In reality, the supplier “does not invest” as such, because that money ends up going back into purchases of its products and services. It is in fact something similar to what OpenAI did with Microsoft when the latter invested $13 billion in it. Rather than investing them, it allowed him to use a kind of subscription for that amount to use his cloud, Azure, and its computing resources. It’s a win-win for some and for others. OpenAI wins. These agreements allow OpenAI to have guaranteed access to computing, something you need like eating. The startup spends billions a year and still not profitablebut thanks to this strategy he obtains a massive flow of capital. In the case of Broadcom, it also manages to collaborate in the design of customized chips for minimize future dependence on other partners (such as NVIDIA or AMD) and thus enjoy a lower total cost of ownership in the long term. And by signing with three different semiconductor suppliers, it encourages competition and improves its bargaining power. Bright. Suppliers win. The circular strategy also benefits NVIDIA, AMD and Broadcom. All of them gain a customer with almost unlimited demand, and can register immediate income from the sale of chips while the cost of the investment is amortized over time. NVIDIA also manages to maintain its dominant position, while AMD and Broadcom manage to expand in this market. If there are also actions involved, all of them are revalued and participating in each other is another element of interest in these financial operations. They reinforce and grow larger among themselves, and while they weaken all the others. A gigantic house of cards. But compared to that strategy, reality. And the reality is that this circular flow of capital is creating artificial demand in which the supplier pays itself. The systemic risk is enormous: if OpenAI fails or AI growth slows, the domino effect can significantly affect these vendors and their investors. We are facing a huge (and fragile) house of cards that, if it collapses, will have equally enormous consequences. The AI ​​bubbleif it really exists, continues to grow and grow. Total uncertainty. There is also absolute uncertainty about the promise of AI: will we really use it as much as these companies think we will? Will OpenAI be able to deliver on its promise and turn a profit in 2030? It is impossible to know. Finally, another problem: these circular agreements make these companies larger, but they make the entry of new competitors in both markets increasingly complicated. There are winners, but also losers. While all this is happening and the shares of these companies are skyrocketing, the reality is that there are also losers. The retail investor is blind to these events—and suspicions about cases of insider trading They are inevitable. And of course when talking about competition we are not talking about new competitors, but also current ones. Anthropic or Perplexity, with already established businesses, now finds it more difficult to compete. Google, Microsoft or Meta have plenty of infrastructure and economic resources, but they are still seeing how OpenAI is getting bigger and bigger without being able to prevent it. If successful, OpenAI may end up being above all of them, because it seeks the same thing that every company seeks even if it does not admit it: become a monopoly. Image | Xataka with Freepik – Gemini In Xataka | You thought you had an amazing connection on Tinder, but you were actually chatting with ChatGPT

The Irobot co -founder believes that there is a robotics bubble

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Rodney Brooks believes that humanoid robots are a bubble condemned to explode. Anyone says it: Brooks was the co -founder of Irobot, the company that manufactures the famous robots aspirations of the Roba family. Too nice to be true. This expert, who before Irobot worked for decades at MIT, does not believe that in the future we live surrounded by human robots. Observe skepticism the developments of companies such as Tesla or Figure, who work in robots that learn to move as humans. In a new essay He talks about this type of way of thinking about the future “is pure fantasy.” The bottleneck of skill. In his opinion, the problem is that trying to imitate the skill of movement of a human hand – for example – is an almost impossible mission. Especially since there are 17,000 specialized tactile receptors (and that detect pressure, vibration, texture or sliding) that it is not possible to find in humanoid robots. There is, however, concrete advances in this area. Insufficient training. According to Brooks, “we don’t have that kind of tradition for touch data.” This area is different from what has been achieved with other areas such as language recognition or image processing. In his essay he explains how learning based on visual videos of humans performing tasks are not enough for robots to acquire that skill. An experiment. To reinforce his theory, Brooks commented on how in an experiment a person was anesthetized the fingertips to analyze the skill of his hands. In this experiment it was seen how the person took four times more to complete a simple task such as lighting a match. The touch sensation, says this expert, is irreplaceable. Tree goes. But it also warns of the security risks posed by these robots. Keeping them standing requires a lot of energy, he says, and if they fall they can end up being A real risk. The reason is that as explained by the kinetic energy of its limbs, it is amplified by the Law of Scale. Robots with tweezers. For him the “humanoid robots” of the future will be of everything but humanoids. Instead in 15 years what we will see are robots with wheels, several arms, industrial tweezers and specialized sensors. The huge current investments that technology companies are making will not crystallize in that theoretical mass production of humanoid robots. China does believe in humanoid robots. Brooks’ arguments are powerful, but the truth is that China is demonstrating have an absolute faith in it future of this segment. The current humanoid robots are limited in their benefits and capacity, but the investment in this market and the advances that are being made are undeniable. What will have to be verified is whether that human skill and tactile perception end up in effect insurmountable obstacles for such robots. In Xataka | China has just opened the first megatienda of humanoid robots. What comes later promises even more

We have been talking for months that there is an AI bubble. The worrying thing is that even Sam Altman agrees

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One thing is that AI pessimists tell us that there is a bubble. Another very different is that Sam Altman suggested, CEO of Openai. But it is what has happened, and that is a worrying indication of the situation in which this segment is located. Every time More expert voices They warn of danger of a bubble from AIbut there are not only voices: there are data that raise a potential crisis. One that could be even more harmful than that of the Puntocom. What has Altman said. The head of OpenAI, the company that develops ChatgPT, invited a group of journalists to comment on the launch of GPT-5. During that meeting, they indicate in The Vergesaid the following: “When bubbles occur, intelligent people are excessively excited about (which is actually so alone) a pinch of truth. Are we in a phase in which investors in general are too excited about AI? My opinion is that yes. Is AI the most important thing that has happened in a long time? My opinion is also that “ Remembering the story. Altman compared the current dynamics with which he experienced During the bubble of the Puntocom In the late 2000s. Between March 2000 and October 2002, NASDAQ lost about 80% of its value: many of the companies that signed up for Internet fever and the web failed La Hora to generate income or benefits. The value of the 10 most important companies of the S&P 500 index is today much greater than the one in the 90s, and that points to a potential (and huge) bubble. Source: Apollo Global Management / Tornsten Slok. Worse than the bubble of the Puntocom. Economic analysts and experts have long offered arguments that point in the direction of a potential bubble of AI. The chief economist of the investment firm Apollo Global Management, Torsten Sløk, indicated in a report That this bubble could be worse than that of the Puntocom: the 10 most important companies of the S&P 500 index have a value well above the 10 that occupied those positions in the late 90s. Too much speculation. Ray Wang, director of the Futurum Group semiconductor firm, showed two faces of the same currency. As he said In CNBC, “From the perspective of a broader investment in AI and semiconductors … I do not see it as a bubble. The foundations of the entire supply chain remain solid, and the long -term trajectory of the trend of AI supports the continuous investment” But at the same time, he stressed that there is a problem with this segment: there is too much speculative investment in companies that have less solid bases and in which there is only one perception of its potential without real foundations – Hello, Safe Superintelligencehello Thinking Machines-. It’s hard, but bubbles have their good side. As Alberto Romero points out In your Newsletter“In a way, bubbles are an inevitable and welcome phase between short -term selfishness and long -term progress.” In his opinion and That of other experts Like Mills Baker, manager at substock: “He Hype It is acceptable under the premise that only an optimistic character, prone to exaggeration and hyperbole, can build the new world for which a bubble is only the starting point, his big bang. The cynical and pessimistic character is a useful counterweight to excessive optimism (…). While optimism is an active creation force, pessimism is a reactive modulation force. “ Source: Paul Kedrosky. When the trains were the AI. Or what is the same: for the world to advance, bubbles are (or can be) necessary. We saw it with the Puntocom: it is true that the crisis existed, but that uncounted optimism in the future of the Internet ended up making sense. Of course, only a few companies (the great current empires) ended up benefiting. But it is that something very similar happened with the railroads at the end of the 19th century. At that time the investment and the capex in these infrastructure was colossal –five times greater that the one who lives now in AI – and although many companies broke, but from that bubble we left with an absolute revolution both at the level of transport and economic and social. But this bubble can be very, very large. As points Romero, the difference here between optimistic and pessimistic (or realistic) speeches is growing, and that is worrying. The expectations that the companies of AI and their CEOs are creating (with Altman in front, The man-hype) They are increasing. They constantly tell us about How are we close to reach the AGIbut the reality is that there are no real indications that this is so and in fact there is a Founder of AI. Faced with the promises of the revolution that theoretically should have begun to generate AI, the reality is that the advances do not seem extraordinary. In fact, a study of the MIT discovered that after asking 150 entrepreneurs and 350 employees of companies that have integrated AI in their processes, 95% had not seen any benefit in doing so. Better Wait for GPT-6. GPT-5 has demonstrated, a model for which we expected A historical jump And that in the end raises an improvement that for now it is discreet and that he introduced changes They were Very criticized. The launch of this model has been a small disaster that He has forced To the company to give reverse In several of your decisions. As He pointed out Walter Bloomberg, Altman himself admitted that GPT-5 had been a failure, and now bets on GPT-6. Source: Michael A. Arouet. The data worries. Seemingly excessive spending In data centers either In talent It is not the only concern. There is also that absolute concentration of companies that concentrate the value. An analyst named Michael A. Aouet published these days A graph in which he showed two income growth trends. On the one hand, that of the 490 companies of the S&P 500 excluding … Read more

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