openai

OpenAi wants to bill as much as Microsoft in five years. For this

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OpenAi projects to enter 2030 about 200,000 million dollars. It is almost the same as Microsoft invoices today, 245,000 million dollars. A company that this year will touch the 12,000 million dollars believes that it will multiply its income in less than five years. To contextualize excess: Apple took four decades to reach those figures. Google, two decades. Openai intends to do so in decade and a half of life, with a nuance: Until three years ago I did not invoice or one hundred million. His “zero moment” was in 2022. The planned growth graph, published by The InformationIt has many layers. The excessive ambition is just one of them. The income is triggered exponentially, but the computer costs – both training as an inference – grow almost linearly. This equation only works if Openai ceases to be what it is today: a company that sells access to LLMS for 20 dollars a month. It needs to be something else that goes much further. The question is not whether they can multiply their income by 17, but what they have to invent to justify such assessment. The secret is in the agents. But not what we imagine. Openai does not aspire to sell you a smarter chatgpt. Aspires to replace entire departments. Deep Research The model already hints: do not charge for consultation but for work done. If a report that previously required three Junior analysts for a week now does an agent in a few minutes, supervised by a single employee, how much is it worth? It is not worth $ 20 of a subscription. It is worth $ 50,000 that these salaries cost. Multiplied by each department of each company of Fortune 500 … Suddenly, the 200,000 million do not seem science fiction. They seem to conservatives. But here comes the existential paradox of OpenAi: pato capture that value need their models to be irreplaceable, unique, unattainable. However, every month that passes, the gap with Claude, Gemini or Deepseek narrows. The Commoditization of the AI It is not a future threat: it is already happening. How do you justify monopoly prices when your product is becoming water or electricity? Openai’s response seems to be the speed: Arrive first. Dominate the market. Create dependence before others can react. It is the old strategy of companies such as Uber or Amazon: losing money to buy market share, praying so that when profitability comes, you are the only one standing. Plan B is in vertical applications. They will not sell generic but specific solutions: The complete customer service system of your company. The educational platform of your university. The legal co -pilot of your office. Each vertical, a new market of billions. This is where the numbers begin to make sense. Microsoft 365 generates Microsoft almost 100,000 million annually. The World Business Software Market Billón approaches. If OpenAI captures just 20% replacing traditional software with intelligent agents, it reaches its goal. You don’t need to invent anything new. You just need to make everything that exists obsolete. Openai’s real bet is not as technological as temporary. They are buying time with 350,000 million in computer costs, betting on the AGI “Or something similar enough, that For something Altman has been moving the goal for some time– It arrives before the money is over. If they get it, those 200,000 million will be an anecdote. If they fail, we will have seen the most spectacular bubble in technological history. And the fascinating thing is not that Openai is trying. Is that everyone who imports –Microsoft, Oracle, Softbank, the US government– They seem to believe they can achieve it. Outstanding image | Adolfo Félix In Xataka | The alliance between Oracle and Openai does not go only from data centers: it goes from advanceing Google, Apple and Microsoft on the right

Openai has just changed the chatgpt rules with Pulse. Stop waiting questions and start anticipating your daily life

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You get a notification to the mobile. It is not the calendar or mail: it is from Chatgpt. It’s called Pulse and, According to OpenAi“investigate proactively“To give you a personalized summary of the day with thematic cards that you can get quickly or open for more detail. The grace is that you stop waiting for your question and advance with ideas and next steps, learning from your chats and your feedback And, if you decide to connect them, of apps such as the calendar. The result is a Briefing Matinal that tries to fit with your routine before it starts. Pulse arrives as a view and, for now, is only available in the ChatgPT mobile application for payment users in THE PRO PLAN. It does not replace the usual model, but is presented as an addition: the assistant maintains the option to answer on demand questions, but adds a new functionality. With this movement, Openai takes the first step towards an assistant who aspires to be present before even the user invoices it. Of the chatbot that responds to the assistant who advances Every night, the system analyzes recent conversations and interactions history to prepare a set of cards with information selected These cards are presented the next day in the application as a daily summary that can be browsing in seconds or expanding to obtain more context. The content expires at the end of the day unless it is saved in the history of chats. In addition, each card can be opened to request clarifications or following steps, so that the experience is not limited to reading, but connects with the usual conversation. Personalization is built on simple signals. The user can give a thumb up or down, ask that the next summary include a specific topic or modify what is not useful. Pulse collects that information and applies it in the next night cycle. Openai points out that all adjustment history is accessible and reversible: it can be consulted or erased when desired. To reduce risks, each set of cards undergoes safety checks that block problematic recommendations or contents that violate the platform standards. One of the characteristics is in the possibility of COnectar Gmail and Google Calendar. In doing so, press can suggest an agenda scheme for a meeting, remember the purchase of a birthday gift or recommend restaurants based on a scheduled trip. These integrations are deactivated by default and are managed from the configuration. Openai insists that they improve the relevance of suggestions, although they also expand the surface of personal information that the assistant handles. The examples are varied and very everyday. Openai mentions from tips to prepare a quick dinner to reminders linked to a trip or training suggestions for a triathlon. In the Chatgpt Lab, several students commented that the utility of Pulse became evident when they began to guide it with concrete requests. One of them reported that, after talking about how to organize his calendar in Taiwan, the system offered him practical steps to optimize train journeys that would not have looked for himself. Openai has been working on the security of his chatbot for some time. Even so, cybersecurity experts warn that the risk never disappears completely. Radware documented a case in which an altered mail managed to The in -depth research function of chatgpt will filter sensitive data. Vulnerability was already corrected, but the example reminds that integrating personal information into such an assistant increases exposure and demands to keep caution. For now, Pulse is in a view phase and only those who have the Pro subscription in the mobile app. OpenAI warns that not always right: Reminders of already closed projects or little relevant suggestions may appear. The idea is to collect that early use to correct failures and refine the model. If everything progresses as planned, the function will open first to Plus clients and then to the rest, in a progressive deployment. It is a launch that fits a broader strategy: to make Chatgpt become a daily assistant and not only a specific tool. OpenAi seeks to increase the time of use and take a step towards the more personal relationship With the application. The movement also marks distance in front of competitors such as COPILOT of Microsoft or Claude of Anthropic, which until now have prioritized professional or productivity uses. According to Reutersthe company also works on a browser with AI that would reinforce this commitment to accompany the user in more facets of their digital life. Images | OpenAI In Xataka | Microsoft has never been so valuable throughout its history. And he has never been so close to the abyss

“Circular financing” between Nvidia and Openai can be the genius of the century … or collapse

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Nvidia has announced A “strategic investment” of up to 100,000 million dollars in Openai. But it is an investment with trap: Openai will use that money to buy Nvidia chips. The semiconductor manufacturer thus becomes the financier of its own most important client. Why is it important. This maneuver dangerously reminds the “circular financing” schemes that characterized the end of the 2000 Puntocom bubble. Companies like Lucent, Nortel and Cisco financed operators as Global Crossing to buy them equipment. We are not the first to see this simile At this stage of AI. When the bubble exploded, both suppliers and customers sank into a spiral of debts and overcapacity. The agreement will allow OpenAI to build data centers with a joint capacity of 10 gigawatts, equivalent to about 10 nuclear reactors. Jensen Huang, CEO of Nvidia, has acknowledged that this represents between 4 and 5 million GPUS: “double those we distributed last year.” Brutal scale In figures. The numbers are astronomical. According to Huang himself in August, creating a 1 Gigavatio data center costs between 50,000 and 60,000 million dollars, of which about 35,000 million are destined for Nvidia chips. With that logic, the 10 projected gigawatts would cost more than 500,000 million dollars. The bags have reacted with euphoria: Nvidia shares rose almost 4%, adding 170,000 million dollars to their stock market capitalization. Jensen Huang Broza’s company is already 4.5 billion dollars of valuation. Yes, but. Parallelism with the ‘Puntocom’ bubble is disturbing. These same schemes of ‘Financing vendor‘We already saw them in the final stage of the 2000 technological bubble. They did not end well for any of the parties. The difference is that current numbers are much larger, even adjusting for inflation. The key is whether the productivity profits of the generative AI will compensate for the spent money. Between bambalins. The agreement explains the current situation in the AI ​​ecosystem: OpenAi desperately needs computing capacity to maintain its competitive advantage over the 700 million weekly users of their products. But infrastructure costs are so high that it needs constant external financing. Nvidia, on the other hand, seeks to ensure the future demand of its most advanced chips. The agreement guarantees mass orders while consolidating its dominant position against competitors such as AMD and Intel. “It is a closed cycle: Nvidia gives OpenAi money, and OpenAi uses it to buy Nvidia products,” Summary Summary Javier Pastor. The threat. Anti -Ponopoopoly experts are already arched eyebrows. Andre Barlow, a lawyer specialized in competition, explained to Reuters that “the agreement could change the economic incentives of NVIDIA and OpenAI, potentially blocking the Nvidia chips monopoly with OpenAi software leadership.” The structure creates extra barriers so that competitors such as AMD in OpenAi chips or rivals in AI models can climb their operations. They paint basts. In perspective. The story is full of similar schemes that ended badly. Global Crossing, the telecommunications operator that broke in 2002it was funded precisely by the same suppliers that sold equipment. When it was discovered that the real demand was much lower than the projected, both Global Crossing and its financiers lost thousands. The key question is whether the demand for AI services will be sufficient to justify this billionaire investment, or if we are faced with the recreation of the same speculative pattern with even more exorbitant figures. As Stacy Rasgon concludesBernstein analyst: “On the one hand, Openai helps meet very ambitious infrastructure objectives. On the other hand, it will further feed concerns about ‘circular’ financing.” Outstanding image | In Xataka | Openai estimates that it will enter 200,000 million dollars in 2030. The figure, like everything in OpenAi, is extremely ambitious

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

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

Openai has a problem with the “Codex” brand. These are all the codex that manages

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Openai has just launched GPT-5-Codex. The problem is that I already had three more calls exactly the same. Why is it important. This accumulation of identical names converts the choice of tools into a headache. Each “codex” does something different, but from the outside it seems the same multiplied product. In detail. The “Codex” family has these members: GPT-5-Codexthe newcomer. A model that program for hours without supervision. Change speed according to complexity: fast for simple, slow and meticulous tasks for large projects. Codex Cloudthe veteran. It works as a remote programmer. You send you work and return with code finished after a few minutes of solo work. Codex Clithe local assistant. A terminal utility that helps you from your computer. Competes directly with tools such as Claude Code. Codex (2021). The grandfather of the family. Fed the first versions of Github co -ilotbut it is no longer operational. Between the lines. Openai is trying to fix the linguistic mess. Now writes “GPT-5-codex” with scripts to differentiate it, implicitly admitting that the situation has been lacking. The new model reduces the use of resources into basic tasks by 94%, but multiplies by two the processing time in complex projects. Internally it already supervises more code than human reviewers. The background. Openai seems to have developed these tools without central coordination, something similar to what ended up with the pre- models selectorGPT-5. Each team chose “Codex” independently. And now what. The company prepares access via API for its latest model. Meanwhile, it is time to assume that “Codex” is more a business philosophy than a specific product. The lesson: even the most advanced companies can stumble with something as basic as putting names to their creations. Outstanding image | OpenAI In Xataka | We thought that Chatgpt was used mostly to work. Openai herself has just demonstrated otherwise

We thought that Chatgpt was used mostly to work. Openai herself has just demonstrated otherwise

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For months, many of us assumed that Chatgpt It had become the perfect tool for the office work and also to program. OpenAi has published His first detailed study about what users really do and who they are, and the portrait breaks that intuition: most conversations do not work. Personal use dominates and grows. The data reflect a notable change in the type of use of ChatgPPT: in June 2025, 73% of the conversations were not work, when in June 2024 the percentages were almost tied. And there are other interesting data: the public is mostly young, with about half of the messages sent by people between 18 and 25 years old. To this is added a turn in the gender profile: the first records showed predominance of male names, but in 2025 52% corresponds to female names. More than work: chatgpt shows your most personal face The company classified more than one million conversations in seven major categories. The most common, “practical orientation”, supposes 28.3% of all interactions and includes help requests for daily tasks, academic consultations or training tips. The study also draws a curious panorama: it points out that adoption grows faster in less rich countries, although it does not list uses by country. The second major block are requests related to writing, which highlight the edition or criticism of texts and personal communication. The programming also appears, which concentrates only 4.2% of the analyzed chats. A trend that gains strength is the search for information. Openai states that these types of consultations have become a nearby substitute for web search engines. Between May and June 2024, it grew constantly, until it was placed as the second most common use. In this section, questions about products also appear, which suppose 2.1% of the consultations within that category. These data plan questions about the future of searches and how the company led by Sam Altman He is challenging Google. Another relevant block is that of personal advice and intimate conversations. The report indicates that 1.9% of the interactions are related to reflections and relationships, And 0.4% are role -playing games, including the use of chatgpt as virtual “companion”. Although the study insists that they are small figures, The issue is in the spotlight in several countries due to the impact of this technology on the mental health of some people. reflections and relationships, The study has 62 pages and covers the period from May 2024 to June 2025, with data from 1.5 million users and a sample of 1.1 million conversations. If the question is how Openai has achieved to obtain this information, the company says it has used its own models to analyze the messages, preventing human researchers from reading individual conversations. Demographic information comes from the data that users provide when registering. Images | Solen Feyissa | Levart_photographer In Xataka | China is selling us a future full of humanoid robots. We have (many) doubts

He has just taken an outstanding Openai researcher, according to Bloomberg

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What are the ingredients to win the artificial intelligence career or, at least, to ensure a place in the elite? There is no magical recipe, but there are three key elements: Leadership, talent and investment. All are intimately related, and the companies that compete in this field spare no resources to ensure them. It is no accident that Google and Meta have offered millionaire conditions to reinforce your artificial intelligence teams. This context has caused the output of outstanding profiles of OpenAIwho have found accommodation in the competition. But to the threats representing the American technological giants now adds a new actor: Tencent. A OPENAI jump to Tencent that does not go unnoticed Bloomberg says that the Chinese conglomerate He has signed the reputed researcher Shunyu Yao, in what he describes as “One of the most notorious defections from the United States AI sector to China. ”The information comes from sources close to the case that spoke with the environment under anonymity. When reviewing the Yao LinkedIn profileit is observed that he worked almost five years at Princeton University before joining Research Intern A OpenAI in February 2024. Four months later he was promoted to Research Scientistposition that continues to appear as his last position. One of the sources cited by Bloomberg points out that Tencent offered Ya a compensation that could reach the 100 million yuan (about 11.9 million euros), although the necessary conditions to reach that figure have not been specified. The medium also emphasizes that Yao is a graduate of the University of Tsinghuaconsidered the reference institution in science and engineering in China, and which later completed a doctorate in the United States. A report from the Information and Innovation Technologies Foundation It reflects how the panorama has changed in just a few years: in 2019, 35% of the highest level researchers (2% higher worldwide) were originally from the United States, compared to 10% of China. However, in just three years, the US fee fell 7%, while China grew 16%. If the rumors are confirmed, we would not be facing a talent formed in the United States that emigrates to China, but before a Chinese researcher who, after acquiring first level experience In the North American country, he returns to his country with that background. China seeks to compete from you to you with the United States for leadership in artificial intelligence. Tencent is not any actor: he is one of the world’s largest technological groups, owner of Wechat —The most used messaging application in China – and the social network QQ. In addition, he is a giant in video games, both as a developer and editor and investor in global studies. According to the sources, his goal when signing Yao is to strengthen the integration of AI in their products and services. It remains to be seen if this movement is an isolated case or the beginning of a trend. What is clear is that the career for the development of AI is no longer just a matter of technological innovation: a war is also fought for attract the best talent. And Chinese companies have no intention of being left behind. Images | Donald Wu | In Xataka | Alibaba has just demonstrated that Openai spends 78 million to do the same as them for $ 500,000

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

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

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

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

Openai and Microsoft’s convenience marriage touches its end. The divorce, surprisingly, is being friendly

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Openai and Microsoft have reached a preliminary agreement in which the new terms of their business relationship are established. In it Official announcement It is made clear that the terms of the agreement still have to define themselves, but there is a clear thing: the idyll is finally ended. Why is it important. What began as a idyllic relationship It has ended up becoming almost a toxic relationship that was preventing both companies from looking for other paths. Between 2019 and 2023 Microsoft invested more than 13,000 million in OpenAiwhat according to The New York Times gave Microsoft about 49% of OpenAi’s future benefits. OpenAi getting rid of their chains. The firm led by Sam Altman has been trying to change its structure and get become a profit company (“For-Profit”). The agreement with Microsoft, who did not want to give up his privileges, was one of the obstacles, but this agreement seems to pave the way for that business transformation. The discord clause. The original agreement included a clause that He rescinded access from Microsoft to OpenAi’s most advanced models when it is I would decide that had reached the famous General Artificial Intelligence or AGI. This clause is still part of the new agreement but has been modified according to sources close to the process Possible outposive. The agreement could “unlock” Openai both in its passage to “for-profit” and for a potential outlet. Right now OpenAi cannot get money from the general public and the traditional investment market, But it would remain managed by the NGO. The startup also indicated that it would offer at least 100,000 million dollars to the non -profit organization that will continue to control Openai’s future once it is transition to its new format. Bret Taylor, company manager, affirmed that in this way the NGO would be “one of the philanthropic organizations with more resources in the world.” Sources close to the agreement indicate that this NGO would have an OpenAI participation that would exceed 20%. What both were looking for. The long commercial relationship has been beneficial for both parties, but market growth has caused one and another to seek ways to continue growing in the AI ​​market and this agreement blocked them largely. According to sources close to the aforementioned negotiations In axios: Microsoft wanted to continue having access to OpenAi’s technology and products, something logical considering that he reverts them Like your Copilot services. Openai wanted freedom to move forward with his restructuring plans and to reach agreements with other infrastructure providers, as has happened with Oracle this week. A friendly divorce. In recent times it has been seen how both OpenAi and Microsoft have been making movements that were clearly aimed at search for a plan B In the AI ​​race. That was causing a delicate situation that now seems to soften satisfactorily for both companies. In Xataka | The marriage between Openai and Microsoft is broken at times. The problem is that both are still needing

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