imitate

If Spain wants to imitate China and be a “country of engineers”, this map reveals the extent to which it has a problem

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An essential requirement for an energy and digital transition to occur in Spain is that there are enough engineers to cover demand. While it is true that there are more and more degrees that have the last name of engineering, the reality is that there are fewer and fewer professionals with the legal capacity to execute the transformation of the state, such as collects the Third Report from the Institute of Graduates in Engineering and Technical Engineers of Spain. In addition, the offer is being concentrated in specific communities. And that is a problem. Why is it important. Enabling engineering is that which grants legal powers for infrastructure and safety, for example what is behind ensuring that a bridge does not fall. With classic branches such as Civil, Mining or Naval Engineering decimated, Spain would lose autonomy and competitiveness by having to resort to imports to sign its essential projects. Jose Antonio Galdón, president of INGITE, deepen on the consequences of this fact: “On the students, who access Degrees with an Engineering denomination without a clear professional exit, and on society, which needs engineers with powers and responsibility to guarantee the safety, quality and sustainability of infrastructures and services.” On the other hand, the lack of complete supply in certain communities forces talent to emigrate, emptying technical capacity to regions that need engineering professionals to develop and establish their industry. Engineers are going to be needed. Two decades ago, those studying engineering represented 24% of the total number of university students and today that weight has fallen to 17%. as detailed by the COIGT. The engineering They are the ones that have lost the most students and also this one concentrates around computer engineering and emerging technological branches. Although the global female quota in engineering is 23%, it is precisely in these branches where it is most concentrated. On the other hand, Engineering such as Mining and Energy, Topography, Civil or Naval continue to decline and in some Autonomous Communities they already have less than 10 graduates. Although there are thousands of graduates each year, it is estimated that in Spain will have a deficit of 200,000 engineers in the next decade to meet demand. More engineering but less enabling. The IGNITE report confirms a phenomenon that has been registering for a long time in previous analyzes: Non-qualifying degrees, that is, those that do not allow the exercise of the regulated profession, have increased massively and now reach 53% of the total. On the other side of the scale, those enabling them are stagnating and even decreasing in some autonomous communities. The decline has been especially serious in places such as Asturias (-28.56%), Castilla y León (-28.79%) or Extremadura (-34.02%). The report makes a special mention: La Rioja. The small upstate community takes the cake with explosive 190% growth in engineering. But in small print: the fault lies with the non-qualifying degrees, which have grown by 431%, going from 433 to 2,289 enrolled. At the opposite extreme is Extremadura, which has the greatest drop in students, with 20.25% less. Engineering students from CCAA in Spain. INGITE Spain at two speeds. According to the reportthe Autonomous Communities that concentrate the largest number of engineering students and graduates are in Andalusia, Catalonia, the Valencian Community and the Community of Madrid. In addition to obviously because its population is larger, also because only Andalusia, Madrid and Catalonia have all the branches of engineering, revealing a territorial inequality in access to studies. The gap between public and private. The phenomenon of non-qualifying degrees is especially important in private universities, a type of center that grows out of control in the statealthough unevenly. Thus, while in the Balearic Islands, Castilla-La Mancha and Extremadura there is no this type of center and Galicia opened the first in 2022-2023, in Madrid there are 13 according to data from the Community itself. Since the 2015 – 2016 academic year, the autonomous communities where the number of degrees in private entities has grown the most has been Andalusia (from two to nine), Aragón (from three to nine) and La Rioja (from two to seven). In Xataka | If the question is which countries have the most workers with higher education, the answer is not Spain In Xataka | The university degree with the most job opportunities in 2025 looks into a great abyss: that of a future conditioned by AI Cover | INGITE

imitate Russia in the Arctic

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While millions of tourists enjoy a privileged climate in Gran Canaria, the infrastructure that supports the island operates on the verge of collapse. The island’s electrical system, isolated and without connection to the mainland, operates with minimum safety margins, dangerously approaching what technicians call “energy zero”: a total blackout. The threat is not theoretical. The neighboring island of La Gomera had a blackout a couple of weeks ago due to the destabilization of the El Palmar thermal power plant, but the inhabitants still remember 2023 in which they spent 37 hours in the dark. Faced with a structural power deficit and a demand that is close to 550 megawatts (MW) at peak times, a technical proposal has emerged that breaks all taboos in Spain: bringing floating nuclear reactors to the Port of La Luz to guarantee electricity and water to the island. Urgency and the fossil “patch.” The energy situation of Gran Canaria is critical. It is estimated that the island has a firm power deficit—safe energy that does not depend on whether it is sunny or windy—of between 120 and 140 MW. Current thermal power plants, based on fuel oil and gas, are aging and the network lacks robust support. To avoid the blackout, the Government of the Canary Islands has chosen a solution emergency: hire a powership of 125 MW. It is a thermal power plant installed on a ship (Shark class) that will dock in the port of Las Palmas to burn fossil fuels and cover that gap. The study that supports it. It is in this context where the Peter Huber Center of the University of the Hespérides emerges. Through a study signed by experts Manuel Fernández Ordóñez and Daniel Fernández Méndez, direct criticism is launched at the current management: he powership It is a “patch” that perpetuates pollution, increases CO2 emissions in a dense urban environment and maintains dependence on imported fossil fuels. Their alternative is radically different: betting on floating nuclear reactors. According to the authors“we are not talking about an experimental technology, but rather an evolution of light water reactors that have been operating safely for decades on military ships and icebreakers.” The glass ceiling of renewables. Here lies the technical core of the debate. If the Canary Islands have plenty of sun and wind, why consider nuclear energy? The answer lies in network stability. Despite the efforts, the contribution of renewables to the energy mix of the Canary Islands has been stagnant at around 20% for four years. Although 2024 aimed for a clean production recordthe technical reality is stubborn: the island electrical grid, being small and isolated, needs an “inertia” that wind and solar energy cannot provide on their own. Without a firm power base, when renewables rise a lot, the system becomes unstable and energy must be dumped to avoid failures. Currently, the big bet to solve this It is Chira Falls: a reversible hydroelectric plant that will function as a 200 MW “megabattery.” This pharaonic work, scheduled to be operational by 2027, will pump water to store excess renewable energy and release it when necessary. However, the Hesperides University study argues that, even with storage, the system still needs a constant generating “backbone” that does not emit CO2. They argue that a 100 MW reactor would provide that fixed power and the auxiliary services (frequency and voltage control) necessary so that, paradoxically, more renewables can be installed without the risk of pulling down the grid. As Manuel Fernández explained in an interview: “The only reliable alternative to fossil fuels in the Canary Islands is nuclear.” Much more than electricity. The proposal goes beyond turning on light bulbs; It strikes a chord with survival on the islands: water. The water-energy nexus The Canary Islands are one of the places in the world most dependent on desalination. More than 70% of the water for human consumption comes from the sea, and these desalination plants devour between 10% and 12% of all the electricity generated on the islands. “The water security of Gran Canaria is strongly coupled to its electrical security,” the study says. While experimental pilots are tested like the DesaLIFE projectwhich seeks to desalinate using wave energy to supply some 15,000 people, the nuclear option presents a brute force solution. A reactor generates electricity and an immense amount of waste heat. According to the report1 MW of electricity can desalinate between 4,000 and 6,000 cubic meters of water per day. A single 70 MW nuclear ship, partially dedicated to this task, could cover a gigantic fraction of the water demand of all of Gran Canaria. The Russian mirror in the Arctic. The proposal is not based on futuristic plans, but on a tangible reality that operates today: Akademik Lomonosov. It is the first modern commercial floating nuclear power plant. It has been docked in Pevek (Russia) since 2020, supplying electricity and heating in extreme weather conditions. Its technology is two KLT-40S reactors (derived from icebreakers) that generate 70 MW. In 2024, it reached an operating factor of more than 94%. Russia is already working on the next generation (RITM-200M), which will offer about 100 MW with a useful life of 60 years. Regarding the logistics of powership fossil, which requires the constant docking of tankers with fuel, a floating reactor is recharged every 3 or 4 years. This would shield the island from the volatility of oil prices. The small print. To understand real viability, you have to look at the global context. Although Russia now leads the market and uses it as a geopolitical tool, the US was a pioneer in operating the nuclear ship Sturgis in the Panama Canal between 1968 and 1976. Today, Western companies such as Westinghouse or Seaborg are trying to regain ground against Chinese (ACP100S) and Russian designs. The “B side” is social rejection. Greenpeace has come to qualify these projects like “Chernobyl on ice”. The study defends security through “defense in depth” design (double hull, passive systems). However, analysts warn of specific … Read more

Many video AIs are learning to imitate the world. And everything points to an unprecedented “looting” of YouTube

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A square, tourists, a waiter moving between tables, a bike passing by in the background or a journalist on a set. Video AIs can now generate scenes in a flash. The result is surprising, but it also opens up a question that until recently was barely posed: where did all those images that have come from come from? allowed to learn to imitate the world? According to The Atlanticpart of the answer points to millions of videos pulled from platforms like YouTube without clear consent. The euphoria over generative AI has moved so quickly that many questions have been left behind. In just two years we have gone from curious little experiments to models that produce videos almost indistinguishable from the real thing. And while the focus was on the demonstrations, another issue was gaining weight: transparency. OpenAI, for example, has explained that Sora is trained with “publicly available” data, but has not detailed which one. A massive workout that points to YouTube The Atlantic piece gives a clear clue as to what was happening behind the scenes. We are talking about more than 15 million videos collected to train AI models, with a huge amount coming from YouTube without formal authorization. Among the initiatives cited are data sets associated with several companies, designed to improve the performance of video generators. According to the media, this process was carried out without notifying the creators who originally published that content. One of the most striking aspects of the discovery is the profile of the affected material. These were not just anonymous videos or home recordings, but informative content and professional productions. The media found that thousands of pieces came from channels belonging to publications such as The New York Times, BBC, The Guardian, The Washington Post or Al Jazeera. Taken together, we are talking about a huge volume of journalism that would have ended up feeding AI systems without prior agreement with their owners. runwayone of the companies that has given the most impetus to generative video, is highlighted in the reviewed data sets. According to the documents cited, their models would have learned with clips organized by type of scene and context: interviews, explanatory, pieces with graphics, kitchen plans, resource plans. The idea is clear: if AI must reproduce human situations and audiovisual narratives, it needs real references that cover everything from gestures to editing rhythms. Fragments of a video generated with the Runway tool In addition to Runway, the research mentions data sets used in laboratories of large technology platforms such as Meta or ByteDance in research and development of their models. The dynamic was similar: huge volumes of videos collected on the Internet and shared between research teams to improve audiovisual capabilities. YouTube’s official stance doesn’t leave much room for interpretation. Its regulations prohibit downloading videos to train modelsand its CEO, Neal Mohan, has reiterated it in public. The expectations of the creators, he stressed, involve their content being used within the rules of the service. The appearance of millions of videos in AI databases has brought that legal framework to the fore and has intensified pressure on platforms involved in the development of generative models. The reaction of the media sector has followed two paths. On the one hand, companies like Vox Media o Prisa have closed agreements to license their content to artificial intelligence platforms, looking for a clear framework and economic compensation. On the other hand, some media outlets have chosen to stand up: The New York Times has taken OpenAI and Microsoft to court for the unauthorized use of their materials, stressing that it will also protect the video content it distributes. The legal terrain remains unclear. Current legislation was not intended for models that process millions of videos in parallel, and courts are still beginning to draw the lines. For some experts, publishing openly is not equivalent to transferring training rightswhile AI companies defend that indexing and the use of public material are part of technological advancement. This tension, still unresolved, keeps media and developers in a constant game of balance. What we have before us is the start of a conversation that goes far beyond technology. Training AI models with material available on the internet has been a widespread practice for years, and now comes the time to decide where the limits are. Companies promise agreements and transparency, the media ask for guarantees and creators demand control. The next stage will be as technological as it is political: how artificial intelligence is fed will define who benefits from it. Images | Xataka with Gemini 2.5 In Xataka | All the big AIs have ignored copyright laws. The amazing thing is that there are still no consequences

OpenAI founder says AI does not imitate brains

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Andrej Karpathy, co-founder of OpenAI and former head of AI at Tesla, has offered a radically different view on the current state of AI in an extensive interview with Dwarkesh Patel. Faced with overwhelming optimism, he maintains that current systems are “digital ghosts” that imitate human patterns, not brains that evolve like animals. His prediction: AGI Functional will arrive in 2035, not 2026. Why is it important. Comparisons between AI and biological brains are dominating technical discourse and guiding many investment decisions. Karpathy argues that this analogy is “misleading” and raises unrealistic expectations. His experience leading autonomous driving at Tesla for five years has given him a unique perspective on the gap between killer demos and truly functional products. The difference. Animals evolve over millions of years, developing instincts encoded in their DNA. A zebra runs minutes after being born thanks to that “pre-installed hardware.” Language models learn by imitating text from the Internet without anchoring that knowledge in a body or a physical experience. “We’re not building animals,” he says. “We are building ethereal entities that simulate human behavior without really understanding it.” Ghosts. The problem of reinforcement learning. Karpathy says that the RL (reinforcement learning) current is “terrible” because it rewards entire trajectories instead of individual steps. If a model solves a problem after a hundred failed attempts, the system reinforces the entire path, including the errors. We humans reflect on each step and adjust. The collapse. The models suffer from “entropy collapse”: When they generate synthetic data to self-train, they produce responses that occupy a very small space of possibilities. ask ChatGPT one joke and you’ll get three repeated variants. Poor human memory is an advantage: it forces us to abstract. The LLM They remember perfectly, which allows them to recite Wikipedia but prevents them from reasoning beyond the memorized data. Between the lines. Karpathy saw that Claude Code and OpenAI agents proved useless for complex code during development. nanochat. They work with repetitive code that abounds on the Internet, but fail when faced with new architectures. “Companies generate slop“, he said. “Perhaps to raise financing.” The core. Their proposal: build models with a billion parameters (dwarf compared to those most used today) trained with impeccable data that contain thinking algorithms, but not factual knowledge. The model would look for information when it needs it, just like we do. “The Internet is full of garbage,” he explains. Giant models make up for that dirt with raw size. With clean data, a small model could feel “very smart.” The unexpected turn. Karpathy expects no explosion of intelligence, only continuity. Computers, mobile phones, the Internet: none have altered the GDP curve. Everything is diluted in the same ~2% annual growth. “We are experiencing an explosion,” he said, “but we see it in slow motion.” His prediction: AI will follow that pattern, spreading slowly through the economy, without causing the abrupt jump to 20% growth that some have anticipated. In Xataka | Privacy is dying since ChatGPT arrived. Now our obsession is for AI to know us as best as possible Featured image | Dwarkesh Patel

Deepseek marked a turning point in the AI race. Now another Chinese company wants to imitate its success: Kimi K2 is born

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The Chinese startup Monshot AI has presented Kimi K2, an open -source artificial intelligence model that arrives with outstanding programming capabilities and autonomous tasks that, according to The published benchmarksThey spray competition in several of their models. Its launch occurs at a key moment for the sector, when Chinese companies seek to replicate the disruptive success of Deepseek with potential height models and much cheaper than market alternatives. Kimi does not come from nothing. MoNshot ai was one of the most promising startups in the Chinese ecosystem of AI and that giants like Alibaba have invested greatly. His Kimi chatbot reached third place in monthly active users in August 2024, but fell to the seventh in June After the emergence of Deepseek R1 in January. Now try to recover ground with a strategy that combines open source and aggressive prices, following the formula that catapulted Deepseek. Image: MoNshot AI What Kimi K2 offers. The model has 1 billion total parameters and 32,000 million activated parameters, using The well-known Mixture-Of-Experts architecture to optimize computational costs. It is presented in two versions: a base for researchers and developers, and another optimized for conversation and autonomous tasks. Kimi K2 thus becomes Moonshot AI’s proposal with the ability to act as an intelligent agent to use tools, write code, complete workflows or talk, among other tasks. Kimi K2 explained in numbers. In performance testsKimi K2 has achieved 65.8% precision at Swe-Bench Verified, one of the most demanding benchmarks for software engineering. In LivecodeBench it reached 53.7%, exceeding 46.9% of Deepseek-V3 and 44.7% of GPT-4.1. In mathematics, its 97.4% score in Math-500 exceeds 92.4% of GPT-4.1, suggesting significant advances in mathematical reasoning. The price factor. MoNshot is charging $ 0.15 per million input tokens and $ 2.50 per million tokens out of the developers who use their API. Compared, Claude Opus 4 It charges 100 times more for the entrance (15 dollars) and 30 times more for the output ($ 75), while GPT-4.1 charges 2 dollars per entrance and 8 per exit. In addition, the model is available for free in Web applications and Kimi mobile, without monthly subscriptions that require chatgpt or Claude for their most advanced models. Technical innovation. MoNshot has developed the MuCanclip optimizer, which allows train models of one billion parameters “With zero training instability.” This technology could drastically reduce the training costs of large models, a problem that has limited the development of AI to companies with greater resources. Double channel strategy. The company offers so much Free access to the source code as payment API at a very competitive price. This strategy allows companies to start with the API for immediate implementation and then migrate to self -healing versions either by regulatory cost or compliance. And it is that each developer who downloads Kimi K2 becomes a potential business client. Moment of inflection. Kimi K2 represents a convergence point where open source models and proprietary alternatives shake hands. MoNshot AI intends to turn Kimi into a tool for everything, while offering its open source model and is reserved to charge for the use of its API for all types of implementations. And now what. The launch reaches a critical point in which both Openai, such as Google or Anthropic, must respond to this wave of cheap and high quality language models. The issue is no longer whether open source models can match the owners, but if large technological ones can adapt their business models fast enough to compete in this new scenario. The looks are put in GPT-5 And in the next movements of the industry at a rate, as always, accelerated. Cover image | Xataka with Mockuuuups Studio and Kimi AI In Xataka | Grok 4 destroys the tests and aims to be the most advanced AI model. The problem is that Elon Musk continues to sabotage his answers

imitate what android had already done

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When Apple presented Apple Intelligence I was quite confusing. One of the companies referring to the world of technology was shouting at the four winds that had practically nothing relevant on the table. One of the most striking novelties, that of A Siri with contextual understanding And capable of executing local Apple models in a conversational context, it ended up delaying without a date in view. The rest of the functions? Warm and little innovative. Meanwhile, Samsung pushed from Google’s hand to create A AI tool suite for mobile to which nothing could not be reproached. Something they recently achieved with the family Samsung Galaxy S25the maximum current reference in artificial intelligence. Apple has shown how AI for mobile. Even missing a lot of what they promised in their daywe already know how Apple understands the AI ​​for mobiles. Its approximation is local, Leaving third parties like OpenAi The complex process (consultations that require search in Siri, contextual analysis of the screen), and centralizing in its own model the native functions of AI that execute their apps (translations, call filters, minor editions of image). It is an AI in which developers will have a lot to do: their models will be accessible so that applications can use artificial intelligence locally and without connection. But this local approach is not enough, Apple has failed to contribute a single function that was no longer present on Android. Arrive late when the rest arrives soon and well. Apple is usually said that it is late, but it is well. The problem is to be late and well when your rivals arrive soon and well. The functions presented yesterday by Apple have been present at Android for some time. The translation of real -time calls was already present in One UI. Text translation on screen is a native Gemini function that already implement manufacturers such as OnePlus and Samsung. The contextual analysis of the screen is a function that Google premiered with “Roda to search”and that has currently advanced to the point where Gemini can talk with us in real time about what he sees on our mobile. Intelligent summaries also have been hand in hand with Gemini. Apple’s approach, in functions such as spam detection, is enough less fine than Google’s. The company analyzes by means of patterns in the call to determine whether or not spam and warns us on the screen of the potential risk. Apple has opted to block all calls from unknown numbers and force the interlocutor to give explanations about who he is and what he wants. Good to block fraudulent calls, annoying for important emergencies and calls from numbers that we do not have stored on the agenda. Samsung and local execution. One of Apple’s most applauded points and its AI is the local approach. Here they seem to be in the lead, although more for demerit of the rest of their rivals than by the operation of their models. Currently, the AI ​​on Android is divided into two: Samsung and the rest of the manufacturers. The rest of Oems bet on implementing the functions of Gemini Nano With little care, so the Internet connection is mandatory. However, manufacturers such as Samsung have been allowing users for two years to use local. Advanced functions such as image generation do not work, but the elimination of sound, light generative editions (allowance) or transcripts work at home. For Apple is not what, is how. Apple has always been pragmatic. He knows that his models are more than valid for the execution of simple tasks, and delegates the complex tasks in OpenAi. It also does it, relying on three pillars. It is optional. It is private. It is interchangeable. For Apple, Private Cloud Compute It is fundamental. The company has designed an architecture that, in case of needing Internet connection for complex tasks, is extremely careful with the data launched to the server. This data shipping is encrypted from end to end, and not even company employees have access, according to Apple. A local, private and jealous with the data is a more limited AI, and Apple is willing to deal with it. Image | Xataka In Xataka | Apple has decided not to lead the AI ​​revolution. Instead, he has chosen to be his best host

LaLiga has in her hand to prevent people from stopping seeing illegal IPTV. You just have to imitate Netflix

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The nightmare of IPS blocks by LaLiga continues. Not only that: it seems to increase. Soccer is becoming a problem For Internet users in our country, and are (we are) paying fair for sinners. Why is this happening? This is what we try to find out analyzing one of the potential root problems – the cost of seeing football – and stating those prices with what has happened on other streaming platforms. Why what works for Netflix or Spotify does not do so for football? Let’s see it. How much does football cost in Spain and Europe Today in Spain football fans depend on telephone operators to enjoy these broadcasts. If the objective is to be able to access all the First Division Soccer matches of LaLiga and those of competitions such as the Champions League, The options are two: Movistar+ and Orange. They told it a few months ago Our mobile Xataka companionswhich explained what were the disputes available plans, in which fiber, mobile and television are always combined in different versions. In those two cases Prices start from 115 euros per month of Movistar or the 80.95 euros per month of Orange (although without mobile data). O2 and Jazztel also offer some games, but much more limited: each day we have access to a LaLiga EA Sports (First Division) match, a Champions League match (if celebrated day) and three games of LaLiga Hypermotion (Second Division). That exclusivity of Movistar and Orange, however, They could change: Yoigo and Masmoble plan a television service with Orange TV infrastructure and in which 90 channels and all football will be included. At the moment there are no prices or defined availability date for this project. And in Europe? Other European countries have different costs, but it is important here to emphasize that the prices we will talk about are access to football without further ad I would go apart. Thus, we have: France: Dazn has a package to see all the link 1 for 35 euros per month (25 euros/month if you are under 26 years). Canal+ has a plan that also includes European competitions and costs 29.99 euros per month. Germany: In Dazn Unlimited All Bundesliga and Champions League matches for 34.99 euros per month are available. There are some optional platforms such as Sky with similar prices. Italy: DAZN offers all the A series A for 30 euros per month, while they can see the Champions League, it must be combined with Sky Italy, which has a cost of 25 euros per month. The total cost is therefore 55 euros per month. England: Sky Sports has all the rights to convey the matches, and the package costs about 22 pounds per month (26 euros/month). BT Sport broadcasts the Champions League, and the cost in that case is 25 euros per month, so the combined cost is about 51 euros per month. What is also true is that these amounts and these plans vary constantly and both operators and platforms offer constant promotions in order to capture more users. When Netflix taught us the way There was a time when music downloads or films on P2P networks were especially popular. That was cumbersome and illegal, but there were not many more options either. Or none. This was what was seen in Netflix in 2015, when he arrived in Spain. Everything would change with the arrival of Netflix, Spotify and its competitors, who showed that we could have streaming services of fantastic content, accessible, with a great catalog and with a more than reasonable price. Suddenly I was no longer compensated to be looking for other places: The legal alternative was really remarkable. The subscription model settled and became the norm, and thanks to a good balance, content companies realized something striking: the best way to fight illegal content was to offer a good service at an acceptable price. This principle has been corrupted in recent years: Servcios like Netflix have Uploaded prices Notably, they have stopped allowing Share accounts And they have also put ads, Like all its competitors. Users can protest (we protest), but time has proved those responsible for these services, who have not stopped growing and They are in record figures. How have things come out to Netflix? We can see it in two quite representative graphics of the situation. Since 2012, when the service began to be available in the US (arrived in Spain Something later), Netflix was raising prices more and more frequent. With each climb protests, yes, but … Sooner or later most return. Netflix price evolution in the US. These changes have been analogous in the rest of the world, and Spain is no exception. Source: The Verge. In fact, growth in users is apparently unstoppable in Netflix. The plan with advertisements, which we can criticize so much, It has been a resounding success And today more than half of the new subscribers arrive at the service thanks to this plan. Evolution of Netflix subscribers globally from 2011 to 2024. Source: Business of Apps. At present, the platform has More than 300 million subscriberswhen a decade ago The figure was five times lower (62.71, According to Business of Apps). There have been hardly two semester throughout its history in which there had The shared accounts or the plan with ads. That seems to make it clear that despite everything to millions of users They are still compensated by paying those subscriptions And not to go to illegal content distribution services, so if it works for them, what is happening with football in Spain? The Netflix of Sports Today the standard plan with Netflix ads costs 7 euros per month. Not bad, especially considering what football costs. Even considering the cost of the most affordable plans to see all football in Spain (with many asterisks, about 29 euros in Orange), the price both here and in other countries in Europe seems elevated. Seeing football in Spain costs about 30 euros a month with Orange … Read more

It was a matter of time for others to imitate OpenAi

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Artificial intelligence companies are making clear a message: accessing the most advanced functions of their chatbots requires paying, and increasingly. It is not a completely new something, but now they begin to appear subscription plans with three -digit prices. At the end of 2024, Openai surprised with Chatgpt Proa modality of 200 dollars a month focused on professional users. It was an important leap compared to the Plus Plan of 20 dollars. Now is Anthropic’s turn, which has launched its own premium proposal for Claude: We are talking about the Max Plan. Claude Max: More use, more expensive. Anthropic, founded by former OpenAI members, offers two variants of the Max Plan. The first costs $ 100 per month (about 90 euros plus VAT) and multiplies the use available in the 20 dollars for five. The second elevates the commitment to $ 200 per month (180 euros plus VAT), with twenty times more use than the basic plan. Both options are already available for those who need a capacity to use much greater than the standard. What does Anthropic offer in front of Openai? Both the 100 and 200 dollars plan give priority access to new functions and models, but with an important difference with respect to OpenAI. While Chatgpt Pro boasts of unlimited use, Claude Max imposes limits. They are quite generous, but they are there. Is the AI ​​price uploading? Artificial intelligence progresses fast and companies are taking advantage of that evolution to launch increasingly expensive plans with premium functions. Scott White, Product Manager of Anthropic, has already dropped in an interview with TechCrunch that could launch even more expensive subscriptions in the future. A career expensive towards profitability Startups such as Openai or Anthropic are not yet profitable. OpenAi has marked 2029 as a goal, According to The Information. Anthropic, meanwhile, continues to increase its income while trying not to be left behind. Along the way, he continues to burn resources as if there were no tomorrow. Startups has some notable advantages, such as the ability to assume high levels of risk and, above all, move very fast. Google or Microsoft, meanwhile, do not have these advantages, but their strength is in a financial support that allows them to move forward even if some of their most ambitious projects fail. Images | Anthropic In Xataka | OpenAi has broken his roof. Its pro plan is a jump to ultra -chair that makes all the meaning of the world In Xataka | The Ghibli paradox: the most viral success of AI is at the same time a symptom of its problems as a daily product

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