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Amazon is clear about its strategy for the AI ​​war: if you can’t beat your enemy, invest in them

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Just two months ago Amazon announced a astronomical investment of $50 billion in OpenAI. Today he made a movement very similar to the announce which will invest $5 billion in Anthropic and could invest an additional $20 billion “tied to certain commercial milestones) in the future. There are counterparts and some circular financing, of course, but also a clear pattern: Amazon has no winning horse in the AI ​​race, so it is betting on its competitors. More circular financing. Amazon now has alliances in the form of active investment with the two leading AI companies in the world. In return, both OpenAI and Anthropic commit to huge spending on their services on AWS. There is a lot of circular financing here: me I lend you the money so that you spend it on me. Those houses of cards that OpenAI and Anthropic are building have clear risks, but the industry is totally immersed in that maelstrom. In Xataka OpenAI is making the tech industry unite its destiny with yours. For the sake of the global economy, it better work Analysts warn. There are concerned analysts here and others who defend this type of agreement. M. Mohan asked in X why regulators are not on top of these types of financially dangerous agreements: the domino effect if OpenAI or Anthropic fall could be terrible. For others like the well-known Jim Cramer this is not circular financing. According to him, circular agreements are designed to inflate profits, and here no one’s profits are being inflated. Their argument is that Amazon has real computing, Anthropic needs real computing, and the value of the investment is genuine. History repeats itself. The same debate occurred in January with OpenAI, and the conclusion was the same then: the image of circular financing is there but it does not necessarily imply fraud, it implies that Amazon has found a way to monetize the AI ​​​​craze without betting on any particular model. Or for the two who seem to be winning the race. But everyone is doing it. The numbers of the agreement with Anthropic. Amazon puts up $5 billion immediately, taking advantage of the company’s current valuation of $380 billion. It is also committed to investing up to an additional $20 billion linked to “certain commercial milestones” that have not been specified. In exchange, Anthropic commits to using Amazon technology, and specifically its Trainium and Graviton chips, for the next decade. No less than 5 GW of computing capacity is secured, which is more or less the capacity consumed by New York City. This is perfect for Anthropic. He Anthropic statement about the agreement contains an interesting paragraph. In it, the company admits that the demand for AI by companies, developers and users is generating “inevitable tension” in its infrastructure. Or what is the same: they can’t do everything, so they are resorting to measures that “penalize” the excessive use of their AI models. They restrict session limits during peak hours, change the pricing model in companies to a “pay as you go”, or change the level of effort of their models and they sign up for token inflation. The agreement with Amazon makes it possible to mitigate the problem of computing shortages. The race for gigawatts. The truth is that Anthropic has been moving for months to try to avoid more and more problems with the computing capacity they can access. In a few weeks we have seen how Amazon’s 5 GW have been secured and also “multiple gigawatts” computing teams contracted with Google and Broadcom. What Amazon is actually building. Viewed as a whole, Amazon’s strategy is simple and elegant. You don’t need to win the AI ​​modeling race, which is unpredictable and extraordinarily expensive. It only needs that whoever wins it depends on it and its infrastructure. By investing at the same time in two rivals like Anthropic and OpenAI and securing massive spending contracts from both, it achieves something striking. Turn uncertainty into an asset: it doesn’t matter who wins, because she will end up getting paid. This also reinforces the relevance of its Trainium and Graviton chips, something that validates its commitment to its own chips. {“videoId”:”xa4n2g8″,”autoplay”:false,”title”:”An initiative to secure the world’s software ｜ Project Glasswing”, “tag”:””, “duration”:”349″} Win-Win. The agreement seems perfect for both parties. Amazon ensures, as we say, consumption in its infrastructure for the next ten years, and Anthropic achieves an investment that increases its market value again. The same happens with OpenAI, and in both cases these agreements and financial support only reinforce expectations about their imminent IPOs. Image | Fortune Brainstorm TECH In Xataka | OpenAI and Anthropic have proposed the impossible: lose $85 billion in one year and survive (function() { window._JS_MODULES = window._JS_MODULES || {}; var headElement = document.getElementsByTagName(‘head’)(0); if (_JS_MODULES.instagram) { var instagramScript = document.createElement(‘script’); instagramScript.src=”https://platform.instagram.com/en_US/embeds.js”; instagramScript.async = true; instagramScript.defer = true; headElement.appendChild(instagramScript); – The news Amazon is clear about its strategy for the AI ​​war: if you can’t beat your enemy, invest in them was originally published in Xataka by Javier Pastor .

Mova Rover X10, the “what do you want me to beat you” of pool robots

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Mova has just landed in Spain con a lot of devices. One of them is the Mova Rover X10, a pool cleaning robot that costs more than 2,000 euros, but that is a lot more than just a ‘Roomba’ for the pool: It is a cleaning submarine. Last year we already analyzed the Dreame Z1 Pro (Mova’s sister company) and although it made my life much easier with pool maintenance, there were things that could be improved to make the experience better, such as the control system and charging. And here comes Mova with the “what do you want me to beat you” of pool cleaning robots. Let’s go with the main features and get into detail. Mova Rover X10 technical sheet Mova rover x10 Dimensions and weight 540 x 460 x 320mm 15.8kg Mapping and navigation 29 sensors Surface and wall mapping Real time control Obstacle Avoidance Dynamic Suction power Maximum of 38,000 L/h Cleaning surface Up to 500 m2 Brush type Two central rollers Two side rollers Filter 3 micron particles 5 liter capacity Control With mobile Battery 6 hours of floor cleaning 12 hours of surface cleaning 6.5 hours of charge Wireless charging Price 2,099 euros Design with multiple brushes There is not much room for innovation when it comes to pool cleaning robots. It’s like the robot vacuum cleaner: There is an almost standardized design because it is ideal for attaching brushes, moles, navigation system and tank. In the case of a pool robot, the same thing happens, although with some extra elements such as the propulsion system. However, Mova has gone all out and he thought that two central brushes for the background were not enough and he attached two smaller ones to the sides. With them you make a first pass by scratching the wall, but they have another function that we will get into later. Something fundamental in a robot vacuum cleaner is the navigation system. The more complete it is, the fewer passes it makes over the surface and the more efficient it is in cleaning. Mova calls theirs ‘360-degree AquaScan’, but basically it is a front sensor, one top and one side to know at all times both the distance from the walls and if there are any obstacles. In the upper backpack we have the reusable filter and Mova ensures that a load of its 15,000 mAh battery It allows six hours of floor cleaning, being compatible with fiberglass, tile, concrete, marble, stainless steel, ceramic and PVC pools. Submarine So far, a “conventional” robot vacuum cleaner. However, there are three features that are really crazy and that we can’t wait to try. One is the propulsion system. The pool cleaner robot has jet propulsion, as this is what allows it to both move forward and stick to the surface and walls. However, the Mova adds another four propellers at the base. So that? To make a ‘jump’ and go up to another platform. Instead of going up, moving close to the wall, he directly pushes himself off. That’s it, an underwater ‘rover’ that solves a problem that some of the competition has: underwater navigation. Other robots have an app that allows very intuitive control and mapping, but once they are submerged, the connection is lost. Some have a knob for basic control, but depending on the water conditions, it may go… or not. What the Rover X10 includes is a beacon. It is connected by WiFi and allows us to have constant communication with the robot. If we want to pause work or change the plan, we simply do it from the app without having to go to the edge of the pool to try to get the remote control right. It also, obviously, allows us to see the work in real time. Surface vacuum cleaner And those two side brushes that we mentioned before are the last trick of this model. Because It is not just a pool cleaner robot, but a surface cleaner. It has a front nozzle that works like a home robot vacuum cleaner: it sucks up dirt thanks to both its advance and what the side brushes attract. According to the manufacturer, it has 12 hours of autonomy in this mode. To charge it, instead of by cable, we have an IPX8 certified base for wireless charging. Mova Rober X10, price and availability Given the characteristics of the Mova Rover X10, it’s time to talk about the price. And as you’d expect, packaging all this technology doesn’t come cheap. The device can now be purchased for 2,099 euros on your website. In the end and as happens with other similar ones such as lawnmower robotsit all depends on the desire you have to automate unpleasant tasks that are not usually pleasant. In Xataka | 3D printing has three big problems. Mova has solved them in a very curious way: with a nozzle roulette

If he wants to beat Anthropic, he needs more hands. So you’re going to double your template.

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OpenAI just realized that they had been launching products without rhyme or reason and they need to focus on something. And that something is the business sector, where an Anthropic with a much clearer business plan has been eating up their ground. To achieve this they need to increase their staff. A lot. More hands. According to Financial TimesOpenAI is planning to increase its staff throughout the year, almost doubling it. They currently have around 4,500 workers and the idea, according to internal sources, is to reach 8,000. To reach that figure they would have to hire 12 people a day; human resources will be on fire. The departments that need the most personnel are product development, engineering, research and sales. In addition, there is a figure that the company wants to reinforce; These are “technical ambassadors”, who will be a type of advisors who will guide companies that use their products so that they get the most out of them. They have also rented new offices in San Francisco, which will bring the total surface area to more than 90,000 square meters. Unstoppable Anthropic. This is part of a strategic reform that seeks to regain ground in the business segment, where Anthropic has gained a very solid position. According to data from Ramp AI IndexAlthough OpenAI is still the most used solution in business, adoption is falling while Anthropic is doing like a shot. 70% of companies that buy AI solutions for the first time choose Anthropic, at this rate, in a short time they will overtake them in the number of business users. It’s not that big of a deal. OpenAI has downplayed this figure because Ramp is a financial service and its data comes only from transactions made with your credit card “it’s like saying that global sales of lemons can be calculated based on my son’s lemonade stand,” said a company spokesperson. Be that as it may, the reality is that OpenAI is taking steps towards a restructuring of its product portfolio and its organization, and recovering business share is among its priorities. Unify portfolio. As part of this strategic pivot, OpenAI is planning the launch of a super app that will unify Codex, ChatGPT and the Atlas browser into a single tool. During 2025, OpenAI launched many very disparate products, many of them being half abandoned along the way like ChatGPT Atlas. In addition to showing a clear lack of focus, it is a very inefficient strategy; There are many computers, they all need computing capacity and no one is clear about what to prioritize, a disaster. The change is led by Fidji Simo, the company’s apps manager, who recently told employees “We cannot waste this moment because we are distracted by parallel projects.” The agreement with the Pentagon. All this coincides with the soap opera of Anthropic and the Pentagon. After weeks of tensions, Anthropic finally ended up on the government’s blacklist and OpenAI signed the agreement. What followed was that people started uninstalling ChatGPT en masse and in the public eye ChatGPT became the bad AI and Anthropic became the good AI that had not given in to government pressures. Sam Altman assured that there was no problemthat we could rest assured and that they also had red lines, a statement that has little to do with the facts. In Xataka | OpenAI wants us to have sex with ChatGPT. Your wellness advisors think it’s a terrible idea Image | Levart_Photographer, Nathan Sack on Unsplash

Two Tajo reservoirs have more water than the 12 Segura reservoirs combined. And that is why Murcia is going to beat Castilla-La Mancha again

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And not a little more water, no. Much more. Because, let’s be honest, since 1979, when the transfer was opened, the Entrepeñas and Buendía reservoirs so much accumulated water has never been seen there: we are talking about reserves of 1,649 hm3. On the other hand, a little further to the southeast, the entire Segura basin has 52 hm3. That is, an almost exact third. These are just a couple of pieces of information, but they are enough to explain why, although the Community Board of Castilla La Mancha sue the Central Government180 hm3 of water from the Tagus will end up in the Segura before the end of the quarter. On autopilot. On March 13, 2026, the Central Transfer Exploitation Commission approved that shipment. The current regulations do not give much room for maneuver: the headwaters of the Tagus entered Level 1 months ago and that, with the current rules, means activating the transfer of water resources. The problem is that the rules have been out of date for years and, in fact, the proposed modification (more favorable to the interests of the Tagus) has been stalled in the Supreme Court for months. And it is still curious that rules designed for a scenario with little water generate problems, precisely, when there is more water. What does Castilla – La Mancha complain about? The most obvious thing is that the Government is manifestly failing to comply with the Royal Hydrographic Planning Decree: According to the text, the new regulations were to be in force in February 2024. That is, we are two years late. And this delay is not innocuous: the Board maintains that the current rules do not ensure the environmental protection of the Tagus or all the associated Natura 2000 network spaces. At the end of the day, they point out from Toledo, what the Exploitation Commission has approved “it wastes 11% of the impounded water” at the head of the river. And what happens in Murcia? We already said months ago that Murcia (and the southeast in general) They had already assumed that depending on transfers It was something very committed. It is true that the expansion of some desalination plants has been approved and is working in construction from others, but the tenders are very slow. This time gap is not only a problem for irrigators, it is a ticking bomb for the different administrations involved. After all, the elections are just around the corner. What can we expect? This is the simplest part of the matter: as long as the Supreme Court does not get its act together or the Ministry decides to take action on the matter, the transfers will continue to occur automatically “as if nothing had happened.” That is to say, the irrigators of the Segura are going to win (again and again) over the riverside municipalities of the Tagus. It doesn’t matter how much politicians stage things. The conflict between regions is in the very core of the country: in the water that runs through its ‘veins’. Image | untypographic In Xataka | The Tagus reservoirs have reached their maximum level. The response of the authorities has been to empty them immediately

We believed that machines could only beat us at chess or Go, but now they are preparing to beat us at tennis

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Kasparov succumbed to Deep Blue and that showed that machines could finally surpass humans. Then came defeats in other fields (Go, StarCraft), but always with algorithms as the protagonists. Now those who want to surpass us are the robots, and after some disappointments and also amazing previewsare wanting to conquer a sport that poses an exceptional challenge: tennis. Be careful, Alcaraz, the robots are coming. Researchers from Tsinghua University and Peking University, among others, have collaborated to develop a robot capable of playing tennis. The project has been named LATENT (Learn Athlethic humanoid TEnnis skills from imperfect human Motion daTa) and it is surprising because the principle is very similar to that of developments like AlphaZero: the machine (the robot) practically learns to play by itself. We have already seen similar advances with sports like ping pong or with kung fu demonstrationsbut this milestone has been achieved in a different and striking way. imperfect movements. Until now, getting a robot to react at the speed of a tennis ball was an almost insurmountable challenge due to the lack of perfect movement data, but the advances made by these researchers are especially striking. Especially since these machines now use “imperfect” information captured from humans to learn how to play. Mini tennis. Capturing accurate data from a real tennis match is very expensive and complex due to the size of the court and the subtlety of the tennis players’ wrist movements. To solve this, the LATENT team chose to collect “primitive skills” data. That is, the robot was shown basic movements such as the forehand drive, backhand, or lateral movements. In addition, an area 17 times smaller than a professional court was used precisely to reduce the complexity of the initial system. The objective: that from there the robot could develop its own technique. Learn from your mistakes. The striking thing about this development is that with those few data the robot was capable of making corrections on the fly when moving or hitting the ball. Thus, he was able to maintain the stability of his body following the style of human movements, but he was also able to finely adjust the angle of the racket to impact the ball appropriately. No strange things. The researchers also wanted to prevent the robot from starting to “make up” strange movements during its reinforcement training. Thus, they created a technique that forced the AI ​​to explore only human-like movements based on the initial data distribution. Unitree G1 already plays tennis. To translate their system into reality, the researchers installed this system on a Unitree G1 robot. This model of humanoid robot It has 29 degrees of freedom and a racket was attached using a 3D printed part. The physical tests were surprising: the G1 was able to return balls thrown at more than 15 m/s (54 km/h), but it was also able to maintain rallies with human players on a real court. The robot was capable of covering a large part of the court and dynamically adapting its posture according to the trajectory of the ball. The beginning of something bigger. These tennis robots are very far from being able to compete with human players—much less with professionals—but they demonstrate that reinforcement learning techniques that have been applied in games such as chess or Go may be valid for physical environments with robots. In fact, this advance raises the possibility that robots can learn any physical discipline (whether sports or not) from a limited learning of basic movements. In Xataka | And finally the human being beat, with much drama, a robot playing ping pong

Doraemon could never beat Goku. Until China invented Seedance 2.0

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Not so many years ago we ridiculed AI for not being able to create hands with five fingers or not getting Will Smith to non-gloomily eat a plate of spaghetti. Today, he is capable of creating animations that would make the best producer in Hollywood uncomfortable. Seedance 2.0. First of all, what are we talking about. Seedance is an AI content generation platform, specifically designed to create dynamic anime-type content, combat, short cinematic scenes and clip stylization. It works with one or more base images and a descriptive prompt. Behind Seedance 2.0 There is Bytedance, the company behind TikTok and one of the five most relevant Chinese companies in AI. Why the world is going crazy. Although it is not perfect, Seedance 2.0 is one of the video generation models that is offering the best results. To the point that X is being filled with replicas of well-known scenes created with this AI that are practically indistinguishable from reality. In some cases, the visual fidelity and animation pace border on a level that until recently seemed reserved for professional studios. Recreation of an animation never published by the Dragon Ball franchise. Goku vs. Doraemon. Will Smith doing the only thing we know how to ask him to do with AI. Jackie Chan vs Jet Li. The big video moment. The world had its moment ChatGPTits moment DeepSeekits moment Nano Banana and, now, we are in the Seedance moment. Giants like OpenAI and Google have been fighting for the best video generation model for some time, with proposals such as Sora 2 and I see 3. But right now, the top scorer is Bytedance with Seedance. Look out for Bytedance. Bytedance is moving into seventh gear to be one of the Chinese giants leading the AI ​​race. It only needed to have its own chips, something that is about to be solved through an alliance with Samsung. The company has strived to be more than the giant behind one of the most important social networks in China and the rest of the world, to become a powerhouse of artificial intelligence. Image | Improved Seedance with ChatGPT In Xataka | How to create videos with artificial intelligence: 13 essential free tools

The Xiaomi electric car that beat Tesla in sales has been renewed. And he has shattered a resistance record along the way

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Xiaomi’s Xiaomi SU7 has broken a world endurance record and has become the first electric sedan in the world capable of traveling 4,264 kilometers in 24 hours. The previous record was held by another Chinese company. the car. The Xiaomi SU7 renewed just a few weeks ago not only some aesthetic touches: now the engine is the V6s Plus, the same one fitted to the Xiaomi YU7 with the promise of achieving 902km (under CLTC cycle) on a single charge and 670 kilometers of autonomy in 15 minutes. The test. The Chinese brand has just announced that the Xiaomi SU7 Max has just broken a record that until now was held by Xpeng’s P7. 4264 kilometers traveled in 24 hours, within a closed circuit. Why is it important. First of all, this number is the immediate translation of what Xiaomi has achieved with its affordable sedan: shattering the endurance record for electric vehicles. A milestone that places it far above the Xpeng P7. Bringing the circuit test to the practical world, the record comes close to the new SU7 going on sale in China. Xiaomi wants to make it clear that its car is capable of withstanding limits well above those that no user will expose it to on the street. How has he achieved it. For much of the test, the SU7 Max maintained a constant speed of 240 km/h, with a maximum of 265 km/h along CATARC, a 7.8 kilometer oval track. The only stops made were to recharge the vehicle. The engine of this updated SU7 mounts a 101.7 kWH NMC battery, capable of recovering 670 km of autonomy (according to the Chinese CLTC cycle) in just 15 minutes. A V6s Plus engine capable of rotating at 22,000 rpm and extracting a maximum power of 681 HP. Sales success. Xiaomi’s SU7 is an unprecedented success. Being the first car manufactured by the company, it has achieved sell more than the Tesla Model 3, outperform rivals in specifications like him Taycan Turbo in its Ultra version. Still, the company is losing money. 800 million dollars. Ironic as it may seem, Xiaomi lost close to a billion dollars in the first year manufacturing the SU7. The company has placed more than 350,000 cars on the market since the launch of the SU7 but… Between 2021 and 2025, it spent 3.3 billion on the development of both the car and its ecosystem. The figure increased to 4.2 billion in research in 2025. Figures that, as astronomical as they may seem, do not represent a major problem for a company that aspires to become the largest manufacturer of electric cars in the world, above Tesla. Image | Xiaomi In Xataka | Xiaomi’s electric car heads to Europe: the global launch will take place in 2027

seven essential pillars to beat the US

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That the power that dominates AI has many roles in dictating the rules of the game at a global level is an open secret. China knows this and has stepped on the accelerator by putting on the table an ambitious plan for 2027 that concerns absolutely all key sectors. Your goal? Being able to securely and reliably provide key AI technologies that are deeply and high-level integrated into a new era of industrialization. Towards the global forefront. The plan is called “Opinions on the implementation of the special action Artificial Intelligence + Manufacturing“, has 2027 as a deadline and a maximum aspiration: that both its artificial intelligence industry and its application at an industrial level are at the global forefront, promoting what they call “new quality productive forces.” To get an idea of ​​its relevance and transversality, it is signed by eight government departments, including the Ministry of Industry and Information Technology, the Cyberspace Administration of China and the National Development and Reform Commission. The seven essential pillars. If there is something that stands out about the program, it is how concrete and detailed it is when it comes to materializing it. Thus, the seven key tasks are: laying the foundation through innovation, AI-driven improvements, product advancements, development of key actors, strengthening the ecosystem, ensuring security and international cooperation. Breaking down how, these are some of the measures to apply: Software and hardware innovation: coordinate the development of AI chips with the necessary software. Integration into production: Introduce AI models into core manufacturing processes, not just administrative tasks. Robotics and machinery: Accelerate the use of AI in industrial robots and machine tools. Open Ecosystem: Build a world-leading open source community. Security: develop technologies to protect algorithms and training data of industrial models. Some dizzying goals in less than two years. And if your measures are concrete, the objectives for the deep application of AI even more so: Large models: Deploy three to five general-purpose AI models for manufacturing, plus specific models for key industries. Data: Creation of 100 high-quality industrial data sets Real use cases: Promote 500 real case application scenarios in factories. Companies: promote two or three leading global companies in the AI ​​ecosystem, seeking strategic concentration of resources and leadership, along OpenAI or DeepSeek. Likewise, it wants to select a thousand model companies among specialized SMEs to support them. Sovereignty and leadership. In conclusion, what China has proposed is a comprehensive roadmap for the Asian giant not only to consume AI, but for its industrial sector to be the basis of technological development to ensure its technical independence in chips and algorithms before the end of the decade. In Xataka | China has an ambitious plan to surpass the West in technology. And it has already chosen its 18 companies to achieve it Cover | Composition with images of idnaklss and Iván Linares with Midjourney

The US already knows when it wants to return to the Moon to beat China. The problem is how the ship will return

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There is already an official date. After years of delays and speculations, NASA has confirmed what was rumored in the halls of Washington: Artemis 2 has the green light for launch on February 6, 2026. And what is its destination? Neither more nor less than the Moon itself. Tuning. With this announcement, NASA is already preparing for the transfer of the gigantic SLS rocket (Space Launch System) to platform 39B this very January 17, starting the final countdown for humans to orbit the Moon again. Something that has not happened since 1972 with Apollo 17. However, this is not a celebration without controversy. The mission, which will take the astronauts Reid Wiseman, Victor Glover, Christina Koch and Jeremy Hansen to a 10-day trip around our satellite, has been brought forward under strong political pressure. And it does so with a worrying technical asterisk: the behavior of the Orion ship’s heat shield. A battle of pressures. On the one hand, Donald Trump has historically shown its impatience with the deadlines that NASA was giving to be able to orbit around the Moon. All this with an eye on China, which threatened to be the ‘first’ and overtake the United States in this fact. What has been the solution? put to Jared Isaacman as NASA Administratora billionaire, private pilot and astronaut (known for his missions in Polaris Dawn and its links with SpaceX) to prioritize speed and calculated risk-taking over the complete risk aversion that “old NASA” had. Because. February 6, 2026 has been set as set in stone for several strategic reasons that outweigh engineering doubts about the heat shield. The first of them It’s the race against Chinasince the Asian country has a very advanced lunar program and aims put taikonauts on the Moon before 2030. If Artemis 2 was delayed to redesign the heat shield (which would have taken years), Artemis 3 would have been gone until 2028-2029 or longer, leaving the door open for China to arrive earlier or very close. But they do not stop here, since for this administration the Moon is a springboard to reach Mars, this mission being a simple way to validate the systems they are using. That is why every delay on the Moon is a delay for the mission to Mars, which promises to be the historical legacy they seek. The Avcoat dilemma. The main point of friction between engineers and the agency’s new management lies at the bottom of the Orion capsule. During the Artemis 1 unmanned mission in 2022the heat shield (made from an ablative material called Avcoat) behaved unexpectedly. And instead of being consumed uniformly, it broke off in pieces, creating craters and cracks due to the gases trapped in the material. during re-entry into the atmosphere. The engineering logic faced with this problem would mark make a new design or material change. But since it is something that would delay everything, NASA has opted for a change in angle during reentry to minimize thermal stress in the most affected areas to maintain the same shield. The doubts. NASA assures that the risk is “acceptable”, but this decision has raised blisters in the aerospace security community. Added to this is that the life support system (ECLSS)provided in part by ESA, has never been fully tested in flight with humans, adding an extra layer of uncertainty to the mission. Charles Camarda, veteran astronaut of the STS-114 mission, the return flight after the Columbia disaster, has been blunt in this regard. In statements, Camarda has compared the current situation with the “dysfunctional culture” that led to the Challenger and Columbia tragedies. But for the NASA administrator, Artemis 2 is a non-negotiable step to ensure American leadership and the future cislunar economy. Operating tension. As if the pressure on Artemis were not enough, NASA also faces a parallel crisis in low orbit. The agency and SpaceX have scheduled January 14 undocking of the Crew-11 mission of the International Space Station (ISS) due to urgent medical evacuation. This is an unprecedented event in the history of the ISS: lowering an astronaut for an unspecified medical problem (although he has been confirmed to be stable). Although Isaacman has assured that this operational incident will not affect the schedule of Artemis 2adds a considerable load of stress to mission control teams in Houston, who must now manage a crisis in real time while preparing for the most important launch of the decade. What can we expect? At the moment, the dates we know are January 17, where the SLS rolls towards its platform, and February 6, when the window for its launch will open. In total, a 10-day flight mission is expected, with a lunar flyby and high-speed return. Specifically, 40,000 km/h. NASA has much more at stake than a mission in February. The validation of its security model is at stake in the new space era, where geopolitical competition and commercial rush collide head-on with the immutable laws of physics and thermodynamics. Images | Pedro Lastra POT In Xataka | We have been deceived by the distances of the Solar System: the closest neighbor to Neptune is Mercury

Amazon is preparing an investment of 10 billion in OpenAI because if you can’t beat your enemy, the best thing is to join him

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Leonidas, had six-pack or not, he died at Thermopylae, but what is curious for our history is exactly what happened afterwards. Xerxes’ Persians had devastated Attica, and faced with the threat that all of Greece would fall, the Spartans—who deeply distrusted the Athenians—agreed to join forces with them. War makes strange allies, they say, and this story is not even close to explaining what is happening with AI. Everyone is joining forces. Then I’ll tell you how it ended with the Spartans and the Athenians. what has happened. OpenAI is negotiating an alliance with Amazon according to which the latter would invest around $10 billion in OpenAI. In The Information They were the first to reveal that negotiation, now confirmed by sources close to the conversations that have been cited on CNBC. What do each other gain?. Thanks to this agreement, Amazon will sell OpenAI its Tranium chips and will also rent more computing capacity in its data centers so that OpenAI can further expand the execution of its AI models and services such as ChatGPT. What OpenAI gains is, once again, economic resources to continue growing. Or what is the same: money to burn on that bonfire that AI has become. A strange agreement. The alliance is surprising, especially considering that Amazon had already put its eggs in another basket. Specifically, Anthropic, OpenAI’s absolute rival in the AI ​​race. It is estimated that Amazon has invested a total of 8 billion dollars at Anthropic, but now there is another reality: that everyone invests in everyone. Anthropic, the best example. The truth is that in recent months we have seen more and more circular financing agreements. Microsoft, which had invested 13 billion dollars, announced last month that would invest $5 billion in Anthropic, and NVIDIA also signed up, doubling that amount: it will invest $10 billion in it. And already, Even Google has teamed up with Anthropic. Long live circular financing. But of course the main protagonist of these agreements is OpenAI, which has been receiving blank checks (or almost) from giants like NVIDIA —100,000 million-, with Broadcom or with amd. We are facing a gigantic house of cards which is in danger of collapsing. But while it doesn’t, players continue adding floors. Or what is the same, money. Win-Win? The agreement is certainly interesting for Amazon, which has been working on its own AI chips since 2015. Trainium are the latest expression of that effort, and the fact that OpenAI is going to use them to train its models—along with those of its competitors, for the record—is good support for that development. In fact, there was perhaps more interesting support recently for those chips: Apple’s. And of course, AWS. In reality, this agreement is a continuation of that (temporary?) love affair between Amazon and OpenAI. The latter, once its ties with Microsoft were released, began to look for new girlfriends in the field of infrastructure, and a little over a month ago announced an agreement with Amazon Web Services worth 38 billion dollars. This is about preservation. All these agreements between big technology companies are not about money, because these circular investments are nothing more than exchanges of kind that compensate each other. What they are about is being stronger and protecting themselves. And if they fall, yes, they will all fall together. Let’s go back to Greece. The alliance between Sparta and Greece crystallized in the naval battle of Salamis (also in 480 BC, shortly after Thermopylae), one of the most important in human history. Sparta reluctantly ceded naval command to Athens, but the strategy worked. That union of forces achieved a decisive victory that saved Greece from being conquered by Persia. Alliances that end as they end. After that battle and that of Plataea a year later, the alliance began to deteriorate and ended up breaking up. Athens and Sparta were enemies again. In fact, 50 years later (430 BC) both would face each other for more than a quarter of a century in the Peloponnesian War. It was totally logical, as it will be that all these alliances end as they should: with each company going about its own thing. Image | OpenAI In Xataka | NVIDIA and OpenAI have just made a masterstroke. One that strengthens them and weakens everyone else

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