rivals

This is how it compares to its rivals in price from POCO, Xiaomi and Samsung

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Yesterday, Google presented its new economical mobile phone, the Google Pixel 10a and whose greatest bet is photography. Available from 549 euroshas several competitors in the market who will try to tread on an almost guaranteed ground of success (seeing the popularity that Google mobile phones have been acquiring for a few years). Among them are the Xiaomi 15The Poco F8 Pro and the Samsung Galaxy S25 FE. If you have questions about which of these mid-range mobiles but with top features is better for you, we are going to compare them in some of their functionalities, so that you can make the right decision. The price could vary. We earn commission from these links Pixel 10a vs Xiaomi 15T, Poco F8 Pro and Samsung Galaxy S25 FE, at a glance Google pixel 10a xiaomi 15t Poco f8 pro samsung galaxy s25 fe screen 6.3″ OLED 120 Hz, 2700 nits 6.83″ AMOLED 3200 nits 6.59″ AMOLED 3500 nits 6.7″ Dynamic AMOLED 1900 nits processor Google Tensor G4 MediaTek Dimensity 8400 Ultra Snapdragon 8 Elite Samsung Exynos 2400 photographic system Dual main 48 MP + ultra Triple with 2x TV Triple with strong main sensor Triple with 3x TV BATTERY 5100mAh 5500mAh 6210mAh ~4900mAh PRICE From 549 euros From 499 euros From 519.99 euros From 544 euros 10 GOOGLE APPS THAT COULD HAVE SUCCESSFUL How are all these phones different? Design and screen Although today there are few brands that innovate in terms of the design of their terminals (see the case of Nothing) it is true that among all these models you can see design differences that can make you opt for one or another smartphone. The Google Pixel 10a is a mobile phone with a very flat and minimalist design, with a 6.3 inch compact size which makes it a perfect option to hold with one hand. On the other hand, the Xiaomi 15T has a 6.8-inch screen, for those looking for a greater sense of immersion, especially when watching multimedia content. For its part, the Xiaomi Poco F8 Pro has a 6.59-inch screen and also has a slightly larger design than the Pixel 10a, although its edges are soft; Yes, the plastic finish does not give it the feel of a premium mobile. Finally, from the design of the Samsung Galaxy S25 FE, it can be noted that it also has a large 6.7-inch screen and a more refined and premium design than the other models. Your photography system The Google Pixel 10a was born with the intention of offering a excellent photography experience within the mid-range. Of this model, we can highlight its own photo app, with AI that considerably improves your photos. Its main lens is 48 MP accompanied by a 13 MP ultra wide angle lens. Although yes, it does not have a dedicated telephoto like its older brothers. Compared to the Google model, the Xiaomi 15T offers greater versatility in photography, thanks to its triple rear camera. Plus, they are made by Leica, so you can get more artistic photos. As for the Poco F8 Pro, it incorporates a telephoto and offers 8K recording, although the Pixel surpasses it in color balance and night processing. Finally, the Samsung model presents a more advanced photographic system than Google’s, thanks to its 3x optical telephoto, which gives us greater flexibility when taking photos from a distance. Battery and charging The Google Pixel 10a battery has a average capacity of 5,100 mAh and provides autonomy for a full day using navigation, social networks and spending time on video and photos. Of course, you should know that this group of phones is not the largest battery. The Xiaomi 15T has a capacity of 5,500 mAh, so its autonomy is superior even in intensive use. Regarding the Samsung model, its battery capacity is about 5,000 mAh (4,900 mAh according to its technical sheet), so the results are very similar to those of the Google Pixel 10a, although it may become more efficient thanks to Samsung’s optimization. Finally, the big winner in terms of battery is the Xiaomi Poco F8 Pro, with a capacity of 6,200 mAh, giving us more than enough autonomy even if you use the phone for gaming. All of these smartphones offer fast charging, although it is different in each of them. The Pixel 10a supports wired charging up to 45W, thus improving on its predecessors and charging it in half in about 30 minutes. The Xiaomi model supports it up to 90 W and charges to 100% in 50 minutes. For its part, the Poco F8 Pro supports fast charging of up to 100W, which makes it possible to fully charge it in about 37 minutes. Finally, the Samsung phone is fully charged in about an hour. Their brains are different too The processor is the brain of a mobile phone and in this group of phones, each one has a different one. The Google Pixel 10a has the Google Tensor G4whose main strength is its optimization of Artificial intelligence and good daily performance, although it is not the most powerful or the best for gaming. A MediaTek Dimensity 8400 Ultra is the processor of the Xiaomi 15T, which is perfect for multitasking and demanding appsalthough it is true that it gets hot in very intense sessions and is not as efficient as Google’s for use with AI. The most powerful processor on the list is the Snapdragon 8 Elite that the Poco F8 Pro has, which is ideal for powerful games and very demanding tasks, although it may be more than necessary for users who do not need that extra power. Finally, the Samsung mobile has a Exynos 2400which provides a good balance in general, although it is not so good for demanding gaming. Operating system and updates The new Google Pixel 10a comes with Android 16 pure and receive updates for seven years. Without a doubt, it is the champion of Android updates, becoming the phone par excellence for those who want … Read more

Qwen3-Max-Thinking rivals Google’s Gemini 3 Pro more than ever. The key is in what is not being told

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There are days when it feels like we open the phone and the dashboard changes again. Since ChatGPT broke out in November 2022the artificial intelligence race has continued to accelerate, and every few weeks a new model appears which promises to push the bar a little further. Sometimes it is an update, other times it is a “flagship” with a different surname, but the pattern repeats itself: more power, more ambition and an increasingly global story. In this context, China is gaining visibility in an increasingly evident way, and the name that is now entering the conversation is Qwen3-Max-ThinkingAlibaba’s proposal with which it wants to play in the same league as the great references of the moment. At first glance, Qwen3-Max-Thinking might seem like just another name in the endless list of models. But there is a relevant nuance here: he presents it as his star model for reasoning tasks, and explicitly places it in the same conversation as Gemini 3 Pro. The company says it has scaled parameters and invested computing resources in reinforcement to improve several dimensions at once, from factual knowledge and complex reasoning to instruction following, alignment with human preferences and agent capabilities. In other words: you are not just selling raw power, but a way to “think” better. What benchmarks teach To land that promise, the most useful thing is to look at the comparative table that we have in hand, with 19 benchmarks and a direct count: Gemini 3 Pro leads in 11, Qwen3-Max-Thinking does it in 8. This data, by itself, does not decide “who is better”but it does help to understand the type of fight that Alibaba poses when faced with Google. Here it is worth being very literal with what we are measuring: each benchmark focuses on a specific skill, from general knowledge to programming, use of tools, following instructions or long context analysis. If we look for the point where Qwen3-Max-Thinking really hits home, there is one that stands out above the rest: following instructions and aligning with what humans prefer in a conversation. In Arena-Hard v2Qwen wins with 90.2 compared to Gemini’s 81.7, which is the largest difference in its favor in the entire table (8.5 points above). It is not a minor nuance, because this type of benchmark does not reward only the technical “success”, but rather the final result that a person considers most useful when blindly comparing answers. Added to that IFBenchwhere Qwen wins by the minimum (70.9 versus 70.4). Translated into real life: when the user does not formulate a perfect instruction, when the assignment has ambiguity or requires interpreting intent, Qwen seems more oriented to nailing what is asked of him and doing it in a way that feels natural. The other area where Qwen supports his “thinking model” narrative is mathematical reasoning and logical problem solving. On HMMT, in both the November 2025 and February 2025 issues, Qwen is ahead (94.7 vs. 93.3 and 98.0 vs. 97.5, respectively). And in IMOAnswerBench it also wins, although by a minimal margin: 83.9 versus 83.3. These numbers do not suggest a beating, but they do suggest a consistent pattern: when the problem demands several steps of logic and it is not solved only with memory or a nice answer, Qwen tends to take advantage. To these improvements Alibaba adds a component that is already becoming the new standard: that the model does not remain in the text, but can act. In its presentation, the company talks about an adaptive use of tools that allows information to be retrieved on demand and a code interpreter to be invoked. And this orientation also appears in the benchmarks: in HLE (w/ tools), Qwen wins with 49.8 compared to 45.8 for Gemini, which suggests a better ability to perform when the model can rely on external tools. Here the fundamental change is important: it is no longer just “what he responds”, but how he investigates, how he decides what tool to use and how he synthesizes what he finds. There is a part of this comparison where the Gemini 3 Pro feels more “engineer” than “conversational,” and it is precisely where many professional users put the focus. The Google model wins in MMLU-Pro and MMLU-Redux, two tests closely associated with general knowledge, and also in GPQA and HLE, which in this table appear as demanding evaluation benchmarks and complex questions. In code, Gemini prevails in LiveCodeBench v6 and also in SWE Verifiedwhich reinforces the idea that, for programming tasksis still a very solid bet. Added to this is AA-LCR, where it leads in analysis of long documents. The fine print hides beyond the price At this point, there is a question that weighs as much as any benchmark: how much does it cost to use these models seriously. In standard prices per 1M tokens, the contrast is clear. On Gemini 3 Pro, the entry moves between 2 and 4 dollars depending on the tranche of input tokens, while in Qwen3-Max The input is listed at $1.2. But the most important difference appears at the output, which is where the “thought” of the model is paid: Gemini marks 12 to 18 dollars compared to the 6 dollars of Qwen. Translated into proportions, in standard use Gemini is approximately 1.67 times more expensive in entry and 2 times more expensive in exit in the usual section. If the tranche exceeds 200,000 entry tokens, the distance increases to 3.33 times in entry and 3 times in exit. Gemini is approximately 1.67 times more expensive on entry and 2 times more expensive on exit in the usual section. And here we come to the part that is usually left out of the conversation when everything focuses on power and price: what happens to your data when you use the model, and under what rules. In the case of Qwen, two worlds must be clearly separated. On the one hand there is the consumer web chat, whose terms They contemplate the use and storage … Read more

Microsoft had the deal of the century on its hands. A break of a year and a half was given to one of his rivals on a platter

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With its early deal with OpenAI, Microsoft was leading the AI ​​race in 2023. A year later it froze its expansion. Now Oracle serves OpenAI models and competitors share what Nadella’s company rejected. Why is it important. This isn’t just about lost data centers. Microsoft has assigned contracts with OpenAI valued at $420 billion to Oracle, equivalent to $150 billion in gross profit over five years. That would have increased its annual profitability by 18%. This means that in addition to losing growth, Microsoft also financed the entry of a rival into the most profitable business of the decade, according to analysis by Semianalysis. The facts. In 2023, Microsoft multiplied its investment in OpenAI tenfold to $10 billion and broke ground on the largest data centers ever built. Represented more than 60% of all infrastructure leases cloud among the greats. In 2024 it stopped everything in its tracks. It canceled 3.5 gigawatts of planned capacity — enough to power 2.5 million homes — and projects in a dozen countries. Its share of contracts fell below 25%. Between the lines. The company has used the argument of financial prudence: it did not want OpenAI to represent 50% of Azure’s revenue with lower margins than the traditional business. But the reality is simpler: he couldn’t keep up: OpenAI demanded a speed that Microsoft couldn’t match. Yes, but. The company has returned to the market with some urgency. The problem is that the options have been running out. Now rents capacity to neoclouds —specialized companies that build infrastructure—to resell it to third parties. It is a business with worse margins. The company that refused to build now pays commissions for having miscalculated. The money trail. Oracle is not the only winner. CoreWeave, Google, Amazon, Nscale and SB Energy have signed large contracts with OpenAI. In 2025, the story of OpenAI has been the story of its diversification away from Microsoft, although it is true that What seemed like a bad divorce ended in a separation of assets with forced smiles. The world’s most valuable AI lab had to fragment its infrastructure across multiple vendors because its original partner couldn’t—or wouldn’t—scale. In applications, Microsoft’s historical dominance with GitHub Copilot is also eroding. There are startups that have built more integrated code editors and scaled beyond Copilot. Microsoft has been forced to add the models of its rival Anthropic on GitHub Copilotwith a brutal cost for their margins. The company that had exclusive access to OpenAI now depends on its competitor to keep its code editor relevant. And now what. Microsoft has until 2032 before its agreement with OpenAI expires. It has Copilot with 100 million users. You have Office 365, Azure, and a business ecosystem that no one else can match. But the “great pause” of 2024 will take years to heal. The company has bet that the future of AI will be enterprise – with security and localization requirements – and not centralized in remote megacenters. You may be right. But 18 months of technology advantage is worth billions. And Microsoft just gave them away to its rivals. In Xataka | OpenAI has to pay debts of $400 billion in 2026. Nobody has the slightest idea how it is going to pay them Featured image | Simon Ray in Unsplash

Spend more on R&D than any of its rivals

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Intel has not just lifted. With An intractable nvidia in the segment of artificial intelligence and with a Unattainable TSMCthe company tries to adapt to The new times. The hope is that the latest capital injections help: in recent days we have seen how Softbank invest 2,000 million euros euros in it and then the United States government has bought 10% of Intel to save it from burning. However, the company Directed by Lip-Bu Tan He is putting all the meat on the grill to try to do it. It is demonstrated by the Spectacular amount of money invested in your R&D department. The surprising thing is not to invest a lot of money; That is expected in a technological company. The really surprising thing is that he invests much more than his rivals. Intel invest more than anyone in R&D, but be careful: their rivals squeeze the step An analysis by Techinsights cited In Korea Joongang Daily It collects the financial results of Intel and some of its rivals in 2024 to study its investments in R&D. According to these data, these were those amounts for various companies: Intel: 16,546 million dollars (PDF) Nvidia: 12,914 million dollars (Nvidia) Samsung: 9,500 million dollars (Joongang) TSMC: 6.5 billion dollars (Joongang) AMD: 6,456 million dollars (PDF) That means that Intel invests 28% more than Nvidia – which right now has a much greater dimension – 47% more than Samsung and nothing less than 156% more than AMD or TSMC, which despite the most important company in the world in the manufacture of semiconductors does not dedicate more money than its rivals to innovate. The thing becomes even more interesting if we compare these R&D investments with the income of these companies. In 2024 Intel invested 31% of its net incomewhile AMD invested 26%. Nvidia only invested 10% – but not to make money with their AI products – but here the truly striking is that Samsung does not seem so interested in its R&D department, because it only invested 4% of its net income. It is also important to note that in AMD they do not have their own production plants such as the rest of their competitors, so although their investment in R&D was the lowest of these four companies, all that investment went to the chip design in full. The problem for Intel is that its growth in investment in R&D grew only 3.1% that in 2023. Compared Samsung grew by 71.3% more, NVIDIA 47% more and TSMC 8.8% more. They all seem to press the step more than Intelwhich raises just the opposite. In fact it is known if in That cuts policy which is carrying out Lip-Bu so will also end up cuts in the division and cost of R&D, but It seems possible that it is so. If so, this 2025 NVIDIA may end up being the company that spends the most in R&D, especially to try not to lose its privileged position in the AI ​​market. Image | Intel In Xataka | Intel’s fall symbolizes the end of an era: the model that dominated technology for 50 years has died

Their companies lack the scale of their rivals

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The Japan government needs its semiconductor industry to be great again. The biggest. In fact, it was in the past. In 1988 NEC, Toshiba, Hitachi, Fujitsu, Mitsubishi, Matsushita and other Japanese companies hoarded nothing less than 50% of the chips industry. However, Today none of these companies It is positioned among the leaders of A sector dominated with iron fist by Taiwanese, American, Dutch, South Korean and German companies. Japan is currently investing more money in its sector of integrated circuits than the US, Germany, France or the United Kingdom. Not in terms of net value, but its effort is greater if we weigh the investment of these countries on their gross domestic product (GDP). The US dedicates 0.21% of its GDP to its semiconductor industry, and Germany 0.41%. France, according to Nikkei Asia0.2%, and, finally, the United Kingdom 0.04%. The difference is very significant and puts on the table the effort that Japan is making with 0.71% of its GDP. However, this country will not be easy to compete from you to you with Taiwan or South Korea in the integrated circuit industry. Toshikazu Maeda, the general director of the company specialized in the manufacture of equipment to produce Marumae chips, holds that many Japanese companies lack the necessary scale to compete effectively and increase their income. In fact, he regrets that most of the Japanese companies are not growing in full rise of the artificial intelligence (AI). To remedy it, it proposes a solution: smaller companies should merge to grow and be ready to react to the next great opportunity. Rapidus is Japan’s best option to compete with South Korea and Taiwan Japan currently has dozens of very specialized small businesses that manufacture components for ASML either Tokyo Electronwhich are two of the largest manufacturers of photolithography and wafering processing equipment. As Maeda defendsits production capacity is too modest to compete with giants from other countries, such as South Korean companies Samsung or SK Hynix, which produce some of their integrated circuit manufacturing equipment, or the American applied materials, among many others. However, if we stick to the manufacture of Japan Chips already has a company that aspires to compete with TSMC, Intel or Samsung. Rapidus corporation It has been expressly created to replace Japan at the forefront of integrated circuits. Interestingly, it is a very young company. It was founded on August 10, 2022 By the Japanese government With an initial capital of 7,346 million yen (just under 46 million euros) contributed by, and here comes the interesting, Sony, Toyota, Nec, Softbank, Kioxia, Denso, Nippon Telegraph and Mufg Bank. The initial capital invested in the constitution of this company is not very bulky, but there is no doubt that the companies that participate in it have an indisputable relevance in the sectors of technology, automotive and telecommunications. Japan currently has dozens of very specialized small businesses that manufacture components for ASML or Tokyo Electron Rapidus is currently putting a circuit manufacturing plant integrated in northern Japan, in the city of Chitose (Hokkaido), in which it plans to produce semiconductors of 2 Nm. The first prototypes of these chips They are already readybut large -scale manufacturing will not arrive at best until 2027. So far there is nothing really surprising because presumably at that time TSMC, Samsung and Intel will already be manufacturing integrated circuits with comparable lithographs. What is causing the new Rapidus factory to monopolize the looks of the semiconductor sector is that, according to Atsuyoshi Koike, which is the president of the company, it will be completely automated. Its purpose is resort to robots and AI To set up an automated production line that will be specialized in the manufacture of 2 Nm chips for AI applications. Its plan consists, in short, to produce integrated circuits faster, with a lower and more quality cost. To manufacture these semiconductors, equipment of extreme ultraviolet lithography (UVE) produced by the Dutch company ASML, and practically all manufacturing processes are automatic. However, the tests of test and validation, interconnection and packaging of the chips are still largely carried out manually in most manufacturing plants. According to Rapidus, its automation technology of all these processes will allow you to reduce the delivery time of your chips by 66% compared to the times they usually offer TSMC and Samsung. If this Japanese company finally achieves its purpose and its competitors do not improve its efficiency will be able to deliver its semiconductors In a third of the time spent by their rivals. A priori is a stinging enough asset for Rapidus to grow in a perceptible way, although for the moment it is just a conjecture. Whatever this company seems to have everything well tied. More information | SCMP In Xataka | Japan takes the initiative with nuclear fusion and sets an extremely ambitious date: the 2030s In Xataka | Japan has taken the carrier to dominate the chips industry. Prepare a 325,000 million dollar plan

The most obsessively competitive gamers have found a trick to win their rivals: Give Electric Downloads

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Today video game developers are really strict in terms of cheating in their creations, with different systems Anti -che that They even affect kernel From our computer as is the case in ‘Valorant‘. But a new generation of Modders It is demonstrating that traps can be done without touching a single line of game code: with electrical discharges. If I can’t hack the game, I’m looking for alternatives. For some people, it is good for it is the same as Apply different tricks to games that they use daily to be able to cross walls, be immortal or have an automatic point when talking about Shooters. But this is something that leaves the rest of the players of a game. Having the player himself. Two Youtubers They have put the solution on the table to skip the barriers that are applied at the hardware level. One of them is ‘Basically Homeless’ that has led the concept of ‘player improvement’ to a new level. And instead of installing software that points for it in Counter-Strike 2, has created a system that electrocutes your arm to react at a superhuman speed. The mechanism is fascinating. An external software analyzes the screen in search of enemies. As soon as one detects one, it sends a signal to a Raspberry Piwhich in turn activates muscle stimulation diodes placed strategically in its forearm and hand. These little cramps force their muscles to get contracting, moving the mouse towards the target and clicking. Surprisingly, it is something that works. The results are very good. The own Youtuber He managed to reduce his reaction time of about 200 milliseconds approximately at only 100 milliseconds. According to its calculations, using an Ethernet cable connection instead of Wi -Fi to communicate the PC with the Raspberry Pi, it could lower this figure to 40 ms, a practically unbeatable speed for a human being. It does not consider it a trap. For this creator this is not something that threatens ethics when playing against other people. It is only a help, or as he calls it, ‘neuromuscular aim assistance’, since it is technically his own body who performs the action, although induced by a machine. Although it remains to be seen what large companies would say if this is popularized. Robotic carpets that point for you. In a similar line, the Modder Kamal Carter has presented another solution of hardware to dominate in Valorant. In his case, the protagonist is not his arm, but a robotic platform located under the mouse mat. And the system is similar. A screen reader identifies the enemy bots in the game’s shooting field in the first place. Next, a program that emulates the techniques of aimed at professional players sends instructions to the platform. This moves with a millimeter accuracy, displacing the mouse to achieve perfect shots. After adding a system that automates the click, Carter achieved almost perfect scores in practical mode. The most advanced anti-cheat systems are weak. “Made the law, made the trap,” says the saying. And in this case it is fulfilled. Large companies no longer know what to do to avoid tricks in their games, coming to ‘invade’ the kernel of our computer with maximum Windows privileges. Something that is designed to detect the use of unauthorized software. And there are many consequences that are being presented by cheating. Valve managed to block 40,000 cheats In ‘Dota 2’ or in ‘Deadlock’ They transformed into frogs to the most cheats to become aware that they should not do that. But also in Warzone they bet on Block the opening of the parachutes with the aim of crashing directly with the ground. But now these new tricks can be more difficult to detect and apply a punishment. In Xataka | Nintendo Switch 2: 17 tricks and tips to squeeze the portable console to the maximum

Bill Gates and Linus Torvalds had been rivals for 30 years. The funny thing is that they have just known and a selfie has been made

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Being fond of technology between the late 90s and the first years 2000 implied Be a witness of a fierce War of sides Among the supporters of Windows, Macos or being an alternative “outsider” that renegated both (and even Graphic environments) and hugged free software from the hand of GNU/Linux. As standards of each of those sides: Bill Gates, Steve Jobs and Linus Torvalds. Between Bill Gates and Steve Jobs there has always been a certain Love -od relationship What He led to collaborate and throw yourself The hit to the head recurringly. However, after more than three decades dedicating expletives, we have had to wait until 2025 so that Bill Gates and Linus Torvalds are face to face and appear together (and well avenues) in a photo. A historical encounter between two legends Bill Gates has defended throughout his career the right of developers to license your programs I already charge for them who uses them. For its part, on the opposite side, Linus Torvalds bet on a Open and collaborative modelin which each user can adapt their tools to their measure freely. Bill Gates and Microsoft. Linus Torvalds and Linux. Both represent the different ways of understanding the evolution of computer science in the last three decades and, despite being the main protagonists and flag bearers of the most fierce dialectical battles In the technology blogs of the 90 and 2000, they did not know each other in person. The person responsible for facilitating the historical meeting has been Mark Russinovich, creator of the popular SysInternals softwarewhich currently acts as Director of Technology (CTO) of Microsoft Azure. Russinovich, always has been very supportive of the Open Source solutions and it was one The drivers of Azure support for Linux. That position has assured him a Good relationship with Torvaldswho accepted the invitation of the director for dinner with Bill Gates and Dave Cutler, one of the main Windows NT developers and Azure promoter. It has transcended very little about what was discussed during the unique dinner, but what has transcended has been the historic selfie that Russinovich did to immortalize the meeting and that he has published in Your LinkedIn profile. It is undoubtedly an unusual image of two staunch enemies for more than three decades, which They just met And they pose with relaxed and affable attitude. Touch the photo to go to the original message Next to the photo, the host could not hide his emotion for having achieved such a milestone: “I had the emotion of my life, organizing dinners for Bill Gates, Linus Torvalds and David Cutler. Linus had never met Bill, and Dave had never met Linus. No important decisions were made about the kernel, but perhaps the next dinner.” Linux very touched and more integrative Microsoft The moment in which it occurs does not go unnoticed either. Linux has gained market share thanks to the proliferation of cloud infrastructure and is already installed in about 100 million equipment (mainly servers), achieving a 4.13% market share. In 2021 and 2022, the system had a 2% share, which has been growing since then. According to data Statcounter, the Windows fee remains in a loaf 70.21%. For its part, Microsoft left behind the times of Steve Ballmer describing “cancer” To Linux. Since the arrival of Satya Nadella to the Microsoft direction, they have been carried out different approach samples between Windows and Linux. One of the most important was the possibility of deploying a Windows subsystem for Linux (WSL) that allows you to execute an environment Linux in Windows computers. Perhaps, as Russinovich said in his post “important decisions were made about the kernel” but, taking into account the attendees of that dinner, they may talk about greater Linux integration On the Azure Platform of Microsoft. Maybe they decide at the next dinner. In Xataka | Bill Gates’ fortune records an unprecedented fact in the last 33 years: Millionaires’ Top 10 ‘has been left out Image | Mark Russinovich

Apple believes that its rivals are not doing well in ia. It is the perfect excuse to delay Siri one more year

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We already have news about the arrival of the expected and Nueva Siri. They are not good. Apple points to the spring of 2026 as a launch objective for its new assistant, with the aim of bringing it as part of the update to iOS 26.4, According to Bloomberg sources. The delay is completely in line with The recent interview of Wall Street Journal Craig Federight and Greg Joswiak: Apple knows that he is losing the AI ​​career, and he only has trust that your proposal ends up working in the long term. They painted you little birds in the air. It has been just one year since that presentation of Apple Centered in Apple Intelligence. One in which they told us about an integration of Siri in the system as we had not seen: an assistant with the ability to understand each corner of iOS, with an advanced contextual understanding and integration with each native app of the system. In principle, the final deployment was planned for autumn of 2024, but the delays accumulated and accumulate until they reached a practically unsustainable point. iOS 26 as first real step. Apple took advantage of the WWDC 25 To present iOS 26, one of the Greater changes at the visual identity level Never seen in Apple’s operating systems, now much more unified. Next to him, they finally arrived Artificial Intelligence Functions Applied to everyday use: although for practical purposes they do not go far beyond the translation of texts, filters for calls and some improvements in the generation of genumjis in image playground. After almost a year of delays, Apple finally implied what is its philosophy with AI: work to make it local, but with a functioning similar to that of its rivals. More delays. After the presentation of iOS 26with novelties in AI but not a single word about the new Siri, the question was forced. What is happening with her? The responses of a Craig Federighi, nothing height but not entirely comfortable, perfectly revealed the moment in which Apple is. (Joanna Stern) “Siri is not better than his competition”, (Craig Federight) “already, but it will be, it is our mission.” (Greg Joswiak) “It would be disappointing to launch something that does not meet our quality standards.” (Craig Federight) “This is a new technology, nobody is doing very well right now.” Joswiak, software leader in Apple, justified its road map around the key point: the company wants its AI to be discreet and that the user can perform tasks with the phone without even realizing that he is using Apple Intelligence. In fact, they do not want a dedicated app, as there is for Gemini either Chatgpt. The problem? Google has achieved this goal for a long time. Apple’s rivals are doing well. Although Apple points to the immaturity of the AI ​​for mobiles, the truth is that one of its best moments lives. And phones like Google Pixel or the Samsung Galaxy S25 Ultra They are the best proof of this. Here you have to make a distinction between Gemini as an app integrated in the system, and with Gemini Nano as a language model. On a telephone like the Ultra S25 can: Translate real -time calls without knowing that AI is doing. Remove the background noise from a video automatically, without Gemini telling you what you are doing. You can transcribe a voice recording with a single click, without opening additional applications. If they call you, the phone will automatically detect whether or not spam, without notices about ia. Yes, Google (although its approach is not so local), is able to integrate Gemini silently into the system. So much so that their functions are still native to the system, and the user does not have to know what is done with Ia and what not. Apple needs to overcome Gemini at AI. It will not be easy. Apple, for now, has not shown to live. During the presentation of Apple, Its action fell 1.5%. The expectations were high, but the presentation was a clear Apple message showing not being above any of its direct rivals, and relegating third parties (OpenAi) the most advanced functions of AI. With the looks put in 2026, the pressure to which Apple is subjected is even greater. The maturity point of its main rival, Google Gemini, is very highabove proposals in Benchmarks regarding Grok 3, O3-mini, Deepseek R1, Claude 3 and calls 4. To recover Apple confidence needs results, not promises. Image | Xataka In Xataka | We have discovered something worrying in the AI ​​models: if the problem is too difficult, they give away immediately

Now the company has a plan to stop benefiting its rivals, according to FT

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Deepmind, the firm of Artificial Intelligence (AI) that Google acquired in 2014 and officially integrated into a single division in April 2023it has been for years one of the great referents of the sector. Over time, he has earned that place for the quality of his scientific publications and for gathering some of the brightest researchers. But there are reasons to believe that this approach has begun to change. Several experts cited by Financial Times They ensure that Google Deepmind is delaying the publication of certain advances that it considers “strategic” or delicate in the field of generative AI. The measure is part of a strategy designed to preserve its competitive advantage and prevent its most recent and valuable developments from being exploited by rivals such as OpenAi. Transformers, star architecture Much of the development of generative artificial intelligence is not understood without Google’s advances. One of the most influential milestones was the publication in 2017 of the article ‘Attention is all you need‘, signed by eight researchers, who introduced the Transformers architecture. This approach, in general, allowed the models to process data more efficiently within large volumes of information. This architecture became the base of models such as Bert (bidirectional encoder representations from transformers), developed by Google itself and incorporated into its search engine in 2019 to improve the understanding of natural language. It was also key to the development of presentful systems such as GPT (Generative pre-trained transformers) of OpenAi, where the current ones are framed GPT-4 and GPT-4.5. Google is one of the world’s largest companies in the world. It has a huge financial muscle and access to key technology. Even so, the launch of Chatgptbased on GPT-3.5a model built on Transformers architecture, He took by surprise to the teams directed by L sundaria Pichai. The reaction was a “red code” and an urgent reorganization to compete again in an AI race that today leads OpenAi. It is no secret: when a company becomes a Big Tech, it loses part of the dynamism that defined it in its beginnings as startup. As we counted exactly one year agothey end up transforming into giants where the “move quickly and breaks things” no longer fits. They have too much to protect and a gear with thousands of pieces that cannot allow failures. Risking is not as easy as it seems. Even in this context, it surprises the speed with which the company of the search engine has managed to catch up. In a short time he has launched a AVALANCHA OF IA PRODUCTS based on advanced language models. There it is Geminihis direct rival of Chatgpt; Gemini Livedesigned to compete with Openai’s advanced voice mode; the Gemsthat work as Personalized GPTS; and amazing tools, such as Notebooklm. The new Google pulse The last years have forced the Mountain View company to introduce internal weight changes. One of the most significant affects the policy of publication of scientific articles: if the content is considered strategic, an seizure of six months is imposed before making it public. In addition, the group led by The Nobel Prize winner Sir Demis Hassabis He has hardened his internal processes, with a stricter review. One of the researchers who spoke on condition of anonymity with Financial Times was clear: today he cannot imagine Google by publishing a document like Transformers for general use. In this new dynamic, they say, “the company has become more concerned about the product and less for sharing the results of the investigation for the benefit of the common good ”, an address that can generate some discomfort in the community. Images | Boliviainteligent | Google Deepmind In Xataka | Openai has just lifted the greatest financing round in history: there is a blind faith in the AI ​​despite everything

Siri is not the only broken toy in the world voice attendees. Their rivals still do

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Apple is still choking artificial intelligence implementation. The company confirmed at the end of the week that Siri’s advanced functions would take “More than expected” In arriving, without giving a specific date but advancing that until 2026 we will not have news. The company is late, but it is not the only one in trouble with its intelligent assistant. The great alternative to Siri is Gemini, a solution that most Android manufacturers are beginning to implement in collaboration with Google and that follows very, very green. Don’t wait for the new Siri soon. One of Apple Intelligence’s reasons was The new Siri. Native integration with chatgpt, Natural language understandinganalysis of the content of our phone to meet in detail … recently we could Test Apple Intelligence beta And the conclusion was clear: everything was half building or, directly, it wasn’t. Weeks later, Apple confirmed that Siri’s smartest version “will take longer than expected.” His artificial intelligence is still in beta and the arrival of all the news from this spring was expected. It won’t be so. Apple decided not to get into the AI ​​car when its main rivals were at a point of relative maturity, and These delays They have taken her to the current situation. His rival rubs his hands. Meanwhile, the answer on Android is being clear. This operating system is owned by Google, and Google has Gemini as vitamin assistant with artificial intelligence. Thus, most phones (Oppo, Samsung, Xiaomi, etc.) that are sold in Europe, arrive from Gemini. This is the agent that replaces the classic Google (OK, Google) assistant that we have been using on our phones for so many years, with the main difference of being a Google response to tools such as Chatgpt. Not everything that shines. Gemini has improved, and much, Since we tried it in February 2024. Gemini Live now It is completely freehas no problem to execute simple actions (alarms, searches, etc.), but it is still very far from being a natural assistant. One of its main problems is precisely that the distinction between Gemini and Gemini Live dilutes the use we want to give as an assistant. If, for example, I ask Gemini what I can do today, he will give me an especially extensive answer. If I want to stop talking (in addition, Gemini’s tone is quite robotic and unnatural) I cannot do it comfortably, since the only way that allows interruptions is that of Gemini Live. In other words, in an independent app (such as Gemini or Chatgpt) this distinction between conversational modes makes sense. In a fast and native assistant, everything should be available in the most accessible way. And no, if you tell Gemini if ​​you can speak using Gemini Live, do not activate this mode, start talking without stopping what this way is. Gemini also does not have access to native applications (it only works by extensions and, today, there are very few. It is not even able to make adjustments as simple as lowering/uploading the brightness of the phone, and the same happens with the volume. Much less can change basic system adjustments if we ask. There are no more rivals in sight (still). The only Android manufacturer who bet on a conversational assistant was Samsung with Bixby. This assistant is still alive in One UI 7, but it is so secondary that Samsung herself preinstall Gemini on her phones and its extensions are key to the operation of Galaxy AI. In China, the great manufacturers are beginning to integrate Depseek as the native but, for the moment, there is no advanced voice or native integration. Honor wants to change everything With its AI agent, one capable of performing all kinds of requests, including the most important, those of native adjustments. Image | Apple In Xataka | The new Siri forgets the devices where it is more important: the Homepod and Apple Watch

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