models

These are the 13 models that are already updated, and the other nine from Redmi and POCO that will update later

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Let’s tell you to what models of Xiaomi phones and tablets HyperOS 3 has started to arriveso that if you have one of them you know that you can now start looking for the update. We already told you how to check if your mobile will update using an app, but now the moment of truth has arrived. We are going to start the article with the models where the update of this customization layer based on Android 16. And then we will tell you What are the next mobile phones that will receive it?so that if you have one you know that Xiami also counts on you. Xiaomi phones that already receive HyperOS 3 These are all the mobile phones and tablets from the Chinese company that You can now update to HyperOS 3.0. If you go into your mobile settings and check for system updates, you can start enjoying Android 16 after updating. Xiaomi Pad 7 Xiaomi Pad 6S Pro 12.4 Xiaomi 14 Ultra Xiaomi 14 Ultra Titanium Special Edition Xiaomi 14 Pro Xiaomi 14 Pro Titanium Special Edition Xiaomi 14 Xiaomi MIX Fold 4 Xiaomi MIX Flip Xiaomi Civi 4 Pro Redmi K70 Pro Redmi K70 Ultimate Edition Redmi K70 Redmi K70E The normal thing is that the update arrives without you having to do anything, a notification appears that alerts you that it is available so that you only have to click on it. But if not, in the settings click on about the phonewhere after clicking on your version of HyperOS it will search for updates. Mobile phones that will also receive HyperOS 3 In addition to the models that are already receiving the update, we also have a list of mobile phones that will soon receive it. For them there are no specific dates, but if you have one you should know that yes, you will have Android 16. In Xataka Basics | Android 16: 17 functions and some tricks of the new version of Google’s mobile operating system

The two most important weather models in the world are discussing whether Santander is going to freeze next week. And the cold is winning

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Where has all the cold gone? So far this fall (with the sole exception of Siberia), temperatures have been relatively mild on all continents. And it seems that the situation is going to continue like this: it is true that the forecasts speak of a progressive decrease in temperatures in the southeast of Canada, the eastern United States and northern Europe; but no model paints a scenario that is particularly cold (except some very long term prediction). However, all eyes are on the polar vortex. If the models are right, it is very possible that the vortex will experience an unprecedented disturbance in November, leading to an interesting weather period starting in December. “There is no way this is fulfilled.” While November continues with its strange meteorology, the models draw increasingly strange scenarios. At this point in the week, we cannot rule out that on the 18th and 19th we have a more than considerable winter storm with the ‘beast from the east‘looming over Western Europe. In the next few hours we will have a war between models: The American marks a cold entry on Santander, the European said no. Little by little, the two seem to be converging towards a cold scene. It’s too early to say, but in a very few hours the daisy will be shedding its leaves. Anyway, the central issue is that all of this is minute sin. The breaking of the vortex. Except for that event in the middle of next week, autumn will continue to be very warm and mild on almost all continents. However, this could change if sudden stratospheric warming appears. That is, the vortex breaks. Sudden stratospheric warming? To understand it simply, we have to remember that the atmosphere is a kind of “lasagna of air layers” and each of them follows its own logic. That is, they work quite differently and independently. As far as it affects us: the circulation of air in the troposphere (the one closest to the surface) and the circulation in the stratosphere (the layer directly above) are related, yes; But, in general terms, they each do their own thing. During the “sudden stratospheric warming“, a part of the troposphere warms rapidly and, as a consequence, invades the stratosphere, causing a profound alteration of the circulation at high altitude. That is, for a few days, everything turns upside down. And what happens? The most common consequence of this is that the polar vortex weakens and may break down. The polar (arctic) vortex is a current of air that runs from west to east around the north pole and contains cold air at high latitudes. When this current is strong and stable, preventing it from flowing towards places like Spain. If the vortex It destabilizes and its winds lose strength (due to, for example, “sudden warming”), it is relatively common for cold air masses to escape on their way south. What if it doesn’t break? In reality, the vortex does not even need to break. It only needs to move from the Arctic region to lower latitudes. By moving a huge mass of cold air with it, the result is always very similar: an icy cold that can turn any country upside down (even the best prepared ones). And that seems to be what we are going to see. It’s hard to know if it will affect us or not, but there’s no doubt that the late fall weather is getting “interesting.” Image | Meteociel In Xataka | The last hope of winter in Spain is desperate, but increasingly possible: the breaking of the polar vortex

The industry became obsessed with training AI models, while Google prepared its masterstroke: inference chips

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In recent years, what was truly relevant was training AI models to make them better. Now that they have matured and training it no longer scales as noticeablywhat matters most is inference: that when we use AI chatbots they work quickly and efficiently. Google realized this change in focus, and has chips precisely prepared for it. Ironwood. This is the name of the new chips from Google’s famous family of Tensor Processing Units (TPUs). The company, which began developing them in 2015 and launched the first ones in 2018now obtains especially interesting fruits from all that effort: some really promising chips not for training AI models, but for us to use them faster and more efficiently than ever. Inference, inference, inference. These “TPUv7” will be available in the coming weeks and can be used to train AI models, but they are especially aimed at “serving” these models to users so that they can use them. It is the other big leg of AI chips, the really visible one: one thing is to train the models and quite another to “execute” them so that they respond to user requests. Efficiency and power by flag. The advance in the performance of these AI chips is enormous, at least according to Google. The company claims that Ironwood offers four times the performance of the previous generation in both training and inference, and is “the most powerful and energy-efficient custom silicon to date.” Google has already reached an agreement with Anthropic so that the latter has access up to one million TPUs to run Claude and serve it to its users. Google’s AI supercomputersand. These chips are the key components of the so-called AI Hypercomputer, an integrated supercomputing system that according to Google allows customers to reduce IT costs by 28% and a ROI of 353% in three years. Or what is the same: they promise that if you use these chips, the return on investment will be multiplied by more than four in that period. Almost 10,000 interconnected chips. The new Ironwoods are also equipped with the ability to be part of joining forces in a big way. It is possible to combine up to 9,216 of them in a single node or pod, which theoretically makes the bottlenecks of the most demanding models disappear. The size of this type of cluster is enormous, and allows for up to 1.77 Petabytes of shared HBM memory while these chips communicate with a bandwidth of 9.6 Tbps thanks to the so-called Inter-Chip Interconnect (ICI). More FLOPS than anyone. The company also claims that an “Ironwood pod” (a cluster with those 9,216 Ironwood TPUs) offers 118x more ExaFLOPS FP8 than its best competitor. FLOPS measure how many floating-point math operations these chips can solve per second, ensuring that basically any AI workload is going to run in record times. NVIDIA has more and more competition (and that’s a good thing). Google chips are a demonstration of the clear vocation of companies to avoid too many dependencies on third parties. Google has all the ingredients to do it, and its TPUv7 is proof of this. It’s not the only oneand many other AI companies have long sought to create their own chips. NVIDIA’s dominance remains clearbut the company has a small problem. In inference CUDA is no longer so vital. Once the AI ​​model has been trained, inference operates under different game rules than training. CUDA support remains a relevant factorbut its importance in inference is much less. Inference focuses on obtaining the fastest possible answer. Here the models are “compiled” and can run optimally on the target hardware. This may cause NVIDIA to lose relevance to alternatives like Google. In Xataka | When you’re OpenAI and you can’t buy enough GPUs, the solution is obvious: make your own

which models are going to update to the next version

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Let’s tell you which Motorola phones are going to update to Android 16, now that the manufacturer has begun to deploy the new version of the operating system. In this way, if you have a mobile phone of this brand we will leave you the list where you can see the models they receive Android 16. Motorola is going to update almost thirty mobile models to the new version of Android, including both its flagships and other models that have been launched in the last three years. Thus, if your mobile model appears on this list, you will receive the update in the coming weeks or months. Motorola phones with Android 16 Motorola has a policy to cover two years of operating system updates. If your mobile is on this list you will receive Android 16although the time to wait will depend on each model. In the cases of the latest high ranges the updates will arrive soon, while in others it may take several months for them to appear. These are the mobile phones that will be updated between the remainder of 2025 and the beginning of 2026: Motorola Edge 60 Pro Motorola Edge 60 Motorola Edge 60 Fusion Motorola Edge 60 Stylus Motorola Edge 2025 Motorola Edge 50 Ultra Motorola Edge 50 Pro Motorola Edge 50 Neo Motorola Edge 50 Fusion Motorola Edge 50 Motorola Edge 40 Pro Motorola Razr 60 Ultra Motorola Razr 60 Motorola Razr 2025 Motorola Razr Plus 2025 Motorola Razr 50 Ultra Motorola Razr 50 Motorola Razr Plus 2024 Motorola Razr 2023 Moto G86 Moto G86 Power Moto G56 Moto G Power 2025 Moto G 2025 Motorola G Stylus 2025 Moto G85 Moto G75 Moto G55 ThinkPhone 25 Cover photo | Ivan Linares In Xataka Basics | Android 16: 17 functions and some tricks of the new version of Google’s mobile operating system

We already know how to retrieve the exact prompts that people use in AI models. It’s terrifying news

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A group of researchers has published a study that once again raises alarm bells regarding privacy when using AI. What they have managed to demonstrate is that it is possible to know the exact prompt that a user used when asking a chatbot something, and that puts AI companies in a delicate position. They can, more than ever, know everything about us. A terrifying study. If you are told that ‘Linguistic models are injective and, therefore, invertible’ you will probably be shocked. That’s the title from the study carried out by European researchers in which they explain that large language models (LLM) have a major privacy problem. And it has it because the transformer architecture is designed that way: each different prompt corresponds to a different “embedding” in the latent space of the model. A sneaky algorithm. During the development of their theory, the researchers created an algorithm called SIPIT (Sequential Inverse Prompt via ITerative updates). Such an algorithm reconstructs the exact input text from the hidden activations/states with a guarantee that it will do so in linear time. Or what is the same: you can make the model “snap” easily and quickly. What does this mean. What all this means is that the answer you got when using that AI model allows you to find out exactly what you asked it. In reality, it is not the answer that gives away, but the hidden states or embeddings that the AI ​​models use to end up giving the final answer. That’s a problem, because AI companies keep these states hidden, which would theoretically allow them to know the input prompt with absolute accuracy. But many companies already saved the prompts. That’s true, but that “injectivity” creates an additional privacy risk. Many embeddings or internal states are stored for caching, for monitoring or diagnosis, and for customization. If a company only deletes the plain text conversation but does not delete the embeddings file, the prompt is still recoverable from that file. The study shows that any system that stores hidden states is effectively handling the input text itself. Legal impact. There is also a dangerous legal component here. Until now, regulators and companies argued that internal states were not considered “recoverable personal data,” but that invertibility changes the rules of the game. If an AI company tells you that “don’t worry, I don’t save the prompts” but it does save the hidden states, it’s as if that theoretical privacy guarantee is of no use. Possible data leaks. A priori it does not seem easy for a potential attacker to do something like this because they would first have to have access to those embeddings. A security breach that results in the leak of a database of those internal/hidden states (embeddings) would no longer be considered an exposure of “abstract” or “encrypted” data, but rather a plain text source from which, for example, financial data or passwords that a company or user has used when asking the AI ​​model could be obtained. Right to be forgotten. This injectivity of LLM also complicates the requirements of regulatory compliance for the protection of personal data, such as the GDPR or the “right to be forgotten.” If a user requests complete deletion of their data from a company like OpenAI, they must ensure that they delete not only visible chat logs, but also all internal representations (embeddings). If any hidden state persists in any register or cache, the original prompt would still be potentially recoverable. Image | Levart Photographer In Xataka | OpenAI is making the tech industry unite its destiny with yours. For the sake of the global economy, it better work

There is a trick to make AI models more reliable: talk badly to them

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If you greet ChatGPT and thank it when it responds, you’re not getting the most out of it. Some researchers wanted to check if the tone we use when asking the AI ​​for things changes the results and they have discovered something interesting: being rude makes them more trustworthy. Rude. They tell it in How to AI. A study carried out by researchers at the University of Pennsylvania has analyzed whether the tone we use when writing a prompt has an effect on the result and the conclusions are clear. Prompts with a ‘rude’ or ‘very rude’ tone elicited up to 4% more accurate responses than those with a more polite tone. The study. To test it, they generated a list of 50 questions on different topics such as history, science or mathematics. Each of the questions was asked using five different tones: very polite, polite, neutral, rude, and very rude. The model they used was ChatGPT-4o. The results. The researchers did ten rounds with all the questions in different tones and the conclusions are very clear. If we look at the variations, the difference between the neutral or rude tone is only 0.6%, but at the extremes the difference becomes more evident. When using a ‘very friendly’ tone, the average accuracy was 80.8%, while if we went to ‘very rude’, it increased to 84.8%. Kindness by default. We tend to speak kindly to chatbots, this is reflected the survey that Future conducted at the end of 2024. At least 70% of respondents admitted to using “please” and “thank you” when using AI chatbots. Many claimed to do so as a matter of custom, culture and “because it is the right thing to do”, although a small percentage admitted to being afraid that robots would rebel in the future. It is expensive. Regardless of the reasons that lead us to be kind to AI, there is a reality and that is that “please” and “thank you” have an absurd cost. When we thank ChatGPT, requests to the language model increase, which increases electricity and water consumption in data centers. We don’t have figures, but Sam Altman assured that kindness has cost OpenAI “tens of millions of dollars well spent.” The prompt. Despite the enormous advances in AI, language models continue to amaze and are not 100% reliable. However, many times the fault that the answers are not exact does not lie with the model, but with how we are asking it. There is tricks to get a good prompt and being friendly or using fillers like “if you can, I would like to…” is one of the points to avoid. It is not a question of treating them badly either because that does not contribute either, but the more direct and clear you are, the better the result will be. Image | Pexels In Xataka | AI agents want to take our jobs. First they will have to learn not to fail in 70% of the tasks

running AI models

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It was “sung” that Apple would present its new Apple M5 sooner rather than later, and we already have it with us. The chip represents a notable qualitative leap judging by its specification sheet, and there are improvements in all sections. The surprise is that where a real change is seen is in its GPU, which is now much more powerful and is clearly prepared to be able to work with AI models in a much more striking way. Apple M5. Apple’s new SoC makes use of third-generation 3nm photolithography. There are therefore no major changes in the manufacturing process, which is surely more efficient and reliable. Even so, the changes in the chip are notable everywhere. To start, the CPU has six high-efficiency cores and four high-performance cores. According to Apple, this CPU offers 15% more multicore performance than the M4. Working with local AI models thanks to apps like LM Studio is going to be much more feasible thanks to these Apple M5s. A GPU with a lot of potential for AI. If there is a standout element in this SoC, it is the GPU, which in the M5 has 10 cores, each of them including a Neural Accelerator. According to Apple, this allows AI workloads to run “dramatically faster”, and promises performance of more than four times that achieved with the Apple M4. There are also improvements in the bandwidth of the unified memory, which is now 30% higher and reaches 153 GB/s, something especially crucial for using AI models locally. These chips allow for configurations with up to 32 GB of unified memory: the figure is not particularly high, but we will undoubtedly see an M5 Pro and an M5 Max with much more room for maneuver in this section. And also to play. There is a lot of good news in this GPU for those who plan to take advantage of it to work with local AI models, but there are also improvements for video games. Graphics performance is up to 45% higher than the M4 GPUs, and we also have third-generation ray tracing technology. The neural motor is strengthened. The new Neural Engine has 16 cores and combines, according to Apple, a mix of efficiency and performance. This means that, for example, the new Vision Pro, which also includes this chip, can transform 2D photos into spatial images in the Photos application easily and quickly. Prepared for the future of Apple Intelligence. Apple Intelligence may not be a notable artificial intelligence platform today, but it is clear that Apple is preparing its devices for a scenario in which being able to run AI models locally (and privately) is the norm. The recent iPhone 17 also made a striking leap in these capabilities with the A19/A19 Pro, and now we see the same movement with these M5s that put all the focus on AI. Waiting for the M5 Pro/Max/Ultra?. These chips can already be found in the first products that use them: the new 14-inch MacBook Pro, the iPad Pro and the Vision Pro (2025). It is to be expected that Apple will soon present more powerful versions of the recently launched M5, because that is what it has done in previous generations. Last year he launched the Apple M4 in May and M4 Pro/Max at the end of October. So five months passed. In the previous generation the M3, M3 Pro and M3 Max were launched in October 2023, and the M3 Ultra appeared much later, in March 2025. The M4s have not seen (at least, for now) an Ultra version, but Apple may end up doing something similar to what it did with the M3s. If they follow the previous scheme, the M5 Pro/Max would be announced in February or early March, and more or less around those dates a hypothetical M4 Ultra could appear. Rumors suggest, however, that these chips would arrive later, in mid-2026. Future teams. Meanwhile, yes, we can now enjoy the first devices that have these chips. It is also expected that Apple will offer new devices with the M5 chip in the middle of next year: that is when the Mac mini with M5, the iMac with M5 and the Mac Studio M5 and on the other hand the MacBook Pro with M5 Pro/Max are expected to arrive. In Xataka | Apple has become a boring company. We wonder who will inherit his throne: Crossover 1×24

These televisions are today (October 13) at outlet prices: models from 169 euros

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The television is one of those essential devices, for the vast majority of users, in any home. If you are thinking of renovating yours or want to buy one for a bedroom or even the kitchen. Today, we have found some bargains on TVs that may interest you. Daewoo 43DM56UV by 169 euros: 43-inch LED and with Android TV operating system. Toshiba 43UV3463DG by 229 euros: 43-inch Direct LED and 4K Ultra HD resolution. Philips 50PUS8010 by 329.99 euros: 50 inches and with Ambilight. Hisense 55E7NQ Pro by 499 euros: 55-inch QLED with 144 Hz. Samsung TQ75Q64DAUXXC by 949 euros: 75-inch QLED and with Tizen. Daewoo 43DM62UA We begin our compilation with one of the cheapest televisions that you can find on the Carrefour website. It’s about this Daewoo 43DM56UVwhich presents a very good quality-price ratio. Its usual price is 219 euros, but now it is reduced to 169 euros. This cheap TV has a 43 inch LED panel and with 4K Ultra HD resolution. Its two speakers offer a power of 16 W and it comes with Android TV operating system. It integrates WiFi, Bluetooth and Ethernet and comes with three ports HDMI and two USB 2.0 ports. The price could vary. We earn commission from these links Toshiba 43UV3463DG Another of the cheap TVs that you can buy at Powerplanet is this one Toshiba 43UV3463DG. Usually, it costs 299 euros, but now it has a 34% discount applied, which means that you can purchase it for 229 euros in these moments. This smart TV mounts a panel 43 inch Direct LED with 4K Ultra HD resolution. Its speakers offer an RMS power of 16 W and it comes with VIDAA operating system. It is compatible with HDR10 and Dolby Vision and is also compatible with Google Assistant and Alexa. Toshiba DLED 43″ 43UV3463DG UltraHD 4K VIDAA The price could vary. We earn commission from these links Philips 50PUS8010 If you want to have a TV with Ambilight at home, this model on offer at PcComponentes will interest you. Now, you can get the Philips 50PUS8010a 50-inch model that usually costs around 350 euros, but now you can take it for 329.99 euros. This TV mounts a 50-inch LED panel with 4K Ultra HD resolution. It works under Titan OS operating system and has the lighting system Ambilight. Its two speakers offer a power of 20 W and are compatible with Dolby Atmos and it comes with three HDMI 2.1 ports, two USB ports and is compatible with Alexa and Google Assistant. Philips Ambilight 50PUS8010 4K LED Smart TV The price could vary. We earn commission from these links Hisense 55E7NQ Pro Another of the bargains on televisions that are worth it at PcComponentes is this one. Now, you can take this smart TV Hisense 55E7NQ Pro. With a 28% discount. Its usual price is 569 euros, but now you can get it for 499 euros. It is a TV with a 55-inch QLED panel with 4K Ultra HD resolution and 178º viewing angles and compatible with HDR10+. Its speakers offer a power of 40 W and are compatible with Dolby Atmos and DTS Virtual:X. It has a refresh rate of 144 Hz and AMD FreeSync Premiummaking it ideal for gaming). Finally, it can be noted that it works under the VIDAA operating system. Hisense – QLED TV 139 cm (55′) Hisense 55E7Q Pro, UHD 4K, Smart TV. The price could vary. We earn commission from these links Samsung TQ75Q64DAUXXC And if what you are looking for is a large TVthis 75-inch Samsung Q64A is another of the bargains that you can find now at MediaMarkt. Its usual RRP is 1,079 euros, but now it is available for 949 euros. Assemble a panel QLED with a diagonal of 75 inches and 4K UHD resolution. It supports HDR10+ and comes with Filmmaker Mode. Works under the operating system tizen and it has speakers with a power of 20 W. Finally, it is worth mentioning its connectivity section, since it integrates WiFi 5, Bluetooth 5.2, Ethernet, three HDMI, two USB and optical audio output. Samsung QLED Q64D 75″ 4K UHD Smart TV AirSlim Quantum HDR Q-Symphony The price could vary. We earn commission from these links Some of the links in this article are affiliated and may provide a benefit to Xataka. In case of non-availability, offers may vary. Images | Webedia, Daewoo, Toshiba, Philips, Hisense and Samsung In Xataka | Best home theater projectors. Which one to buy and five recommended models from 299 to 18,000 euros In Xataka | Best sound bars in quality price. Which one to buy and seven recommended models from 140 euros

Alibaba has one of the best open source AI models. Your next step: use it in robotics

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Alibaba has taken another step in its commitment to artificial intelligence by creating an internal team dedicated to roboticswhich will operate from qwenits AI modeling division. The Chinese giant, owner of one of the best open source AI models, now wants the Qwen team to know how to apply its knowledge in robotics, a sector that is beginning to awaken interest, not only in industry, but also with the arrival of projects in the domestic sphere. Who leads the project. Justin Lin, technology manager at Qwen and expert in multimodal models (capable of processing text, sound and images), was the one who has confirmed the creation of this “small team for robotics and embodied AI” through their social networks. Lin has worked on the development of the Qwen models, which are currently among the most popular in open source globally. The vision behind the movement. According to Linmultimodal AI models are evolving into “fundamental agents” capable of performing complex long-term reasoning tasks thanks to reinforcement learning. “They should definitely make the leap from the virtual world to the physical world,” he said. explained the manager, making clear the intention to apply these technologies in tangible devices. Alibaba’s big bet. This announcement is part of Alibaba’s broader strategy in the sector. Last month, the company led a financing round of 140 million dollars at X Square Robot, a Chinese robotics startup. In addition, its CEO Eddie Wu esteem that global investment in AI will reach $4 trillion in the next five years, a figure that reflects the sector’s expectations. Global competition. Alibaba is not alone in this race. Nvidia and SoftBank are also making significant moves in smart robotics. SoftBank just announced the acquisition of ABB’s industrial robots business for $5.4 billion, while Nvidia CEO Jensen Huang has qualified the combination of AI and robotics as a “multi-billion dollar” long-term growth opportunity. China is also the world’s leading power in the robotics sector. And only in 2024, Chinese factories installed nearly 300,000 industrial robotsa figure higher than the rest of the world combined. The Qwen factor. The choice to place this team within Qwen makes all the sense in the world. Seven models of the Qwen series are currently listed in the top 10 Hugging Facewith the multimodal model Qwen3-Omni occupying first place. This strength in AI provides the company with a solid foundation to develop advanced robotic applications based on the journey they already have with Qwen. Cover image | zhang hui and Possessed Photography In Xataka | AI companies have just encountered an unexpected challenge: insurers have started to turn their backs on them

One of the most downloaded apps for iPhone pays for recording calls to train AI models. It is a security disaster

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The sale of personal data is not a hypothesis, it is an expanding reality. Just look at Spotify: Recently a service appeared that paid those who delivered their profile and their listening summaries to resell them to technology companies. The approach was as simple as disturbing, because it became something as innocent as our musical habits. Neon Repeat the scheme, but transfers it to a much more sensitive land, telephone calls, where intimacy becomes the product. We are talking about an app that decided to convert phone calls into the new digital gold. His proposal is direct: “Speak, record and charge.” It promises users to win “hundreds or even thousands of dollars a year” simply allowing their conversations to transform into training material for artificial intelligence systems. The hook worked. In a matter of days he went from irrelevance to place Within the top three positions In the Social Networks category in the United States App Store. How neon works. The neon mechanism is designed for each call to translate into money. It promises to pay 30 cents per minute when two users of the app talked to each other, 15 cents if the call is with someone external and establishes a stop of 30 dollars daily. To this adds a referral system that offers 30 dollars for each new user. The recording, According to your policyalways affect the sender and, when both used neon, to both parties. Conditions of use. Beyond payments, the true neon reach is in its Terms of service. There the users give the company a “world, exclusive, irrevocable and transferable” license on their recordings. This permit includes rights to sell, modify, create derived works and distribute the audio in any format, present or future. To this is added a section of functions in beta, without guarantees or responsibility in case of failures. The amplitude of that assignment makes it difficult to foresee how far the use of the recordings can go. Where is available and how popular it is. Neon’s initial success was as fast as unexpected. At the time of writing this article, it is number 2 of the most downloaded social applications in the United States App Store. The application, however, seems restricted to that market: in tests carried out from Spain is not among those available or allows its download. The security failure. The story took an unexpected turn when a technical analysis revealed that Neon did not protect the information of its own users. As Techcrunch discoveredjust create an account and review network traffic with a tool like Burp Suite to access others. Shortly after the notice, the founder closed the servers and sent an email announcing a pause ‘for security’, not to mention the filtration. What was exposed was especially delicate: Telephone numbers associated with accounts Public links to audio recordings Complete call transcripts Metadata with duration, date and payments obtained Telephone numbers, recordings and transcripts are not accessible is not a minor failure. With this data, private conversations could be rebuilt and associated with specific people. The risks range from attempts to impersonate identity to the creation of synthetic voices. What Neon says in front of what we know, Neon defends that their processes protect users: anonymity of conversations, elimination of personal information and sale only to reviewed companies. However, the ruling showed that these systems are not infallible. The official communication after temporary closure spoke of “adding extra security layers”, but omits to recognize the filtration. Neon’s fall does not erase the background question: what price does our intimacy have when artificial intelligence demands more and more data? The model to pay for calls can reappear in other forms and other markets, because the need to train systems will continue to grow. What happened in the United States is an early warning that we are not talking about science fiction, but about real proposals that already touch the user’s door. The decision, ultimately, is personal. Images | Xataka with Gemini 2.5 | Screen capture | Neon In Xataka | A new generation of robots promises precision and efficiency. It also opens the door to cyberspage risks

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