intelligence

“Any planet that has developed intelligence should have noosignatures, a physical history of cognitive activity”

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¿We are looking for evil extraterrestrial life Or are we alone in the Universe? Some experts opt for the former. They believe that it would be quite egocentric to think that we are the only ones who inhabit the immensity of the cosmos. The problem is that we are busy searching for alien intelligence, but perhaps we are not smart enough to find it. Or, toning things down a bit, we haven’t found the best strategies. Normally we look for biosignatures or technosignatures. That is, biological traces or radio signals from some extraterrestrial technology. Now, astrobiologist Julia De Marines, from the University of California, Berkeley, has devised a new term that focuses right in the middle: noosignatures. Smart, but not that advanced. If an extraterrestrial had landed its radio telescopes on Earth during the stone age I wouldn’t have found anything. I would have concluded that, in that direction, there are no planets with intelligent extraterrestrial life. The failure would have been in thinking that any planet with intelligent life must be at the same point of technological development. Seen this way, it is a pretty big mistake. But the reality is that we are doing just that. For this reason, De Marines believes that technofirms are not the best options. As to biosignaturesdo not always point to biological processes. The history of space exploration is full of examples in which it cannot be ruled out that the biosignature has a geological origin. In fact, it is most likely. For this reason, this astrobiologist proposes that intermediate point in which life is not sought, but rather intelligent activity at an intermediate point before developing advanced technologies. Because it may not have been sought at the right time or, simply, that civilization may not have advanced that much. To be able to detect it correctly, the key is in Assembly Theory. Too many pieces to put together alone. Assembly Theory is based on the assembly index of an object. That is, the number of pieces that had to be joined to form it. Sometimes pieces can be assembled by natural processes. However, above a certain threshold, a complexity is denoted that can only have certain intelligent activity behind it. Stone age tools are a good example. No need to look for stone axes. Although we take prehistoric tools as an example, this cannot be sought by launching telescopes and sensors into space. However, there are activities that can be measured from the outside. For example, agriculture left a measurable trace of nitrogen in our atmosphere. Even food manufacturing, such as fermented products, can be detected in waste chemistry thousands of years later. It is not necessary to understand it. Something important about this method of searching for extraterrestrial life is that it is not necessary to understand noosignatures. Returning to examples from our own history, in Phys point out the case of the Indus Valley writing. At the moment, no one has been able to decipher it, but we know that it was not written alone. There was an intelligent mind behind it. In this case the same thing happens. We must look for traces that do not fit with the natural behavior of the planet, even if it is not understood how they could have arisen. The limitations. This method of searching for extraterrestrial life has a major limitation. And noosignatures are ephemeral. If they are not measured at the right time, they can disappear. Additionally, they can be quite complex to decipher. To all this we must add that the study published by De Marines is a preprint. This means that it has not yet undergone review by an independent research team. Therefore, we must take their approaches with a grain of salt. Anyway, the reality is that, since the beginnings of SETIthe search for intelligent extraterrestrial life is not bearing good fruit. Not even the search for life, in general. The twists in methodology can be interesting, so this one deserves, at the very least, the attention of other astrobiologists. Image | Brooke Denevan (Unsplash) In Xataka | What is the Fermi paradox and why the architect of the atomic bomb gave a twist to the search for extraterrestrial life

news and everything that changes in ChatGPT with the new version of its artificial intelligence model

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Let’s tell you what are the news GPT-5.6the new version of the model artificial intelligence of ChatGPT. We are going to do it in a simple way, synthesizing in a list what the improvements are so that you can understand what will change when the model starts to arrive. The first thing you should know is that GPT 5.6 comes with three variants different, each with its own characteristics. But we are going to try to explain all this to you in the simplest way possible. What’s new in GPT-5.6 Next, we are going to give you a list with the main news that brings this new version of the OpenAI artificial intelligence model. We are going to do it in list format with a brief explanation of each news so that it is easier to understand. A family of 3 models: GPT 5.6 has three variants called Sol, Terra and Luna. Sol is the most advanced model, Luna is designed for greater speed and a lower price in tokens, and Terra is the intermediate model that seeks a balance between performance and cost. GPT-5.6 Sun: It is the new OpenAI flagship model, designed to improve especially in programming, scientific research, knowledge-based professional work, computer use and cybersecurity. GPT-5.6 Terra: Terra costs half as much as GPT-5.5, but maintaining competitive performance against that model. It is the most balanced option, the standard for doing general tasks. GPT-5.6 Moon: It becomes the fastest and cheapest OpenAI model. This makes it especially good for use in applications where speed and cost take top priority over more robust and advanced capabilities. Sol has Max and Ultra modes: The Sol model also has different modalities. The Max gives you more time to reason, check and revise your approach. Meanwhile, Ultra coordinates four agents in parallel by default, giving you better results in less time, but spending more tokens. Software Engineering Improvements: OpenAI ensures that GPT-5.6 especially improves in software engineering, where it increases its capabilities to solve more advanced programming tasks, as well as complex development flows. Improvements when using your computer: AI is lately focused on agents, so it is not surprising that its capabilities have also expanded to work with interfaces and execute tasks within computing environments. A big leap in design: With only general indications, this new model can create functional and careful interfaces. Additionally, the aforementioned computer capabilities allow you to inspect and refine the rendered output for visual glitches before submitting the work. Best scientific research: This area has also been improved, with improvements aimed at scientific reasoning and specialized work. Best knowledge-based jobs: OpenAI highlights advances in knowledge-based professional work, with the goal of delivering better results in complex tasks performed by professionals. You can create editable presentations from scratch, and improve results when you follow templates and reference documents to apply to new content. What’s new for developers in the API: In the Responses API, the Programmatic Tool Calling function allows GPT-5.6 to write and execute in-memory programs that coordinate tools and process intermediate results. And the multi-agent feature, initially in beta, allows you to run simultaneous subagents and synthesize their work into a single request. Cybersecurity news: They also improve cybersecurity capabilities, allowing more complex tasks to be solved within this area. More security for AI: OpenAI strengthens protections against high-risk activities, sensitive cybersecurity-related requests, and potential repeat misuse. It also incorporates the most robust security system in the history of GPT, with several layers of protection to reduce risks during the use of the model. Automated network teaming tests: OpenAI claims to have spent several weeks doing automated red teaming, searching for vulnerabilities and stress testing the system. With this, the model has been strengthened against real attacks before its launch. Availability according to your plan: In ChatGPT, Plus, Pro, Business and Enterprise users can access GPT-5.6 Sol, and Pro and Enterprise users can also choose GPT-5.6 Sol Pro. In ChatGPT Work and Codex, Free and Go users use Terra, while paid plans can choose between the three models and adjust the effort level of each. The deployment began on July 9 and will be gradually completed within 24 hours.

China launches the first factory for personalized vaccines with artificial intelligence

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Cancer treatment is on the verge of a historic revolution driven by the hyperpersonalization of medicine. Until now we were working with the idea of ​​manufacturing general medicines to treat cancer, but the idea of ​​manufacturing a unique and exclusive medicine for the genetics of each patient’s tumor has been around for years in laboratories, but the great bottleneck has always been the manufacturing time and, logically, the immense costs. A new step. China just gave the green light to the world’s first production line for cancer vaccines powered entirely by artificial intelligence. Located in Beijing, this facility is owned by Likang Life Sciences, a firm that has invested approximately $16.1 million in setting up a factory designed to operate at unprecedented speed. Its most advanced product is the LK101 neoantigen vaccine and it delegates the complex task of sequencing tumor DNApromising to synthesize customized doses in just one day. The definitive objective of this technological deployment is for patients to receive their personalized injection a few days after undergoing the biopsy. Why an AI? The key here is in the “neoantigens”, small mutated proteins that are exclusively in tumor cells and in each patient we find specific antigens. Here AI intervenes as an ultra-fast analytical engine by scrutinizing the tumor’s genetic information and predicting which parts of the antigen will be most effective in awakening and directing immune system cells to kill the tumor. Because here the only thing we seek is to activate the natural defenses we have, as we already do with immunotherapy, so that it is able to find tumor cells and destroy them, just as it does, for example, when we have an infection. But this is a process that requires great personalization and, above all, great speed to act as soon as possible on patients. And this is something an AI can do. for a long time Science has been paving this path, as we saw with an article published in 2024 which demonstrated that the integration of AI in the design of mRNA and DNA oncological vaccines is essential to know with maximum accuracy the composition of a tumor and its weak points. And to avoid failures, the algorithms are trained with large databases that we already have, where all the possible variants that a tumor may have are found. Another good news is that pioneering publications in Nature had already demonstrated the feasibility of RNA vaccines to induce specific and memory immune responses in patients with melanoma or even in such lethal and complex tumors. like pancreatic cancer. The nuance. It must be made very clear, first of all, that the promising results obtained in animals do not directly guarantee success in all patients, with clinical efficacy in humans still being very limited. And currently the vast majority of studies focused on this new personalized treatment are in very early stages. On the other hand, although China has built the first large algorithmic factory, its clinical research ecosystem remains very closed, and the data indicates that between 2014 and 2024 89 clinical trials of oncological vaccines were registered in this country. Something that greatly clashes with the 757 tests that have been carried out in the United States in this same period. And more limited. Added to this is that Chinese trials have an almost exclusively domestic vocation, with barely 2.2% global reach compared to 47.6% in the United States. But they also address less oncological diversity, focusing on about 5 types of cancer compared to the more than 20 studied by North American competitors. Images | Testalize In Xataka | Cancer in people under 50 years of age has been growing for decades. A macro study finally points to the big culprit: biological aging

How to create a calendar with your teams’ matches from the 2026 World Cup and add them to Google Calendar with artificial intelligence

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Let’s tell you how to create a calendar with matches of your favorite teams from the 2026 World Cup using artificial intelligencesomething quite simple to do. Because here it gets interesting, because later we will tell you how to add them to your Google Calendar so you don’t miss them. This is something that we are going to be able to do both in Gemini as in Claudeand it’s pretty simple. You can do it only with the matches of your country’s team, or directly with those of all the teams you are interested in following. Create a World Cup calendar with AI The first thing you have to do is ask Claude or Gemini to generate a calendar with the games played by the teams you want. You can request it with a prompt that looks like this: I want you to make me a calendar with the 2026 World Cup matches played by the teams of Spain, Argentina and Mexico. Obviously, you can modify the prompt to add the selections you want, or keep just one. This will generate a group stage schedule which is already underway, because it is not yet known which teams are going to qualify. Once you have the calendar created, now you have to tell the AI ​​to add it to your Google Calendar. You can use a prompt like this: Now save the games to my Google Calendar account Now comes the important part. Gemini and Claude have connectors to access your Google account, and will ask you to configure them to be able to do so and add the matches. ChatGPT does not have these connectors, and cannot do so. In Xataka Basics | How to prevent AI from always being right by default and thus make Claude, Gemini and ChatGPT have fewer hallucinations

list of new features of the new version of Anthropic’s Artificial Intelligence model

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Let’s tell you What’s new about Claude Fable 5, Anthropic’s new public model for your chat artificial intelligenceThis is the first model of the new Mythos classwhich already when it launched its preview version two months ago did so saying that it was so powerful that they would limit its power. Anthropic has launched two new models, the Claude Mythos 5 which will be available only to “a small group of cyber defenders and infrastructure providers”, and a Claude Fable 5 more adapted for mainstream users. It is a model with all the capabilities of Mythos Preview, but with security measures so that it is not used for bad things. And precisely because it is the model that is reaching users, it will be precisely Claude Fable 5 that we are going to focus on. we will give you a list with everything that changes so you know what it’s like to use compared to the previous version. Claude Fable 5 news Mythos-level capabilities for everyone: Fable 5, along with Mythos 5, is the most powerful AI model in history. Their capabilities are enormous, with performance that makes them lead the test benches. It is the first that allows you to use the capabilities of Mythos 5, and the jump from Claude Opus 4.8 is truly surprising, leaving GPT-5.5 and Gemini 3.1 Pro far behind. Longer freelance work: Fable 5 can work autonomously for longer than their predecessors. This makes it possible to tackle longer and more complex tasks that could not be sustained before. A big leap in programming: Programming is another aspect where this model has improved the most. Anthropic highlights the case of Stripewhich during initial testing performed a complete migration of a 50 million-line Ruby code base in one day, a job that would have taken a human team more than two months. More efficiency: Fable 5 is also more efficient in token consumption than previous Claude models, good news for teams who want to get the most out of it. Improvements in knowledge work: Fable 5 shows solid performance on complex analytical tasks. Anthropic claims to outperform the competition in senior-level reasoning, with notable improvements in reasoning about documents, interpreting graphs and tables, and problem solving. Great improvement in vision tasks: This new model can extract concrete figures from detailed scientific figures and reconstruct the source code of a website based solely on screenshots. For example, he was even able to beat Pokémon FireRed based on vision alone, while previous models had trouble playing even with assistive tools. Better memory and long context: The model is able to not get lost over millions of tokens, maintaining focus on the context, and improving memory. Something perfect for longer and more complex tasks. Maintains its barriers against misuse: Anthropic also says its new model keeps the level of misaligned behavior. This means that deceiving him or trying to get him to cooperate in misuse is still just as difficult. Safeguards with forwarding to Opus 4.8: Fable 5 is based on Mythos 5, which Anthropic said was so powerful it was scary. That is why it comes quite well-equipped and with many security measures. For example, if it detects that we are asking something “dangerous”, it avoids the question and even forces the use of an inferior model, Claude Opus 4.8. New data retention policy: For Mythos-class models, including Fable 5, Anthropic requires 30-day data retention for security monitoring purposes, both on its own and third-party surfaces. Of course, they say that they will not use that data to train new models or for anything that is not related to security. After 30 days, it will delete all data from our conversations in almost all cases. Price and availability: Fable 5 costs $10 per million tokens in and $50 per million tokens out, less than half of what Claude Mythos Preview cost. Developers can use it in the Claude API with the identifier claude-fable-5. Plus, it’s included at no extra cost until June 22 for Pro, Max, Team, and Enterprise subscribers. Of course, starting June 23, it will require usage credits until the capabilities of the company’s servers allow it to be incorporated as standard in payment plans in the future. In Xataka Basics | How to prevent AI from always being right by default and thus make Claude, Gemini and ChatGPT have fewer hallucinations

These are all the new features from Apple Intelligence and Siri AI that come to your iPhone with iOS 27

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We are going to tell you all the Apple Intelligence and Siri AI news that will come to your iPhone when it updates to iOS 27. Because the main protagonist of the next version of Apple’s mobile operating system is artificial intelligence, driven by the Gemini models, and which will revolutionize Siri. So that you understand everything that is coming, we are going to give you a list of all the new features, briefly describing each of them. And then, we will also give you the bad news about its arrival in Europe. What’s new in Apple Intelligence in iOS 27 Let’s continue with the list of new features from Apple Intelligence and Siri AI that have been presented by Apple. We are going to tell you in summary so that you can see and understand them easily. Apple Intelligence Architecture Apple Founding Models: Apple’s new AI models have been created in collaboration with Google. They take advantage of the technology behind the Gemini family of models by adapting it for use in local processing and on servers. Hybrid processing: Apple’s new AI will be able to work both locally on your device and in the cloud, using servers with Private Cloud Compute architecture to guarantee that the data you store is not accessible by Apple or third parties. Advanced local model: There will be a more powerful secondary version optimized for use locally on systems with the most capable Apple Silicon processors. This version will understand and generate speech, text and images with high precision. Multimodal and understands the context: The new Apple Intelligence is multimodal, that is, it understands text, image and video. You can also securely coordinate system capabilities through personal context, actions in applications (App Actions) and awareness of what is on the screen (On-screen awareness). Semantic Indexing: Integration with Spotlight to instantly search for old or new content locally on the device. Siri AI New Siri: Siri is officially renamed Siri AI. The Apple assistant becomes an artificial intelligence assistant, and becomes powered by the new Apple Intelligence architecture. Coherent Conversational Experience: Allows you to have fluid conversations with Siri, speaking to her and receiving detailed responses. Interactions are saved privately and synchronized via iCloud in the new app. New dedicated Siri app: Siri has a new standalone app on iOS, iPadOS, and macOS to improve the way we interact with her. Visual Redesign: More fluid interface than on iOS allows you to swipe down from the Dynamic Island to write to you directly. In visionOS it is presented as a 3D visualization that can be placed anywhere in space and activated just by looking at it. On macOS you can also invoke it from context menus or Spotlight. Enhanced System Dictation: Great increase in keyboard precision, respecting spellings, punctuation and capitalization thanks to the integrated advanced model. Personality settings: Siri has a new, more natural and conversational voice. But you will also be able to customize it to adjust your personality, speed or type of voice. Integrated into the search engine: Siri is also integrated into the search engine. When you type a request, it will be detected as something for AI and Siri AI will respond. Visual Intelligence: There is a native Siri mode in the iOS camera app. It allows you to take a photo of what’s in front of you and get detailed information about whatever, ask for recipes, get nutritional information. You can even scan an account and split the payment. Writing and Creativity Tools Siri in writing: Siri has the ability to generate texts from scratch in any app on your mobile or Mac, describing what you need in natural language. In Mail and Messages, adapt your tone by mimicking how you usually communicate with a specific contact. Automatic System Correction– Apple Intelligence automatically reviews and corrects writing in the background in almost all apps, including third-party ones, without additional steps. An integrated concealer. Evolution of Image Playground: Image generation improves in quality, including styles such as photorealism. It does this with a model in Private Cloud Compute. It allows you to apply styles to photos in your library and edit them using natural language or touch gestures. Intelligence Applied to Native Apps Safari: AI can automatically classify and organize open tabs by theme or topic. Also the function of monitoring web pages using natural language and notifying if something changes. In addition, it allows you to create custom extensions describing in natural language what you want the tool to do on the web. Passwords: Allows you to automatically update eligible accounts to give them strong passwords with a single touch. The system autonomously navigates the website in question safely to apply the change. Only if they are compatible. Shortcuts: Creating shortcuts is made as simple as possible. Now you just have to describe the automation you want in natural language and Apple Intelligence brings together all the steps and applications required to build it. Photos: Advanced editing with distraction removal in complex scenes with more realistic backgrounds. You can also stretch the edges of an image to change the aspect ratio or straighten horizons using smart generation. Additionally, you can change the three-dimensional perspective of an already taken photo using local spatial models, recalculating the angles of the scene as if you had physically moved the camera sideways or down when shooting. Integration at Home: Siri AI will also work at Home, and will integrate with smart speakers. Siri AI will not arrive in Europe (for now) Siri AI and all the new artificial intelligence news will arrive with iOS 27. However, They will not reach Europe because Apple fails to comply with European legislation. EU law forces Apple to allow any third-party assistant to do the same as Siri AI, to don’t make users only have one optionand can choose from others available. Apple hides behind the fact that allowing other AI apps to access your apps, read your messages, modify files or make purchases for … Read more

list of new features of the new version of Anthropic’s Artificial Intelligence model

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Let’s tell you What’s new in Claude 4.8 Opus, the new version of Anthropic’s most advanced and powerful artificial intelligence model. This version has surprised us by arriving just 41 days after Claude Opus 4.7, and it seems that the improvements are minimal, but there is a really important change in its honesty when it comes to telling you if it doesn’t know something. In any case, here you have a complete list with all the new features that come with this new version of Claude 4.8 Opus. We are going to explain each of them briefly so that they are easy to understand. Another thing you should know is that Opus is the most advanced line of Claude models, the one indicated for more complex tasks for programming and the one that uses up your limits the fastest when you use it. There is also the most efficient Sonnet model for day-to-day tasks, which continues in version 4.6 since February 2026, and a Haiku for quick and simple questions that continues in version 4.5 since October 2025. News from Claude 4.8 Opus A more honest AI: The prominence of this new version goes to honesty. He’s significantly more honest about his own work, telling you when he’s unsure about something. It’s also about four times less likely to let bugs in code slip by without flagging them, compared to its predecessor. Performance improvements: The Agentic code score for creating code with agents increases from 64.3% to 69.2%, and multidisciplinary reasoning with tools increases from 54.7% to 57.9%. On other test benchesin the SWE-bench Verified it goes from 87.6% (Opus 4.7) to 88.6%, and in Terminal-Bench 2.1 it rises from 66.1% to 74.6%. GPT-5.5 still falls short in terminal/CLI workflows, although there have been big improvements in Claude, and both models are practically on par in web browsing and graduate-level science topics. Alignment improvements: Alignment assessments show new highs in prosocial traits such as supporting user autonomy and acting in their best interest. Rates of misaligned behavior such as cheating are lower than in Opus 4.7. Fewer hallucinations: As usual, the number of hallucinations is also reduced. Honesty when telling yourself when you don’t know something also helps reduce them. Quick mode: According to AnthropicOpus 4.8’s fast mode is now about 2.5 times faster. The company claims that the improved Quick Mode also costs three times less than before. Effort control– Users can choose between “extra” or “max” levels so that the model spends more tokens and obtains better results. Dynamic Workflows (preview for research): With this new feature, Claude can schedule work and run hundreds of subagents in parallel in a single session, being able to complete codebase-scale migrations of hundreds of thousands of lines. Available for Claude Code on Enterprise, Team and Max plans. No change in base price: The base price of API tokens is unchanged from Opus 4.7. It is 5 dollars per million input tokens, and 25 dollars per million output, with up to 90% savings with prompt caching and 50% with batch processing. In Xataka Basics | How to prevent AI from always being right by default and thus make Claude, Gemini and ChatGPT have fewer hallucinations

There is a booming job in the era of artificial intelligence: cybersecurity expert

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Yeah Mythosfrom Anthropic, and GPT-5.4-Cyber, from OpenAI, have been presented as models capable of detecting and exploiting vulnerabilities, the quick conclusion seems quite evident: cybersecurity profiles could begin to become redundant. After all, we are talking about models aimed at moving in one of the most delicate areas of technology: finding flaws before others take advantage of them. The answer, at least for now, goes in the opposite direction to that first intuition. AI is not making the expert irrelevant. On the contrary: today it is more necessary than ever. That signal is already beginning to be noticed clearly in the United States, where the NYT has put figures and testimonies to a trend that was gaining strength: the hiring of cybersecurity profiles. The American newspaper points out that offers in the sector grew by 11% year-on-year in the first quarter, according to Glassdoorand shows how some executive search firms are receiving more assignments to find managers with experience in security breaches, data protection and code review. The reason is not just to protect data. There is also a need to respond to incidents and understand how AI changes the risk surface of companies. The key is that this new layer of AI not only changes the tools of those who protect the systems. It also modifies the possibilities of those who try to compromise them. Reuters pointed out a few days ago that Attackers are increasingly using AI to detect vulnerabilities, and Check Point has warned in its 2026 Cybersecurity Report that AI attacks have moved from the experimental phase to a routine criminal deployment. More tools do not mean fewer cybersecurity experts The market, furthermore, is not asking for exactly the same thing as it did a few years ago. Cybersecurity continues to be the umbrella, but more specific capabilities are beginning to weigh heavily within it: AI, cloud security, engineering, analysis and risk assessment. The 2025 ISC2 Cybersecurity Workforce Study points out that hiring managers place AI among the most in-demand skills, with 27%, and professionals raised that perception to 44%. The conclusion is important: knowing about security is not enough. It is becoming increasingly important to understand how this security is integrated into complex systems obviously crossed by AI. Fortinet did a survey and found that 49% of respondents fear that AI will increase cyberattackswhile 97% of organizations already use or plan to use a cybersecurity solution that takes advantage of this technology. So it seems that companies are not only concerned about the offensive use of AI, they are also trying to incorporate it into their own defenses. And that opens up another less visible, but equally important, need: having teams capable of evaluating these tools and integrating them judiciously. In Spain, photography also points to a sector in full expansion. INCIBE summarizes it with a very useful phrase to ground the phenomenon: “Cybersecurity is already one of the most dynamic sectors of the Spanish digital economy.” According to the study on the cybersecurity industry in Spain 2025the organization places employment at 164,761 people and points out that cybersecurity already represents 25.55% of employment in the ICT sector. The forecast, furthermore, does not speak of a specific increase: between 2026 and 2029, the sector will grow at an annual rate of 14.25%, until reaching 282,157 jobs at the end of that period. “Cybersecurity is already one of the most dynamic sectors of the Spanish digital economy.” The problem is that this growth comes with an obvious tension: there are not always enough profiles prepared to cover what companies need. Deloitte formulates it from the side of those responsible for security: “Nearly 38% of CISOs identify reliance on scarce profiles as a significant challenge, reflecting a persistent gap between growing demand for capabilities and limited market supply.” The consequence is that many organizations end up relying on external talent to support your defenses. In fact, Deloitte points out that in 2026, 60% of cybersecurity personnel will be external. Seen from Spain, the phenomenon shares the same background, although with its own nuances. The United States remains one of the epicenters of the AI ​​industry and we cannot understand this trend without looking at what is happening there, but it is also not advisable to extrapolate its market dynamics as if they were identical to those of Europe. Other indicators come into play here: employment growth, relevant weight within the ICT sector and dependence on external profiles in many organizations. The conclusion, however, points in the same direction on both sides of the Atlantic: AI is forcing cybersecurity capabilities to be strengthened, not reduced. Images | Xataka with Nano Banana In Xataka | How often should we change ALL our passwords according to three cybersecurity experts

Gemini Intelligence promises to be Google’s AI revolution. The problem is that almost no one will be able to use it.

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Updates have always been Android’s Achilles heel, but for several years we have seen how manufacturers are pushing to offer up to seven years of updates on your mobiles. It is good news for users and regulators. The problem is that AI threatens to introduce a new form of fragmentation: having an updated mobile phone no longer guarantees access to the most important functions, even if it is high-end. What has happened? A few days ago, during the Android Show, Google announced the new star feature coming to Android: Gemini Intelligence. We are no longer talking about specific functions, but rather about a layer of AI that covers everything, making the mobile phone act autonomously within the system and the apps. It sounds great, what doesn’t sound so good is the list of requirements. Hardware requirements. Google has detailed the minimum requirements for a mobile phone to run Gemini Intelligence and it is quite not encouraging. We are talking about devices with 12 GB of RAM and that mount recent “flagship” processors. These requirements directly leave out the majority of the current vehicle fleet, but also at the current time with the memory crisis raising pricesthe high-end is going to become even more unattainable. The real problem. If the RAM and the processor already leave out many mobile phones, the software requirements are even worse. This is where Google makes the real difference since, to run Gemini Intelligence, compatibility with Gemini Nano V3, the local language model for mobile phones, is necessary. If we look at the current compatibility list, it is no longer that it affects cheap phones, it is that it also leaves out phones like the Samsung Galaxy Z Fold7 which was launched in the summer of 2025 and cost 2,109 euros, or the Xiaomi 17 Ultra which has just been launched for almost 1,500 euros. It is not clear that the list is definitive, since it is possible that there are changes because they allow it to be updated later, but for now the outlook is bleak: The list of devices compatible with Gemini Nano v2 and Gemini Nano v3. Image: Xatakamovil There is still more. The software requirements don’t end here. Google has also put several additional conditions for a device to have Gemini Intelligence. The device must receive at least five years of operating system updates and six years of security patches, in addition to meeting a series of quality requirements regarding stability, failure rate and multimedia, among others. The privilege of AI. “The best of Gemini in our most advanced devices” is the phrase we find in the Gemini Intelligence official websiteso Google already warns us from the beginning. That updates or more advanced functions reach the most expensive phones is something we are used to, but with AI we are seeing the bar rise even higher. Furthermore, it is not a specific function as it was ARCorewe are talking about the central axis of the proposal, a new way of interacting with the mobile that only a small percentage of users will be able to test, including those who have a Google Pixel. Cover image | Google In Xataka | Android 17 news: list with a summary of everything that will arrive in this version of the operating system

It’s called Gemini Intelligence and it wants to change how we use our mobile phones

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Google just introduced Gemini Intelligence in The Android Showthe great event dedicated to the green android operating system. The name, which inevitably reminds Apple Intelligencemakes it quite clear where the news is going: artificial intelligence. But here we are not just talking about creating emojis or generating images, but about something more ambitious, at least on paper. The company wants to change the way we use our devices. So how does that promise hold up? Google assures that Gemini Intelligence will allow us to automate tasks, as can be seen in the example shown during the event and included in the cover image, reading the information that appears on our screen and interacting with it. It will also arrive with a navigation assistant for Google Chrome, make it easier to fill out forms, and update Gboard to help us shape our thoughts out loud. Let’s see in a little more detail what each new feature consists of. Everything Gemini Intelligence brings to Android Google says it has been working on automation features for months alongside several popular food and transportation apps. The goal is for Gemini Intelligence to be able to take care of certain tasks for us, not just answering questions, but acting within the device and some compatible applications. “Gemini takes care of the logistics so you can enjoy the moment,” the company says. These are some of the examples that Google has shared: Reserve a bike in the front row for a spinning class Find a class program in Gmail Add to cart the books you need Gemini Intelligence may also use the context of the screen or an image. The company proposes, for example, an open shopping list in a notes application. In that scenario, it would be enough to press and hold the power button to activate Gemini Intelligence and ask it by voice to create a shopping cart with those products. In theory, the system would take care of it. Another example is photographing the poster for an activity and asking them to search Expedia for a similar tour for six people. Another important piece of Gemini Intelligence will be in Chrome. Google wants to make its browser on Android smarter starting at the end of June, with Gemini built in to help us research, summarize information, and compare content on the web. It is not just about reading a page and returning a summary, but about accompanying us in tasks that normally require jumping between several tabs or services. In addition, Chrome will incorporate a function called auto browse, aimed at more mechanical tasks. Google gives examples of booking an appointment or a parking space. On paper, it is another step in the same direction: less manual interaction and more capacity of the system to take care of specific procedures. Android autofill will also take a leap with Gemini Intelligence. So far, Autofill with Google has mostly served to save time in basic fields, but Google wants to take it further. The feature will be able to take advantage of Gemini’s personal intelligence to fill out more fields within apps and Chrome, even when forms are longer or have small boxes spread across the screen. The promise is simple: that filling out forms from your mobile will no longer be such a burdensome task. Android may use relevant information from connected applications to fill in that data for us. In any case, Google emphasizes an important point: this integration will be strictly optional. Each user will decide if they want to connect Gemini with Autofill, and that connection can be activated or deactivated from the settings. Gboard will also be updated with a new Gemini Intelligence feature called Rambler. The starting point is quite recognizable: Android already allows you to quickly convert voice to text, but we don’t speak the same way we write. We correct ourselves as we go, we repeat ideas, we leave half-sentences or we fill in the gaps with fillers. Rambler wants to take care of just that. The idea is that you can speak naturally, without having to construct the perfect sentence before starting. The system will take the important parts of what you say and organize them into a clearer, more concise message. Google ensures that Gboard will clearly show when Rambler is activated and that the audio will only be used to transcribe in real time, without being stored or saved. In addition, Rambler will be designed for multilingual conversations. Thanks to Gemini’s advanced model, you will be able to change languages ​​within the same message and understand the context even if we mix several languages. Google uses a combination of English and Hindi as an example, but the idea is broader: that the message still sounds like us, just a little more polished. 10 GOOGLE APPS THAT COULD HAVE SUCCESSFUL Which phones will be compatible with Gemini Intelligence Google has made it clear that Gemini Intelligence will be an exclusive function of Android phones, something that we could already imagine due to its characteristics. Nothing about an application that allows you to use some of its new features on the iPhone. Now, even within the Android ecosystem, its deployment will also be limited: it will be focused on the “most advanced devices” and will arrive in phases. According to official information, Gemini Intelligence will first arrive on compatible Samsung Galaxy and Google Pixel phones as early as this summer. Later, at the end of the year, it will also land on other devices, such as smart watches, cars, glasses and laptops. In development. 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