Create

create your own data center

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Z.AI has been the protagonist of big headlines in recent weeks, especially after the launch of its very powerful GLM 5.2 language model. Formerly known as Zhipu, the company has now just finished building a massive 1 gigawatt data center that, according to they count from Bloomberg, it will work exclusively with semiconductors made in China. To put it in context, it would be the most ambitious bet yet by a Chinese technology startup to completely dispense with Nvidia. They can’t buy Nvidia chips. Since January 2025, Z.AI has been on the US Department of Commerce’s entity list, which prevents it from legally purchasing Nvidia chips. The most curious thing of all is that this veto, far from stopping it, has pushed it to build all its future infrastructure relying only on national suppliers, according to they explained from Bloomberg. But it is not at all strange, since it is a movement that fits with Beijing’s strategy of reducing its technological dependence on Washington in the midst of the AI ​​race. In detail. As shared by the media, the data center has already begun to operate partially and is designed to train and deploy the company’s family of GLM models. With a power of 1 gigawatt at full capacity, from Bloomberg they assure that the facility could consume as much electricity as about 750,000 homes need, making it one of the largest data centers ever built by a Chinese artificial intelligence startup. For now, the company has installed at least 10,000 chips from China there, although there is no information on what proportion of the total planned capacity that figure represents. Between the lines. Although the media does not detail which company provides the chips, everything points to Huawei. Z.AI already presented its GLM-5.2 model in June, trained entirely with Huawei Ascend accelerators and without resorting to Nvidia hardware. The model also came out ahead of the rest in rankings of open source models such as Design Arena. The problem is that, according to they claim Bloomberg, Chinese chips like the Ascend still perform worse per watt than Nvidia’s current Blackwell, which means that one gigawatt of Chinese power is not equivalent, in practice, to the same computing power as one gigawatt consumed with Nvidia hardware. Added to this is a manufacturing bottleneck. From Tom’s Hardware they point out that SMIC’s most advanced and stable process (equivalent to a 7-nanometer node) is already operating at over 93% of its capacity, and that the shortage of domestically produced HBM memory limits how many accelerators Huawei, which last year shipped around 812,000 AI chips, can assemble. Bloomberg pointed In addition, citing a previous report, Huawei plans to manufacture about 1.6 million Ascend cores in 2026, enough for about 600,000 chips of its flagship model, the 910C, while Cambricon, another of Nvidia’s major Chinese rivals, has set a goal of half a million accelerators this year. In short: China can build data centers faster than it can make the chips needed to fill them. sweet moment. The Z.AI thing comes at the height of the pulse among Chinese AI startups. Its great rival, Moonshot, had to suspend new subscriptions to its platform last Sunday to prioritize the computing capacity of its current users, after the launch of his amazing Kimi K3 modelaccording to explained the company itself on social networks. Z.AI, for its part, is going through a good financial moment. And it is that according to sources consulted by Bloombergthe company is on track to reach $1 billion in annual recurring revenue after meeting its 2026 sales target this month, and has recently bolstered its capital with an IPO in Hong Kong and a subsequent expansion. The company’s shares have closed with an increase of 37% this Tuesdaycoinciding with the news of the new data center. A more ambitious plan. The Z.AI case is part of a much broader plan by the Chinese Government. And Beijing is preparing an investment of about 2 trillion yuan (about $295 billion) within five years to build a national network of AI data centers, with at least 80% of the technology coming from Chinese suppliers, according to they count from Tom’s Hardware. And in that plan, Z.AI, Moonshot, and the rest of the AI ​​startups that are beginning to deploy their weapons are included. Cover image | Z.AI and İsmail Enes Ayhan In Xataka | ASML sells the most important machines in the chip industry. Now everything indicates that they will be more expensive

In 1962 the United States exploded an atomic bomb in orbit to create an anti-missile “wall.” The result was electrical chaos 1,000 km away

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July 9, 1962, an aurora appears in the skies of Hawaii, Tonga and Samoa. It would be strange for these phenomena to form so far from the poles, although experience has shown us that it’s not impossible. Even so, in this case the auroras were not formed by a solar storm, but by Starfish Prime, a US experiment that went wrong. Very badly. Basically, they decided to launch an atomic bomb into space to widen the ring of natural radiation that surrounds the Earth and, thereby, create a wall against Soviet missiles. They managed to distort it, yes, but not in the way they expected. Furthermore, by the way damaged electrical systems, satellites and telephones, caused blackouts more than 1,000 kilometers away and there were even fears for the health of the astronauts who would travel to the Moon 7 years later. As a result of that incident, an international agreement was signed to prohibit atomic testing in the atmosphere, outer space or the bottom of the sea. Since then, all countries have complied with it, although there are scientists who do not trust that it will continue to be done, so they have devised a plan curiously related to Starsfish Prime. Starfish prime. The Starfish Prime project consisted of the detonation in low earth orbit of a 1.44 megaton nuclear warhead. That is, they used a bomb 100 times more powerful than the one dropped on Hiroshima. The goal was to stretch the Van Allen belta ring composed of swarms of highly energetically charged particles that are trapped in the network of the Earth’s magnetic field. If the ring could be stretched, they thought it could incapacitate the Soviet missiles that posed a threat to the nation. They achieved the goal. But the rest of the consequences were too serious to want to repeat. More radiation. The amount of radiation in the Van Allen ring increased. By 1969, when the Apollo 11 astronauts they traveled to the moonthere was still a slight increase in radiation that they could absorb on their way to our satellite. Several studies were carried out to check if their health would be seriously at risk, but it was seen that the danger was manageable, so it was decided to continue with the mission. An international agreement. In 1963, the United States, the United Kingdom and the Soviet Union signed the Limited Nuclear Test Ban Treaty, in which they committed to freeing the atmosphere, outer space and the seabed from nuclear tests. Later, in 1967, was signed he International Outer Space Treatywith which the great world powers established a mode of action for the exploration and use of outer space. Since then there is no evidence that nuclear weapons have been sent into space. However, there are scientists who do not trust that other countries may be acting as agreed. One of them is Areg Danagoulian, from MIT, and the idea you had to solve it is, to say the least, curious. Neutron spallation. Danagoulian’s proposal consists of taking advantage of a phenomenon called neutron spallation, by which very high-energy particles are capable of causing atomic nuclei to expel their neutrons. And where have we seen that there are charged particles with a lot of energy? Indeed, in the Van Allen belt. This MIT scientist believes that if a satellite loaded with a nuclear device were to pass through this ring, something it necessarily has to do, its particles would cause the nuclei of the uranium atoms to lose neutrons. For this reason, it proposes to build a specific detector for this type of neutrons, which would be responsible for sounding the alarm if it detects said expulsion. Aurora seen from Hawaii A feasibility study. At the moment, Danagoulian has not built anything. Has carried out a feasibility study in which he demonstrates that his project is plausible. It is based on sound physics and the techniques needed already exist. If Russia had a nuclear satellite, as this and other scientists fear, it could be a useful device. Now, just because it is possible does not mean that it is easy. Neutrons coming from uranium would have to be differentiated from those from other elements and, furthermore, distinguished from those that could come directly from the Earth. There is a lot of work ahead. With Starfish Prime it was discovered that the consequences of an abrupt release of radiation in the Earth’s magnetic field can be very serious, whether it occurs artificially, with an atomic bomb, or naturally due to solar activity. It is important that we are prepared. Ideally, everyone will comply with the agreements; But, just in case, it doesn’t hurt to resort to detection techniques. Without a doubt, it is a much healthier way to take advantage of what the Van Allen belt gives us. Image | US Air Force 1352nd Photographic Group, Lookout Mountain Station/NASA In Xataka | SpaceX has launched 8,000 Starlink satellites in five years, but they are not enough. And we’re starting to understand why

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

Jeff Bezos says AI won’t destroy jobs. He then launched a company to create artificial engineers

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Jeff Bezos is one of the representative figures of current technological optimism regarding artificial intelligence. While in the United States we are seeing the university students who boo to those who claim that AI is the new industrial revolution due to pessimism when it comes to finding a job, Bezos point that this pessimism around AI is “the opposite of reality.” Come on, young people are wrong because what AI is going to do is create jobs. At the same time, Bezos has returned to talk of Prometheusa startup that will open the door to fewer workers being needed… while increasing productivity. It’s a bit of a mess, but it makes sense to Bezos. Prometheus. It is not a model or a technology, but a startup. Founded by Bezos in 2024, it has about 150 employees spread across headquarters in San Francisco, London and Zurich and already has a valuation of $41 billion. The central purpose of Prometheus is to develop AI systems capable of assisting in the entire engineering process from start to finish (end to end, as they call it). This means that the system will cover from the initial design of physical products to their manufacturing and launch, passing through all the simulation and testing phases. It is like a kind of artificial general engineer and does not seek to be just something that supports the engineers, who will then create the physical products. His goal is… that, to be a physical engineer. Accelerate inventions. Beszos’ goal is to empower engineers to be able to invent things more quickly and easily. An example is that this AI product is capable of carrying out all the aforementioned steps to build, for example, a jet engine. And here is the twist, since a jet engine is something extremely complex, but what Bezos is looking for is that what the startup develops allows smaller teams to do much bigger things in much shorter cycle times. Landing it: if before 100 people made you a new generation jet engine, now 10 can make it for you. I don’t know, Rick.… We suppose that in his head it is a good way to reassure those young people worried about the future of work, but in case it is not clear, Bezos commented that the fear of AI and the future of work is “the opposite of reality”, pointing out that what Prometheus does will be a catalyst for work. The curious thing is that he has presented it in a slightly strange way. If AI makes work cheaper, faster and easier, employment will increase because, “even though the number of people needed is being reduced by 10, technology will create opportunities to multiply those jobs by 10.” They are a bit strange accounts, but the boss of Amazon gives as an example a two-person household in which only one will have to work because productivity thanks to AI will be much greater. It does not say what that other person will do or if, thanks to AI, that member of the household who continues to work will earn more to replace one who stays at home. What it suggests is that there will be such a massive increase in productivity that not everyone will have to work, a somewhat questionable message because bills are not paid with productivity, but with money. colossal background. But well, beyond Bezos’ curious message, Prometheus is valued at $41 billion and has raised $12 billion from investors such as JPMorgan Chase, Goldman Sachs and BlackRock, apart from Bezos himself. And, currently, it is in deals to raise a fund of 100,000 million. But Bezos isn’t the only one moving to build AI startups. We have the founders of Uber, Coinbase or Robinhood (curious name) building new companies around this technology boom due to something that these profiles are very clear about: It is a new golden era and the best way to start a company. Young Americans are not so clear. In Xataka | Jensen Huang, CEO of Nvidia, on the possibility that we are facing a work apocalypse: “It’s nonsense”

Create expands its collection of discounted ceiling fans

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It’s almost summer now, and it’s time to repeat the same move as every year: look for something to keep us from dying of heat at home. There is air portable conditioner or other split typebut there are many people who bet on a ceiling fan. The problem is that there are many of these fans that have boring and bland designs. No matter how much they work, They can affect the atmosphere or the decoration we have. If this is something that concerns you, keep an eye on it. the fans that Create has. The price could vary. We earn commission from these links Silent fans that are also design pieces As we say, there is a lot to choose from. For example, this one that appears in the image above is the Wind Calm, a blade fan with an elegant design, especially if we take into account their different shades. The sage green one (called Sage) fits perfectly with wood tones and is available in two sizes. In addition, we can choose it with or without light, as well as with different control options. Part from the 69.95 euros (its RRP is 149.5 euros). If you don’t like that color, you can go for a cobalt blue or a mocha color that goes great with minimalist spaces. The price could vary. We earn commission from these links This fan has blades and has a more traditional cut, but there are more options. He Wind Clear Studio and the Wind Clear Lamp are two retractable blade fans. In this way, they look like a lamp when they are folded and, when we turn them on, they take out the blades. They are a very elegant option that has linen as a material, which makes them have a warm appearance that is very appropriate for, for example, a bedroom. In that same line we have the Wind Clear Rattanwhich is exactly what we can see in the image that is just above these lines. It has rattan as its protagonist, which gives a great natural touch. Along the same lines, we have the Wind Lamp Natural Woven or the Wind Calm Custom Rattanthe latter a fan with more conventional cut blades, but with a rattan area above with lighting that will project lighting that will help make the atmosphere in the room warmer. In fact, you can choose with main light and ambient light. The price could vary. We earn commission from these links To finish, the Wind Clear Bladeless and the Wind Shapetwo fans with lighting that are not only designed to be another point of light in the room, but to create a cozy atmosphere. The second of them is done with a double lighting system: one located practically in the anchoring area and another more oriented towards the ground. This ambient light system is present in both models. Any of these fans (and the many others that we can find on the Create page) has several points in common: They are silent, have a winter function and can be programmed, in addition to helping repel mosquitoes. All without forgetting that, as we said at the beginning of this article, they are on sale. If we add everything we have mentioned up to this point, we can say that they are ceiling fans that differ from the majority and that not only seek to be a device to avoid heat in summer, but also to be another element that integrates into the decoration. and help us create different environments at home. 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 | Create In Xataka | Five things to consider before buying a portable air conditioner In Xataka | Which smart air conditioner to buy. How to choose a connected air conditioning system and featured models

DeepSeek is good, pretty and very cheap. And above all, the weapon to create a Chinese hardware industry independent of Nvidia

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The arrival of DeepSeek-V4-Pro It hasn’t caused that much of a stir. like the one caused by DeepSeek R1 a year and a half ago, but we may be facing an even more important model. If that version revealed to the world that China was advancing spectacularly in this race, this other one is beginning to allow us to glimpse something else more interesting. What most people see is a very decent model and above all “low priced”. Which hide the company It’s another more important thing: achieve independence from Nvidia and US hardware. what has happened. Last Friday, those responsible for DeepSeek announced something surprising: their promotional offer with a 75% price cut to use their DeepSeek-V4-Pro model will be maintained permanently. That makes this model offer very decent features (but not exceptional) for a really low price: 1M entry tokens 1M tokens output DeepSeek-V4-Pro 0.435 0.87 GPT-5.5 5 30 Opus 4.7 5 25 Gemini 3.5 Flash 1.5 9 Good, pretty and very cheap. It is true that the performance of DeepSeek-V4-Pro is inferior to that of rival models from OpenAI, Anthropic or Google. Artificial Analysis tests indicate that the DeepSeek model is at a very good level, but it is also much cheaper than its competitors. This is especially relevant for agentic tasks that consume many tokens and that with this model become accessible and very affordable. According to Artificial Analysis, DeepSeek is close to the performance of the best models in the industry, and although it is slower in its responses, it is also much cheaper than the frontier models from OpenAI, Anthropic or Google. A different strategy. How is this company going to make money? It does not have subscription plans like its local competition (GLM, Kimi) or the western one (ChatGPT Plus, Claude Pro). It also does not have voice or image models. It does not have an AI agent for programming that competes with Claude Code. It publishes the open weights of its models and shares its technical innovations with the industry (and with its competitors). For those who closely follow the company and these decisions, the strategy is clear. DeepSeek’s goal is not to win the AI ​​model race. Their goal is to build a Chinese AI hardware industry that doesn’t depend on Nvidia or TSMC… and get paid their share in that process. Hardware independence. China has a structural problem in this AI race: sanctions and vetoes imposed by the US make you unable to access the most advanced chips nor to ASML UVE photolithography. And since China cannot currently compete in terms of computing power, what its companies are doing is ensuring that their AI models need less computing power to achieve similar results. Efficient architectures. The Mixture of Experts (MoE) and Multi-head Latent Attention (MLA) architectures are two key weapons in this strategy. The first already existed but was adapted by DeepSeek for their model: with it only part of the total parameters of the model are activated to answer the query without losing precision. What MLA does is compress the attention information (the so-called KV Cache) with which the model maintains the context of a conversation, reducing it by 90%. Both techniques allow us to reduce the need to use high-speed HBM memories, something that is also striking in order to reveal DeepSeek’s probable strategy. The importance of KV Cache. As the GDP analyst explains in Xthat use of MLA allows that for one million tokens, DeepSeek-V4-Pro only needs 5.48 GB of HBM memory. Competitors like Zhipo AI, which develops GLM 5, need 60 GB for the same, while Alibaba’s Qwen 3 needs 89 GB. This advantage allows DeepSeek to offer much lower prices to obtain performances similar to those of its competition, but it also means that DeepSeek models can run on Chinese memory chips that cannot compete in speed with HBM modules. Goodbye HBM, hello NAND and SSD. These innovations open the door to the use of NAND memories and even SSD drives to process this data, and there YMTC enters the scenea Chinese Flash memory manufacturer that is slowly becoming a global giant. Also CXMTwhich manufactures DRAM memoriesbecomes an alternative here and the reason is equally interesting: DeepSeek introduced a memory search module in LLMs called Engram which is also intended to avoid excessive dependence on HBM memories. How to bypass the CUDA monopoly. Nvidia continues to have a fundamental element in CUDA to maintain its market dominance, but here DeepSeek too has proposed an alternative. Is called Tile Kernels and these are software cores created with TileLang (a variant of Python for this field) that allow governing advanced AI chips (GPUs). Huawei as an invisible ally. Those responsible for Huawei recently indicated that its new Ascend AI supernodes fully support DeepSeek v4 models. Precisely this provides another fundamental advantage to the company, which thus avoids (at least in part) total dependence on the use of Nvidia chips and prepares to further strengthen Huawei’s relevance in a market in which until recently Jensen Huang’s company was queen and mistress. Open models to attract the hardware industry. US companies continue to maintain their closed and proprietary models, but DeepSeek is one of the many Chinese startups that publish them with open weights. With this, what she and the others intend to do is not only attract AI developers and users, but also create a hardware ecosystem that adopts these architectures. DeepSeek invites its rivals to use techniques such as MoE or MLA precisely so that all these advances become a de facto standard and hardware manufacturers also adopt them and integrate them in an optimized way into their designs. A round of 10,000 million to advance. The company is also preparing a financing round in which they intend to raise 10,000 million dollars and with which they would achieve a valuation of between 45,000 and 50,000 million dollars. Still far from the mammoth valuations of OpenAI or Anthropic (already close to a billion dollars) but certainly … Read more

How to create a pack of Chibi stickers from your photo with Gemini or ChatGPT and then use them on WhatsApp or wherever you want

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Let’s explain to you how to create a “Chibi” style sticker packthat Japanese style in which a face is caricatured with a big, adorable head. Let’s do this using artificial intelligenceand a prompt that you will be able to use both Gemini as in ChatGPT. Once you have generated your sticker packall you have to do is cut out each one of the image and use it as you want. For example, you can use the methods we have told you to convert any image into sticker directly on WhatsApp. The positive part of the prompt that we are going to tell you is that it will make you a series of stickers defined with pre-established expressions that you will be able to edit together with the prompt. And although it was created by OpenAI for ChatGPT, you can use it by hand both in this and in any other AI that generates images, such as ChatGPT. Create a sticker pack from your photo To create a sticker pack from your photo, you first have to upload a photo in which your face can be seen well and your features. If it’s a selfie, better, because then the AI ​​can use your features to compose the pack. Once you have attached your photo to the ChatGPT and Gemini writing field, write the following prompt. You have to send both things at the same time, the photograph and the prompt. The command to use is the following: Using the uploaded photo, create a pack of adorable, illustrated chibi stickers. Clean white background, vertical format with a thick white border. Create various tender expressions: laughing, crying, sleepy, surprised, confused, eating, grumpy, cute expressions… Each expression must include a tender text, for example: Good morning! Whatee? / Huh? / I remind you! / What a dream / Wow! Approved! / Brilliant! / Hey, you! Achís! / Angry! / Huh??? / Good night :3 / Too cute / Am I cool now?! Once you send the image along with the prompt, AI will create a set of stickers from your photograph, and it will put them all into a single image. Now all you have to do is digitally cut out each one and use it to generate your sticker for your messaging app. In Xataka Basics | How to create a character in ChatGPT and Gemini to use it in all the images you make with artificial intelligence

Microsoft wanted to create a mega data center in Kenya. To function, half the country had to live without electricity

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In May 2024 Microsoft announced what seemed like a historic agreement for Kenya’s technological development. The goal: create a gigantic data center that would be powered by geothermal energy. This center was going to be created in the Olkaria region, but the Kenyan president, William Ruto, has been blunt with Microsoft’s energy claims: to power the total requested 1 GW capacity, the country “would have to shut down half the nation.” too fair. Kenya has an electrical capacity installed capacity of between 3 and 3.2 GW, with peak demand that already reaches 2.44 GW. Microsoft’s project would consume approximately a third of the country’s total capacity. Even the first phase, which requires a capacity of 100 MW, would take a huge bite out of the production of the Olkaria geothermal complex, which generates about 950 GW in total. Kenya seems to be clear that sacrificing domestic consumption was not worth it when most of the project’s profitability will end up in the hands of a large foreign technology company. Financial disagreement. In addition to the energy problems, the negotiations have ended up getting stuck in the economic field. According to sources close to the process cited in BloombergMicrosoft and the investment firm G42 have reportedly asked the Kenyan government for a financial commitment. Specifically, payment for a certain amount of capacity each year, something with which the Kenyan leaders did not fully agree. The project has not been canceled. John Tanui, head of Kenya’s Ministry of Information, explained that his country is still in negotiations with Microsoft and G42, and that the agreement “has not failed or been abandoned. The scale of the data center they needed requires some structuring,” and that includes solving both the energy and economic problems. A project with a lot of geopolitics behind it. This project was not only a technological milestone for Microsoft and Africa, but also a diplomatic one. It is part of a $1.5 billion deal between Microsoft and Abu Dhabi-based G42, which was designed to counter potential deals on this continent with China. In fact, as a condition for the G42 agreement had to divest its Chinese assets and remove Huawei equipment from their systems. While the project is on hold, however, the Chinese company continues to expand in this region and has recently launched new broadband services over fiber with the largest Kenyan operator, Safaricom. Bottlenecks everywhere. The case of Kenya is not the only one that is stopping Microsoft’s plans. The company has announced a capex of 190 billion dollars by 2026 that will be invested in data centers, and the company is adding approximately 1 GW of computing capacity each quarter globally. However, about half of the data centers planned in the US this year have been canceled or delayed due to the shortage of electrical infrastructure. Image | Microsoft In Xataka | In 2024, Big Tech spent absurd amounts of money on AI. In 2025, they managed to spend 77% more

How to create a Telegram bot that summarizes your Google Calendar appointments every morning with AI

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We are going to tell you how to create a Telegram bot that summarize your Google Calendar appointments and events each daymaking him a personal secretary who gives you a summary every morning. To do this, we will make the bot use artificial intelligence as Gemini, ChatGPT, Claude or whatever you prefer. To carry out this task we are going to use two third-party services. First we will use BotFather from Telegram to create the bot, and then we will go to the service Make to create a workflow or workflow that adds an AI, which in the case of our step by step will be Gemini, but you can use any other. But before we start, just one warning. This method is very easy and useful, but in the end you will be giving your calendar information to third parties. Google already has it, but you will also be sharing it on the Make platform, and that is something you should always keep in mind. First you must create the bot The first thing you should do is create a bot on Telegram with BotFather. To do this, write a message to the bot @BotFather and write to you as if you were a new user. Type the command /newbot to create a new bot, to which you have to give a name to identify yourself and a unique username to access the bot whenever you want. When you do it, it will give you two things, first the username and address of your bot to access it, and second an access token with various figures and letters. You have to save this token to use later. In the message that Telegram will return to you, will also give you a link to the bot you createdwhich will basically be t.me/@botname. This will be important for later. Also you can use BotFather options to customize your botputting a profile image, a description or whatever you want. We have explained all this to you in our post about BotFather. Once the bot is created you must enter and run it with the /Start command so that it remains active, even if doing so does not respond to anything. Now get the API of an AI Now you need the API of an AI. We will use the Free Gemini APIwhich although it has some limits in its use, is more than enough for a little use. To get it go to the website aistudio.google.com and sign in with your Google account. When you do, go to Dashboard and click on API keys. in here, click on the option Create API key which you have at the top right. Now you have to click on the option Create API key that appears at the top of the screen you have created. This will open a window where you have to create the project for which you are going to use it in order to identify it, for example “Secretary Bot”. When you create the project, you can now create the API. And by the way, if you want something more advanced, We have also explained payment alternatives to the Google API. In Basics you have articles where you can see the prices and how to get the ChatGPT APIthe Claude APIthe DeepSeek API wave Qwen API. Now create the workflow Now it’s time to create your workflow. For this, you will have to enter Make.com, and create a new scenario. This will take you to a screen where you just have to click on the add button to add the first module, and then to the right of each module click on + to add another adjacent one. But to do this, you will have to configure each module before chaining the next one. We are going to guide you and explain to you the four modules you should add and how to configure themas well as then scheduling the scenario to run every day at the time you want. 1. Add the calendar module To start, you have to create a new module. On the screen that opens, choose Google Calendarand in the options click on the module Search Events. You will have to sign in with your Google account. In the configuration window, you will have to add the following elements that we are going to list: Calendar ID: Choose the primary calendar or the one where you have the data of the meetings or elements that you want to summarize. Start Date: Paste the following: {{formatDate(now; “YYYY-MM-DD”)}}T00:00:00Z End Date: Paste the following: {{formatDate(now; “YYYY-MM-DD”)}}T23:59:59Z Single Events: In this field, choose the option Yes. When you have everything, click on Save. If you want, click below Run eleven so that Make takes a look at your calendar, and so in the next module you can put options related to the results obtained. 2. Add the text aggregator Now you have to add a next module chained with the calendar. In the applications press Toolsand inside click on Text Aggregator. Now, enter the module, and in the field text you will have to choose the options 1.Summary and 1.Start. If you get confused, just by clicking on the text field a window with suggestions will appear. In it, search for Google Calendar suggestions, and in the results click on the options Summary and startso that when filled in they appear with the number 1. If they do not appear, first do a Run eleven with the calendar module alone so that they appear when creating the Text Aggregator. 3. Add Gemini into the equation With what we have done so far, the automation analyzes your calendar and obtains the events. Now it’s the turn of send it all to Gemini so that it then generates the response. For this, choose the module Geminiand link the AI ​​using the API we obtained before. Once you have done it, it’s time to configure the module. In AI Model you have to … Read more

AI already knew how to create images. OpenAI says it has found the missing piece with the new ChatGPT Images 2.0

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Over the last few years we have seen image generators become increasingly more spectacular, faster and also more popular. The problem is that a striking image is not always useful to work with. It is one thing to ask for an astronaut cat and quite another to obtain a usable marketing poster, a coherent vignette or a graphic that respects what we have asked for. That’s where OpenAI now wants to move the conversation with its new model: not so much towards the pretty image, but towards the useful image. The answer. What OpenAI proposes goes in that direction. The company led by Sam Altman He maintains that his new model is not only created to generate attractive images, but to solve visual assignments with more intention and less trial and error. In the presentation he went so far as to state that “images are a language, not decoration”, a fairly clear way of summarizing where he wants to take the product in a present with quite a bit of competition. The thesis is that: that asking for an image in ChatGPT It’s less like launching a creative prompt and more like commissioning a piece that we can actually use. The missing piece. If the firm wants us to talk about something more than showy images, it had to improve exactly the points where these models usually fail. Here they promise important changes on three very specific fronts: following complex instructions more precisely, better organizing elements within the image and reproducing dense text with greater reliability. In other words, we are not only looking for more beautiful results, but also less ambiguous and more controllable ones. Think before you draw. One of the novelties that OpenAI tries to highlight most strongly is that this is its first image model with reasoning capabilities. Translated into practical terms, the company maintains that, when a model with “thinking” is chosen within ChatGPT, the system can take more time, structure the task better, rely on the web to search for updated information and review its own results before delivering the image. And we have tried it, asking for the image of two people walking along Gran Vía, in Madrid, near Cines Callao, and some notes on activities to do in Spain during May. These are the images that we can see in the cover image. The keys. OpenAI talks about game prototyping, storyboards, marketing creatives, comics, social graphics and other materials where both content and form matter. To sustain that ambition, the company says it has improved on two delicate fronts: the handling of non-Latin text, with advances especially in Japanese, Korean, Chinese, Hindi and Bengali, and the more faithful reproduction of very marked visual styles. It also expands the possible formats, with proportions of up to 3:1 and 1:3, resolution of up to 2K and, in certain modes, the possibility of generating up to ten images within the same request with continuity between characters and objects. The competitive context. This announcement also cannot be read as if OpenAI had suddenly discovered a new market. Midjourney has already become a clear reference for works with a strong artistic charge, Nano Banana has attracted attention for its conversational editing capabilities and FLUX 2 has become strong in photorealism. With that board in front, the company seems to be looking for another angle. Rather than contesting each terrain separately, it tries to present ChatGPT as an environment where the image is not generated in isolation, but as part of a broader flow, something that on paper can be attractive if it really delivers what it promises. It’s already starting to unfold: One of the keys to the announcement is that OpenAI ensures that the model does not remain in the showcase phase, but is beginning to reach a product. The company places its deployment in ChatGPT for all users, including Free and Go, and associates the most advanced results with Plus and Pro, as also reported by Engadget. Additionally, it takes you to the API and Codex, a sign that they don’t want to limit it to casual use within the chat. If your strategy involves turning the image into another work tool, it made sense for the deployment to start precisely there. Images | Xataka with ChatGPT Images 2.0 | OpenAI In Xataka | Amazon wants to win the AI ​​race at any price. That is why it has invested both in Anthropic and OpenAI

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