Anthropic

The AI ​​Claude Code “only” programmed. With Cowork, Anthropic wants its AI to take care of everything else

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Claude Code has become a revolution for programmers, but at Anthropic they are not satisfied with that, and now they want their Claude family AI models to serve much more. And that’s why have created Coworka different agent, especially ambitious and who opens the door to fantastic options… if you trust him. What is Cowork. Those responsible for this project have taken the foundations of Claude Code and applied them to the Claude desktop application (for now, only the macOS one). But they have also done something equally special: giving Claude permission to access a specific folder on our computer and, from there, he can take control of those files and work with them as we want. Hello, robot-secretary. Instead of access to the “vibe coding” we will have access to a kind of “vibe working”. Thus, we can ask Cowork to do all kinds of operations with those files: If we have a folder full of disorganized icons, we can ask you to ordered them to us and reorganize them all into folders by file type or theme If there are a lot of photos of receipts in that folder, we can tell you to create an expense report If what we have is a bunch of digital voice or text notes, we can ask you to write a report summarizing and combining them all. If we have a folder full of podcasts, we can have it go through it, analyze it and summarize the top 10 points of all of them or transcribe them If you have all your financial trading and investment reports and data, you can ask them to create a final report for you. help you declare them If you have videos and want to find one of a squirrel and then convert it to another format, also does. Full autonomy. We are therefore faced with an AI agent capable of accessing our files, analyzing them and working with them to generate new information and useful content from all that data. And we only have to ask it with natural language, because the agent is capable of understanding it, asking us questions if it needs more details, and then solving the task autonomously even if it involves several steps. Cowork operates in a container. The way CoWork works allows you to grant permission to certain folders, but when the AI ​​operates on said files it does so in isolation. As explains Simon WillinsonClaude uses a virtual machine and downloads and boots a custom Linux file system to operate on those files independently and isolated, which theoretically guarantees that our files are theoretically safe and Cowork does not access anything that we have not given permission to. Connections to other apps. In addition to being able to work directly with your files, Cowork benefits from its ability to connect with other applications that you have installed on your computer. You can use ffmpeg to convert the squirrel video, Asana if you want to organize your notes into projects, or an office application if you need to create a spreadsheet. But we will have to trust. Willinson himself warns that these types of systems have the danger of someone “hacking” them with jailbreaking or prompt injection techniques that now become more dangerous because, as we say, what Cowork does is work on our files. And of course we have to be careful with the information and data we share with CoWork: those responsible for Anthropic themselves have a document to “use it safely“. Limited release. Cowork is available as a “research preview”, and is only available to users of the Claude Max subscription which costs between $100 and $200 per month. It is clear that at Anthropic they prefer to go step by step with a very powerful but also delicate feature if we do not use it with caution: in the end we are giving access to our files to an AI, and we know that AIs can make mistakes. An AI on your computer. This release from Anthropic points to what all AI agents that want to conquer our computer should theoretically point to. Since that Computer Use that Anthropic launched in October 2024, things have come a long way, and little by little we are getting closer to that future in which we will be able to work with our computer in a very different way than we did until now… if we want and trust AI, of course. In Xataka | Operator also “looks” at the screen and moves your mouse for you like other AI agents. It does it better thanks to CUA

OpenAI, Google and Anthropic fight among themselves. Samsung fights everyone else elsewhere

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Samsung has presented at the CES 2026 its “AI philosophy,” a grandiloquent concept that sums up its strategy: using its 430 million SmartThings users as moat (or ‘defensive moat’) against the invasion of AI in homes. Why is it important. OpenAI, Google and company remain focused on announcing the most powerful model. There is little to do against them on that side if you haven’t been doing it for years, so Samsung is playing something else that is not about winning the algorithm war, but about controlling where those algorithms live. SmartThings is not just an app. It is a platform Matter compatible that connects hundreds of millions of devices already in homes around the world. That means Samsung can add AI to products people already use, without asking them to buy anything new or change their habits. Others have to convince you to put a smart speaker in the kitchen. Samsung already has your refrigerator, your television, your washing machine and your vacuum cleaner. And everyone talks to each other. Between the lines. Samsung’s “AI philosophy” seems, above all, a response to Amazon with its Alexa+. Both proposals have things in common: they understand that if AI models tend to commoditize (to be technically equal until they are not easily distinguishable), the value is in who has the speaker in your kitchen, the TV in your living room and the refrigerator that knows what you eat. Samsung has been building that ecosystem for years and now it is activating it for something else. Implementation makes the difference: Family Hubwith AI and Gemini vision, recognizes what you put in and out of the refrigerator, suggests recipes and connects with other appliances. It’s real tracking so that when you ask yourself “what can I make for snack-dinner?”, the system suggests recipes based on what you have, not on an inventory you made by hand three weeks ago. Vision AI Companion It recognizes what you’re watching on TV and suggests recipes if food appears on the screen. Then send that recipe to the Family Hub in your refrigerator, which checks what ingredients you have and tells you what you’re missing. If you decide to cook it, send the instructions to the oven so that it is preheated to the exact temperature. AI Soccer Mode Pro Automatically adjusts image and sound when it detects that you are watching football. You can turn up the audience volume, turn down the commentators, or balance both. It’s AI applied to something as specific as “I want to enhance the field atmosphere” or “I want to prioritize the narrator’s voice.” It is perhaps not as attractive an approach as the war of chatbots that are increasingly capable of more, but maybe (just maybe) it will end up being more profitable. And something else: SmartThings as a Matter-compatible standard. That expands the potential ecosystem far beyond Samsung’s own products. Yes, but. There are two weak points in that strategy: Samsung depends on third-party models. Gemini is your main partner, also for the home, for the smart component. If the models run out commoditizingwe will have to compete on price. And in the price war there always appears a Chinese manufacturer willing to go lower. privacy. An ecosystem that knows what you eat, what you see, when you sleep or how you move is also an ecosystem that can monetize that data. The last threat It’s called Dreame. and there is a red flag On that second point: Samsung has announced an agreement with the insurer HSB to give discounts on home insurance in exchange for connecting home appliances to SmartThings. That is, saving some money in exchange for handing over your behavioral data. As what we already saw with health insurance and wearables. It’s a double-edged sword: if your behavior reduces your premium, it can also increase it. Or directly invalidate coverage. The bet. If it works, Apple will speed up with Home (previously HomeKit), Google will push with its Nest and Amazon will double down with Alexa+ and Ring. The battle is no longer for the best language model. It’s because more devices in more homes capturing more data. Samsung has been losing ground in mobile phones for years fruit of Apple’s clamp in premium and Chinese manufacturers in price. Also against LG in some appliances not to mention Chinese baking for the home. But in the sum of connected devices per home, it does not have so many rivals. That is its trump card: converting the fragmentation of its catalog into the advantage of its ecosystem. The question is whether consumers will give up control of their home in exchange for convenience. The answer determines whether Samsung ends up being the silent winner of the AI ​​era or simply the maker of gadgets that run other people’s intelligence. In Xataka | I would never have imagined answering a call from the washing machine. Until I tried the latest from Samsung Featured image | Screens even in washing machines and appliances that talk to each other: this is how Samsung imagines the future of the connected home

To the question of what sense it makes to compete with Google, OpenAI or Anthropic in AI, Mistral has an answer: small and local models

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French startup Mistral AI Mistral 3 has been launcheda family of 10 open source artificial intelligence models that represent its most ambitious commitment to date. The Parisian company, which is often considered the main European hope in the development of AI, seeks to differentiate itself from the large American technology companies by betting on flexibility and deployment in all types of devices instead of raw power. Under these lines we tell you all the news. What Mistral has presented. The Mistral 3 family includes a flagship model called Mistral Large 3, with 675 billion parameters, and nine compact models grouped under the name Ministral 3 (in three sizes: 14,000, 8,000 and 3 billion parameters). All models are released under Apache 2.0 license, allowing unrestricted commercial use. The large model also has multimodal capacity, being able to process text and images. It is also multilingual, with a special emphasis on European languages. On the other hand, small models can run on devices with just 4 GB of memory, making them perfect for modest laptops, mobile phones and embedded systems without the need for an internet connection. Why strategy matters. While OpenAI, Google and Anthropic focus on increasingly powerful and closed systems with agentic capabilitiesMistral has focused on the breadth and scope of its models, efficiency and what its co-founder Guillaume Lample calls “distributed intelligence.” According to declared told VentureBeat, the company believes the future of AI is defined not by scale, but by ubiquity: models small enough to run in drones, vehicles, robots and consumer devices. The economic and practical argument. Lample explained It means that in more than 90% of cases, a small, specifically tuned model can get the job done, especially if it is trained with synthetic data for specific tasks. According to Lample, this is not only cheaper and faster, but it eliminates concerns about privacy, latency and reliability. The company also has teams that work directly with customers to analyze specific problems and fine-tune small models that perform specific tasks. This, above all, can attract companies that become frustrated when choosing the best possible model for a specific task and, if it does not perform adequately, they end up giving up. Europe is lagging behind. If we talk about innovation and technology around AI, we do not hesitate to say that Europe is leagues away of what companies in the United States and China are offering. This is why Mistral AI advocates a different approach in which it prioritizes massive deployment in devices and the flexibility of its smaller models. The capacity offered by open models can be a great asset to continue betting on these technologies. In China, for example, the open models of DeepSeek, Alibaba or Kimi are emerging widelyabove in certain tasks even competitors as large as ChatGPT. Lample explained that most leading Chinese models are exclusively text-based, with separate image processing systems. For this reason, they also want to opt for a multimodal approach. A complete ecosystem. Mistral no longer only offers language models. The company has built an entire ecosystem that includes Mistral Agents APIwith connectors for code execution, web search and image generation; Masterlyyour reasoning model; Mistral Code for programming assistance; and AI Studioan application deployment platform that also has analytical and logging capabilities. Furthermore, his assistant Le Chat It has incorporated a deep research mode, voice capabilities and a list of more than 20 enterprise integrations. Thus, in addition to its model offering, the company can provide other companies with a whole layer of personalized products and services, with the aim of being their main source of financing. Digital sovereignty. Although Mistral is often characterized as Europe’s answer to OpenAI, the company prefers to consider itself as ‘a transatlantic collaboration’. Its CEO, in fact, is in the United States, has teams on both continents and trains these models in collaboration with American teams and infrastructure. However, its positioning as a defender of European digital sovereignty has earned it strategic partnerships with the French army, the country’s employment agency, the Luxembourg government and various European public organizations. The European Commission presented in October a strategy to promote European AI tools that provide security and resilience while boosting the continent’s industrial competitiveness. Offline capabilities for democratization. The use cases that Mistral has designed for its small models include, above all, local applications, such as factory robots that use sensor data in real time and without relying on the cloud, drones in natural disasters or rescues that operate offline, and smart cars with functional AI assistants in remote areas. Lample stood out that there are billions of people without internet access but with laptops or cell phones capable of running these small models, which he considers potentially revolutionary. Additionally, by running on the device, these apps preserve the privacy of user data. Real “open source” debate. Not everyone celebrates Mistral’s approach. Some critics question his decision to opt for models’open weight‘, that is, free to access but providing less information about their code than truly “open source” models, which provide the code and training data necessary to train a model from scratch. Andreas Liesenfeld, assistant professor at Radboud University and co-founder of the European Open Source AI Index, declared to the Financial Times that data at scale is the missing key in the European AI innovation ecosystem and that Mistral does not contribute to that at all. The long-term strategic bet. Lample recognize that their models are “a little behind” the most advanced closed systems, but argued that the important thing is that “they are catching up quickly.” Time will tell if Mistral’s approach to low-cost, versatile models with local applications ends up working for them to end up positioning themselves as one of the great European bets on AI. Cover image | Mistral AI In Xataka | China already has an army of 5.8 million engineers. His new plan involves accelerating doctorates

NVIDIA, Microsoft and Anthropic have signed a new multi-million dollar agreement

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Microsoft, NVIDIA and Anthropic have announced recently a series of strategic alliances that redistribute the map of power in the generative AI race. Anthropic will deploy its Claude models in Azure, Microsoft’s cloud, while committing to purchase $30 billion in computing capacity and contract additional capacity of up to one gigawatt. For their part, NVIDIA and Microsoft will invest up to 10,000 and 5,000 million dollars respectively in the startup. The triangular pact, in figures. Anthropic will have access for the first time to Microsoft Foundry, where its most advanced models (Claude Sonnet 4.5, Claude Opus 4.1 and Claude Haiku 4.5) will be available to Azure enterprise customers. With this, Claude becomes the only advanced model present in the three main cloud services in the world. Additionally, Microsoft promise maintain the integration of Claude into its Copilot family, including GitHub Copilot, Microsoft 365 Copilot, and Copilot Studio. In parallel, NVIDIA and Anthropic establish their first collaboration of such caliber. To do this, they will work together in design and engineering to optimize the Claude models on future NVIDIA architectures, starting with systems Grace Blackwell and Vera Rubin. Microsoft looks for alternatives to OpenAI. This move comes just weeks after OpenAI will complete its restructuring towards a for-profit model and will renew its agreement with Microsoft. Although Microsoft maintains a 27% stake in OpenAI valued at about $135 billion, the new terms of the deal have relaxed some key elements of its exclusivity. And OpenAI can now collaborate with third parties and release open source models, while Microsoft no longer has the right to try to be its sole computing provider. According to The Vergethese changes in the relationship with OpenAI have precisely allowed Microsoft to close this pact with Anthropic. In fact, Microsoft had already been betting on Claude in some of its services, for example, in Visual Code, prioritizing Claude over GPT-5 in your model selector. It also recently added Claude Sonnet 4 and Claude Opus 4.1 to Microsoft 365 Copilot. Circular financing: money that comes back. As is customary in these AI macro-agreements, a clear circular financing dynamic. Microsoft and NVIDIA pump capital into Anthropic, which in turn commits to spending tens of billions on infrastructure provided by those same companies. In essence, some of the money invested returns as revenue from cloud computing services and specialized hardware. It is not a new phenomenon: in fact, Anthropic already has similar agreements with Amazon, which has invested 8 billion dollars and continues to be its main infrastructure provider, and with Google, which in recent weeks announced a pact to provide up to one million TPUs to the startup. These types of cross-investments have become the norm in the generative AI ecosystem, creating almost symbiotic relationships between companies to meet their computing and infrastructure needs. one gigawatt. Building a data center with that capacity could cost around $50 billion, according to industry estimateswith some 35 billion dedicated exclusively to AI chips. Although the figure pales compared to OpenAI’s Stargate project, which aspires to 500,000 million dollars In investing, Anthropic’s approach seems more pragmatic and execution-focused. The company led by Dario Amodei has gained ground in the business market with less media noise but with solid results. And its annualized revenue rate now reaches $7 billion, although like the rest of the AI ​​startups it continues to spend much more than it earns. Diversification. What is really relevant about this agreement is that it confirms a trend: that large technology companies are no longer betting everything on a single card in AI. Microsoft, which has invested billions in OpenAI since 2019 and made it the flagship of its AI strategy, is now expanding its portfolio with Anthropic. For its part, Anthropic demonstrates its ability to maintain multiple alliances without compromising its independence. It is the sensible option and the one that minimizes risks. Cover image | Microsoft In Xataka | Tim Cook’s end at Apple is approaching

OpenAI teamed up with NVIDIA and made circular financing fashionable. Anthropic has returned the ball with a surprise girlfriend: Google

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Let’s see if we were going to believe that OpenAI was going to be the only one to look for powerful allies. Nothing of that: Anthropic just did the same and has announced an eye-catching agreement with Google. The AI ​​startup will have access to up to one million Google TPUs in a pact that is worth “tens of billions of dollars.” Less noise, but a lot of nuts. The figures of the agreement are modest if we compare them with those that OpenAI has managed in its circular financing agreements with NVIDIA, amd either Broadcombut here Anthropic seems to take a very different position. Compared to colossal projects like Stargate, Anthropic’s idea is focused on execution. Without making much noise, the company led by Dario Amodei has been gradually conquering the business sector. More than 1 GW of computing capacity. On CNBC indicate that this investment will allow the creation of a data center with a computing capacity greater than 1 GW and have it ready in 2026. It is estimated that a center of these characteristics would cost about 50,000 million dollars, of which about 35,000 million would be dedicated to AI chips. It may not be comparable to Stargate and the idea of ​​investing $500 billion in data centers, but the alliance between Anthropic and Google is significant. More than circular financing. The partnership certainly features elements of circular financing, but it is more of a symbiotic relationship with that cross-investment component. The dynamic is simple and is now completed with that commercial return. The agreement requires Anthropic to buy or rent infrastructure services from Google Cloud. Virtuous circle. With its original investment in Anthropic, Google helped that company grow, which in turn allows Anthropic not only the ability to grow, but the need for enormous computing power… provided by Google. In essence, some of the money Google invests in Anthropic returns to Google Cloud as revenue. The vicious (or virtuous, as they say in the US) circle is complete. Anthropic diversifies. Anthropic’s AI models are trained and used using infrastructure from various manufacturers. Thus, they use both Google TPUs and Amazon Trainium processors and NVIDIA GPUs: each platform is assigned to a specialized workload. In the case of Google’s TPUs, according to Anthropic the focus is “its strong price/performance ratio and its efficiency.” Promising successes, but… Anthropic’s growth is evident, and its annualized revenue rate (ARR) is now estimated to reach $7 billion. Claude Code, its developer assistant, managed to generate 500 million dollars after just two months on the market. But as always, that revenue can’t hide the fact that Anthropic, like other AI startups, you continue to spend much more money than you earn. Amazon is your other great ally. In fact, the company led by Andy Jassy has invested around $8 billion, when official data indicates that Google has invested $3 billion. AWS is still considered the largest infrastructure provider for Anthropic, and its supercomputer Project Rainierbased on the Trainium 2, allows you to have a large computing capacity for every dollar invested, they point out on Amazon. The company’s influence is not only financial: it is structural. Image | Wikimedia | Fortune Brainstorm Tech In Xataka | You thought you had an amazing connection on Tinder, but you were actually chatting with ChatGPT

Anthropic is spending much more money than it brings in. The question is how long can it continue like this?

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How much does AI cost? That question can be answered by AWS, which has billed Anthropic a whopping $2.66 billion so far this year. The problem is twofold, because in that same period it is estimated that Anthropic has earned 2.55 billion dollars, so with that alone it has spent more than it earns. But Anthropic has many more expenses and the accounts, once again, do not work out in the AI ​​segment. Why is it important. The data revealed by Ed Zitron confirms the problem they face all AI startups: They spend (much) more than they earn, and that trend does not seem to be reversing. In fact, although these companies are growing in revenue, they are also growing proportionally in expenses. And the question, of course, is whether this pace is sustainable. The Anthropic case. According to Zitron data, in 2024 Anthropic earned between $400 and $600 million, but spent $1.35 billion on AWS, that is, 226% of its income. The trend appears to continue in 2025, because the share of spending on AWS is 104% of its revenue. It seems that things have improved, but that expense does not include what it costs Anthropic use Google Cloud infrastructureanother of its partners in all its operations. The expenditure on it is also likely to be enormous, which complicates the situation. The mystery of unexplained costs. The unaccounted cost gap is also enormous. In 2024 Anthropic’s total spending was estimated at 6.2 billion dollars. If we know that he spent $1.35 billion on AWS, there is $4.85 billion left that is not explained. That suggests that spending on Google Cloud and other operational costs is absolutely astronomical. In fact, computing costs may be much higher than we thought. Another startup desperate for investment. Meanwhile, Anthropic continues to raise capital. Zitron analysis reveals that between 2023 and 2025 achievement raise investment rounds for a total of 37.5 billion dollars (20,000 of them in 2025 alone). A good part of that money came precisely from the companies that provide infrastructure: Amazon and Google. Despite that funding, Anthropic appears as desperate as OpenAI to raise new rounds of investment. The company run by Dario Amodei recently resorted to money from Middle Eastern countries, for example. Spending continues to skyrocket. The study figures further reveal that Anthropic spends more the more time passes. In January 2024, it spent $52.9 million on AWS, but in December 2024 that amount rose to $176.1 million. In September 2025, it is estimated that spending on AWS was no less than $518.9 million: the escalation in costs is very notable. And he tightens the screws on Cursor. One of Anthropic’s most important clients is the startup vibe coding Cursor. This company has clearly been affected by that situation, and Cursor’s costs on AWS doubled from $6.19 million in May 2025 to $12.67 million in June. Just in those Anthropic months implement the so-called “Service Levels” with which it forced business customers to spend a minimum amount and pay higher rates for prompt caching, a special component designed for startups that use generative AI models for programming. What did Cursor do? Increase prices (and apologize for it) of your customer subscriptions. This can’t go on like this forever. For Zitron, always very critical of this reality of AI companies, the conclusion is clear: Anthropic’s costs are out of control. In fact, he argues that they increase practically linearly with respect to revenue, which makes their business model unsustainable. The only solution is to increase prices drastically (possibly 100%) to become profitable. The problem is that the market accepts paying twice as much at once for AI as it currently pays for. Image | Anthropic | Taylor Vick In Xataka | Anthropic says Claude Sonnet 4.5 can clone a service like Slack in 30 hours. The reality is more complicated

Anthropic says that Claude Sonnet 4.5 can clone a service like Slack in 30 hours. Reality is more complicated

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Anthropic has launched Claude Sonnet 4.5 ensuring that they put it to work 30 hours in a row to build a Slack replica. During that time, it generated 11,000 lines of code without supervision and only stopped when completing the task. In May, its Opus 4 model managed to operate for seven hours. The company presents it as “the best model in the world for agents, programming and use of computers.” Why is it important. Anthropic, Openai and Google free a battle to dominate Autonomous agents and programming tools. Those who convince will capture a lot of money in business licenses. Scott White, product manager, says that “at the level of a cabinet chief”: coordinates agendas, analyzes data, writes reports … Dianne Penn says he uses it to search for candidates on LinkedIn and generate spreadsheets. Yes, but. The developers tell another more nuanced story. Miguel Ángel Durán, known as @Midudevsummarizes it: “Claude Sonnet 4.5 Refactor my entire project in a Prompt. 20 minutes thinking. 14 new files. 1,500 modified lines. Applied clean architecture. Nothing worked. But how beautiful it was. “ Other developers They report the same: thousands of lines with an impeccable structure, but do not execute. Code that seems professional but collapses when compiling it. Between the lines. Anthropic has not shown the application of Slack working. He has only said that he built it. Nor has it shown that the code is operational. The difference between communicating something and demonstrating it, Underlined by Ed Zitron. The company is indirectly recognizing the problem: Claude Sonnet 4.5 arrives with extra infrastructure to build agents – virtual management, memory management, context management, multiagente support …–. Translation: Even with the most advanced model, developers need extra tools for agents to program reliably. In detail. Penn He explained to The Verge that the improvements surprised the internal team. The model is three times more skilled using computers than the October version. The team spent the last month working with feedback of github and cursor. Canva, Beta-fieldsHe says he helps with “complex long context tasks.” The contrast. There is a huge gap between marketing and technical reality. Anthropic promises an AI that operates 30 hours building complex software. Developers confirm that it generates very well structured but functionally broken code. This pattern is repeated throughout the industry. The models improve generating code that seems professional. They systematically fail generating code that really works without important human intervention. And now what. The question is still unanswered: when will we pass from Which generates beautiful but diffunctional code What generates functional code alone? Anthropic bets that his combination of powerful model and extra infrastructure closes that gap. At the moment we must continue waiting for concrete evidence to arrive, do not give without verifiable code. In Xataka | Openai signs with Samsung and SK Hynix for a potential chips demand of 900,000 wafers per month. It is an absurd figure Outstanding image | Anthropic

Anthropic wants to be unbeatable in programming, although his ambition goes further

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Anthropic has just presented Claude Sonnet 4.5an evolution that The company defines as its most precise model to date. The focus is in Agentsprogramming and computer use, with the idea of ​​expanding what the previous versions of the Sonnet series already offered. His arrival is interpreted inside an increasingly adjusted struggle: Openai has launched GPT-5 With different levels of capacity and Google continues to bet on Geminiconfiguring a board where each advance generates new expectations. The family’s trajectory helps to understand the place occupied by this new version. With Sonnet 3.7Anthropic introduced a hybrid reasoning model that marked a remarkable leap in coding, content generation and data analysis. The subsequent arrival of Sonnet 4 He consolidated that bet, reinforcing his position as a practical option for attendees. These improvements made Sonnet into UNa Outstanding Alternative for Programmersand it is from that base where the expectation is now raised about what 4.5 can contribute. What Anthropic promises with his new model Sonnet 4.5 introduces improvements designed for agents that require maintaining attention for long periods. According to Anthropic, he is able to sustain the focus during More than 30 hours in complex tasks and admits outputs of up to 64,000 tokens, which expands the capacity of planning and generating code in extensive blocks. The developers have finer controls about the time that the “think” model before responding, which opens margin to balance speed and detail based on the need for each project. Another of the areas where Sonnet 4.5 seeks to differentiate is in the use of computer and browser. Anthropic points out that the model has reached 61.4% in Osworld, a Benchmark which measures the ability to complete real tasks in a desktop environment. This is a considerable leap compared to 42.2% obtained by Sonnet 4 just a few months ago. The company shows practical examples with its extension of Chrome, where Claude is capable of navigating websites, filling spreadsheets or perform competitive analysis without constant supervision. Programming is the land where Sonnet 4.5 wants to consolidate its leadership. Anthropic ensures that the model can cover The entire development cycle Software: from initial planning to the refactorization of large projects, through the maintenance and correction of errors. With Claude Code’s support, he seeks to become a stable assistant for technical teams. The range of Sonnet 4.5 extends to a wide range of applications that, according to Anthropic, make it a model designed for corporate and research environments. The most repeated examples in your presentation include: Cybersecurity: deployment of agents that correct failures without human intervention. Finance: Constant monitoring of regulatory changes and risk management. Productivity: Edition and creation of office files in different formats. Investigation: Integration of internal and external data to prepare reports. CONTENTS: writing with math understanding and deep semantic analysis. The company adds that Sonnet 4.5 has passed reviews with external experts to validate its safety and reliability. Sonnet 4.5 is now available for any user in Claude.AIboth on the web and in iOS and Android applications. In parallel, developers can integrate it into the Claude Developer Platform, in addition to services such as Amazon Bedrock and Google Cloud VerTex AI. The free plan works with a session limit that is restarted every five hours and with a variable number of messages according to the demand. Regarding prices, part of $ 3 per million input tokens and $ 15 per million departure tokens. Images | Anthropic | Xataka with Gemini 2.5 In Xataka | “The humanoid robots is pure fantasy”: Irobot’s co -founder believes that there is a robotics bubble

Anthropic is worth 183,000 million even though he invoices 5,000 million a year. Or it is the business of the century, or it is the madness of the century

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Anthropic has just closed A financing round of 13,000 million dollars that values ​​it in 183,000 million. The figure sounds like madness when we put it in context: the company invoices 5,000 million a year. The figures. Anthropic is valued 36 times. Google, to compare, quotes 6 times. Apple at 8. Microsoft to 14. They are mature companies in front of a startup, but none remotely approaches this multiple. The round F It has been led by ICONIQ Capital, with Fidelity and Lightspeed as co-investors. Heavyweights such as Blackrock, the sovereign background of Qatar and Ontario Teachers’ Pension Plan have participated. What has happened. In just eight months, Anthropic has multiplied its income by five: from 1,000 million to 5,000 million in August (annualized). It is one of the fastest growth in the history of technology. Claude Codeits programmers tool, generates 500 million in annualized revenues. It has multiplied its use in three months since its complete launch in May. The context. The AI ​​career has become a war of valuations disconnected from classical financial reality. OpenAI negotiates an assessment of 500,000 million. XAI of Musk looks for 75,000 million. Investors are betting Billions to these companies will dominate the future. Anthropic serves 300,000 business clients. Its large accounts (those that pay more than $ 100,000 a year) have multiplied by seven in twelve months. Yes, but. Developing elite AI models is very expensive. Anthropic depends on Amazon and Google for his computational infrastructure, and costs him billions annually. The costs are not going down, they are accelerating. Sam Altman, CEO of Openai, has said that his company will need to invest billions of dollars. The generative AI business remains structurally deficient for almost all participants. Nvidia always wins. Between bambalins. Dario Amodei, CEO of Anthropic, has admitted in An internal memo that is not “excited” to accept money from sovereign funds of dictatorial governments. But says It is difficult to direct a business excluding “bad investors.” The company has promised to use 13,000 million to expand capacity, deepen international security and expansion research. It is also developing specific products by industry. The end of a dream. A few months ago We speculated that Apple could buy Anthropic to accelerate your entry into AI. With an assessment of 183,000 million, that option has been buried: it would be 60 times more expensive than Beats, Apple’s greatest acquisition in its history. Not even Tim Cook (who He was open to check) With 150,000 million in cash available, you can justify such a check before your shareholders. The big question. Are we facing the birth of the new technological giants or the greatest bubble from the Puntocom? With assessments that multiply by 36 income, the margin of error is non -existent. Investors are betting on Anthropic and their rivals will not only dominate AI, but the AI ​​will transform the entire global economy. If they are right, 183,000 million will seem cheap. If they are wrong, it will be a historical disaster. Outstanding image | Anthropic, Xataka In Xataka | People are celebrating funerals by the Ia withdrawn for a reason: they are not a “tool” but a support

Anthropic cuts Claude’s access to Openai. He has done it before the launch of GPT-5

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The AI race is very intense lately. The last episode is stars in Anthropic, who have cut access to Openai so that they cannot access their family of models Claude. The company claims to have caught the engineers of Chatgpt wearing Claude programming toolswhich has not fallen very well. This, According to a spokesman From the company to the medium Wired, it is “a violation of its terms of service”, so they have restricted access to the API. What has happened exactly. Openai connected Claude to his internal tools through his API, instead of the conventional chat interface. This allowed the company to carry out comparative evidence between Claude and its own models in areas such as programming, creative writing and security -related responses. The results helped Openai evaluate the behavior of their models and make necessary adjustments. An endless war. This decision goes beyond a simple contractual dispute: marks a turning point in the relationship between two of the main powers of the generative AI. Anthropic was born in 2021 precisely from an Openai split, when several key researchers, including the brothers Dario and Daniela Amodei, left Altman’s company due to differences on the direction and safety of AI. Since then, The tension has been palpablealthough it had remained in the background. The justification of Anthropic. “Claude Code It has become the preferred option of programmers everywhere, so we were not surprised to know that Openai’s technical staff were also using our programming tools before the launch of GPT-5“said Christopher Nulty, spokesman for Anthropic. The company considers that this constitutes a direct violation of its commercial terms, which expressly prohibit using the service to” build a competitive product or service “or” make reverse engineering. “ Openai’s response. Sam Altman’s company He has defended its practices as “standard in the industry” to evaluate other AI systems and improve security. “Although we respect Anthropic’s decision to cut our access to the API, it is disappointing considering that our API is still available for them,” said Hannah Wong, director of communications of OpenAI. Between the lines. What we see now is the materialization of a cold war that has been being taken for years. Anthropic has positioned Claude as the “safer and more ethical” alternative against Chatgpt, while Openai has maintained his leadership for mass adoption and general abilities. This rivalry is not only business: it is also philosophical, with very different approaches on how to develop and market the AI. In addition, the blockade of the API is not an isolated case in the technological sector. As They mention In Wired, Facebook also blocked Vine In his day and Salesforce He recently limited access to competitors. What is clear is that this reflects how competition in AI is becoming more aggressive and territorial. Important nuances. Despite the blockade, Anthropic has clarified that will maintain OpenAi access “for benchmarking purposes and security evaluations”, a practice considered standard in the industry. However, the company has not specified how this current restriction will affect these activities. And now what. This climb arrives at the worst possible time for OpenAi, especially considering that we would be officially knowing GPT-5, which promises significant programming improvements. Therefore, everything indicates that Anthropic is willing to use all the tools at their disposal to stop the advance of its competitors. The worrying thing is that this could only be the beginning of a more open war between the Big Tech and the use of AI. In Xataka | The investment in AI already represents 2% of the US GDP. The problem is that it doesn’t even work well

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