Hub Artificial Intelligence

Artificial intelligence is either a field of research, the most important technical innovation of mankind, its downfall – or simply a pipe dream from Silicon Valley. Can machines really be intelligent? What is intelligence anyway? What opportunities does AI technology offer, and what are the risks? From neural networks to the science fiction vision of super AI, from deepfakes to AI surveillance: THE DECODER delivers the latest AI news and information on all facets of artificial intelligence.

Artificial Intelligence

OpenAI launches new ChatGPT agent that automates complex tasks for Pro, Plus, and Team

Artificial Intelligence

OpenAI launches GPT-5 as a unified system with adaptive reasoning for complex tasks

Artificial Intelligence

OpenAI releases its first open-weight language models since GPT-2 with GPT-oss

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Anthropic is ramping up its European operations, opening new offices in Paris and Munich to build on its presence in the region. These locations join existing hubs in London, Dublin, and Zurich, and will act as regional centers for sales, partnerships, and policy engagement.

The company says the EMEA market is its fastest-growing segment, with sales jumping more than ninefold over the past year. To support this growth, Anthropic is putting together a dedicated leadership team for Europe, naming Pip White to lead Northern Europe and Thomas Remy for Southern Europe.

Anthropic now operates twelve offices worldwide. In Europe, major customers like BMW, SAP, Sanofi, and Doctolib are already using the Claude AI model for software development, network management, and other tasks. Anthropic is also working with organizations such as TUM.ai and Unaite.

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Google has added a File Search Tool to the Gemini API, allowing developers to query their own documents using a vector database. The tool manages storing files, splitting them up, searching for relevant content, and inserting that information into Gemini's responses. Supported file types include PDF, DOCX, TXT, and JSON. The tool is free to use, except for a small fee when indexing data ($0.15 per million tokens). Source references are included automatically in the responses.

Google says the main use cases are internal search systems and chatbots that need to answer questions based on specific company documents. Developers can find more information in the documentation or test out the demo in Google AI Studio.

Artificial Intelligence
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Nvidia turns to synthetic data to tackle robotics’ biggest challenge: the lack of training data.

"We call this the big data gap in robotics," a Nvidia researcher said at the Physical AI and Robotics Day during GTC Washington. While large language models train on trillions of internet tokens, robot models like Nvidia’s GR00T have access to only a few million hours of teleoperation data, gathered through complex manual effort - and most of it is narrowly task-specific.

Nvidia’s answer is to rethink what it calls the "data pyramid for robotics." At the top sit real-world data - small in quantity and expensive to collect. In the middle lies synthetic data from simulation - theoretically limitless. At the base is unstructured web data. "When synthetic data surpasses the web-scale data, that's when robots can truly learn to become generalized for every task," the team states. With Cosmos and Isaac Sim, Nvidia aims to turn robotics’ data shortage into a compute challenge instead.

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Meta is bringing its AI video feed Vibes to Europe through the Meta AI app. Every clip on Vibes is generated by artificial intelligence - users can create short videos from text prompts, remix existing ones, add music, and adjust the visual style. Over time, the feed learns what users like and tailors its suggestions accordingly. Finished clips can be shared directly in the app or posted to Instagram and Facebook.

Vibes first launched in the U.S. in September 2025. The Meta AI app also includes the company’s AI assistant, plus tools for image editing and managing Meta’s AI glasses. By comparison, OpenAI has separated its own AI video experience into the standalone Sora app, which isn’t yet available in the EU.

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Google's new TPU v7 Ironwood chips are now general available for training and running large AI models. According to Google, Ironwood delivers ten times the peak performance of the previous TPU v5p and is four times more efficient than the TPU v6e. Early adopters like Anthropic, Lightricks, and Essential AI are already using Ironwood for demanding AI workloads. Amin Vahdat, VP and GM for AI Infrastructure at Google, recently said every TPU Google has built so far is currently in use.

Alongside Ironwood, Google is introducing Axion, a new line of Arm-based virtual machines aimed at everyday computing tasks. Vimeo and ZoomInfo report that Axion N4A instances deliver up to 60 percent better price-performance than comparable x86 systems. With both Ironwood and Axion, Google is challenging competitors like Nvidia and working to offer more flexible AI infrastructure with better cost efficiency, especially for serving its own AI products like Gemini.

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AI and society
Comment

OpenAI and Microsoft call AGI pointless, then make it the linchpin of billion-dollar deals

AI in practice

Google leans on token metrics, not revenue, adding to bubble talk about AI growth

AI and society

OpenAI restructures under new foundation, Microsoft takes 27 percent stake

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