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  • FEB. 10, 2026 / AI

    Making Gemini CLI extensions easier to use

    To simplify the user experience and prevent startup failures, the Gemini CLI has introduced structured extension settings that eliminate the need for manual environment variable configuration. This update enables extensions to automatically prompt users for required details during installation and securely stores sensitive information, such as API keys, directly in the system keychain. Users can now easily manage and override these configurations globally or per project using the new Gemini extensions config command.

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  • FEB. 9, 2026 / AI

    Access public data insights faster: Data Commons MCP is now hosted on Google Cloud

    Data Commons has launched a free, hosted Model Context Protocol (MCP) service on Google Cloud Platform, eliminating the need for users to manage complex local server installations. This update simplifies connecting AI agents and the Gemini CLI to Data Commons, allowing Google to handle security, updates, and resource management while users query data natively.

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  • FEB. 4, 2026 / AI

    Introducing the Developer Knowledge API and MCP Server

    Google is launching the Developer Knowledge API and MCP Server in public preview. This new toolset provides a canonical, machine-readable way for AI assistants and agentic platforms to search and retrieve up-to-date documentation across Firebase, Google Cloud, Android, and more. By using the official MCP server, developers can connect tools directly to Google’s documentation corpus, ensuring that AI-generated code and guidance are based on authoritative, real-time context.

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  • FEB. 3, 2026 / AI

    Easy FunctionGemma finetuning with Tunix on Google TPUs

    Finetuning the FunctionGemma model is made fast and easy using the lightweight JAX-based Tunix library on Google TPUs, a process demonstrated here using LoRA for supervised finetuning. This approach delivers significant accuracy improvements with high TPU efficiency, culminating in a model ready for deployment.

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  • JAN. 29, 2026 / DeepMind

    Beyond the Chatbot: A Blueprint for Trustable AI

    At Thunderhill Raceway Park, a team of Google Developer Experts (GDEs) put a new "Trustable AI Framework" to the test. Here is how they used GCP, Gemini and Antigravity to turn high-velocity racing into a masterclass for agentic architecture.

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  • JAN. 28, 2026 / AI

    Tailor Gemini CLI to your workflow with hooks

    New Gemini CLI hooks (v0.26.0+) let you tailor the agentic loop. Add context, enforce policies, and block secrets with custom scripts that run at predefined points in your workflow.

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  • JAN. 28, 2026 / Mobile

    LiteRT: The Universal Framework for On-Device AI

    LiteRT, the evolution of TFLite, is now the universal framework for on-device AI. It delivers up to 1.4x faster GPU, new NPU support, and streamlined GenAI deployment for models like Gemma.

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  • JAN. 16, 2026 / AI

    A Guide to Fine-Tuning FunctionGemma

    FunctionGemma is a specialized AI model for function calling. This post explains why fine-tuning is key to resolving tool selection ambiguity (e.g., internal vs. Google search) and achieving ultra-specialization, transforming it into a strict, enterprise-compliant agent. A case study demonstrates the improved logic. It also introduces the "FunctionGemma Tuning Lab," a no-code demo on Hugging Face Spaces, which streamlines the entire fine-tuning process for developers.

    Train a GPT2 model with JAX on TPU for free
  • JAN. 11, 2026 / AI

    Under the Hood: Universal Commerce Protocol (UCP)

    The Universal Commerce Protocol (UCP) is a new, open-source standard for agentic commerce, co-developed by Google and industry leaders. It establishes a common, secure language to connect consumer surfaces (like Gemini and AI Mode in Search) with business backends, enabling seamless shopping from product discovery to purchase. UCP simplifies integration for businesses, supports various payment providers, and is designed to power the next generation of conversational commerce experiences.

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  • JAN. 5, 2026 / AI

    A Developer's Guide to Debugging JAX on Cloud TPUs: Essential Tools and Techniques

    A practical guide to debugging and profiling JAX on Cloud TPUs. It outlines core components (libtpu, JAX/jaxlib) and essential techniques. Tools covered include: Verbose Logging (via libtpu env vars), TPU Monitoring Library for performance metrics, tpu-info for real-time utilization, XLA HLO Dumps for compiler debugging, and the XProf suite for in-depth performance analysis.

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