Search for "agentic systems"

53 results

Clear filters
  • OCT. 15, 2025 / AI

    Say hello to a new level of interactivity in Gemini CLI

    We're excited to announce an enhancement to Gemini CLI that makes your workflow more powerful a...

    Gemini CLI - Interactive Shell hero image
  • SEPT. 26, 2025 / AI

    Delight users by combining ADK Agents with Fancy Frontends using AG-UI

    The ADK and AG-UI integration enables developers to build interactive AI applications by combining a powerful backend (ADK) with a flexible frontend protocol (AG-UI). This unlocks features like Generative UI, Shared State, Human-in-the-Loop, and Frontend Tools, allowing for seamless collaboration between AI and human users.

    Screens-2-banner
  • SEPT. 25, 2025 / AI

    Continuing to bring you our latest models, with an improved Gemini 2.5 Flash and Flash-Lite release

    Google is releasing updated Gemini 2.5 Flash and Flash-Lite preview models with improved quality, speed, and efficiency. These releases introduce a "-latest" alias for easy access to the newest versions, allowing developers to test and provide feedback to shape future stable releases.

    Rev21Flash_Metadatal_RD2-V01
  • SEPT. 25, 2025 / AI

    Building the Next Generation of Physical Agents with Gemini Robotics-ER 1.5

    Gemini Robotics-ER 1.5, now available to developers, is a state-of-the-art embodied reasoning model for robots. It excels in visual, spatial understanding, task planning, and progress estimation, allowing robots to perform complex, multi-step tasks.

    Robotics-ER 1.5_Metadatal_RD6-V01
  • SEPT. 24, 2025 / AI

    Introducing the Data Commons Model Context Protocol (MCP) Server: Streamlining Public Data Access for AI Developers

    Data Commons announces the availability of its MCP Server, which is a major milestone in making all of Data Commons’ vast public datasets instantly accessible and actionable for AI developers worldwide.

    BLOG-HERO-A2
  • SEPT. 22, 2025 / AI

    Gemini CLI 🤝 FastMCP: Simplifying MCP server development

    Gemini CLI now seamlessly integrates with FastMCP, Python's leading library for building MCP servers. We’re thrilled to announce this integration between two open-source projects that empowers you to effortlessly connect your custom MCP tools and prompts, directly to Gemini CLI!

    Gemini CLI - FastMCP metadata image
  • SEPT. 9, 2025 / AI

    A2A Extensions: Empowering Custom Agent Functionality

    A2A Extensions provide a flexible way to add custom functionalities to agent-to-agent communication, going beyond the core A2A protocol. They enable specialized features and are openly defined and implemented.

    GfD_evergreen_meta
  • SEPT. 4, 2025 / Gemma

    Introducing EmbeddingGemma: The Best-in-Class Open Model for On-Device Embeddings

    Introducing EmbeddingGemma: a new embedding model designed for efficient on-device AI applications from Google. This open model is the highest-ranking text-only multilingual embedding model under 500M parameters on the MTEB benchmark, enabling powerful features like RAG and semantic search directly on mobile devices without an internet connection.

    EmbeddingGemma_Metadata
  • AUG. 27, 2025 / Gemini

    Beyond the terminal: Gemini CLI comes to Zed

    Google and Zed have partnered to integrate Gemini CLI directly into the Zed code editor, bringing AI capabilities directly into the editor for developers and allowing for faster and more focused coding, enabling tasks like in-place code generation, instant answers, and natural chat within the terminal with a seamless review workflow for AI-generated changes.

    Gemini CLI is now integrated into Zed, bringing AI directly to your code editor
  • JULY 30, 2025 / Gemini

    Gemini Embedding: Powering RAG and context engineering

    The Gemini Embedding model enhances AI applications, particularly through context engineering, which is being successfully adopted by various organizations across industries to power context-aware systems, leading to significant improvements in performance, accuracy, and efficiency.

    Gemini Embedding: Powering RAG and context engineering