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  • JULY 23, 2025 / Firebase

    Unleashing new AI capabilities for popular frameworks in Firebase Studio

    New AI capabilities for popular frameworks in Firebase Studio include AI-optimized templates, streamlined integration with Firebase backend services, and the ability to fork workspaces for experimentation and collaboration, making AI-assisted app development more intuitive and faster for developers worldwide.

    Unleashing new AI capabilities for popular frameworks in Firebase Studio
  • JULY 22, 2025 / Gemini

    Gemini 2.5 Flash-Lite is now stable and generally available

    Gemini 2.5 Flash-Lite, previously in preview, is now stable and generally available. This cost-efficient model is ~1.5x faster than 2.0 Flash-Lite and 2.0 Flash, offers high quality, and includes 2.5 family features like a 1 million-token context window and multimodality.

    Gemini 2.5 Flash is making it easy to build with the Gemini API in Google AI Studio
  • JULY 21, 2025 / Gemini

    Conversational image segmentation with Gemini 2.5

    Gemini's advanced capability for conversational image segmentation allows intuitive interaction with visual data by understanding complex phrases, conditional logic, and abstract concepts, streamlining developer experience and opening doors for new applications in media editing, safety monitoring, and damage assessment.

    Conversational image segmentation with Gemini 2.5
  • JULY 17, 2025 / Gemini

    Build with Veo 3, now available in the Gemini API

    Veo 3, Google’s latest AI video generation model, is now available in paid preview via the Gemini API and Google AI Studio. Unveiled at Google I/O 2025, Veo 3 can generate both video and synchronized audio, including dialogue, background sounds, and even animal noises. This model delivers realistic visuals, natural lighting, and physics, with accurate lip syncing and sound that matches on-screen action.

    Build with Veo 3, now available in the Gemini API and Google AI Studio
  • JULY 16, 2025 / AI

    Unlock Gemini’s reasoning: A step-by-step guide to logprobs on Vertex AI

    The `logprobs` feature has been officially introduced in the Gemini API on Vertex AI, provides insight into the model's decision-making by showing probability scores for chosen and alternative tokens. This step-by-step guide will walk you through how to enable and interpret this feature and apply it to powerful use cases such as confident classification, dynamic autocomplete, and quantitative RAG evaluation.

    logprobs_meta
  • JULY 16, 2025 / Cloud

    Stanford’s Marin foundation model: The first fully open model developed using JAX

    The Marin project aims to expand the definition of 'open' in AI to include the entire scientific process, not just the model itself, by making the complete development journey accessible and reproducible. This effort, powered by the JAX framework and its Levanter tool, allows for deep scrutiny, trust in, and building upon foundation models, fostering a more transparent future for AI research.

    Stanford Marin project in JAX
  • JULY 16, 2025 / Gemini

    Simplify your Agent "vibe building" flow with ADK and Gemini CLI

    The updated Agent Development Kit (ADK) simplifies and accelerates the process of building AI agents by providing the CLI with a deep, cost-effective understanding of the ADK framework, allowing developers to quickly ideate, generate, test, and improve functional agents through conversational prompts, eliminating friction and keeping them in a productive "flow" state.

    ADK + Gemini CLI: Supercharge Your Agent Building Vibe
  • JULY 14, 2025 / Gemini

    Gemini Embedding now generally available in the Gemini API

    The Gemini Embedding text model is now generally available in the Gemini API and Vertex AI. This versatile model has consistently ranked #1 on the MTEB Multilingual leaderboard since its experimental launch in March, supports over 100 languages, has a 2048 maximum input token length, and is priced at $0.15 per 1M input tokens.

    Gemini Embedding now generally available in the Gemini API
  • JULY 10, 2025 / Gemini

    Announcing GenAI Processors: Build powerful and flexible Gemini applications

    GenAI Processors is a new open-source Python library from Google DeepMind designed to simplify the development of AI applications, especially those handling multimodal input and requiring real-time responsiveness, by providing a consistent "Processor" interface for all steps from input handling to model calls and output processing, for seamless chaining and concurrent execution.

    Announcing GenAI Processors: Streamline your Gemini application development
  • JULY 10, 2025 / Cloud

    Advancing agentic AI development with Firebase Studio

    Updates in Firebase Studio include new Agent modes, foundational support for the Model Context Protocol (MCP), and Gemini CLI integration, all designed to redefine AI-assisted development allow developers to create full-stack applications from a single prompt and integrate powerful AI capabilities directly into their workflow.

    Advancing agentic AI development with Firebase Studio