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  • AUG. 18, 2025 / Gemini

    URL context tool for Gemini API now generally available

    The Gemini API's URL Context tool is now generally available, allowing developers to ground prompts using web content instead of manual uploads. This release expands support to PDFs and images.

    URL context tool for Gemini API now generally available
  • AUG. 15, 2025 / Google AI Studio

    Announcing Imagen 4 Fast and the general availability of the Imagen 4 family in the Gemini API

    Google announces the general availability of Imagen 4, its advanced text-to-image model, in the Gemini API and Google AI Studio, featuring significant improvements in text rendering. The new Imagen 4 Fast model, designed for speed and rapid image generation, is now available alongside Imagen 4 and Imagen 4 Ultra, with Imagen 4 and Imagen 4 Ultra also supporting up to 2K resolution image generation.

    Imagen 4 Fast and the generally availability of the Imagen 4 family in the Gemini API
  • AUG. 14, 2025 / Gemma

    Introducing Gemma 3 270M: The compact model for hyper-efficient AI

    Google's new Gemma 3 270M is a compact, 270-million parameter model offering energy efficiency, production-ready quantization, and strong instruction-following, making it a powerful solution for task-specific fine-tuning in on-device and research settings.

    Gemma 3 270M
  • AUG. 13, 2025 / Gemini

    Gemini CLI + VS Code: Native diffing and context-aware workflows

    The latest Gemini CLI update provides a deep IDE integration within VS Code for intelligent, context-aware suggestions, and native in-editor diffing, allowing developers to review and modify proposed changes directly within the diff view for a more efficient workflow.

    Gemini CLI + VS Code integration
  • AUG. 12, 2025 / Kaggle

    Train a GPT2 model with JAX on TPU for free

    Build and train a GPT2 model from scratch using JAX on Google TPUs, with a complete Python notebook for free-tier Colab or Kaggle. Learn how to define a hardware mesh, partition model parameters and input data for data parallelism, and optimize the model training process.

    Train a GPT2 model with JAX on TPU for free
  • AUG. 12, 2025 / Google Labs

    Meet Jules’ sharpest critic and most valuable ally

    Jules' critic functionality addresses potential issues like subtle bugs and missed edge cases in AI-generated code by acting as a peer reviewer within the generation process. This "critic-augmented generation" means proposed code changes undergo adversarial review, allowing Jules to improve its output and ultimately deliver higher-quality, pre-reviewed code.

    Jules critic agent
  • AUG. 1, 2025 / Cloud

    The Google Developer Program is evolving

    The Google Developer Program is rolling out major updates to make its tools and community more accessible and powerful. These enhancements include a new flexible monthly subscription tier, a centralized GDP Forum for collaboration, and increased Gemini CLI access for all members.

    The Google Developer Program is evolving: New ways to join, connect, and code
  • JULY 31, 2025 / AI

    Veo 3 Fast and new image-to-video capabilities

    Google introduces Veo 3 Fast, an optimized model for speed and price, along with new image-to-video capabilities for both Veo 3 and Veo 3 Fast, enabling developers to efficiently create high-quality video content from text or still images, with varying pricing based on the model and audio inclusion, now available in the Gemini API.

    Build with Veo 3 Fast and new image-to-video capabilities, now available in the Gemini API
  • JULY 30, 2025 / Gemini

    Introducing LangExtract: A Gemini powered information extraction library

    LangExtract is a new open-source Python library powered by Gemini models for extracting structured information from unstructured text, offering precise source grounding, reliable structured outputs using controlled generation, optimized long-context extraction, interactive visualization, and flexible LLM backend support.

    LangExtract_meta
  • 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