Google Cloud Dataflow's Managed I/O simplifies using Apache Beam I/O connectors by automatically updating connectors to the latest versions and providing a standardized API, optimizing connectors specifically for Dataflow, ensuring efficient performance and reducing the need for manual configuration, freeing users to focus on pipeline logic.

Google DeepMind releases TxGemma, built on Gemma, which predicts therapeutic properties, and Agentic-Tx, powered by Gemini 2.0 Pro, which tackles complex research problem-solving with advanced tools.

The Google I/O 2025 puzzle used the Gemini API to generate dynamic riddles for bonus worlds, enhancing player engagement and scalability. Here's what our developers learned on using the Gemini API effectively, including creativity, design, and implementation strategies.

Gemma 3 1B, a new small language model for mobile and web applications via Google AI Edge, is now available, with increased efficiency, improved performance, and offline availability.

Gemma 3 is a new, advanced version of the Gemma open-model family featuring multimodality, longer context windows, and improved language capabilities, with various sizes and deployment options for developers to experiment.

The experimental native image generation feature of Gemini 2.0 Flash – allowing for the combination of text and images, conversational image editing, and leveraging real-world knowledge for contextual visuals – is now available for developers to test through Google AI Studio and the Gemini API.

ShieldGemma 2, built on Gemma 3, is a 4 billion parameter model that can be used as an input filter for vision language models or an output filter for image generation systems, and is designed to respond to a wide range of diverse and nuanced imagery.

An enhancement to Google Cloud Dataflow templates for MongoDB Atlas enables direct integration of JSON data into BigQuery, eliminating complex data transformations, reducing operational costs, and enhancing query performance for users.

Google Cloud Next 2025, happening April 9-11 in Las Vegas, will feature expanded developer content, interactive experiences, and opportunities to connect with peers and Google experts.

A new experimental Gemini Embedding text model, now available in the Gemini API, achieves top rankings on the Massive Text Embedding Benchmark (MTEB) leaderboard and offers expanded language support and high-dimensional embeddings.

This blog post introduces Gemini's code execution feature, which allows the AI model to generate and run Python code for tasks like solving equations, data analysis, and creating visualizations.

CalCam, a calorie-tracking app, uses the Gemini API to analyze meal photos, providing users with fast and accurate nutritional information. Polyverse, CalCam's creator, highlights Gemini API's speed, accuracy, and structured JSON output are crucial for CalCam's seamless user experience and efficient development, allowing for easy integration and detailed food analysis.

The Data Science Agent in Google Colab, powered by Gemini, can now generate complete, working notebooks from simple natural language descriptions, so developers can automate data analysis tasks, saving time to focus on deriving insights.

Gemini 2.0 Flash-Lite is now generally available in the Gemini API for production use in Google AI Studio and for enterprise customers on Vertex AI. 2.0 Flash-Lite offers improved performance over 1.5 Flash across reasoning, multimodal, math and factuality benchmarks. For projects that require long context windows, 2.0 Flash-Lite is an even more cost-effective solution, with simplified pricing for prompts more than 128K tokens.

PaliGemma 2 mix, an upgraded vision-language model, is now available, offering capabilities like image captioning, OCR, and object detection in various sizes.

Updates to the Gemini API, including the production readiness of Veo 2 for video generation, the preview of the Live API for real-time interactions, and the upcoming Gemini 2.5 Flash model, alongside the existing Gemini 2.5 Pro aim to enhance developer capabilities in building AI applications with improved thinking models, dynamic interactions, and high-quality video generation.

The Agent Development Kit (ADK), an open-source framework from Google designed to simplify the development of multi-agent systems, providing tools for building, interacting, evaluating, and deploying agents.

The Google Developer Program is evolving with AI-powered tools like Gemini Code Assist and expanded resources, including new Premium and Enterprise offerings, access to product previews, and increased workspace capacity, making it easier for developers to build and innovate.

Agent2Agent (A2A) protocol is an open standard designed to enable AI agents from different vendors and frameworks to collaborate and exchange information across enterprise platforms aiming to foster a future of seamless AI agent interoperability and enhanced automation.

The Gemini API and ESP32 microcontroller simplify custom voice commands for IoT devices, leveraging speech recognition for devices to understand and react to custom commands, bridging the gap between digital and physical worlds.