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.

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.

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.

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.

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.

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.