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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.

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.

Imagen 3 – now available in Google AI Studio and the Gemini API – offers developers state-of-the-art image generation with brighter, better-composed images in diverse styles, and simplified image generation through text prompts.

Google I/O returns May 20-21. Watch the livestreams for updates on Android, AI, web, and cloud. Registration is open on the Google I/O website.

A practical guide to constructing a Gemma 2-based Agentic AI system – a type of AI that can make its own decisions and use external tools to achieve goals – that can generate dynamic content for a fictional game world.

Langbase empowers developers to build and deploy powerful, scalable AI agents by leveraging the Google Gemini API, particularly Gemini 1.5 Flash, unlocking a new era of intelligent applications and streamlined workflows.

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

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.

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.

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.