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.

Vertex AI RAG Engine, a managed orchestration service, streamlines the process of retrieving and feeding relevant information to Large Language Models. This enables developers to build robust, grounded generative AI apps that ensure responses are factually grounded.

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.

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.

The Gemini 2.0 model family is seeing significant updates, including the release of Gemini 2.0 Flash, which is now production-ready and boasts higher rate limits, enhanced performance, and simplified pricing. Developers can also start testing an updated experimental version of Gemini 2.0 Pro today. Additionally, a new variant called Gemini 2.0 Flash-Lite, specifically designed for large-scale workloads, will be made available next week.

The Google AI Developers Community Spotlight Contest is seeking innovative, diverse projects using Google's AI tools like Gemini and Gemma to create code repositories, videos, documentation, and more.

The Google Home APIs are now in public developer beta for Android, allowing developers to build innovative smart home experiences for over 600M devices using Google's hubs, Matter infrastructure, and automation engine.

The public beta launch of Home APIs for Android allows developers to create better smart home experiences. This launch emphasizes investments in Matter to improve device connectivity and interoperability, and increase smart home accessibility.

Learn how to build a visual search tool using Google's Multimodal Embeddings API and explore how to apply this technology for searching images, slides, and more.

The Multimodal Live API for Gemini 2.0 enables real-time multimodal interactions between humans and computers, and can be used to build real-time virtual assistants and adaptive educational tools.

AI Singapore and INSAIT teams have leveraged Gemma, a family of open-source language models, to create LLMs tailored to the unique needs of their communities, in a show of innovation and inclusivity in AI.

Explore innovative projects from the Gemini API Competition, like Omni, EcoTrack, ITMZ, Jana AI, Eagle AI, and AlphaFit, demonstrating the potential of the Gemini API to enhance productivity, promote sustainability, and improve well-being.

Explore three Gemini starter apps that provide developers with production ready tools to build AI-powered projects with open source functionalities like spatial analysis, and video interactions.

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.

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.

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.

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

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.

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.