Résultats de recherche pour : multimodal

Posted by Jolanda Verhoef, Senior Developer Relations Engineer, Android Developer Relations Building GenAI features in your app usually means navigating through various models, APIs and architecture choices:  Execution location: Where does your model run? On device, in the cloud, or both? Complexity: How complex is your setup? Are you doing a single inference call or do […]

Google DeepMind’s Gemma 4 12B model brings agentic, multimodal AI capabilities to everyday laptops with 16GB of RAM, enabling local data processing and visual insight generation. Users can leverage this model on macOS through the Google AI Edge Gallery for dynamic Python code execution and visualization, as well as via Google AI Edge Eloquent for

The newly released Gemma 4 12B is a dense, multimodal model designed for high-performance local AI execution on consumer devices. By introducing a novel, encoder-free architecture, it bypasses traditional visual and audio encoders to feed multimodal data directly into the LLM backbone.

We’re introducing new multimodal capabilities into Google Ads’ Asset Studio — your creative destination to create, build and test your assets.

Posted by Luke Hopkins, Android Developer Relations Engineer for OpenXR & Ryan Bartley, Android XR Product Manager Today, we are excited to announce that official support for Unreal Engine and Godot has arrived for Android XR. Alongside these engine expansions, we are also launching new tools designed to boost your productivity and enable new XR

Posted by Matt Dyor, Senior Product Manager Android Studio Panda 4 is now stable and ready for you to use in production. This release brings Planning Mode, Next Edit Prediction, and more, making it easier than ever to build high-quality Android apps. Here’s a deep dive into what’s new: Planning Mode Before the Agent starts

The Google Cloud AI Agent Bake-Off highlights a shift from simple prompt engineering to rigorous agentic engineering, emphasizing that production-ready AI requires a modular, multi-agent architecture. The post outlines five key developer tips, including decomposing complex tasks into specialized sub-agents and using deterministic code for execution to prevent probabilistic errors. Furthermore, it advises developers to

Posted by David Chou, Product Manager and Caren Chang, Developer Relations Engineer At Google, we’re committed to bringing the most capable AI models directly to the Android devices in your pocket. Today, we’re thrilled to announce the release of our latest state-of-the-art open model: Gemma 4. These models are the foundation for the next generation

The provided workflow streamlines motion-controlled game development by using Gemini Canvas to rapidly prototype mechanics like the MediaPipe Pose Landmarker through high-level prompting. Developers can refine these prototypes in Google AI Studio by optimizing for low-latency « lite » models and stable tracking points, such as shoulder landmarks, to ensure responsive gameplay. The process concludes by using

European Commission Communiqué de presse Brussels, 16 Mar 2026 La Commission européenne a adopté aujourd’hui les lignes directrices relatives aux aides d’État au transport terrestre et multimodal (les «lignes directrices su…