Tag: Google

Updates in Firebase Studio include new Agent modes, foundational support for the Model Context Protocol (MCP), and Gemini CLI integration, all designed to redefine AI-assisted development allow developers to create full-stack applications from a single prompt and integrate powerful AI capabilities directly into their workflow.

Developers adapt LLMs like Gemma for diverse languages and cultural contexts, demonstrating AI's potential to bridge global communication gaps by addressing challenges like translating ancient texts, localizing mathematical understanding, and enhancing cultural sensitivity in lyric translation.

The Magic Mirror project utilizes the Gemini API, including the Live API, Function Calling, and Grounding with Google Search, to create an interactive and dynamic experience, demonstrating the power of the Gemini models to generate visuals, tell stories, and provide real-time information through a familiar object.

Google Pay support within Android WebView is now available, starting with WebView version 137 and Play Services 25.18.30, allowing users to utilize the native Google Pay payment sheet within embedded web checkout processes.

Three developer-friendly MarTech solutions – sGTM Pantheon for data control, GA4 Dataform for data transformation, and FeedX for A/B testing shopping feeds – empower developers to leverage marketing data for insights, strategies, and better results.

Use a sandboxed iframe to implement Google Pay on checkout pages, which helps comply with PCI DSS v4 requirements by isolating scripts. Shopify successfully implemented this method and passed the PCI DSS v4 audit.

Google is releasing updates to its Gemini 2.5 model family, including the generally available and stable Gemini 2.5 Pro and Flash, and the new Gemini 2.5 Flash-Lite "thinking models" in preview, offering enhanced performance and accuracy, with Flash-Lite providing a lower-cost option.

Gemini Code Assist in Apigee API Management enhances API development with AI-assisted features like natural language API creation, AI-generated summaries, and iterative design, allowing seamless integration with your organization's existing API ecosystem and ensuring consistency, security, and reduced duplication, while offering enterprise-grade security and a streamlined development workflow.

Google, along with Amazon and Cisco, announces the formation of the Agent2Agent Foundation under the Linux Foundation, establishing A2A as an industry standard for AI agent interoperability, fostering a diverse ecosystem, ensuring neutral governance, and accelerating secure innovation in AI applications.

KerasHub enables users to mix and match model architectures and weights across different machine learning frameworks, allowing checkpoints from sources like Hugging Face Hub (including those created with PyTorch) to be loaded into Keras models for use with JAX, PyTorch, or TensorFlow. This flexibility means you can leverage a vast array of community fine-tuned models while maintaining full control over your chosen backend framework.