Tag: Google

Google Home is enabling new Gemini-powered features for our partners’ devices and launching a new program to help them build the next generation of AI cameras.

Colab is back with a few new and exciting features meant to simplify and enhance your notebook-based...

Today, we’re launching three big Veo updates: support for vertical format outputs (9:16 aspect ratio...

JAX, a framework known for large-scale AI model development, is proving to be a powerful tool in scientific computing, particularly for solving complex Partial Differential Equations (PDEs), now being leveraged by researchers to achieve significant speed-ups and memory reductions in solving high-order PDEs and demonstrating its potential to unlock new frontiers in scientific discovery.

We are launching 1.0 stable release of Genkit Go, empowering Go developers to build performant, production-ready AI-powered applications with Genkit. Recent enhancements include support for integrating and building MCP tools, expanding third-party model provider support, and production AI monitoring with Firebase. Additionally, we are announcing a new feature in the Genkit CLI to provide AI development tools, like the Gemini CLI and Cursor, with the latest knowledge of Genkit - supercharging Genkit development experience when using AI assistance.

A2A Extensions provide a flexible way to add custom functionalities to agent-to-agent communication, going beyond the core A2A protocol. They enable specialized features and are openly defined and implemented.

Batch API now supports Embeddings and OpenAI CompatibilityToday we are extending the Gemini Batch AP...

The recent 0.2.0 release of Google’s Agent Development Kit (ADK) for Java adds an integration with t...

Gemini CLI now seamlessly integrates with FastMCP, Python's leading library for building MCP servers. We’re thrilled to announce this integration between two open-source projects that empowers you to effortlessly connect your custom MCP tools and prompts, directly to Gemini CLI!

Data Commons announces the availability of its MCP Server, which is a major milestone in making all of Data Commons’ vast public datasets instantly accessible and actionable for AI developers worldwide.