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At the 2026 Google I/O conference, Google officially launched the "Gemini Spark" all-time online AI agent platform, aiming to redefine the standard for smart assistants through round-the-clock automated task processing capabilities. The product is powered by the next-generation Gemini 3.5 Flash model, with its core architecture running on Google Cloud virtual machines, ensuring that the agent can continue executing complex tasks such as writing emails, generating study guides, and monitoring subscription bills in the background even when the user's device is turned off.
Gemini Spark demonstrates strong ecosystem integration and cross-platform capabilities. In addition to deep integration with native workspace apps like Gmail, Docs, and Sheets, the platform also seamlessly connects with third-party applications such as Canva, OpenTable, and Instacart through the open standard "Model Context Protocol" (MCP). According to the roadmap, Gemini Spark will gain macOS local file interaction permissions this summer and plans to provide real-time task updates via a new "Android Halo" interface in the future. In terms of interaction, users can converse with Spark as they would with instant messaging software.
Regarding security, Google emphasized that Spark follows the "controlled execution" principle, requiring explicit user permission before performing high-risk operations such as making payments or sending emails. At the same time, Google has upgraded its AI-assisted coding tool Antigravity, launching a new desktop application for the management center, a command-line interface (CLI), and a software development kit (SDK) to empower developers to build custom AI agent ecosystems.
Gemini Spark is now available to trusted testers, and a beta version will be released next week to Google AI Ultra subscribers in the United States. As this product takes shape, Google is pushing artificial intelligence from a single logical prediction to an "action agent" stage with actual execution capabilities. This not only marks the acceleration of the Agentic AI era but also signals a fundamental transformation in the interaction logic between large models and operating systems.