Conversational Search Redefined

Google announced an upgrade to AI Mode that makes image search feel like a conversation with a friend. Instead of relying on traditional filters such as color, size, or brand, users can simply describe the visual style or product they seek. Phrases like “barrel jeans that aren’t too baggy” or “show me acid‑washed denim” trigger a set of rich visual results that match the described vibe.

Dynamic Refinement and Mixed Inputs

The new system lets users continuously refine results. After an initial set appears, a follow‑up request such as “I want more ankle length” narrows the selection further. Users can also start a search by uploading a reference image or snapping a photo, then follow up with textual cues to hone in on similar items. This hybrid approach of images plus descriptions enables more nuanced queries.

Built on Gemini 2.5 Multimodal AI

Google says the upgrade builds on the Gemini 2.5 model, combining advanced language understanding with visual perception. The AI can recognize subtle details and secondary objects within images, allowing it to grasp context and deliver more precise visual matches. The technology ties into existing Google Search, Lens, and Image Search infrastructure, extending their capabilities with conversational nuance.

Rollout Details

The conversational image search feature is rolling out in English to users in the United States. Availability may vary as the update propagates, and Google notes that it could take a few days for the new capabilities to appear for all users. The upgrade is presented as part of AI Mode, a suite of AI‑driven search experiences currently available on Google’s platforms.

Implications for Shoppers and Creators

For shoppers, the update promises a faster path to discovery and purchase, delivering shoppable options directly within search results. For creators and designers, the ability to find visual inspiration through natural language and mixed inputs streamlines the research process. Google positions the feature as a step toward more intuitive, human‑like interaction with its search ecosystem.

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