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1/2Gemini Embedding 2 maps text, images, video, audio, and documents into a single semantic space, allowing single-request processing of multimodal inputs. This improves performance for tasks like agentic RAG and visual search. (1/2)
2/2Supporting over 100 languages, it provides an efficient foundation for building complex AI agents, affecting workflows that rely on multimodal input processing and content moderation. (2/2)
⚡ Gemini Embedding 2 maps text, images, video, audio, and documents into a single semantic space, allowing single-request processing of multimodal inputs. This improves performance for tasks like agentic RAG and visual search.…
developers.googleblog.com/building-with-gemini-embedding-2
Gemini Embedding 2 maps text, images, video, audio, and documents into a single semantic space, allowing single-request processing of multimodal inputs. This improves performance for tasks like agentic RAG and visual search. Supporting over 100 languages, it provides an efficient foundation for building complex AI agents, affecting workflows that rely on multimodal input processing and content moderation.
Practical takeaway: review whether this affects current AI/mobile build, integration, or release workflows.
⚡ Building with Gemini Embedding 2: Agentic multimodal RAG and beyond
Building with Gemini Embedding 2: Agentic multimodal RAG and beyond
Gemini Embedding 2 maps text, images, video, audio, and documents into a single semantic space, allowing single-request processing of multimodal inputs. This improves performance for tasks like agentic RAG and visual search. Supporting over 100 languages, it provides an efficient foundation for building complex AI agents, affecting workflows that rely on multimodal input processing and content moderation.
#Gemini #Android #Kotlin #KMP #MobileDev #iOS
developers.googleblog.com/building-with-gemini-embedding-2