While previous embedding models were largely restricted to text, this new model natively integrates text, images, video, audio, and documents into a single numerical space — reducing latency by as muc ...

Google Gemini Embedding 2 unifies text, images, audio, PDFs, and video; it supports 3,072-dimension vectors, simplifying retrieval stacks.

Google has launched Gemini Embedding 2, its first natively multimodal embedding model supporting text, images, video, audio, ...

Video-text retrieval techniques endeavour to bridge the semantic gap between visual content and natural language descriptions. By learning joint representations for both video and text, these ...

Retrieval-Augmented Generation (RAG) systems have emerged as a powerful approach to significantly enhance the capabilities of language models. By seamlessly integrating document retrieval with text ...