Gemini Embedding 2 ships cross-modality retrieval with Matryoshka vectors, offering flexible dimensions for cost and accuracy tradeoffs.
In the realm of natural language processing (NLP), the concept of embeddings plays a pivotal role. It is a technique that converts words, sentences, or even entire documents into numerical vectors.
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 has launched Gemini Embedding 2, its first natively multimodal embedding model supporting text, images, video, audio, ...
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