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TopK introduces semantic_index, a single schema annotation that abstracts multi-vector retrieval complexity for production systems, achieving state-of-the-art performance with sub-second latency and high throughput.
SMART is a framework that unlocks latent multi-vector capabilities in single-vector models for multimodal retrieval, improving state-of-the-art performance with reduced computational costs via contrastive training and late-interaction inference.
OpenAI released text-embedding-ada-002, a unified embedding model that consolidates five previous models into one with superior performance, 4x longer context (8192 tokens), smaller dimensionality (1536), and 99.8% lower pricing than previous Davinci embeddings.