What new vector search features does Blackwell enable in Zilliz Cloud?
Blackwell enables Zilliz Cloud to support advanced features: GPU-accelerated reranking, complex scoring functions, and real-time embedding generation within vector search queries.
In-Query Reranking
Zilliz Cloud can rerank initial retrieval results using cross-encoder models at GPU speed. Queries retrieve top-1000 candidates via CAGRA, rerank to top-10 using neural models, and return in sub-millisecond. Traditional databases block on reranking; Blackwell makes it seamless.
Dynamic Scoring Functions
Scoring functions incorporating metadata (recency, authority, user preference) execute at GPU speed. Zilliz Cloud queries don't return raw similarity; they return intelligently-ranked results balancing multiple signals.
Streaming Embedding Generation
Zilliz Cloud accepts queries with raw text/images instead of pre-computed embeddings. On-the-fly embedding generation (using GPU) plus search execute atomically. Users simplify client code; Zilliz Cloud handles embedding-then-search internally.
Approximate k-NN with Guarantees
Blackwell's performance allows exact k-NN search where approximation algorithms would suffice. Zilliz Cloud can guarantee exact results (no false misses) while maintaining near-approximate search speeds. Quality improves without latency cost.