31. We just released Qdrant 1.19.1, a patch release with some serious performance improvements under the... We just released Qdrant 1.19.1, a patch release with some serious performance improvements under the hood. Quantized HNSW search is now ~1.5–2.5× faster, and payload-heavy shard tr 09/05 00:47 ♡
32. @ @huggingface 7/ Compute from @Vultr. Distribution with @skypilot_org. Corpus and hosting from @huggi... @huggingface 7/ Compute from @Vultr . Distribution with @skypilot_org . Corpus and hosting from @huggingface . The era of 1M-vector datasets and synthetic approximations is over. R 09/01 21:09 ♡
33. 6 6/ Supernova, the open-source engine that we used, is fully open source and free. Four phases: embe... 6/ Supernova, the open-source engine that we used, is fully open source and free. Four phases: embedding generation, GPU-native brute-force ground truth, cluster loading, evaluatio 09/01 21:09 ♡
34. @ @huggingface 5/ Two companion datasets ship alongside it: PubMed-Multi-Vector: dense, sparse, and C... @huggingface 5/ Two companion datasets ship alongside it: PubMed-Multi-Vector: dense, sparse, and ColBERT-style multi-vector over one corpus. 8.37B multi-vector tokens. Coyo-Vector 09/01 21:08 ♡
35. @ @huggingface 4/ The 120,000 queries cover dense, sparse, and filtered search, so you can measure wha... @huggingface 4/ The 120,000 queries cover dense, sparse, and filtered search, so you can measure what production runs: deep retrieval and filters against exact answers, not 90% rec 09/01 21:08 ♡
36. @ @huggingface 3/ Qdrant-FineWeb-10B, the largest open-source vector search benchmark dataset, is live... @huggingface 3/ Qdrant-FineWeb-10B, the largest open-source vector search benchmark dataset, is live on Hugging Face: 10B FineWeb documents Dense + sparse vectors from gte-multilin 09/01 21:08 ♡
37. @ @huggingface 2/ Why was this unsolved? Exact ground truth at billion scale means comparing every que... @huggingface 2/ Why was this unsolved? Exact ground truth at billion scale means comparing every query against every vector. At 10B documents, over a quadrillion distance computati 09/01 21:07 ♡
38. 1 1/ Production vector search: billions of vectors, thousands of RPS, tight tail latency. Public bench... 1/ Production vector search: billions of vectors, thousands of RPS, tight tail latency. Public benchmarks don't come close. So we built what was missing and gave it away. Write 09/01 21:07 ♡
39. V Vector Space Stream - September 17 - Virtual Register: https://t.co/qlSQ3Tdtlo Vector Space Stream - September 17 - Virtual Register: luma.com/vector-space-s… 💬 0 🔄 0 ❤️ 1 👀 114 ⚡ Powered by xgo.ing 09/01 01:47 ♡
40. ( (6/7) And there’s a session on hybrid search tuning. The work benchmarks a hybrid pipeline across 5... (6/7) And there’s a session on hybrid search tuning. The work benchmarks a hybrid pipeline across 5 datasets to understand which tuning parameters actually move retrieval quality. 09/01 01:46 ♡
