11. Lucy built a source-of-truth retrieval layer over 2.8M+ SEC and Korea DART filings. Four hybrid lan... Lucy built a source-of-truth retrieval layer over 2.8M+ SEC and Korea DART filings. Four hybrid lanes on Qdrant, payload filters applied inside the query, not after it. 94.7% Recal 10/03 18:18 ♡
12. / /5 Constella is still a research preview, so there’s plenty more to explore around the quality/late... /5 Constella is still a research preview, so there’s plenty more to explore around the quality/latency trade-offs and real-world workloads. qdrant.tech/blog/constella… 💬 0 09/29 13:52 ♡
13. /4 Nano and Zero are specifically trained to produce vectors compatible with Stella’s document embe... /4 Nano and Zero are specifically trained to produce vectors compatible with Stella’s document embeddings. So you can switch between them depending on the trade-off you want betwee 09/29 13:51 ♡
14. / /3 Constella takes a different approach here: Documents → Stella → document vectors → Qdrant The... /3 Constella takes a different approach here: Documents → Stella → document vectors → Qdrant Then, for queries, you can use different models: Query → Stella / Nano / Zero → query v 09/29 13:51 ♡
15. / /2 Normally, your documents are embedded with a model and stored as vectors in Qdrant. When a user s... /2 Normally, your documents are embedded with a model and stored as vectors in Qdrant. When a user searches, the query needs to be converted into a vector in the same vector space 09/29 13:50 ♡
16. What if you could change your query embedding model without re-embedding all your documents? That’s... What if you could change your query embedding model without re-embedding all your documents? That’s the idea behind Constella, a research preview from Qdrant. 💬 10 🔄 09/29 13:50 ♡
17. T Thank you to the team at @BetterStackHQ for this video! Thank you to the team at @BetterStackHQ for this video! 💬 0 🔄 0 ❤️ 3 👀 190 📊 1 ⚡ Powered by xgo.ing 09/25 23:04 ♡
18. R Recently, we released an open-source embedding generation tool, Supernova, with a 10B dataset (Qdran... Recently, we released an open-source embedding generation tool, Supernova, with a 10B dataset (Qdrant-FineWeb-10B) for free on @huggingface . These resources are excellent for eval 09/25 23:03 ♡
19. N New course Launch: Building AI Assistants with On-Device Memory We’re excited to announce Building ... New course Launch: Building AI Assistants with On-Device Memory We’re excited to announce Building AI Assistants with On-Device Memory, a new course built in partnership with @Deep 09/24 23:51 ♡
20. 4 400K+ document vectors, migrated from Milvus to Qdrant. The team at Kaivid Labs recently migrated t... 400K+ document vectors, migrated from Milvus to Qdrant. The team at Kaivid Labs recently migrated their vector database from Milvus to Qdrant and documented the entire process. The 09/24 17:36 ♡
