Weaviate 1.23 Release Podcast with Etienne Dilocker!

Weaviate Podcast

Hey everyone! Thank you so much for watching the Weaviate 1.23 Release Podcast with Weaviate Co-Founder and CTO Etienne Dilocker! Weaviate 1.23 is a massive step forward for managing multi-tenancy with vector databases. For most RAG and Vector DB applications, you will have an uneven distribution in the # of vectors per user. Some users have 10k docs, others 10M+! Weaviate now offers a flat index with binary quantization to efficiently balance when you need an HNSW graph for the 10M doc users and when brute force is all you need for the 10k doc users! Weaviate also comes with some other "self-driving database" features like lazy shard loading for faster startup times with multi-tenancy and automatic resource limiting with the GOMEMLIMIT and other details Etienne shares in the podcast! I am also beyond excited to present our new integration with Anyscale (@anyscalecompute)! Anyscale has amazing pricing for serving and fine-tuning popular open-source LLMs. At the time of this release we are now integrating the Llama 70B/13B/7B, Mistral 7B, and Code Llama 34B into Weaviate -- but we expect much further development with adding support for fine-tuned models, the super cool new function calling models Anyscale announced yesterday. and other model such as Diffusion and multimodal models! Chapters 0:00 Weaviate 1.23 1:08 Lazy Shard Loading 8:20 Flat Index + BQ 33:15 Default Segments for PQ 38:55 AutoPQ 42:20 Auto Resource Limiting 46:04 Node Endpoint Update 47:25 Generative Anyscale Links: Etienne Dilocker on Native Multi-Tenancy at the AI Conference in SF: https://www.youtube.com/watch?v=KT2RFMTJKGs Etienne Dilocker in the CMU DB Series: https://www.youtube.com/watch?v=4sLJapXEPd4 Self-Driving Databases by Andy Pavlo: https://www.cs.cmu.edu/~pavlo/blog/2018/04/what-is-a-self-driving-database-management-system.html