Bob van Luijt on why a growing number of organizations use vector search engines.
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Bob van Luijt, is CEO of SeMI Technologies, the company behind the popular vector search engine Weaviate. Weaviate has integrations with OpenAI, Huggingface Inference, and very shortly for Cohere and other tools popular with developers. While vector databases are used for recommendation, anomaly detection, and Q&A systems, they primarily target search and information retrieval applications.
This episode is a great introduction to the growing importance of vector databases and vector search engines. Bob describes their key features and core components, popular use cases, and he also provides an overview of Weaviate’s near-term roadmap. We also discuss how vector search engines compare with existing data management systems.
Highlights in the video version:
- What are vector search engines and vector databases?
Why not just use a file system?
Data management features, including UX and ease of use
Vector databases in the context of other data management systems
Computing embeddings (vectorization)
Comparing their open source and proprietary offerings
Weaviate roadmap
Hybrid search
Specialized vs general data management systems
Related content:
- A video version of this conversation is available on our YouTube channel.
- Documentation (for developers to get started with Weaviate open source)
- The Vector Database Index
- Ram Sriharsha of Pinecone: A new storage engine for vectors
- Summer of Orchestration: conversations with co-creators of Prefect, Dagster, Flyte, and Orchest.
- New open source tools to unlock speech and audio data
- fastdup: Introducing a new free tool for curating image datasets at scale
- A Guide to Data Annotation and Synthetic Data Generation Tools
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[Image: What is a vector search engine?; by SeMI Technologies, used with permission.]