Open-source AI search plugin Evoke: 30 million parameters, recall rate nearly matches that of a 600 million-parameter model.
56 minutes ago
Beating AI News Brief: Intelligent Internet, the new venture of Stability AI co-founder Emad Mostaque, has open-sourced Evoke, a PostgreSQL database search plugin with a built-in AI model of roughly 30.3 million parameters. Once installed, developers can directly search documents and knowledge bases within the database, supporting both keyword matching and semantic similarity searches. Built on IBM’s Granite-Embedding-30M-Sparse model, Evoke generates a set of weighted relevant terms for documents, enabling retrieval of matching content even if the search query does not appear in the original text. Keyword and semantic information share a single search index, eliminating the need for separate vector index maintenance. The model runs natively on standard CPUs, requires no GPU, and does not involve sending data to external AI services. Official English retrieval tests previously released show Evoke achieves a 66.7% relevant document retrieval rate in its top 100 results, outperforming traditional keyword search (56.3%) and nearly matching the 67.1% rate of a 600-million-parameter model. Evoke’s code and model are both open-sourced under the Apache-2.0 license, making it suitable for use cases including internal enterprise document retrieval and AI Agent knowledge bases.
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