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edgeml-recommender
POC: similarity search recommendation engine at the edge using only Fastly Compute & Rust
Simple enough to transform that into two columns, an ID and a string:
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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Now we have 500 small datasets and an index that maps centroid points to the relevant dataset. Next, to enable real-time performance, we want to precompile search graphs so that we don't need to initialize and construct them at runtime, and can use as little CPU time as possible. A really fast nearest-neighbor algorithm is Hierarchical Navigable Small Worlds (HNSW), and it has a pure Rust implementation, which we're using to write our edge app. So we wrote a small standalone Rust app to construct the HNSW graph structs for each dataset, and then used bincode to export the memory of the instantiated struct into a binary blob.
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Now we have 500 small datasets and an index that maps centroid points to the relevant dataset. Next, to enable real-time performance, we want to precompile search graphs so that we don't need to initialize and construct them at runtime, and can use as little CPU time as possible. A really fast nearest-neighbor algorithm is Hierarchical Navigable Small Worlds (HNSW), and it has a pure Rust implementation, which we're using to write our edge app. So we wrote a small standalone Rust app to construct the HNSW graph structs for each dataset, and then used bincode to export the memory of the instantiated struct into a binary blob.