embeddings

PostgreSQL vision token embedding overflow during ML training

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Problem – Vision Token Embedding Overflow During ML Training A machine‑learning pipeline extracts image embeddings (e.g., CLIP vision tokens) and stores each intermediate token vector in a PostgreSQL table while training. During a nightly training run the following symptoms were observed: Rapid disk consumption: storage grew from 200 GB to 1.2 TB within a few hours. PostgreSQL … Read more

Pinecone audio embeddings fail in air-gapped environment

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Problem Description In an air‑gapped deployment the audio‑embedding service that feeds vectors to Pinecone returns either an empty vector ([]) or a vector of length 0. Subsequent query calls to the Pinecone index fail with errors such as: Invalid vector length: expected 512, got 0 Empty query vector Vector dimension mismatch Symptoms observed in production … Read more