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Show HN: TurboQuant for vector search – 2-4 bit compression
Show HN: TurboQuant for vector search – 2-4 bit compression
TurboQuant targets a high-growth bottleneck in AI infrastructure by optimizing vector search memory usage, a critical need for scaling RAG and LLM applications. However, the project currently lacks institutional backing and faces intense competition from established vector database incumbents who are rapidly integrating similar quantization features.