Master Vector Database with Python for AI & LLM Use Cases
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Scaling vector search is one of the biggest challenges for AI-driven applications. We tested MongoDB Atlas Vector Search with a 15.3 million vector dataset and found it retains 90-95% accuracy with less than 50ms of query latency. In our new blog post, we break down the methodology, key performance factors like quantization and dimensionality, and what the results mean for your own large-scale workloads. Learn how to optimize your deployment. Read the full analysis: https://mongodb.social/6186fQ
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