So, data is converted into vectors. But how does a vector database find the *most similar* ones instantly, even with millions of entries? Welcome to Part 2!
We're diving into the technical guts of vector databases, covering the essential processes that make them so fast and efficient. Perfect for CS grads who want to understand the 'how' behind the 'what'.
🔗 **DON'T MISS THE REST OF THE SERIES:**
Part 1: What Are Vector Databases? → https://youtu.be/1sILNMF_jbE
Part 2: How Vector Databases Work? → https://youtu.be/pxzJu6LVD78
Part 3: Real-World Use Cases → https://youtu.be/ESOXljWvXHw]
Part 4: Vector vs. Traditional DBs → https://youtu.be/gW0GSh7zbMU
Part 5: Getting Started with Vector Databases → https://youtu.be/yc7Cr4WmDQs
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