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What feature of vCore-based Azure Cosmos DB for MongoDB simplifies the building of AI-driven applications?
Flexible shard key implementation
Integrated Vector Search feature
Integrated Azure Monitor
Which method can you use to create a vCore-based Azure Cosmos DB for MongoDB cluster?
Direct database insertion without a cluster
Using the Azure portal
Manual configuration of each database node of the cluster
Why is native support for storing and searching vector embeddings important in vCore-based Azure Cosmos DB for MongoDB?
It enables efficient AI features like similarity search
It reduces the cost of storage significantly
To automate AI model training directly within the database
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