Pinecone offers a number of best practice tips for making the most of your use of the system. We’ve collected some of them here for your convenience.
The choice of vector embeddings depends on your specific application. For text-based applications, embeddings like BERT or GPT can be effective. For images, CNN-based embeddings might be better. It’s crucial to experiment with different embeddings to find the one that offers the best performance for your needs.
This guidance applies to pod-based indexes only. With serverless indexes, you don’t configure any compute or storage resources, and you don’t manually manage those resources to meet demand, save on cost, or ensure high availability. Instead, serverless indexes scale automatically based on usage.
Pinecone offers a number of best practice tips for making the most of your use of the system. We’ve collected some of them here for your convenience.
The choice of vector embeddings depends on your specific application. For text-based applications, embeddings like BERT or GPT can be effective. For images, CNN-based embeddings might be better. It’s crucial to experiment with different embeddings to find the one that offers the best performance for your needs.
This guidance applies to pod-based indexes only. With serverless indexes, you don’t configure any compute or storage resources, and you don’t manually manage those resources to meet demand, save on cost, or ensure high availability. Instead, serverless indexes scale automatically based on usage.