From the course: Semantic Kernel in Action: Fundamentals
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Semantic Kernel memory
From the course: Semantic Kernel in Action: Fundamentals
Semantic Kernel memory
- (Narrator) We are going to delve into how to store and retain memories with semantic kernel, which is key to provide a way to an AI to store and receive sematic information in a meaningful way. As we mentioned, memory at this moment is experimental alpha being the main reason that the team wants to make them more generic, able to support a wider breadth of scenarios. This is also for providing better interoperability and is the creation of memory connectors. Memory connectors enable us to abstract the complications of a concrete vector database. So the main message here is that we will see next change in the following months for the better, but probably the changes will not be that big. First, to do that now, we will create the kernel as you know. After this, we will create the memory store, which is what connects us to the vector database. We will have a set of connector components in a near future that will enable us to connect to many different vector databases in a similar way…
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