This approach relies on having more context data as part of the overall generative AI system that recalls what the user has asked about before. These techniques may add further trips between the generative AI system? the vector data used? and the LLM? but the result should be a more accurate response that is sent back to the user.
One thing to consider is how all of these elements integrate together. run this infrastructure yourself? so that you can have full control and flexibility.
This can make it easier to respond to
Potential new developments or innovations? and it qatar whatsapp number data should also ensure that you are not locked into a specific provider. However? you will need to integrate and manage these components and dependencies? which is a technical overhead? particularly at scale.
Alternatively? you may want to rely on a single provider to manage the infrastructure. While this option might be simpler to get started? you will have to work at another organization’s pace and will be locked into their technology? which can be limiting..
A stack-based approach is a useful alternative. Look at the the approach depends on elements around RAG-like vector databases and integrations and decide how to integrate the different components together into one stack. You have the option to change those elements within the stack as needed with minimal impact on integrations. Working with a stack-based alb directory approach gives more flexibility around future growth and integration? but also reduces the management and integration overhead compared to running everything yourself.
Developing Generative AI with Your Data
Generative AI applications and services are only helpful to customers or users if they can leverage data in effective ways. To be effective? this data has to be available? usable? and up to date. Without preparation to cope with scale? generative AI will be relegated to simple tasks rather than automating tasks and more efficient processes.