The aim of the project is to optimise the performance of an AI language using specific data provided
by the Brain and Mind Centre (BMC) that consists of many case studies and academic papers. Using
this optimisation we aim to adapt the model to function as an AI expert on the topic of the Mental
Wealth Initiative that offers intelligent answers specifically based on the data that it has been presented
and prompted by.
In order to tackle this problem we have created a web app that is equipped with a chat function
that allows users to prompt it for answers based on their inputs. This will serve the user with a
conversational interface that they can seek information from relating to the Mental Wealth
Initiative.
This chat function is also paired with a chat history page that allows for its users to analyse and
rate replies they have received from the AI. The rating function allows users to further optimise the
replies from the AI and further improve it, creating an environment where the AI will always improve.
These features will ensure the improvement of the AI especially in conjunction with uploading new case
studies and academic papers that are provided to the AI. The integration of Pine Cone within our system
further boosts the optimisation of the AI allowing it to produce better replies. Pine Cone allows uploading
of contextual data to allow the AI to further understand questions and improve responses.