Objective: To improve the overall transparency of the grant awarding process, AI can be leveraged to allow non-technical users to ask questions about the funded grants in the Arbitrum eco-system
Data: Data on each Arbitrum grantee as stored in the Karma platform
Methodology: The data could be exported as a .csv, converted into a database, vectorized and then stored in a vector db that's chained to an AI such as Chat-GPT. A wrapper interface could then be built to allow users to "chat" with the dataset.
Deliverable: A front end that allows users to ask questions about projects funded by the DAO.
Objective: To improve the overall transparency of the grant awarding process, AI can be leveraged to allow non-technical users to ask questions about the funded grants in the Arbitrum eco-system
Data: Data on each Arbitrum grantee as stored in the Karma platform
Methodology: The data could be exported as a .csv, converted into a database, vectorized and then stored in a vector db that's chained to an AI such as Chat-GPT. A wrapper interface could then be built to allow users to "chat" with the dataset.
Deliverable: A front end that allows users to ask questions about projects funded by the DAO.