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  • Open Business and Artificial Intelligence Connectivity (OBAIC) borrows the concept from Open Database Connectivity (ODBC), which is an interface that makes it possible for applications to access data from a variety of database management systems (DBMSs). The aim of OBAIC is to define an interface allowing BI tools to access machine learning models from models and to run inferencing against those models on a variety of different AI platforms from a variety of AI platforms - “AI ODBC for BI” 
  • Through OBAIC, BI vendors can connect to any AI platform freely without concerning themselves with the underlying implementation, or how the AI platform trains the model or infers results. It's just like what we use for databases via ODBC - the caller doesn't need to concern about how the database stores the data or execute queries.
  • The committee has decided this standard will only define the REST APIs protocol of how AI and BI communicate. The design or the actual implementation of OBAIC, such as whether this should be Server VS Server-less VS Docker, will be left up to the implementing vendors. If this protocol grows to another open-sourced project, that team may provide such implementation guidance/example(s). 
  • There are 3 key aspects designed into this standard: 
    • BI - What specific call do I need this standard to provide so that I can better leverage any underlying AI/ML platform?
    • AI - What should the common denominator be for an AI platform that can provide support for this standard?
    • Data - Shall data be moved around in the communication between AI and BI (passed by value) or will the data remain in it's source location (passed by reference)?

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