MPAI has developed an approach to standards for AI-based data coding that relies on the identification of Use Cases. A Use Case can be implemented as an AI Workflow (AIW) composed of AI Modules (AIM) arranged with a specified topology. Technical Specification: AI Framework (MPAI-AIF) V2.1 specifies an environment that enables initialisation, execution, dynamic configuration, and control of AIWs. AIWs and AIMs perform certain functions on input data and produce output data both of specified data types. AIMs can be Composite when they are composed of other AIMs and are called Basic when they are not, or when the internal structure is not exposed.
MPAI has developed six Technical Specifications based on MPAI-AIF that include 20 AI Workflows, 120 AIMs, and 180 data types.
The level of sophistication of AIMs that are part of the AIWs varies considerably in terms of processing required, number and variety of data types involved, and number of interconnected AIMs.
MPAI has developed and is currently refining the notion of Perceptible and Agentive AI (PAAI), an AI System performing functions that MPAI has standardised in its Technical Specifications.
Technical Report: AIW and AIM implementation Guidelines (MPAI-WMG) V1.0 has been developed to review its AIW and AIM portfolio in light of Perceptible and Agentive AI.
