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The second round of MPAI standardisation begins

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On 19 July 2020 – two years ago – the wild idea of an organisation dedicated to the development of AI-based data coding standards was made public. What has happened in these two years?

  1. MPAI was established in September 2020.
  2. Four Calls for Technologies were published in December 2020, and January-February 2021.
  3. The corresponding four Technical Specifications were published in September-November-December 2021:
    1. AI Framework (MPAI-AIF, a standard environment to execute AI workflows composed of AI Modules),
    2. Compression and Understanding of Industrial Data (MPAI-CUI, standard AI-based financial data processing technologies and their application to Company Performance Prediction).
    3. Multimodal Conversation (MPAI-MMC, standard AI-based human-machine conversation technologies and their application to 5 use cases),
    4. Context-based Audio Enhancement (MPAI-CAE, standard AI-based audio experience-enhancement technologies and their application to 4 use cases)
  4. Completion of the set of specifications composing an MPAI standard, namely: Reference Software, Conformance Testing and Performance Assessment in addition to Technical Specification. So far this has been partly achieved.
  5. IEEE adoption without modification of the Technical Specifications. The first MPAI technical specification converted to an IEEE standard is expected to be approved in the second half of September 2022.
  6. Publication of three Calls for Technologies and associated Functional and Commercial Requirements for data formats and technologies:
    1. The extended AI Framework standard (MPAI-AIF V2) will retain the functionalities specified by Version 1 and will enable the components of the Framework to access security functionalities. See 1 min video: YT Non YT
    2. The extended Multimodal Conversation standard (MPAI-MMC V2) will enable a variety of new use cases such as separation and location of audio-visual objects in a scene (e.g., human beings, their voices and generic objects); the ability of a party in metaverse1 to import an environmental setting and a group of avatars from metaverse2; representation and interpretation of the visual features of a human to extract information about their internal state (e.g., emotion) or to accurately reproduce the human as an avatar. See 2 min video: YT non-YT
    3. The Neural Network Watermarking standard (MPAI-NNW) will provide the means to assess if the insertion of a watermark deteriorates the performance of a neural network; how well a watermark detector can detect the presence of a watermark and a watermark decoder can retrieve the payload; and how to quantify the computational cost to inject, detect, and decode a payload. See 1 min video: YT non YT
  7. Finally, MPAI has decided to establish the MPAI Store. This is the place where implementations of MPAI technical specifications will be submitted, validated, tested, and made available for download.

A short life with many results. Much more to accomplish.