MPAI releases new version of Neural Network Watermarking Reference Software; starts new project on XR Venues – Live Theatrical Stage Performance

November 25, 2023
Top Quote MPAI, non-profit, and unaffiliated organisation developing AI-based data coding standards has concluded its 38th General Assembly (MPAI-38) approving the release of a new version of its Neural Network Watermarking reference software and the start of the development of the new XR Venues – Live Theatrical Stage Performance standard. End Quote
  • (1888PressRelease) November 25, 2023 - Geneva, Switzerland – MPAI, Moving Picture, Audio and Data Coding by Artificial Intelligence, the international, non-profit, and unaffiliated organisation developing AI-based data coding standards has concluded its 38th General Assembly (MPAI-38) approving the release of a new version of its Neural Network Watermarking reference software and the start of the development of the new XR Venues – Live Theatrical Stage Performance standard.

    The new version of the Neural Network Watermarking (MPAI-NNW https://mpai.community/standards/mpai-nnw/) reference software makes it possible to upgrade conventional AI-based processing workflows with traceability and integrity checking functions. For instance, it is now possible to add AI Modules to an MPAI-AIF workflow to detect whether a particular text was indeed produced by the expected service or AI Module (AIM). Register at https://tinyurl.com/mt885ty8 to attend the online presentation on 2023/12/12T15:00 UTC.

    The XR Venues (MPAI-XRV) – Live Theatrical Stage Performance (https://mpai.community/standards/mpai-xrv/) standard project specifies functions and interfaces of AI Modules designed to automate live multisensory immersive stage performances which ordinarily require extensive on-site show control staff to operate. By running AI Workflows (AIW) composed of AIMs, it will be possible to obtain a more direct, precise yet spontaneous show implementation and control of multiple complex systems to achieve the show director’s vision.

    MPAI is continuing its work plan that involve the following activities:
    1.AI Framework (MPAI-AIF https://mpai.community/standards/mpai-aif/): reference software, conformance testing, and application areas.
    2. AI for Health (MPAI-AIH https://mpai.community/standards/mpai-aih/) development of the standard.
    3. Context-based Audio Enhancement (CAE-DC https://mpai.community/standards/mpai-cae/): new projects.
    4. Connected Autonomous Vehicle (MPAI-CAV https://mpai.community/standards/mpai-cav/): Functional Requirements of CAV architecture.
    5.Compression and Understanding of Industrial Data (MPAI-CUI https://mpai.community/standards/mpai-cui/): preparation for extension of existing standard.
    6. Multimodal Conversation (MPAI-MMC https://mpai.community/standards/mpai-mmc/): reference software, drafting conformance test-ing, and new areas.
    7. MPAI Metaverse Model (MPAI-MMM https://mpai.community/standards/mpai-mmm/): reference software and metaverse technologies requiring standards.
    8. Neural Network Watermarking (MPAI-NNW https://mpai.community/standards/mpai-nnw/): reference software for enhanced applications.
    9. Portable Avatar Format (MPAI-PAF https://mpai.community/standards/mpai-ara/): reference software, conformance testing and new areas.
    10. End-to-End Video Coding (MPAI-EEV https://mpai.community/standards/mpai-eev/): video coding using AI-based End-to-End Video coding.
    11. AI-Enhanced Video Coding (MPAI-EVC https://mpai.community/standards/mpai-evc/). video coding with AI tools added to existing tools.
    12. Server-based Predictive Multiplayer Gaming (MPAI-SPG https://mpai.community/standards/mpai-spg/): technical report on mitigation of data loss and cheating.
    13. XR Venues (MPAI-XRV https://mpai.community/standards/mpai-xrv/): preparation for the development of the standard.
    Legal entities and representatives of academic departments supporting the MPAI mission and able to contribute to the development of standards for the efficient use of data can become MPAI members (https://mpai.community/2022/11/02/seven-good-reasons-to-join-mpai/)

    Please visit the MPAI website (https://mpai.community) , contact the MPAI secretariat (secretariat ( @ ) mpai dot community) for specific information, subscribe to the MPAI Newsletter and follow MPAI on social media:
    - LinkedIn (https://www.linkedin.com/groups/13949076/).
    - Twitter (https://twitter.com/mpaicommunity).
    - Facebook (https://www.facebook.com/mpaicommunity).
    - Instagram (https://www.instagram.com/mpaicommunity/).
    - YouTube (https://www.youtube.com/ ( @ ) MPAIstandards)

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