MPAI publishes “AI for Health” and “Neural Network Watermarking- Technologies”

May 26, 2026
Top Quote MPAI has concluded its 68th General Assembly (MPAI-68) publishing AI for Health (MPAI-AIH) – Health Secure Platform (AIH-HSP) and Neural Network Watermarking (MPAI-NNW) – Technologies (TEC)” as MPAI Standards End Quote
  • (1888PressRelease) May 26, 2026 - Geneva, Switzerland - MPAI - Moving Picture, Audio and Data Coding by Artificial Intelligence - the international, non-profit, unaffiliated organisation developing AI-based data coding standards – has concluded its 68th General Assembly (MPAI-68) publishing AI for Health (MPAI-AIH) - Health Secure Platform (AIH-HSP) and Neural Network Watermarking (MPAI-NNW) - Technologies (TEC)” as MPAI Standards.

    AIH-HSP enables End Users to use their Front Ends to capture, process, license, and upload health data to the system Back End where user-generated licences are converted into smart contracts, and their health data are processed per the smart contracts. From time to time the neural networks in the Front Ends are collected, updated using Federated Larning Technologies, and redistributed to End Users. .

    NNW-TEC utilises the previously approved Neural Network Watermarking - Traceability (NNW-NNT) standard to assess different watermarking technologies. MPAI-68 has also approved Version V1.1 of Connected Autonomous Vehicle (MPAI-CAV) – Technologies (CAV-TEC) as a draft standard published with a request for Community Comments until 2024/07/08. The focus is on ensuring security of the processing subsystem of the Connected Autonomous Vehicle.

    MPAI is continuing the development of its work plan that involves the following activities:
    1.AI Framework https://mpai.community/standards/mpai-aif/ (MPAI-AIF): extending the MPAI-AIF specification to enable a client to access a remote MPAI-AIF Controller and an AI Module to communicate data to another AIM with associate metadata.
    2.AI for Health https://mpai.community/standards/mpai-aih/ (AIH-HSP): developing the specification of a system receiving and processing licenses AI Health Data and enabling clients to improve health processing models via federated learning.
    3.Context-based Audio Enhancement https://mpai.community/standards/mpai-cae/ (CAE-USC): developing the Audio Six Degrees of Freedom (CAE-6DF) and the Audio Object Rendering (CAE-AOR) specifications.
    4.Connected Autonomous Vehicle https://mpai.community/standards/mpai-cav/ (CAV-TEC): developing a new version of the flagship specification CAV-TEC with security support.
    5.Compression and Understanding of Industrial Data https://mpai.community/standards/mpai-cui/ (CUI-CPP): expecting comments on the Company Performance Prediction V2.0 specification.
    6.End-to-End Video Coding https://mpai.community/standards/mpai-eev/ (MPAI-EEV): exploring the potential of AI-based End-to-End Video coding in compressing video sequences.
    7.AI-Enhanced Video Coding https://mpai.community/standards/mpai-evc/ (MPAI-EVC): exploring use of AI to enhance the video codec performance.
    8.Governance of the MPAI Ecosystem https://mpai.community/standards/mpai-gme/ (MPAI-GME): operating the MPAI Ecosystem per the MPAI-GME Specification.
    9.Human and Machine Communication https://mpai.community/standards/mpai-hmc/ (MPAI-HMC): exploring the use of AI in human-to-machine and machine-to-machine communication.
    10.Multimodal Conversation https://mpai.community/standards/mpai-mmc/ (MPAI-MMC): exploring the impact of the PGM-AUA Call for Technologies on human-to-machine and machine-to-machine conversation.
    11.MPAI Metaverse Model https://mpai.community/standards/mpai-mmm/ (MMM-TEC): developing security-protected protocols in the MMM-TEC specification.
    12.Neural Network Watermarking https://mpai.community/standards/mpai-nnw/ (NNW-TEC): Developing the new Neural Network Watermarking (MPAI-NNW) – Technologies (NNW-TEC) including assessments of Neural Network Traceability Technologies.
    13.Object and Scene Description https://mpai.community/standards/mpai-osd/ (MPAI-OSD): discussing the impact of MPAI standards planned or under development on MPAI-OSD V1.4.
    14.Portable Avatar Format https://mpai.community/standards/mpai-paf/v1-2/ (MPAI-PAF): discussing the impact of MPAI standards planned or under development on MPAI-PAF V1.5.
    15.AI Module Profiles https://mpai.community/standards/mpai-prf/ (MPAI-PRF): extending the scope of the current version of AI Module Profiles.
    16.Server-based Predictive Multiplayer Gaming https://mpai.community/standards/mpai-spg/ (MPAI-SPG): exploring new standard opportunities in the domain.
    17.Data Types, Formats, and Attributes https://mpai.community/standards/mpai-tfa/ (MPAI-TFA) extending the standard to data types used by MPAI standards that are planned or under development.
    18.XR Venues https://mpai.community/standards/mpai-xrv/ (XRV-LTP): developing the standard for improved execution of Live Theatrical Performances using AI.

    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/).
    - X(https://twitter.com/mpaicommunity).
    - Facebook(https://www.facebook.com/mpaicommunity).
    - Instagram(https://www.instagram.com/mpaicommunity/).
    - outube(https://www.youtube.com/ ( @ ) MPAIstandards) dot
    - Bluesky (https://bsky.app/profile/mpaicommunity.bsky.social)

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