MPAI publishes the AI for Health V1.0 standard with a Request for Community Comments

Geneva, Switzerland – 21^st January 2026. 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 64^th General Assembly (MPAI-64) publishing the AI for Health V1.0 standard.

Technical Specification: AI for Health (MPAI-AIH) – Health Secure Platform (AIH-HSP) V1.0  envisages that AIH-HSP subscribers use personal devices running AI Framework implementations (front ends) to locally process and submit health data to the AIH-HSP back end. A licence attached to health data specifies the types of processes that the back end or specific organisations called Third-Party Users may perform and the type of use they can make of the process data. The back end is connected to a blockchain storing the smart contracts governing the processes that the back end and the Third-Party Users can perform on subscriber data. From time to time, the backend collects neural networks trained by front ends and distributes an updated neural network used by AIH-HSP subscribers with the knowledge acquired by the community using Federated Learning.

There are several ways to know more about the standards:

• Register to attend the public online presentation of the standard on 9 February 2026 at 15 UTC.
• Read AI for Health (MPAI-AIH) – Health Secure Platform (AIH-HSP) V1.0
• Read a short Introduction to AIH-HSP V1.0.

MPAI is also publishing V2.4 of Context-based Audio Enhancement (MPAI-CAE) – Use Cases (CAE-USC).

MPAI is continuing the development of its work plan that involves the following activities:

1. AI Framework (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 (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 (CAE-USC): developing the Audio Six Degrees of Freedom (CAE-6DF) and the Audio Object Rendering (CAE-AOR) specifications.
4. Connected Autonomous Vehicle (CAV-TEC): developing a new version of the flagship specification CAV-TEC with security support.
5. Compression and Understanding of Industrial Data (CUI-CPP): expecting comments on the Company Performance Prediction V2.0 specification.
6. End-to-End Video Coding (MPAI-EEV): exploring the potential of AI-based End-to-End Video coding in compressing video sequences.
7. AI-Enhanced Video Coding (MPAI-EVC): exploring new standards that benefit from the use of Super Resolution filters.
8. Governance of the MPAI Ecosystem (MPAI-GME): operating the MPAI Ecosystem per the MPAI-GME Specification.
9. Human and Machine Communication (MPAI-HMC): exploring the use of AI in human-to-machine and machine-to-machine communication.
10. Multimodal Conversation (MPAI-MMC): developing specifications of new data types especially in the context of the PGM-AUA standard.
11. MPAI Metaverse Model (MMM-TEC): developing security-enabling protocols in the MMM-TEC specification.
12. Neural Network Watermarking (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 (MPAI-OSD): developing specifications of new data types especially in the context of the PGM-AUA standard.
14. Portable Avatar Format (MPAI-PAF): discussing the impact of MPAI standards planned or under development on MPAI-PAF V1.5.
15. AI Module Profiles (MPAI-PRF): extending the scope of the current version of AI Module Profiles.
16. Server-based Predictive Multiplayer Gaming (MPAI-SPG): exploring new standard opportunities in the domain.
17. Data Types, Formats, and Attributes (MPAI-TFA) extending the standard to data types used by MPAI standards that are planned or under development.
18. XR Venues (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.

Please visit the MPAI website, contact the MPAI Secretariat for specific information, subscribe to the MPAI Newsletter and follow MPAI on social media: LinkedIn, Twitter, Facebook, Instagram, and YouTube.