MPAI marks its sixth anniversary with the publication of Thalia

October 13, 2026
Top Quote MPAI has concluded its 72nd General Assembly marking the sixth anniversary of MPAI's founding with the final approval of the MPAI as a Service standard implemented as a demo service Thalia End Quote
  • (1888PressRelease) October 13, 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 72nd General Assembly (MPAI-72), marking the sixth anniversary of MPAI's founding with the final approval of the MPAI as a Service (MPAI-MAS https://mas.mpai.community/) standard implemented as a demo service Thalia and with the publication of reference software for the Connected Autonomous Vehicle - Technologies (CAV-TEC https://cav.mpai.community/) V2.0 standard, published with a request for Community Comments. MPAI as a Service makes it possible to run MPAI applications remotely. This benefits the chain of service providers who can draw on an open market of AI components, leveraging technologies developed by technology developers, to the advantage of end users. Thalia, accessible at https://thalia.mpai.community/, demonstrates the potential of the MPAI as a Service standard. Using a browser on a desktop computer or smartphone, a user can interact by speech and text with Thalia, an avatar, across six applications built from the MPAI reference software released today and from openly available AI models.

    Thalia plays multiple roles such as using a Large Language Model (LLM) to converse with a user (Multimodal Dialogue), responding to questions about pictures (Answer to Multimodal Questions), acting as a personal interpreter across a variety of languages (Multimodal Translation), holding affective conversations with a user, and modulating the features of her speech and face in response to those of the user (Multimodal Affective Dialogue). Thalia’s operation draws on a range of MPAI standards. The AI Framework (https://mpai.community/standards/mpai-aif/)specifies an environment enabling the initialisation, dynamic configuration, and control of AI applications implemented as a collection of AI Modules interconnected according to a standard topology. The Process Instance Trust Framework (https://mpai.community/standards/mpai-ptf/) enables a Zero-Trust implementation of the AIF environment.

    Other standards used include Multimodal Conversation (https://mpai.community/standards/mpai-mmc/) , Object and Scene Description (https://mpai.community/standards/mpai-osd/) , Portable Avatar Format (https://mpai.community/standards/mpai-paf/), and Data Types, Formats and Attributes (https://mpai.community/standards/mpai-tfa/). These standards are currently published with requests for Community Comments. The Thalia software is also published to facilitate the formulation of comments to the MPAI Secretariat (secretariat ( @ ) mpai dot community) dot MPAI as a Service will be presented online on 2026/10/26 at 16 UTC dot Register at https://us06web dot zoom dot us/meeting/register/GI2fSV3JTWafnlIi9IcdVg to attend dot

    The General Assembly has also published the Connected Autonomous Vehicle – Technologies (CAV-TEC) standard with requests for Community Comments. Previously published as Version 1.1, CAV-TEC is being revised with the inclusion of reference software. The software is a comprehensive implementation of the standard including the human-machine interaction, the environment sensing, the vehicle control, and the motion actuation subsystems. The software, available from the MPAI GitHub at https://github.com/mpai-community/mpai-sw can run in real time if executed on a computer with adequate GPUs. MPAI encourages use of the software and welcomes comments and contributions.

    About MPAI
    Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) is an international, non-profit, unaffiliated organisation developing standards for AI-based data coding. Its standards specify AI Modules (AIMs) – their function and interfaces - rather than AI models, so implementations conforming to the same standard can be freely combined and replaced. More information is available at mpai.community. MPAI members are 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. Please visit the website (https://mpai.community) , subscribe to the Newsletter (https://mpai.community/news/newsletters/)

    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/).
    -Youtube(https://www.youtube.com/ ( @ ) MPAIstandards) dot
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    - Media contact
    MPAI Secretariat, secretariat ( @ ) mpai dot community.

    MPAI projects and standards
    Short overview of MPAI projects and standards is given below.
    1.AI Framework https://aif.mpai.community/ (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://aih.mpai.community (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. AI Passport https://aip.mpai.community/ (MPAI-AIP) – develops a standard enabling humans and AI systems understand the parameters characterising an AI system.
    4. AI Tools https://ait.mpai.community/– develops open-source implementations of AI standard components (AI Modules), distributed to the community under a 3-Clause BSD licence.
    5. Context-based Audio Enhancement https://cae.mpai.community/ (CAE-USC): developing the Audio Six Degrees of Freedom (CAE-6DF) and the Audio Object Rendering (CAE-AOR) specifications.
    6.Connected Autonomous Vehicle https://cav.mpai.community/ (CAV-TEC): developing a new version of the flagship specification CAV-TEC with security support.
    7 Compression and Understanding of Industrial Data https://cui.mpai.community/ (CUI-CPP): expecting comments on the Company Performance Prediction V2.0 specification.
    8.End-to-End Video Coding https://eev.mpai.community/ (MPAI-EEV): exploring the potential of AI-based End-to-End Video coding in compressing video sequences.
    9.AI-Enhanced Video Coding https://evc.mpai.community/ (MPAI-EVC): exploring use of AI to enhance the video codec performance.
    10.Governance of the MPAI Ecosystem https://gme/empai.community/ (MPAI-GME): operating the MPAI Ecosystem per the MPAI-GME Specification.
    11.Human and Machine Communication https:/hmc./mpai.community/ (MPAI-HMC): exploring the use of AI in human-to-machine and machine-to-machine communication.
    12.Multimodal Conversation https://mmc.mpai.community/ (MPAI-MMC): exploring the impact of the PGM-AUA Call for Technologies on human-to-machine and machine-to-machine conversation.
    13.MPAI Metaverse Model https://mmm.mpai.community/ (MMM-TEC): developing security-protected protocols in the MMM-TEC specification.
    14.Neural Network Watermarking https://nnw.mpai.community/ (NNW-TEC): Developing the new Neural Network Watermarking (MPAI-NNW) – Technologies (NNW-TEC) including assessments of Neural Network Traceability Technologies.
    15.Object and Scene Description https://osd.mpai.community/ (MPAI-OSD): discussing the impact of MPAI standards planned or under development on MPAI-OSD V1.4.
    16.Portable Avatar Format https://paf.mpai.community/ (MPAI-PAF): discussing the impact of MPAI standards planned or under development on MPAI-PAF V1.5.
    17. Process Instance Trust Framework https://ptf.mpai.community/ (MPAI-PTF) – develops standard to establish and assess trust in an AI-based process instance whose AI Modules may have unknown reliability.
    18.AI Module Profiles https://prf.mpai.community/ (MPAI-PRF): extending the scope of the current version of AI Module Profiles.
    19.Server-based Predictive Multiplayer Gaming https://spg.mpai.community/ (MPAI-SPG): exploring new standard opportunities in the domain.
    20.Data Types, Formats, and Attributes https://tfa.mpai.community/ (MPAI-TFA) extending the standard to data types used by MPAI standards that are planned or under development.
    21.XR Venues https://xrv.mpai.community/ (XRV-LTP): developing the standard for improved execution of Live Theatrical Performances using AI.

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