The latest – 15 June 2024 – MPAI General Assembly (MPAI-44) proved, if ever there was a need, that MPAI produces non only standards, but also promising new projects. MPAI-44 launched three new projects on 6 degrees of freedom audio (CSAE-6DF), technologies for connected autonomous vehicle components, and technologies for the MPAI Metaverse Model. The CAE-6DF Call is seeking innovative technologies that enable users to walk in a virtual space representing a remote real space and enjoy the same experience as if…

Geneva, Switzerland – 20 March 2024. 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 42nd General Assembly (MPAI-42) approving the release of Reference Software using Neural Network Watermarking for Generative AI applications. The new V1.1 version of the Neural Network Watermarking (MPAI-NNW) Reference Software includes an implementation of the AIF Framework and of an AI Workflow enabling a user to make queries…

In the last few months, MPAI has published eight new or update MPAI standards. They have been presented online in the 11-15 March 2024 week. Here are the titles of the standards with links to the presentations and video recording provided by two services. They are a good opportunity to stay abreast of the progress in MPAI rev MPAI Metaverse Model (MPAI-MMM) - Architecture ppt  YT  nYT new Portable Avatar Format (MPAI-PAF) ppt  YT  nYT new Human and Machine Communication…

At its 40th General Assembly (MPAI-40), MPAI approved one draft, one new, and three extension standards. For an organisation that has already nine standards in its game bag, this may not look like big news. There are two reasons, though, to consider this a remarkable moment in the MPAI short but intense life. The first reason is that the draft standard posted for Community Comments – Human and Machine Communication (MPAI-HMC) – does not specify new technologies but leverages technologies…

In a previous article, Ihave described the Architecture of the MPAI Connected Autonomous Vehicle (CAV). The CAV’s Environment Sensing Subsystem (ESS) captures data of the environment with a variety of sensors and produces the Basic Environment Representation (BER) that is passed to the Autonomous Motion Subsystem (AMS). This exchanges (subsets of) the BER with other CAVs in range and uses the received information to produce the Full Environment Representation (FER). Then, the AMS can issue commands to the Motion Actuation Subsystem…