Categories: News

MPAI Tackles AI Risk Analysis Standard in a New Call for Technologies

MPAI has promoted its 4th standard project Compression and understanding of industrial data (MPAI-CUI) to the Call for Technologies stage. The standard aims to enable Artificial Intellig-ence (AI)-based filtering and extraction of information from a company�s governance, financial and risk data enabling prediction of company performance, e.g., organisational adequacy or default probability.

Geneva, Switzerland, March 21, 2021 –(PR.com)– At its 6th General Assembly, the international, unaffiliated Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) standards association has promoted its 4th standard project Compression and understanding of industrial data (MPAI-CUI) to the Call for Technologies stage. The standard aims to enable Artificial Intellig­ence (AI)-based filtering and extraction of information from a company’s governance, financial and risk data enabling prediction of company performance, e.g., organisational adequacy or default probability.

All parties, including non-MPAI members, who believe they have relevant technologies satisfying all or most of the MPAI-CUI Functional Requirements (https://mpai.community/standards/mpai-cui/#UCFR) are invited to submit proposals for consideration by MPAI. The MPAI-CUI Call for Technologies (https://mpai.community/standards/mpai-cui/#CfT) requests that technologies proposed, if accepted for inclusion in the standard, be released according to the MPAI-CUI Framework Licence (https://mpai.community/standards/mpai-cui/#FWL) to facilitate eventual definition of the final licence by patent holders.

The content of the Call for Technologies will be introduced at two online conferences. (https://mpai.community/standards/calls-for-technologies/). Interested parties are welcome to attend.

MPAI is continuing the development of its AI Framework standard, nicknamed MPAI-AIF (https://mpai.community/standards/mpai-aif/). The goal of the standard is to enable creation and automation of mixed Mach­ine Learning (ML) – Artificial Intelligence (AI) – Data Processing (DP) and inference workflows, implemented as software, hardware, or mixed software and hardware. A major MPAI-AIF feature is to offer enhanced explainability to applications conforming to MPAI standards. MPAI retains its intention to release the standard in July 2021.

At its previous General Assembly (MPAI-5), MPAI has issued two Calls for Technologies supporting two new standards:

1. Context-based Audio Enhancement (MPAI-CAE https://mpai.community/standards/mpai-cae/) covering four instances: adding a desired emotion to a speech without emotion, preser­ving old audio tapes, improving the audioconference experience and removing unwanted sounds while keeping the relevant ones to a user walking in the street.

2. The Multimodal Conversation (MPAI-MM https://mpai.community/standards/mpai-mmc/) covering three instances: an audio-visual conversation with a machine impersonated by a synthesised voice and an animated face, a request for information about an object while dis­playing it, a human sentence translated using a synthetic voice that preserves the human speech features.

The MPAI web site provides information about the other AI-based standards being developed: AI-Enhanced Video Coding (MPAI-EVC https://mpai.community/standards/mpai-evc/) will improve the performance of existing video codecs, Integrative Genomic/ Sensor Analysis (MPAI-GSA https://mpai.community/standards/mpai-gsa/) will compress and understand the results of com­bining genomic experiments with those produced by related devices/sensors, and Server-based Predictive Multiplayer Gaming (MPAI-SPG https://mpai.community/standards/mpai-spg/) will improve the user experience of online multiplayer games.

MPAI develops data coding standards for applications that have AI as the core enabling technology. Any legal entity who supports the MPAI mission may join MPAI (https://mpai.community/how-to-join/join/) if it is able to contribute to the development of standards for the efficient use of data.

Visit the MPAI web site (https://mpai.community/) and contact the MPAI secretariat (secretariat@mpai.community) for specific information.

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