An introduction to the MPAI-AIF Call for Technologies

On 202/12/21 MPAI has held a teleconference to illustrate the MPAI-AIF Call for Technologies (CfT) and associated Framework Licence (FWL). This article summarises the main points illustrated at the teleconference: Whay and who is MPAI, the MPAI-AIF Functional Requirements, the MPAI_AIF Call for Technologies and the MPAI-AIF Framework Licence.

• See the powerpoint presentation.

Miran Choi, an MPAI Director and Chair of the Communication Advisory Committee, recalled the reasons that led to the establishment of MPAI.

Over the past 3 decades, media compression standards have allowed manufacturing and services to boom. However, the technology momentum is progressively slowing while AI technologies are taking stage by offering more capabilities than traditional technologies, by being applicable to data other than audio/video and by being  supported by a global research effort. In addition to that, industry has recently suffered from the inadequacy of the FAIR, Reasonable and Non-Discriminatory (FRAND) model to deal with the tectonic changes of technology-intensive standards.

Miran then summarised the main characteristics of MPAI. A non-profit, unaffiliated and international association that develops

• Standards for
  • AI-enabled data coding
  • Technologies that facilitate integration of data coding components in ICT systems and
• Associated clear IPR licensing frameworks.

MPAI is the only standards organisation that has set AI as the key enabling technology for data coding standards. MPAI members come from industry, research and academia of 15 countries, representing a broad spectrum of technologies and applications.

The development of standards must obey rules of openness and due process, and MPAI has a rigorous process to develop standards in 6 steps

The transitions from one stage to the next are approved by the General Assembly.

The MPAI-AIF standard project is at the Call for Technologies stage.

Andrea Basso, Chair of the MPAI-AIF Development Committee (AIF-DC) in charge of the development of the MPAI-AIF standard introduced the motivations and functional requirements of the MPAI-AIF standard.

MPAI has developed several Use Cases for disparate applications coming to the conclusion that they can all be implemented with a combination of AI-based modules concurring to the achievement of the intended result. the history of media standards has shown the benefits of standardisation. Therefore, to avoid the danger of incompatible implementations of modules put to the market, where costs multiply at all levels and mass adoption of AI tech is delayed, MPAI seeks to standardise AI Modules (AIM) with standard interfaces, combined and executed within an MPAI-specified AI Framework. AIMs with standard interfaces will reduce overall design costs and increase component reusability,create favourable conditions leading to horizontal markets of competing implementations, and promote adoption and incite progress of AI technologies.

AIMs need an environment where they can be combined and executed. This is what MPAI- AIF – where AIF stands for AI Framework, is about. The AI Framework is depicted in the figure.

The AI Framework has 6 components: Management and Control, Execution, AI Modules, Communication, Storage and Access.

The MPAI functional requirements are

1. Possibility to establish general Machine Learning and/or Data Processing life cycles
   1. for single AIMs to
      1. instantiate-configure-remove
      2. dump/retrieve internal state
      3. start-suspend-stop
      4. train-retrain-update
      5. enforce resource limits
      6. implement auto-configuration/reconfiguration of ML-based computational models of
   2. for multiple AIMs to
      1. initialise the overall computational model
      2. instantiate-remove-configure AIMs
      3. manually, automatically, dynamically and adaptively configure interfaces with Com­ponents
      4. one- and two-way signal for computational workflow initialisation and control of
      5. combinations of AIMs
2. Application-scenario dependent hierarchical execution of workflows
3. Topology of networked AIMs that can be synchronised according to a given time base and full ML life cycles
4. Supervised, unsupervised and reinforcement-based learning paradigms
5. Computational graphs, such as Direct Acyclic Graph (DAG) as a minimum
6. Initialisation of signalling patterns, communication and security policies between AIMs
7. Protocols to specify storage access time, retention, read/write throughput etc.
8. Storage of Components’ data
9. Access to
   1. Static or slowly changing data with standard formats
   2. Data with proprietary formats
10. Possibility to implement AI Frameworks featuring
    1. Asynchronous and time-based synchronous operation depending on application
    2. Dynamic update of the ML models with seamless or minimal impact on its operation
    3. Time-sharing operation of ML-based AIMs shall enable use of the same ML-based AIM in multiple concurrent applications
    4. AIMs which are aggregations of AIMs exposing new interfaces
    5. Workflows that are a mixture of AI/ML-based and DP technology-based AIMs.
    6. Scalability of complexity and performance to cope with different scenarios, e.g. from small MCUs to complex distributed systems
11. Possibility to create MPAI-AIF profiles

Panos Kudumakis, MPAI member, explained the MPAI-AIF Call For Technologies

1. Who can submit
   1. All parties, including non members, who believe they have relevant technologies
   2. Responses submitted to secretariat who acknowledges via email
   3. Technologies submitted must
      1. Support the requirements of N74
      2. Be released according to the MPAI-AIF Framework Licence (N101) – if selected by MPAI for inclusion in MPAI-AIF
   4. MPAI will select the most suitable technologies on the basis of their technical merits for inclusion in MPAI-AIF.
   5. MPAI in not obligated to select a particular technology or to select any technology if those submitted are found inadequate.
2. A submission shall contain
   1. Detailed documentation describing the proposed technologies.
   2. Annex A: Information Form (contact info, proposal summary).
   3. Annex B: Evaluation Sheet to be taken into consideration for self-evaluation (quantitative & qualitative) of the submission but will be filled out during the peer-to-peer evaluation phase.
   4. Annex C: Requirements Check List (N74) to be duly filled out indicating (using a table) which requirements identified are satisfied. If a requirement is not satisfied, the submission shall indicate the reason.
   5. Annex D: Mandatory text in responses
3. A submission may contain
   1. Comments on the completeness and appropriateness of the MPAI-AIF requirements and any motivated suggestion to extend those requirements.
   2. A preliminary demonstration, with a detailed document describing it.
   3. Any other additional relevant information that may help evaluate the submission, such as additional use cases.
4. Assessment
   1. Respondents must present their submission or proposal is discarded.
   2. If submission is accepted in whole or in part, submitter shall make available a working implementation, including source code (for use in MPAI-AIF Reference Software) before the technology is accepted for the MPAI-AIF standard.
   3. Software can be written in compiled or interpreted programming languages and in hardware description languages.
   4. A submitter who is not an MPAI member shall immediately join MPAI, else submission is discarded.
   5. Assessment guidelines form to aid peer-to-peer evaluation phase being finalised.
5. Calendar
   1. Call for Technologies 16 Dec (MPAI-3)
   2. Presentation Conference Calls 21 Dec/07 Jan
   3. Notification of intention to submit 15 Jan
   4. Assessment form 20 Jan (MPAI-4)
   5. Submission deadline 15 Feb
   6. Calendar of evaluation of responses 17 Feb (MPAI-5)
   7. Approval of MPAI-AIF standard 19 July (estimate)

Davide Ferri, MPAI Director and Chair of AIF-FWL, the committee that developed the MPAI-AIF Framework Licence (FWL) explained that FWL covers the MPAI-AIF technology that specifies a generic execution environment, possibly integrating Machine Learning, Artificial Intelligence and legacy Data Processing components, implementing application areas such as

1. Context-based Audio Enhancement (MPAI-CAE)
2. Integrative Genomic/Sensor Analysis (MPAI-GSA)
3. AI-Enhanced Video Coding (MPAI-EVC)
4. Server-based Predictive Multiplayer Gaming (MPAI-SPG)
5. Multi-Modal Conversation (MPAI-MMC)
6. Compression and Understanding of Industrial data (MPAI-CUI)

These six application areas are expected to become MPAI standards.

The FWL includes a set of definitions that are omitted here. In particular the definition of Licence, namely, the Framework Licence to which values, e.g., currency, percent, dates etc., related to a specific Intellectual Property will be added.

The FWL is expressed in concise form as below

1. The Licence will:
   1. be in compliance with generally accepted principles of competition law and the MPAI Statutes
   2. cover all of Licensor’s claims to Essential IPR practiced by a Licensee of the MPAI-AIF standard
   3. cover Development Rights and Implementation Rights
   4. apply to a baseline MPAI-AIF profile and to other profiles containing additional technologies
2. Grant access to Essential IPRs of the MPAI-AIF standard in a non-discriminatory fashion.
3. Have a scope to legal, bias, ethical and moral limitations
4. Royalties will:
   1. apply to Implementations that are based on the MPAI-AIF standard
   2. not be based on the computational time nor on the number of API calls
   3. apply on a worldwide basis
   4. apply to any Implementation
5. An MPAI-AIF Implementation may use other IPR to extend the MPAI-AIF Implementation or to provide additional functionalities
6. The Licence may be granted free of charge for particular uses if so decided by the licensors
7. The Licences will specify
   1. a threshold below which a Licence will be granted free of charge and/or
   2. a grace period during which a Licence will be granted free of charge and/or
   3. an annual in-compliance royalty cap applying to total royalties due on worldwide rev­enues for a single Enterprise
8. A preference will be expressed on the entity that should administer the patent pool of holders of Patents Essential to the MPAI-AIF standard
9. The total cost of the Licences issued by IPR holders will be in line with the total cost of the licences for similar technologies standardised in the context of Standard Development Organisations
10. The total cost of the Licences will take into account the value on the market of the AI Framework technology Standardised by MPAI.

Miran reminded how easily legal entities or individuals representing a technical departments of a university supporting the MPAI mission and able to contribute to the development of MPAI standards can join MPAI. They should

1. Choose one of the two classes of membership (until 2021/12/31):
   1. Principal Members, with the right to vote (2400 €)
   2. Associate Members, without the right to vote (480 €)
2. Send secretariat@mpai.community
   1. a signed copy of Template for MPAI Membership applications
   2. a signed copy of the MPAI Statutes. Each page should be signed and initialled
   3. a copy of the bank transfer