For 30+ years, digital media have been the powerful driver that has fostered research, industry and commerce. The engine that has sustained the development could expand its coverage and provide new standards to a growing group of client industries. Academia and research, all facets of industry, and billions of users have benefited from this bonanza.
Unfortunately, the engine has run out of steam – technology-wise and business-wise.
Thirty years of practical data compression show the importance of the business that is built of data compression standards. Old technology has had its day. To renew it, we need two things: fresh new technologies, but also a fresh new approach to the field.
A new engine is coming to rescue. There is a vast group of technologies – going under the general name of Artificial Intelligence – that provide alternative and more promising approaches than statistical correlation. They go deeper understanding what are the physical phenomena we are trying to represent.
Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) is the vehicle designed to implement the plan. It is a win-win proposal because Digital Media gets more performing technologies and Artificial Intelligence extends the range where its technologies are applied – not just digital media, but also other data types whose use can be more effective if converted to a more efficient representation.
The MPAI Statutes define data coding as the transformation of data from one representation into another representation that is more convenient for a particular purpose. Reducing the amount of data, a.k.a. compression, is one purpose that has proved to be very important to billions of people, but there are many other purposes. Having AI as the underlying technology layer will ensure that AI technologies for data coding will have wider applications, practical deployment will be accelerated and interoperability improved.
This is the grand plan, but we should not forget that the devil is in the details. MPEG has shown that technically excellent standards are no guarantee that their access will be easy and their use possible. Therefore, MPAI abandons the old FRAND approach because it does not guarantee that a licence for a supposed FRAND standard will be available. It embraces instead the Framework Licence approach where IPR holders agree to a business model, and possibly a cap to the total cost of a licence, _before_ the work on the standard starts.
MPAI attacks the main issue of the digital world – data representation, i.e. coding – and leverages AI to get the best results achievable in the current time frame. However, it has learnt the lesson: industry is no longer available to wait for the terms after the standard is done. They want to know more before starting the work.
