1. User experience and workflows
A simple self-explanatory user interface with intuitive workflows is the basic requirement for a successful product. Neither for the iPhone nor for YouTube did the users need training or education. Rather, the objectives/application possibilities of such a product can be easily identified and the corresponding functions and processing options derived.
In addition, automated individual (video) workflows must be configurable in order to relieve users of as much work as possible and allow them more time and concentration for their actual work.
medialoopster already offers this today. Deutsche Welle rejected training for medialoopster because the project manager said (quote): “Everyone knows YouTube. And if you can work with YouTube, you can also work with medialoopster.”
2. Metadata is valuable and has to be managed
At the moment the systems are called Video Asset Management, Media Asset Management, Project Asset Management, Digital Asset Management, etc. This distinction will probably become blurred or even disappear in the future, since the requirements for such systems will continue to increase and their functions can no longer be clearly defined. In the past, systems could often only manage a certain number of specific file formats, but in the future this must be possible for almost all formats, especially with the increased use of VR and AR. More important than the formats, however, will be the associated metadata in the future. These are time-related for videos and even space- and size-related within a frame. This metadata will flood the systems mentioned above through the use of AI and must be managed by these systems.
medialoopster is designed to store and orchestrate this vast amount of metadata. We therefore often refer to medialoopster as Metadata Asset Management System.
3. Use of AI to increase effectiveness and efficiency
In order to accelerate processes, save costs, increase the quality and quantity of metadata and increase production output, the use of AI in media production is indispensable. In the past, this was simply not possible due to the mass of data. Now these analyses can be carried out within a very short time over the entire video stock and can even be linked with other analyses of other systems in the future. However, the focus must always be on the human being in order to understand which data is involved, how the results are determined and what consequences are associated with this. After all, the use of AI should only be supportive for video production, the creative spirit that generates the video content should not be uniform but unique, unmistakable and certainly not subject to any general algorithms.
medialoopster sees itself as a kind of AI aggregator or connector. The aim is to integrate as many different AI services as possible into medialoopster via a connector interface and make them available to the customer. The customer can then decide for himself which of the respective AI services he wants to use.
4. Concentration on the core competence and integration of competent third- party providers
It will be important for such systems to expand their core competencies and focus on them. In the future there will be expert software for each area, which will be provided in accelerated form by different development teams. This is why such production asset systems must offer open interfaces (e.g. REST-API) in order to be able to easily integrate third-party providers (with expert software) in order to benefit from their services. It will be important that you are no longer dependent on one software vendor! The software should let the user work independently and independently, e.g. the producer should always be able to get his assets with metadata into and out of the system without outside help.
medialoopster has been following this approach since 2014.
5. Everything must be “standard”, no matter where
Standard hardware, standard software, open API, open documentation, manual, so that everyone can help themselves and is not necessarily dependent on the manufacturer support. Therefore, the system complexity must also be taken out. The system architecture must be designed so that it runs in the private, hybrid or complete cloud. Especially due to the use of 5G technology, this specification is absolutely necessary and an elementary prerequisite to enable collaborative work (even across multiple locations). In addition, this enables the path to low-res editing, no matter where the user is currently located.
medialoopster essentially consists of standard IT components, is high performance and highly available as well as easy to scale and administer. Everything is documented and made available to the customer. Even complex production environments can be installed and configured within a very short time (in days and not weeks) thanks to the simple medialoopster system architecture.