**Problem + Importance for Society**
The annual global consumption of internet data has increased exponentially more than tenfold from 120 Exabytes to 1,870 Exabytes from 2008 to 2018 and is set to increase to 3,276 Exabytes by 2021. The average adult in the US now spends 6.3 hours per day with digital media. Image and video data comprises more than 85% of all global internet traffic. This exponential growth trend shows no sign of slowing, and the volume of data will rise further with upcoming services like 4K, 5K, 8K, Virtual and Augmented Reality streaming and cloud gaming. Additionally, the number of mobile internet users is expected to grow from 3.6 billion in 2018 to 5.3 billion by 2025. Every two years, the global consumption of data doubles; this is not a sustainable situation. Even South Korea, with the fastest average domestic internet connection (28.6 Megabit/sec.), cannot reliably stream 4K or use cloud gaming. Jeff Hecht states "Researchers are scrambling to repair and expand data pipes worldwide to keep the information revolution from grinding to a halt".
Deep Render has been developing a highly innovative approach to video compression not based on previous compression technologies or codecs. Built from scratch, we have re-invented the entire domain of compression around modern frameworks, creating a radically new class of compression methods. We combine artificial intelligence, machine learning, statistics, and information theory, in a non-linear approach to video compression that mirrors the neurological processing of the best video compressor known, the human eye — aka, Biological Compression.
The importance for society is straightforward given the problems mentioned above. Without radically better compression technology, the entire digital revolution is grinding to a halt, impacting the economy, the ease of communicating and sharing data, the governments (non-popular policies + ISP subsidies) and future digital innovation speed. There is also the importance of saving money and getting fair bandwidth access. Currently, bandwidth access is not fairly distributed in the world and not fairly distributed within countries. Typically, more remote areas (the countryside) are bandwidth-starved, contributing to an unequal society split between urban and rural areas. Governments are aware of this problem and try to fix it with ISP subsidies, with not much success.
**Objectives**
In this project, we will take our proven video compression algorithm and develop a full demonstration video codec market-ready for commercialisation for video-on-demand (VoD), with a compression efficiency 80% better than the best existing codecs. We will test and pilot this codec using a real-life VoD streaming service provided by Contentflow, thereby identifying, and solving all integration issues, ensuring we can begin commercialisation post project. TU Wien will use its specialist technical skills in computer vision to extend our codec for four use cases, each with specific challenges — medical imaging, satellite imaging, stereo virtual reality, and autonomous cars. Codecs have numerous applications but are rarely translated to niche use cases due to the time and cost of development. Our codec can rapidly re-deploy, and we wish to confirm this by extending it to these applications. The knowledge gained will be vital for future application to other markets and cross-sector.
