Project description DEENESFRITPL AI mimics human eye for ultra-efficient video compression The explosion of data and our desire to connect everything, from our ovens to self-driving cars and surgical equipment, to the internet is causing a tremendous flurry of research into how to accommodate all this fast data transmission reliably, securely and with low power consumption. A significant portion of research is directed at technologies to increase bandwidth. The EU-funded AISTREAM project will offer an innovative solution focused on reducing the data – not the actual data going in and coming out but the size during transmission – via AI-supported compression. The team will focus on video, which accounts for a huge volume of the internet traffic, and will demonstrate the technology in a streaming service. Show the project objective Hide the project objective Objective Deep Render combines the fields of artificial intelligence, statistics and information theory to unlock the fundamental limits of video compression.The best data compressor known to mankind is the human eye, with compression ratios at least 2,000 times better than anything developed to date. Our Biological Compression technology mimics the neurological processes of the human eye through a non-linear, learning-based approach, creating an innovative class of highly efficient compression algorithms. By building an entirely new foundation for compression, avoiding the limitations of current codecs, our objective is to develop a video compression approach 80% more efficiency than the state-of-the-art.With 85% of all internet traffic being video data, growing exponentially, bandwidth supply is being used up at an unsustainable rate. Even worse, emerging video technologies such as VR-streaming, Medical and Satellite Imaging, and Autonomous driving are bottlenecked by the unavailability of sufficient bandwidth. Further, the amount of energy used and CO2 generated with online video is now being recognised as a major problem.If the EU Digital Single Market and economic growth are to be delivered, and Climate Change obligations met, a more efficient compression system is vital to free up bandwidth and reduce energy usage. Our value proposition is simple, by reducing file sizes by 80%, we directly increase the bandwidth supply of the internet by a factor of 5, thus reducing data transport and storage requirements, reducing energy usage and CO2 emissions.Initially, the end-users of our technology will be content delivery networks, online streaming services and media production organisations. The video encoding market is estimated to be worth €1.5Bn a year. Our collaboration, including TU Wien and Contentflow (end-user), will develop, demonstrate and pilot the codec in a streaming service and begin extending the codec to new high growth, high value and high need markets. Fields of science natural sciencescomputer and information sciencesartificial intelligencenatural sciencescomputer and information sciencesinternetengineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technologynatural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changes Keywords Compression Codec Video Technology Human Visual System Visual Quality Entropy Neural Network Artificial intelligence Deep Learning Machine Learning Licensing Statistics Mathematics Programme(s) H2020-EC - Horizon 2020 Framework Programme Main Programme H2020-EU.3. - PRIORITY 'Societal challenges H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies Topic(s) EIC-FTI-2018-2020 - Fast Track to Innovation (FTI) Call for proposal H2020-EIC-FTI-2018-2020 See other projects for this call Funding Scheme IA - Innovation action Coordinator TECHNISCHE UNIVERSITAET WIEN Net EU contribution € 340 000,00 Address Karlsplatz 13 1040 Wien Austria See on map Region Ostösterreich Wien Wien Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00 Participants (2) Sort alphabetically Sort by Net EU contribution Expand all Collapse all DEEP RENDER LTD United Kingdom Net EU contribution € 2 267 928,00 Address 1st katharines way E1W 1UN London See on map SME The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed. Yes Region London Inner London — East Tower Hamlets Activity type Private for-profit entities (excluding Higher or Secondary Education Establishments) Links Contact the organisation Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 971 969,50 CONTENT FLOW GMBH Germany Net EU contribution € 392 000,00 Address Kiefholzstrasse 1 12435 Berlin See on map SME The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed. Yes Region Berlin Berlin Berlin Activity type Private for-profit entities (excluding Higher or Secondary Education Establishments) Links Contact the organisation Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 168 000,00
