We are incredibly excited to announce that we collaborate with researchers at Imperial College London to provide research and recommendations to develop cutting-edge, advanced AI solutions for the AIOZ Network.
With the advantage of our AIOZ Network technology stack and firm foundation of research capability in academia at Imperial College London, our goal is to transform the AI applications in the existing content delivery system, delivering a scalable solution for web 3.0 and beyond.
The Challenges of Improving AIOZ Network
One of the potential and challenging problems we address is optimal routing for node applications in the AIOZ Network. The success of the user experience has always been intimately linked to routing efficiency. However, with an expanding number of digital channels and limitless data sources to understand what drives ideal results, delivering the user to the right resource has increased its difficulty.
At AIOZ, we are overcoming this obstacle by implementing AI-driven predictive routing, which delivers strategic, high-resolution matching between network stakeholders. The goal is to connect end-users and content deliverers more effectively and efficiently.
It is well-known that with the remarkable success of machine learning in recent years, applications of Artificial Intelligence and Machine Learning (AI&ML) in networking have gained a lot of attention.
Compared to painstakingly developed (white-box) tactics, AI&ML (black-box) approaches offer significant benefits in networking systems. For example, AI&ML provides a generic model and consistent learning approach for diverse network settings without predefined procedures.
Furthermore, such strategies can handle complicated issues and high-dimensional circumstances well. AI&ML methods have already achieved great success in many complex system control areas, such as computer games and robotic control.
Aside from the vast benefits of AI&ML for networking, the creation of novel network approaches is also fertile ground for AI&ML implementation. In-band Network Telemetry (INT), for example, provided end-to-end network visualization at the millisecond scale in 2015, and Cisco released PNDA, a big data analytics platform for networking, in 2017.
As a result, the growing trend of using AI&ML in networking is driven by job requirements (increasing network complexity and increasingly demanding QoS/QoE needs) and technical advancements (new network monitoring technologies and big data analysis techniques).
In this collaboration with Imperial College London, we will work together to study, examine, and evaluate a variety of state-of-the-art AI-driven network routing methods to develop a rigid solution for the AIOZ Network.
The collaboration with the university also connects the AIOZ team with talented students, researchers who would join us via internships and as contributors to constantly elaborate the network’s growth with the latest technologies and innovations.
The collaboration comes after AIOZ entered NVIDIA’s Inception, a startup acceleration platform providing firms go-to-market support, expertise, and technology only one of the world’s leading GPU distributors could offer.
About the AIOZ Network
AIOZ Network is a Layer-1 Blockchain-based Content Delivery Network that will bring a revolution to the entertainment industry.
AIOZ Network utilizes Blockchain to better content distribution through decentralization. A distributed Content Delivery Network (dCDN) uses Nodes for storing, streaming, and transferring data instead of traditional data centers operating on a P2P model.
AIOZ Network uses a faster, cheaper, and more robust platform for content streaming making it affordable, fast, and better quality.
By using this revolutionary technology, AIOZ Network can efficiently change the way the world streams content. Thus taking the world one step closer to the future.
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