Media Services in Dense, Static and Mobile Environments Leveraging Edge Deployments.
ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS AIAI 2023 IFIP WG 125 INTERNATIONAL WORKSHOPS(2023)
Intracom Telecom SA
Abstract
The media sector is one of the domains that are highly impacted by the 5G network principles and capabilities, in terms of service provisioning and performance in versatile environments. At the same time the media sector is gradually becoming an integral part of transportations, as a variety of media services can be offered and used to facilitate passengers' needs in various directions, especially infotainment and safety/security. The 5GPPP 5G-VICTORI project proposes the integration of Content Delivery Network-aided infotainment services in 5G network deployments to enable the uninterrupted delivery of such services with high quality to dense, static and mobile environments. The solution is deployed and evaluated in an experimentation setup in lab and in operational railway environments. This paper discusses the service Key Performance Indicators and technical requirements and provides an overview
MoreTranslated text
Key words
5G,Content Delivery Networks,CDN,Edge Computing,vertical services,railways
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined