Seizing the opportunity of edge AI, telecom operators embark on a transformation journey

5G makes the Internet of Everything possible. The generation of massive data not only puts huge pressure on the network, but also further pushes the demand for computing power to the edge. Edge AI has spawned scenario innovation in multiple vertical industries such as consumer electronics, security, automobiles, and industrial manufacturing.

Seize the opportunity of edge AI and telecom operators start a transformation journey

For example, in the industrial field, AI and edge applications are expected to develop in smart factories play an increasingly important role. Driven by the Industry 4.0 model, the next generation of smart factories applies advanced robotics, machine learning technology to software services and the industrial Internet of Things to improve organization and maximize productivity.

Edge AI has become critical to the future of telecom service providers, and for this reason, they are continuously investing to ensure that they have strong application, data and AI development and management capabilities at the edge.

Edge AI has become the “new favorite”

Why are telecom service providers keen to invest in edge AI? There are three main reasons for this.

First, edge AI enables telecom service providers to meet the low-latency requirements of new services. The main motivation for telecom service providers to invest in edge AI is to enable networks to achieve the low latency required to deliver new services. 5G can reduce latency to 5 milliseconds, enabling operators to provide a variety of new services, including mobile gaming, AR/VR, Internet of Things (IoT), and autonomous driving. 5G is combined with distributed computing and storage capabilities to enhance With latency capabilities, operators can improve customer experience.

Secondly, edge AI will enhance network performance. The enterprise market is key for operators to make edge investments, with industrial IoT and automated factories being the most profitable use cases. Considering the growth of edge traffic and the need to meet low latency, operators manage and optimize network resources to improve efficiency. Therefore, operators need AI applications to enhance the performance of edge network resources to ensure that customers receive high-performance and secure edge services.

Finally, edge AI can effectively reduce operating costs. Operators' operating costs account for approximately 60% of total revenue; therefore, they want to reduce costs, and edge AI provides exactly this opportunity. Taking video traffic as an example, if the video traffic is transmitted to the core network for processing, high bandwidth costs will be incurred. With edge AI, operators can process part of the data close to customers and only send the analysis results to the core network, thereby reducing backhaul costs

Opportunities for edge AI

As telecom services are provided As vendors modernize their networks, they are prioritizing AI applications to create new revenue streams. Telecom service providers are leveraging high-bandwidth 5G connectivity and the real-time performance of edge AI computing to develop new services to help enterprises meet growing demand and customer expectations.

There are many ways for telecom service providers to profit from the edge:

Enterprise and B2B services – Telcos can offer software-as-a-service (SaaS) capabilities and tap into app marketplaces to facilitate Enterprises popularize the use of AI applications.

Managed Services and Private Networks – Telcos can provide enterprises with managed services that include not only the management of end-to-end network infrastructure, but also edge computing and applications that support innovative use cases.

Consumer Services – Telcos can leverage 5G to deploy new and richer immersive content (such as location-based entertainment and esports) to deliver engaging new experiences.

Profiting from the 5G Network Edge

NVIDIA is a technology leader in the field of AI and has partnered with large global industries such as transportation, healthcare, logistics, manufacturing, robotics, smart cities, and retail. of companies are collaborating to unlock new potential and promote innovation to drive future competitiveness.

With the help of NVIDIA, telecommunications companies will have a unique opportunity to become trusted technology partners, providing end-to-end infrastructure such as connectivity, edge computing and enterprise applications.

To help telecom operators seize the opportunities brought by edge AI, NVIDIA provides a full-stack computing platform for AI.

For example, NVIDIA-Certified Systems use NVIDIA's industry-leading GPUs and DPUs, off-the-shelf commercial servers provided by original equipment manufacturers (OEMs) and original design manufacturers (ODMs).

NVIDIA GPUs and DPUs are supported as part of the commercial stack, and their resources can be virtualized, managed, and shared by multiple applications and tenants.

In order to provide telecom companies with the tools they need to innovate and deploy solutions using AI and GPU-accelerated computing, NVIDIA provides developers with a variety of application frameworks, including SDK, developer Kits, APIs, and documentation.

On this basis, NVIDIA has established a vast ecosystem of ready-to-use applications provided by various independent software vendors (ISVs) to accelerate various workloads in various industries.

Moreover, NVIDIA has cooperated with telecommunications companies to create many implementation cases:

As a research arm of China Mobile, China Mobile (Chengdu) Industry Research Institute is working to leverage NVIDIA GPUs connected to next-generation 5G mobile networks to accelerate natural disaster response, improve emergency medical services, and provide new education and training tool. In an emergency, they will dispatch drones equipped with high-resolution cameras and infrared technology to transmit the recorded video to the emergency dispatch headquarters through the 5G network. Instead of waiting for the drone to return to process the data, emergency responders can immediately begin parsing these videos using AI image algorithms running on NVIDIA GPUs to better understand the crisis situation in real time and focus rescue efforts.

Deutsche Telekom and NVIDIA combine 5G, edge computing and CloudXR to create a high-end AR user experience. Glass House is an app from Deutsche Telekom that allows users to enjoy high-fidelity extended reality (XR) experiences wirelessly over a 5G connection. This XR experience is actually created and rendered at the 5G edge using NVIDIA RTX and CloudXR technology (including ray tracing), adding outstanding beauty and realism to the rendered finished product. The rendered content is then displayed in AR glasses that are connected locally to the smartphone.

This feature can be applied to numerous use cases. In building construction, designers can visualize and interact with high-resolution CAD and CAM models before and during construction to speed up construction while preventing costly engineering changes. Other use cases include product design collaboration, remote field support, healthcare applications, business meetings, and more.

From the above typical cases, we see that from computer vision to augmented reality/virtual reality (AR/VR), more and more mature edge AI applications have been put into use. Telecom service providers are leveraging this edge AI application ecosystem to quickly and easily enable new capabilities for enterprises.

To learn more about the "Using AI to Profit at the Network Edge White Paper", please visit the special area "Using AI to Profit at the Network Edge: NVIDIA Platform Built for the Telecom Edge"

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