AI IN TELECOMMUNICATIONS

The demand on the wireless industry to absorb, process, and deliver data at an unprecedented scale requires a new kind of network. The world’s leading telcos are turning to NVIDIA technologies to optimize networks, innovate faster, and deliver new services.

Accelerate Your Telecom Networks with AI

Increase productivity. Improve network quality. Enhance Customer Service.

  • Network Operations

    Network Operations

  • Edge Computing

    Edge Computing

  • Ultra-Efficient 5G

    Ultra-Efficient 5G

AI-Based Network Operations

Network operations primarily based on statistical algorithms or static policies can be turned into deep learning (DL) and AI-based models. Adopt AI and ML in network operations to gain the ability to manage exponentially increasing complexity, and the realtime optimization required by SDNs. Minimize labor-intensive operational expenses and increase end-user productivity.

Watch curated video "GPU Accelerated Data Science Platform" presented by NVIDIA CEO Jensen Huang
Download the “AI for Network Operations” solution brief
Watch the “Accelerate Your Operations in Telecom with AI" on-demand webinar
Read the "5V to 5G: How Telecom, and Other Industries, Are Adopting AI" blog
AI-Based Network Operations

Telecommunications companies can visualize and understand the deluge of big data with RAPIDS, a suite of open-source, GPU-accelerated software libraries.

Verizon reduced computing time from 24 hours to 1 hour with equal or better accuracy than traditional methods.

Bryan Larish, Verizon
Predicting 4G Wireless Network Quality with Deep Learning Algorithm - GTC 2018

Ultra-Efficient 5G

NVIDIA LIVE WEBINAR
ACCELERATE YOUR OPERATIONS IN TELECOM WITH AI

Discover how telecom service providers can leverage AI to improve network quality, optimize resource planning, and enhance customer service.

Date: Thursday, May 30, 2019
Time: 9:00–10:00 a.m. PT

Register

5G Edge Computing

NVIDIA GPUs make it possible to deliver ultra low-latency 5G services from the cloud. This makes applications like cloud-based virtual reality (VR), smart cities, cloud gaming, 360-degree immersive video, connected drones, and autonomous vehicles possible. Open source containers and libraries also help accelerate speed to market.

5G Edge Computing

We’ll be collaborating with NVIDIA to experiment with new ways of delivering experiences over 5G and edge computing technology.

Alisha Seam, AT&T Foundry in Palo Alto

AI- Accelerated 5G

NVIDIA GPUs and CUDA® technology let telcos accelerate compute-intensive applications and VNF workloads with the largest amount of parallelizable code. Applications will be able to take advantage of the growth in computing power with GPUs from generation to generation without having to change software functionalities.

Ultra-Efficient 5G

NVIDIA GPUs helped Ribbon deliver 9X better performance with half the power.

Kevin Riley, Ribbon Communications

BreadCrumb Navigation - Tabs

Technologies transforming telecommunications

Deep Learning for Wireless Communications

Deep Learning for Network Operations

NVIDIA GPUs accelerate the actual training of channel autoencoders to speeds comparable to compiling programs for desktop processors in minutes, and sometimes even seconds. Once the model has been trained, it can then be deployed into a low-power, high performance embedded systems like the NVIDIA Jetson™ TX2 or AGX  Xavier™. This creates a design flow where communications engineers can easily build optimized physical layers and then deploy them to embedded devices at the edge.

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Data Science

Data Science

With vast amounts of data being stored, processed, and analyzed in telecoms, accelerated data science maximizes productivity, provides optimized AI models and reduces TCO. Learn more about how the GPU accelerated ecosystem provides end-to-end data science solutions for telecom.

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Webinar 
Accelerating Large-Scale Object Detection

Accelerated Large-Scale Object Detection

Accurately detecting the presence of humans is critical to a variety of applications. High-performance deep learning training makes it possible to create robust and generalizable models for objects, humans, animals, and machines for object detection over 5G using NVIDIA TensorRT. Maintaining real-time inference performance in production environments while preserving high accuracy is critical, whether in the data center or at the edge. Every percent increase in accuracy leads to exponential gains for organizations providing video-based services.

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Background Noise Suppression

Background Noise Suppression

Existing noise suppression solutions in today’s mobile phones aren’t perfect, but they do provide an improved user experience. NVIDIA’s deep learning solution requires just a single microphone with all the post-processing handled by software. This allows hardware designs to be simpler and more efficient, completely muting the background noise for more pleasant and intelligible communications.

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TAKE A DEEPER DIVE INTO THE TELECOM INDUSTRY

As we hurtle toward the era of 5G, where cars, MRI scanners, and even washing machines will be connected, telecommunications companies are challenged to serve the vast amounts of content and services it will generate. To manage data loads, process complex network functions, provide new services, and drive revenue growth, they need to build a new kind of network.

Watch this talk from GTC 2019 to delve into this new era. It covers the challenges, strategies, a potential solution, and global case studies.

WATCH NOW

After you watch the video, explore the other resources available in the link to see how AI is transforming the telecom industry.

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