Drive cost savings and efficiencies.
Telcos across the globe are realizing cost savings and new levels of operational efficiency by adopting generative AI, AI and machine learning across their business. From improving customer experiences and optimizing complex network operations with AI to extracting business insights through data science, telcos are unlocking new ways to positively impact their bottom line.
Get insights on industry AI trends, challenges, and business impacts with data from a survey of over 400 telecommunications professionals from around the world. Learn what’s being prioritized, where investments are being made, and how teams across the industry are approaching AI in 2023.
Learn how telcos built mission-critical large language models (LLMs), powered by NVIDIA DGX™ systems and the NVIDIA NeMo™ framework, to simplify their business and increase customer satisfaction while achieving the fastest and highest return.
Powered by generative and speech AI.
Satisfied customers drive brand loyalty and are essential for sustainable growth. AI and machine learning generate actionable insights on behaviors that can improve the customer experience. Through technologies such as generative AI, speech AI, and recommender systems, customer engagements can be enhanced with digital voice agents and personalized interactions, including payment alerts and promotional offers.
Harness the power of AI and the metaverse.
AI is reshaping the way telco operators run their networks. Generative AI lets telcos interact with their networks in new, powerful ways, such as responding to queries on critical issues, identifying incidents within specified timeframes, and recommending solutions. And when field technicians are called out to the physical network, dynamic route optimization and virtual field agent assistants improve the speed and accuracy of service, enhancing customer satisfaction while reducing travel time and fuel costs.
New tools for network planning are also unlocking efficiencies. Digital twins can be used to test scenarios and asset placement within a 3D, true-to-reality model before expensive investments are made in the physical world.
Shorten time to business insights and actions.
The telecommunications industry has access to vast amounts of data generated by networks, customers, and operations. But data alone isn't enough to gain a competitive advantage. The real value lies in the insights that can be derived from it through data science.
Using advanced analytics and machine learning, telecom operators can extract valuable insights to improve network performance, customer experiences, and operational efficiency. The NVIDIA AI Enterprise software suite enables quicker time to results for AI and machine learning initiatives, while improving cost-effectiveness. Telcos can reduce cloud costs for use cases such as customer churn prediction, predictive maintenance of network equipment, advanced security, fraud detection, and much more.
Learn from telecom providers using AI to optimize processes, improve customer satisfaction, and trim costs.
AT&T adopts NVIDIA AI to process data more efficiently, optimize service-vehicle routing, and create digital twins and avatars.
T-Mobile offers award-winning customer service in their Customer Experience Centers and aims to never have customers repeat themselves. To empower their frontline agents, T-Mobile implemented Expert Assist. This AI-based software transcribes real-time customer conversations and recommends solutions to thousands working on the frontline.
South Korea’s leading mobile operator builds billion-parameter large language models trained with the NVIDIA DGX SuperPOD™ platform and NeMo™ framework. The AI-powered speaker from KT can control TVs, offer real-time traffic updates, and complete a slew of other home-assistance tasks based on voice commands.
Test
Image courtesy of Korea Telecom
Ask AT&T was originally built on OpenAI’s ChatGPT functionality. But Ask AT&T is also interoperable with other large language models (LLMs), including Meta’s LLaMA 2 and the open-source Falcon transformers. We’re working closely with NVIDIA to build and customize LLMs. Different LLMs are suited for different applications and have different cost structures, and we’re building that flexibility and efficiency in from the ground floor.
– Andy Markus, Chief Data Officer, AT&T
With NVIDIA® Riva services, fine-tuned using T-Mobile data, we’re building products to help us resolve customer issues in real time. After evaluating several automatic speech recognition (ASR) solutions, T-Mobile has found Riva to deliver a quality model at extremely low latency, enabling experiences our customers love.
– Matthew Davis, Vice President of Product and Technology, T-Mobile
The collaboration between NVIDIA and HEAVY.AI [on telco digital twins] enables telcos to make nationwide business decisions through a single pane of glass with up-to-the-minute insights. This ensures telcos are realizing better return on their investments made on networks.
– Jon Kondo, CEO, HEAVY.AI
Amdocs plans to build custom LLMs for $1.7 trillion global telecommunications industry using NVIDIA AI foundry service on Microsoft Azure.
Join us for an exciting and interactive day delving into cutting-edge techniques in large language model (LLM) application development. LLM Day will offer hands-on, practical guidance from practitioners, who’ll share their insights and best practices for getting started with and advancing LLM application development.
Learn about the technology powering new levels of insight and efficiency in telecoms.
The combination of accelerated computing and generative AI is set to transform telcos’ customer experience, network operations, and productivity. Telcos can train diagnostic AI models with proprietary network and equipment data and services to boost performance monitoring, diagnostics, and security. Generative AI applications bring new levels of support to agents in the call center and technicians in the field with faster resolution and personalized offers.
Telcos are introducing speech AI-based applications such as agent assists, virtual assistants, and digital avatars to improve customer service, self-service, and satisfaction. But building highly scalable speech AI-based applications that learn from conversations, detect customer preferences, make personalized recommendations, and engage dynamically in real time isn’t easy. With NVIDIA Riva, telcos can build accurate, real-time speech and translation AI applications with customizable pipelines that seamlessly integrate with telco workflows.
Data science workflows have traditionally been slow and cumbersome, relying on CPUs to load, filter, and manipulate data and train and deploy models. The NVIDIA RAPIDS™ Accelerator for Apache Spark automatically replaces operations with GPU-accelerated versions without any code changes or risk, since you can revert back to your previous infrastructure at any time. Run existing Apache Spark 3.x jobs 5X faster than CPU-only systems, with up to 75 percent less cost and realized energy savings, enabling efficient customer churn prediction, network anomaly detection, fraud detection, and more.
Videos
Generative AI describes technologies that are used to generate new content based on a variety of inputs. It uses neural networks to identify patterns and structures within existing data to generate new content such as images, words, and computer code. In this course, you'll learn generative AI concepts, applications, as well as the challenges and opportunities of this exciting field.
Learn how to build, train, fine-tune, and deploy a GPU-accelerated automatic speech recognition (ASR) service with NVIDIA Riva that includes customized features.
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