AI IN 5G MEETUP
11 October

AI IS TRANSFORMING TELECOMMUNICATIONS

Connect with artificial intelligence (AI) and Telecommunications experts to explore the latest breakthroughs for the industry. With sessions on AI for Telecoms, NVIDIA's initiatives, and interactive discussions on AI and machine learning inference in the 5G era, you cannot afford to miss this event.

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AGENDA

Thursday 11 October

11:15 Special Update: AI in Telecoms, NVIDIA Platform and Ecosystem (H4 Hotel)

Join us for an overview on NVIDIA initiatives in the Telecommunications Industry. Special update on AI at the edge and its value proposition for 5G and Autonomous Machines. Learn how to leverage NVIDIA developer assets and tools for Telecoms ecosystem.

12:00 Working Lunch (H4 Hotel)

12:25 AI and ML Inference in the 5G Era (H4 Hotel)

Join us for an interactive panel discussion on AI Inference in the era of 5G. Learn about NVIDIA GPU, NVIDIA Software stacks, Inference use cases, challenges in 5G, innovation required.

13:30 Machine Learning Enabled 5G Wireless Networks: GPU Convex Feasibility Solvers (Room 14a, ICM)

In current wireless networks, most algorithms are iterative and may not be able to meet the requirements of some 5G technologies such as ultra-reliable low-latency communication within a very low latency budget. For instance, requiring end-to-end latency below 1ms, many signal processing tasks must be completed within microseconds. Therefore, only a limited number of iterations can be performed, which may lead to uncontrollable excessive errors. We highly recommend formulating the underlying optimization problems as convex feasibility problems in order to enable massive parallel processing on GPUs for online learning and vigorous tracking. Moreover, convex feasibility solvers allow for an efficient incorporation of context information and expert knowledge can provide robust results based on relatively small data sets. Our approach has numerous applications, including channel estimation, peak-to-average power ratio (PAPR) reduction in Orthogonal Frequency Division Multiplexing (OFDM) systems, radio map reconstruction, beam forming, localization, and interference reduction. We'll demonstrate how they can benefit greatly from the parallel architecture of GPUs.

14:30 An Efficient CUDA-Accelerated Machine Learning Inference for 4G and 5G Radio Networks (Room 14a, ICM)

We're describing the design of scalable CUDA-based service framework for ML model inference tasks to efficiently distribute such workloads across a cluster of dedicated GPU-based servers. These servers can also be easily integrated with existing telecom cloud infrastructure. In telecom data centres, ML models are increasingly being deployed for use cases such as automation, analytics and anomaly detection. Handling diverse datatypes and request rates ranging between hours and milliseconds can become a challenge with a legacy CPU-dominated cloud environment.

16:00 Connect with Experts (H4 Hotel)

Network with AI and Telecommunications experts.

DISCOVER THE LATEST 5G BREAKTHROUGHS

At our AI in 5G Meetup, discover the latest research in 5G algorithms from the experts at NVIDIA, Technical University of Berlin, and the Heinrich Hertz Institute.

We’re showcasing cutting-edge developments unifying deep learning, compressive sensing, and bandwidth saving in communication—all supported by solid mathematics. Be sure to check-out our latest demo showing how to reconstruct improved classifications via constructed neural networks.

2018 SPEAKERS

SOMA VELAYUTHAM

NVIDIA
Global IBD - Telecommunications

Special Update: AI in Telecoms, NVIDIA Platform and Ecosystem

DEEPU TALLA

NVIDIA
Vice President and General Manager of Autonomous Machines

Special Update: AI in Telecoms, NVIDIA Platform and Ecosystem

MANISH HARSH

NVIDIA
Developer Relations - Global Telecoms

Special Update: AI in Telecoms, NVIDIA Platform and Ecosystem

Connect with Experts

SLAWOMIR STANCZAK

TECHNICAL UNIVERSITY BERLIN AND FRAUNHOFER HEINRICH-HERTZ-INSTITUTE BERLIN
Professor

AI and ML Inference in the 5G Era

Machine Learning Enabled 5G Wireless Networks: GPU Convex Feasibility Solvers

ALEX KELLER

NVIDIA
Director of Research

AI and ML Inference in the 5G Era

TERO RISSA

NOKIA
Chief Architect, Machine Learning

AI and ML Inference in the 5G Era

An Efficient CUDA-Accelerated Machine Learning Inference for 4G and 5G Radio Networks

ERIC HARPER

NVIDIA
Solution Architect

Connect with Experts

KEITH MORRIS

NVIDIA
Senior Director of Product Management

AI and ML Inference in the 5G Era

PRADEEP GUPTA

NVIDIA
Head Solution Architect Autonomous Driving

Connect with Experts

GET HANDS-ON DEEP LEARNING TRAINING

LEARN MORE

DEEPU TALLA

NVIDIA, Vice President and General Manager of Autonomous Machines

Special Update: AI in Telecoms, NVIDIA Platform and Ecosystem

Join us for an overview on NVIDIA's initiatives in Telecommunications Industry. Special update on AI at the edge and its value proposition for 5G and Autonomous Machines. Learn how to leverage NVIDIA developers assets and tools for Telecoms ecosystem.

ABOUT THE SPEAKER: Deepu Talla is vice president and general manager of Autonomous Machines at NVIDIA, where he is responsible for deploying AI technology in devices such as factory robots, commercial drones and video analytics. Previously, he was responsible for NVIDIA’s mobile business unit. Prior to joining NVIDIA in 2013, he worked at Texas Instruments for more than 10 years in various executive management and technical leadership roles.Talla holds a Bachelor of Engineering degree in electronics and communication engineering from Andhra University in India, a Master of Science degree in electrical engineering from Villanova University, and a Ph.D. in computer engineering from the University of Texas at Austin.

MANISH HARSH

NVIDIA, Developer Relations - Global Telecoms

Special Update: AI in Telecoms, NVIDIA Platform and Ecosystem

Connect with Experts

Network with NVIDIA and Telecommunications experts.

ABOUT THE SPEAKER: Manish Harsh manages Global Developer Relations for Telecoms with a focus on developer communities for AI operations and Network Security initiatives on NVIDIA's AI stack. Previously he used to manage NVIDIA's developer engagement platforms horizontally across all verticals and products. Before joining NVIDIA, he was a co-founder of Halosys Technologies, offering a enterprise mobility solution with a patent on workflow notification in mobile devices. He has globally presented and hosted various user groups on forward-looking technology solution events. He holds a Bachelors Degree in Electronics Engineering and is currently pursuing a management program from UC Berkeley on Leadership and Technology Management.

SLAWOMIR STANCZAK

TECHNICAL UNIVERSITY BERLIN AND FRAUNHOFER HEINRICH-HERTZ-INSTITUTE BERLIN, Professor

AI and ML Inference in the 5G Era

Join us for an interactive panel discussion on AI Inference in the 5G era. Learn about NVIDIA GPU, NVIDIA Software stacks, Inference use cases, challenges in 5G, innovation required.

Machine Learning Enabled 5G Wireless Networks: GPU Convex Feasibility Solvers

In current wireless networks, most algorithms are iterative and might not be able to meet the requirements of some 5G technologies such as ultra-reliable low-latency communication within a very low latency budget. For instance, requiring and end-to-end latency below 1ms, many signal processing tasks must be completed within microseconds. Therefore, only a strictly limited number of iterations can be performed, which may lead to uncontrollable excessive errors. We argue in favor of formulating the underlying optimization problems as convex feasibility problems in order to enable massively parallel processing on GPUs for online learning for fast and robust tracking. Moreover, convex feasibility solvers allow for an efficient incorporation of context information and expert knowledge, and can provide robust results based on relatively small data sets. Our approach has numerous applications, including channel estimation, peak-to-average power ratio (PAPR) reduction in Orthogonal Frequency Division Multiplexing (OFDM) systems, radio map reconstruction, beam forming, localization, and interference reduction. We show that they can greatly benefit from the parallel architecture of GPUs.

ABOUT THE SPEAKER: Slawomir Stanczak studied electrical engineering with a specialisation in control theory at the Wroclaw University of Technology and at the Technical University of Berlin (TU Berlin). He received the Dipl.-Ing. degree in 1998 and the Dr.-Ing. degree (summa cum laude) in electrical engineering in 2003, both from TU Berlin. His Habilitation degree (venialegendi) followed in 2006. Since 2015, he has been a Full Professor for Network Information Theory at TU Berlin and the Head of the Wireless Communications and Networks department. Prof. Stanczak is a co-author of two books and more than 200 peer-reviewed journal articles and conference papers in the area of information theory, wireless communications, signal processing and machine learning. He was an Associate Editor of the IEEE Transactions on Signal Processing between 2012 and 2015.

TERO RISSA

NOKIA, Chief Architect - Machine Learning

AI and ML Inference in the 5G Era

Join us for an interactive panel discussion on AI Inference in the 5G era. Learn about NVIDIA GPU, NVIDIA Software stacks, Inference use cases, challenges in 5G, innovation required.

An Efficient CUDA-Accelerated Machine Learning Inference for 4G and 5G Radio Networks

We describe the design of scalable CUDA-based service framework for ML model inference tasks to efficiently distribute such workloads across a cluster of dedicated GPU-based servers. These servers can also be easily integrated with existing telecom cloud infrastructure. In telecom data centres, ML models are increasingly being deployed for use cases such as automation, analytics and anomaly detection. Handling diverse datatypes and request rates ranging between hours and milliseconds can become a challenge with a legacy CPU-dominated cloud environment.

ABOUT THE SPEAKER: Tero has 20 years of industrial experience of scaling new technologies from research and concept engineering into commercial products. He started working with artificial neural networks in 2009, and has since held senior positions in both engineering and management. Tero holds a MSc in CS/EE, Digital and Computer Systems from TUT, Finland, and a PhD in Computing from Imperial College London, UK. He is also an emeritus member of the Nokia CEO Technology Council and Bell Labs Distinguished Member of Technical Staff.

KEITH MORRIS

NVIDIA, Senior Director of Product Management, Accelerated Computing

AI and ML Inference in the 5G Era

Join us for an interactive panel discussion on AI Inference in the 5G era. Learn about NVIDIA GPU, NVIDIA Software stacks, Inference use cases, challenges in 5G, innovation required.

ABOUT THE SPEAKER: Keith leads product management for data center GPUs. His team is responsible for defining and enabling the ecosystem with solutions for a broad set of accelerated applications and vertical markets that span from high performance computing to artificial intelligence and machine learning. Prior to joining NVIDIA, Keith led silicon product planning at Xilinx where his team drove the product definition and business planning for multiple generations of FPGAs and SoCs. A native of the UK, he has also held executive management positions at multiple technology startup companies, including both an initial public offering and acquisitions.

ADRIEN BESSE

AIRBUS, Data Scientist

Developing Deep Learning Solutions Against Cybersecurity Threats

Deep Learning is key in defending cybersecurity threats for companies. In the future, not only will hackers attack companies manually, but also complex programs will be able to take advantage of systems. Through attending this session, you will learn how to identify such attacks and how big players in the market are preparing for this development. Use cases will be presented by ATOS and Volkswagen Data Lab.

ABOUT THE SPEAKER: Adrien is data scientist and product owner in the R&D Software department in ATOS on the development of deep learning applications in cybersecurity. Adrien owns a PhD in theoretical physics and has been working since 2014 on the development of deep learning solutions to solve real world challenges.

AI IN 5G MEETUP 11 October

AI IS TRANSFORMING TELECOMMUNICATIONS

AGENDA

Thursday 11 October

DISCOVER THE LATEST 5G BREAKTHROUGHS