Explore featured sessions for manufacturing.

Discover the latest manufacturing advances in AI, visualization, and real-time simulation that are enabling leading design and engineering teams to bring innovative products to market faster. See how predictive maintenance, automated inspection, edge computing, and other innovations are enabling new levels of efficiency and transforming the factory floor.

GTC KEYNOTE

Jensen Huang | NVIDIA | Founder and CEO

Don’t miss the chance to hear Jensen Huang inform how the company is driving the rapid pace of technology advancements and new offerings to help solve the world's toughest challenges. The live keynote broadcast happens on November 9, at 9:00 a.m. Central European Time with a rebroadcast at 8:00 a.m. PST / 11:00 a.m. EST.

The keynote webcast will be open for everyone to watch (no registration required).

Featured Speakers

VR Anywhere: Streaming Autodesk VRED from AWS Cloud

Lukas Fäth
Senior Product Manager - Automotive Visualization, Autodesk

Software 2.0 for Industry 4.0

Chitra Singh
Member of Technical Staff, Drishti

Featured Sessions By Topic

Product Design and Visualization

  • Enter the Omniverse for Product Design and Manufacturing

    • Michael Geyer, Omniverse Product Management, NVIDIA

    From manufacturing to design and engineering, Omniverse has the potential to revolutionize the way we build. NVIDIA experts are looking forward to having an engaging conversation about future visions of the manufacturing industry.

  • VR Anywhere Streaming Autodesk VRED from AWS Cloud

    • Pietro Fabiani, Sr. Business Development Manager, NVIDIA
    • David Randle, Principal Go-to-Market Specialist for Spatial Computing, AWS
    • Lukas Fäth, Sr. Product Manager - Automotive Visualization, Autodesk

    Join us for a panel featuring experts from Autodesk VRED, AWS, and NVIDIA XR discussing how they were able to deliver high-quality XR experiences from the cloud over connections to tethered and untethered devices.

  • Streaming VR Training from Azure Cloud for Automotive Inspection and Maintenance

    • Veronica Yip, XR Product Marketing, NVIDIA
    • William Cannady, Technical Product Manager, NVIDIA
    • Gauhar Junnarkar, Senior Program Manager, Microsoft
    • Oswin Breidenbach, Information Manager, TÜV SÜD

    Virtual reality is the ultimate medium for training factory workers, enabling immersive experiences that closely mimic the real world without the risk, cost, and physical location requirements of in-situ training. Learn how TÜV SÜD, a world-leading testing, certification, auditing, and advisory services company, is streaming CloudXR from Azure with Innoactive to enable deployment of VR training for automotive inspection and maintenance—anywhere, anytime.

Simulation

  • Future Directions of Simulation-Driven Product Innovation

    • Dr. Prith Banerjee, CTO, Ansys

    Companies around the world use simulation to engineer and test products without the need for costly and error-prone physical prototypes and experimentation. I'll provide an overview of how engineering simulation is being used to solve problems today, provide a view into our long-term technology strategy, and highlight key technologies that will assist our customers in their innovation journey with rapid prototyping and virtual validation.

  • Toward Developing High Reynolds Number, Compressible, Reacting Flows in SimNet

    • Tarak Nandi, General Engineer, Battelle
    • Oliver Hennigh, Senior Software Engineer, NVIDIA

    This work focuses on the development and application of SimNet for modeling turbulent, reacting fluid flow in industrial applications. The governing partial differential equations (PDEs) are incorporated into the neural network (NN) training process, where the NNs are optimized by minimizing the PDE residuals. The method doesn’t require training data, and once trained, can generate flow field predictions for multiple operating conditions almost instantaneously.

  • AI-Assisted Physical Modeling in the Cloud-Native Era

    • Linfeng Zhang, Chief Scientific Officer, DP Technology

    We'll present several theories, methods, and engineering efforts that integrate physical models with AI and high-performance computing (HPC) for molecular simulations. Examples include AI-assisted electronic structure models, molecular dynamics models, and enhanced sampling schemes.

Building the AI Factory

  • Case study: Edge AI for Industrial Applications

    • German Suvorov, Head of Industrial AI, Data Monsters

    The Data Monsters team, in cooperation with NVIDIA, implements AI quality inspections on a high-speed packaging line of a major beverage company. It's a computer vision solution based on edge self-supervised AI.

  • Leveraging GPU-accelerated Computing to Scale AI in Steel and Defense Operations

    • Dan Kearns, CTO, Falkonry

    Falkonry provides AI-enabled predictive digital twins for process and asset intelligence. We'll present our experiences in building a scalable and manageable AI platform through the lens of two applications: a large steel maker and the U.S. Navy. Both of these cases involve discovery, diagnostics, and predictive analytics of time series data from industrial sensors, resulting in 430 million inferences per year for the steel case alone.

  • Honeywell Vision Intelligence Platform

    • Manjuprakash Rao, Director of Data Sciences, Advanced Technology, Honeywell

    Video analytics is a critical enabler that cuts across several businesses of Honeywell, including Building Technologies, Safety & Productivity Solutions, Process Solutions, and Aerospace. While each of these businesses poses unique challenges, the foundational building blocks are largely common across several use cases. A unified platform and unified deployment methodologies across edge to cloud would maximize development and operational efficiencies.

  • BMW and Omniverse for Production

    • Ross Krambergar, Digital Solutions for Production Planning, BMW Group

    Take a deeper look at how BMW is utilizing the Omniverse platform to realize their vision for a digital twin factory of the future and enable on-demand agile manufacturing across their global production facilities.

  • Achieving Safety and Efficiency for Industrial Sites with AI

    • Dan Kearns, CTO, Falkonry
    • Anastasia Zorina, Inception Partner Manager, NVIDIA
    • Pierre Baque, CEO, Neural Concept
    • Kamil Szewc, Senior Software Engineer, Engineering Software Steyr
    • Lior Work, CEO, Kitov System
    • Piyush Modi, IBD, NVIDIA
    • Rajesh Jha, CEO, SimInsights

    Product defects, long product design cycles, equipment failures, and safety violations can cost a modern producer great financial losses and become a health threat for the employees. Join some remarkable startups—members of the NVIDIA Inception program—to learn how AI helps to mitigate these risks, as well as some specifics of applying AI solutions in manufacturing.

Industry 4.0

  • Physics Simulation and Deep Reinforcement Learning for Contact-Rich Robotic Assembly

    • Kier Storey, Distinguished Engineer, NVIDIA
    • Yashrah Narang, Senior Research Scientist, NVIDIA

    Robotic assembly is one of the most challenging areas of industrial robotics, but physics simulators for the inherently contact-rich interactions have been viewed as computationally intractable. We'll show that the latest advances in NVIDIA PhysX 5 within Omniverse allow highly robust, performant, and parallelizable simulations of contact-rich interactions, demonstrated on robotic assembly tasks.

  • Software 2.0 for Industry 4.0

    • Chitra Singh, Member of Technical Staff, Drishti

    Drishti performs intelligent video analytics at scale with cutting-edge computer vision and deep learning technologies, using only video data. Manufacturing is only too human; dynamic, evolving, and chaotic. Each day on the factory floor is unique, so the initial best-fit models soon become obsolete and require further refinement to keep up the high standards of reliability and quality.

  • Introducing AeroBERT, an Aerospace-Centric Language Model for all NLP Applications at Rolls-Royce

    • Muhannad Alomari, European AI Hub Lead, Rolls-Royce

    We'll introduce AeroBERT, a transformer-based language model trained on millions of aerospace-related documents collected from various publicly available sources such as NASA reports, Wikipedia articles, and arXiv papers. AeroBERT is currently used to tackle all natural language processing (NLP) challenges at Rolls-Royce, providing our AI teams with a great foundation to build on.

See manufacturing session highlights from the previous GTC. Get ready for what’s to come.

Find the complete GTC On-Demand playlist here.

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