AiThority Interview with Rev Lebaredian, VP of Omniverse and Simulation Technology at NVIDIA

Rev Lebaredian, VP of Omniverse and Simulation Technology at NVIDIA discusses the future of industrial digital twins and robotics, top challenges in adopting OpenUSD, innovation in AI-driven applications and more about AI-driven applications in this interview.

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Hello Rev! Welcome to AiThority.com’s Q&A series. Please share your journey in computer graphics and simulation that led you to your current role at NVIDIA.

Early in my career, I focused on rendering and simulation technologies, exploring how they could be used to create more realistic and interactive experiences. This passion led me to NVIDIA, where, for the last five years, my team and I have been combining the rendering, physics simulation, and AI technologies pioneered by NVIDIA into a single platform for creating physically accurate virtual worlds: NVIDIA Omniverse.

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NVIDIA recently announced major advancements to OpenUSD. What do these developments mean for the future of industrial digital twins and robotics?

• We recently announced major advancements that will expand adoption of OpenUSD to robotics, industrial design and engineering, and accelerate developers’ abilities to build highly accurate virtual worlds for the next era of AI; robotics.
• The next wave of physical AI – where autonomous machines can sense, plan and act autonomously in a physical world – will start in simulation. Simulation unlocks the ability to test, train, optimize the robot’s actions in a safe environment before actual implementation. OpenUSD is key to achieving the next level of autonomy.
• With these developments we’re making it easier for developers across industries to create, manage, and interact with complex digital representations of physical systems. These improvements will enable more accurate and scalable simulations, streamline workflows, and facilitate better integration across various tools and platforms.
• For industrial digital twins, this means more robust and detailed models, delivering more accurate simulation representations of industrial environments.
• For robotics, this will enable simulation of real-world environments, which is crucial for developing and testing autonomous systems in virtual worlds before deploying them in the real world.

Can you highlight the top challenges in adopting OpenUSD in sectors like manufacturing and automotive?

• Transitioning to OpenUSD can be challenging for those in the heavy industries because their current processes and workflows often rely on proprietary software, data formats, and general purpose computing infrastructure. These environments weren’t necessarily developed with today’s needs for data interoperability and large scale simulation in mind.
• Individuals and teams who want to adopt OpenUSD into their workflows also require new skills, knowledge, and tools to enable them to take advantage of OpenUSD.
• To accelerate their learning and adoption, we’ve developed a foundational Learn OpenUSD curriculum and will continue to work with the ecosystem to develop advanced curriculum and pathways to certification for OpenUSD.
• With NVIDIA NIM, we’ve built the world’s first generative AI models for OpenUSD development to accelerate developers’ abilities to build highly accurate virtual worlds for the next evolution of AI.
• To accelerate OpenUSD ecosystem expansion, we’ve developed an OpenUSD Exchange software development kit, enabling developers to build their own robust OpenUSD data connectors.
• We’re also investing in a series of new USD connectors for robotics data formats that will enable roboticists to seamlessly bring their robot data across applications, including for design, simulation and reinforcement learning.

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What are the key benefits for developers using NVIDIA NIM microservices in their workflows, particularly with OpenUSD-based applications?

• NVIDIA NIM are a set of easy-to-use microservices designed for secure, reliable deployment of high performance AI model inferencing.
• NVIDIA NIM™ microservices include the world’s first generative AI models for OpenUSD development that enable developers to generate OpenUSD language to answer user queries, generate OpenUSD Python code, apply materials to 3D objects, and understand 3D space and physics to help accelerate digital twin development.
• With NVIDIA NIM, more industries can now develop applications for visualizing industrial design and engineering projects, and for simulating environments to build the next wave of physical AI and robots.

Looking ahead, according to you what role does generative AI play in transforming traditional industries and driving innovation in AI-driven applications?

The role that generative AI will play in making simulation an accurate and reliable technology is more important than ever as it continues to be deployed in production.

• Generative AI is quickly becoming the new interface to engage with software and systems and unlocks many new possibilities for traditional industries. Generative AI-enabled digital twins will enable us to solve problems we’ve never been able to solve and will help us bridge the domain knowledge gap between humans and the capabilities of our systems, so that more people can use them.
• We will rely on generative AI to help us build the industrial scale digital twins needed to train and test AIs and autonomous systems before deploying them in the physical world.
• Employees will leverage generative AI to interact with these digital twins of physical AI and systems in natural language to quickly retrieve knowledge, conduct analysis, and get recommendations.
• In industrial settings, generative AI will help engineers optimize their workflows and identify potential bottlenecks and improvements. Copilots will enable them to understand product and machine behavior, and quickly retrieve insights to be more productive.
• These technologies give us new superpowers and will continue to make work and the way we interact with technology easier and more intuitive.

Thank you, Rev Lebaredian, for your insights; we hope to see you back on AiThority.com soon.

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