Accelerating AI Deployment: A Partnership Between EY and NVIDIA for Physical Testing and Deployment Solutions

AI is increasingly making its way into the physical world, with EY paving the way for companies to collaborate with robots, drones, and other smart devices in a more structured manner. EY is unveiling a physical AI platform that utilizes NVIDIA tools, establishing a new EY.ai Lab in Georgia, and appointing new leaders to steer its efforts in this domain.

The platform leverages NVIDIA Omniverse libraries, NVIDIA Isaac, and NVIDIA AI Enterprise software. EY asserts that this setup provides organizations with a clearer framework to strategize, test, and manage AI systems functioning in real-world environments, spanning from factory robots to drones and edge devices.

The Omniverse libraries enable the development of digital twins, enabling firms to simulate and test systems before deployment. NVIDIA Isaac tools offer accessible models and simulation frameworks for designing and validating AI-powered robots in intricate 3D environments. NVIDIA AI Enterprise furnishes the necessary computing foundation to handle heavy AI workloads.

EY describes the platform as centered around three key areas:

– AI-ready data: Generating synthetic data to replicate a variety of physical scenarios.
– Digital twins and robotics training: Tools facilitating the connection between digital and physical systems, monitoring real-time performance, and ensuring operational continuity.
– Responsible physical AI: Incorporating governance and controls to address safety, ethics, and compliance.

The platform is designed to support activities ranging from initial planning to long-term maintenance across sectors such as industrials, energy, consumer goods, and healthcare.

Raj Sharma, EY Global Managing Partner for Growth & Innovation, emphasizes that physical AI is already reshaping operations in various sectors, enhancing automation, and reducing operational costs. Sharma anticipates that the collaboration between EY’s industry expertise and NVIDIA’s infrastructure will accelerate the transition of companies from experimental phases to large-scale deployment.

John Fanelli from NVIDIA highlights the trend of more enterprises integrating robots and automation into real-world settings to adapt to workforce changes and enhance safety. Fanelli sees the EY.ai Lab, supported by NVIDIA AI infrastructure, as instrumental in helping organizations simulate, optimize, and securely deploy robotics applications on an enterprise scale, marking a pivotal phase in industrial AI.

Moreover, EY has appointed Dr. Youngjun Choi as its Global Physical AI Leader to oversee robotics and physical AI initiatives and shape EY’s advisory role in this space. With nearly two decades of experience in robotics and AI, Choi previously led the UPS Robotics AI Lab, focusing on digital twins, robotics projects, and AI tools to modernize the network. Prior to that, he served as research faculty in Aerospace Engineering at the Georgia Institute of Technology, contributing to aerial robotics and autonomous systems.

A vital aspect of Choi’s role is overseeing the newly launched EY.ai Lab in Alpharetta, Georgia, the first EY facility dedicated to physical AI. The Lab is equipped with robotics systems, sensors, and simulation tools for organizations to test concepts and develop prototypes prior to large-scale deployment.

Joe Depa, EY Global Chief Innovation Officer, notes that clients are seeking more effective ways to leverage technology for decision-making and performance enhancement. He emphasizes that strong data foundations and trust are crucial from the outset in physical AI initiatives. With Choi at the helm of the Lab, Depa believes that EY teams are delving deeper into the realm of possibilities and establishing the groundwork for scalable operations.

The Lab enables organizations to:

– Design and evaluate physical AI systems in a virtual test environment.
– Develop solutions for humanoid, quadruped, and other advanced robots.
– Enhance logistics, manufacturing, and maintenance through digital twin technologies.

The new platform and Lab build upon previous collaborations between EY and NVIDIA, including the launch of an AI agent platform earlier this year. Both entities plan to expand their physical AI endeavors into sectors like energy, healthcare, and smart cities, aiming to support automation projects that reduce waste and environmental impact.

Overall, the integration of physical AI into various industries signifies a transformative shift in how businesses operate, driving efficiency and innovation. The partnership between EY and NVIDIA is poised to accelerate the adoption of AI technologies on a broader scale, ushering in a new era of industrial AI advancements.