NVidia's Jensen Huang on Training AI Robots in tthe Omniverse | Future of Selling EP004

Nvidia's Jensen Huang discusses the future of AI, highlighting two key areas: digital AI agents and physical AI robots. Digital agents, akin to digital employees, can be trained and deployed for various tasks, while physical AI utilizes the Omniverse platform to train robots in a simulated environment before deployment in the real world. This technology has the potential to significantly impact productivity and transform industries.

Digital AI Agents

• 00:00:04 AI agents, also known as digital AI workers, are essentially digital employees that can be trained for various tasks like marketing, customer service, and manufacturing. These agents can be trained, evaluated, and guarded to ensure they fulfill their designated roles within an organization. Companies can build these AI agents using Nvidia's enabling technology, rather than purchasing pre-built solutions.

Training AI Agents

• 00:02:11 The process of training AI agents involves providing them with data, teaching them about the company, and developing their specific skills. This training is similar to onboarding a human employee, including job descriptions, guardrails, and evaluations to ensure they perform as intended. After training, the agents can operate independently, communicate with other agents, and contribute to business scaling.

AI Agent Platforms

• 00:04:57 Nvidia's Nemo platform provides libraries and workflows for the AI agent life cycle, encompassing data curation, training, evaluation, and guardrails. Independent Software Vendors (ISVs) can leverage the platform to create agents for specific company needs, simplifying the process for businesses unfamiliar with AI development. This platform concept is comparable to readily available agents or ‘agents in a box’ for easy implementation and application.

Physical AI & Robotics

• 00:13:17 Physical AI, encompassing robotics, is becoming increasingly important for industries. The Omniverse platform simulates real-world environments, allowing robots to be trained and tested virtually before deployment. This platform uses physics-based simulations and leverages technologies like Isaac Lab and Groot to enable robots to learn and adapt to diverse conditions.

Humanoid Robotics

• 00:19:19 The development of human or robots presents a significant challenge due to the complexity of the required software. However, the potential benefits are substantial, particularly in adapting to existing environments. Nvidia's Isaac Lab, featuring workflows like Groot Mimic and Groot Gen, facilitates training robots using reinforcement learning and synthetic data generation, enabling them to perform diverse tasks autonomously.