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NVIDIA Ushers in New Era of Robotics, Making It Easier to Build and Train Intelligent Machines

By   /  May 16, 2017  /  No Comments

by Angela Guess

According to a recent press release, “NVIDIA today ushered in a new era for the robotics industry, introducing breakthroughs that radically simplify the work of building and training intelligent machines. In his keynote at the eighth annual GPU Technology Conference, NVIDIA CEO and founder Jensen Huang introduced the NVIDIA Isaac™ robot simulator, which utilizes sophisticated video-game and graphics technologies to train intelligent machines in simulated real-world conditions before they get deployed. The company also introduced a set of robot reference-design platforms that make it faster to build such machines using the NVIDIA Jetson™ platform. ‘Robots based on artificial intelligence hold enormous promise for improving our lives, but building and training them has posed significant challenges,’ Huang said. ‘NVIDIA is now revolutionizing the robotics industry by applying our deep expertise in simulating the real world so that robots can be trained more precisely, more safely and more rapidly’.”

The release goes on, “Prior to deployment, robots must be extensively trained and tested. With physical prototypes, this can be expensive and impractical. Creating the complete environment a robot will interact with can be unsafe or very complex. Modeling all possible interactions between a robot and its surrounding environment can be highly time consuming. The Isaac robot simulator advances these tasks by providing an AI-based software platform that lets teams train robots in highly realistic virtual environments and then transfer that knowledge to real-world units. Isaac is built on an enhanced version of Epic Games’ Unreal Engine 4 and uses NVIDIA’s advanced simulation, rendering and deep learning technologies. Working within this virtual environment, developers can set up extensive test scenarios using deep learning training, and then simulate them in minutes — which would otherwise take months to perform.”

Read more at Marketwired.

Photo credit: NVIDIA

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