KNOXVILLE, Tenn. (WATE) — A first-of-its-kind agreement between Oak Ridge National Laboratory and General Motors could speed up the car manufacturer’s building of autonomous vehicles and increase onboard computing capacity.
The Department of Energy’s lab has licensed its artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to GM for use in vehicle technology and design.
The AI system, known as MENNDL, uses evolution to design optimal convolutional neural networks – algorithms used by computers to recognize patterns in datasets of text, images or sounds. General Motors will assess MENNDL’s potential to accelerate advanced driver assistance systems technology and design.
This is the first commercial license for MENNDL as well as the first AI technology to be commercially licensed from ORNL.
“MENNDL leverages compute power to explore all the different design parameters that are available to you, fully automated, and then comes back and says, ‘Here’s a list of all the network designs that I tried,” Robert Patton, leader of the AI software’s development team, said. “Here are the results – the good ones, the bad ones.’ And now, in a matter of hours instead of months or years, you have a full set of network designs for a particular application.”
For automakers, MENNDL can be used to accelerate advanced driver assistance technology by tackling one of the biggest problems facing the adoption of this technology: How can cars quickly and accurately perceive their surroundings to navigate safely through them?
The use of MENNDL offers potential to better clear that roadblock.
The neural networks can instantly analyze on-board camera feeds and correctly label each object in the car’s field of view. This type of advanced computing has the potential to enable more efficient energy usage for vehicles while increasing their onboard computing capacity.
The MENNDL AI system can dramatically speed up that process, evaluating thousands of optimized neural networks in a matter of hours, depending on the power of the computer used. It has been designed to run on a variety of different systems, from desktops to supercomputers, equipped with graphics processing units.
Since its inception in 2014, MENNDL has been used in applications ranging from identifying neutrino collisions for Fermi National Accelerator Laboratory to analyzing data generated by scanning transmission electron microscopes. Last year, in a project with the Stony Brook Cancer Center at Stony Brook University in New York, MENNDL was used on ORNL’s Summit supercomputer to create neural networks that can detect cancer markers in biopsy images much faster than doctors.