Amazon Web Services, KBR and NASA collaborated to stage a â€œDeepRacerâ€ event on Aug. 8th to showcase a race of fully autonomous vehicles operated by NASA and KBR interns who used an advanced machine learning technique called reinforcement learning, KBR said Thursday.
The â€œDeepRacerâ€ event was held at NASAâ€™s Goddard Space Flight Center to see whose machine-learning models could propel an AWS DeepRacer vehicle around a track the fastest. Minh Nguyen, an intern with KBR, was the developer of the winning vehicle, which had a track time of 13.14 seconds.
â€œKBR understands the importance of investing in tomorrowâ€™s workforce. We are proud to have played a key role in an event that fueled internsâ€™ imaginations and developed their AI skills,â€ said Byron Bright, president of U.S. government solutions. â€œThe DeepRacer event also provided an opportunity for NASA to experiment with autonomous systems for future exploration missions and showcased how the private and public sector can collaborate to leverage and advance technology,â€ he continued.
KBR worked with AWS and NASA to organize this event, as well as a pre-race, four-hour workshop with an AWS DeepRacer expert to help interns build, test and fine-tune their reinforcement learning models.
At one-eighteenth the size of a normal car, the AWS DeepRacer allows reinforcement learning models built in virtual environments to be tested in the real world, which presents an accessible opportunity for exploring artificial intelligence and machine learning.
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