We sat down with each of our Advisory Board Members to ask them why they’re excited about working with AEye…
Willie Gault is a former NFL wide receiver and Olympic athlete. Gault was an All-American at the University of Tennessee from 1979 to 1982. He played in the National Football League for 11 seasons for the Chicago Bears and Los Angeles Raiders. Considered one of the fastest NFL players of all-time, Gault was a member of the Chicago Bears team that won Super Bowl XX, and was also a participant of both the summer and winter U.S. Olympic teams. Gault is currently an investor, remains active, and holds several world records in masters track and field.
Q: What in your past experience ultimately drew you to the autonomous vehicle arena?
As a professional athlete, I have always been fascinated and amazed by human perception and the role it plays in athletic performance. The brain’s ability to sense the details in the world around you and then accurately calculate where your body needs to be in space and time is remarkable. I have been curious about how these capabilities might be replicated with technology and artificial intelligence. Recently, I have been tracking the application of artificial intelligence in autonomous vehicles which led me to AEye.
Q: Why AEye?
What AEye is doing aligns with my interests in biomimicry, which uses knowledge of natural processes found in humans, plants, and animals to better inform technology and design. After I found out AEye was pursuing research in this field, I knew I had to be part of it.
Q: Where do you see ADAS solutions, autonomous vehicles, and/or artificial perception, heading within the next few years? The next decade? Beyond? How do you see AEye playing a pivotal role in this vision?
I live in Southern California where traffic has a major impact on quality of life. Autonomous vehicles will not only improve safety and efficiency on the roads, but will greatly improve quality of life around the world. I would like to see this technology adopted quickly and widely. However, one of the barriers to its adoption is cost. I believe that AEye’s iDAR system can be manufactured at tremendous scale, efficiently, and at a price point that encourages rapid adoption.