Human brains are great at sorting through a barrage of sensory information - like discerning the smell of tomato sauce upon stepping into a busy restaurant - but artificial intelligence systems are challenged by large bursts of unregulated input.
Using the brain as a model, Cornell researchers from the Department of Psychology's Computational Physiology Lab and the Cornell University AI for Science Institute have developed a strategy for AI systems to process olfactory and other sensory data. Human (and other mammalian) brains efficiently organize unruly input from the outside world into reliable representations that we can understand, remember and use to make long-lasting connections. With these brain mechanisms as a guide, the researchers are designing low-energy, efficient robotic systems inspired by biology and useful for a wide range of potential applications.
"The brain performs amazing feats of cognition in real time and with startlingly low energy consumption. This includes sorting through lots of sensory information - often occluded, partially blocked, or degraded - to identify the information that matters, and interpret it based on contextual cues and prior experience," said Thomas Cleland, professor of psychology in the College of Arts and Sciences (A&S). "In principle, artificial physical systems should be able to do the same, once we figure out how it works."
In this study, which was published April 23 in Scientific Reports with Cleland as co-corresponding author, the researchers illuminate key aspects of how brains process sensory information, both to understand neural computation and to help build artificial devices with new capabilities. A goal of this "neuromorphic design" is to make AI devices that are as efficient and low-power as the brain. It would be a tremendous advance in design, said postdoctoral researcher Roy Moyal, first author and co-corresponding author of the study, but there is a lot of work to do before it can be realized.
Read the full story on the College of Arts and Sciences website.
