Ishmam Khan ’25 Deep learning involves the use of machinery to simulate biological phenomena, especially human behavior. Researchers have developed two systems of programming that proved useful in mimicking movements: convolutional neural networks (CNNs), which are based on virtual imagery and spatial information, and recurrent neural networks (RNNs), which adapt long-short term memory (LSTM) to model long term contextual information of temporal sequences.  When used … Continue reading Optimizing Movement-Based Behavior Networks in Artificial Intelligence