Synthetic experience design: using multi-modal and rich media to create artificial experiences constructs for bots

Inspired by Learning Theory, cognitive science, psychological descriptions of experience and memory, unsupervised labeling, and computer vision; Terry Traylor - a retired military information and artificial intelligence professional - borrows techniques from both the social and natural sciences to identify processes that enable experimental AI learning from cybersecurity videos. Specifically, he uses mixed-methods theory development techniques from qualitative science to study students learning cybersecurity processes to develop a biologically-inspired synthetic framework to bootstrap machine learning or other generalized synthetic learning processes. Using the learning cybersecurity tradecraft from videos case, he exposes processes and challenges associated with handling multi-modal information that enables generalized synthetic learning. Special attention is paid to Sensory AI challenges, synthetic perception, and multi-modal processing. The session will expose attendees to a synthetic structure for multi-signal/multi-modal learning, a proposed language for synthetic experience memory structures, and a biologically-inspired structure for the multi-modal learning problem.