|GMW is a physicist and software developer interested in functional and logic programming, quantum mechanics, statistical mechanics, symbolic logic, natural language processing, topology, artificial intelligence, mean field game theory, musical set theory, and symmetry. He has a B.S. in chemistry from UCLA, a Ph.D. in chemical physics from the University of Washington, Seattle, and a postdoctoral fellowship in software development from UCSF. As of 2018, GMW has been developing and prototyping software algorithms for 28 years with applications in the physical sciences, bioinformatics, diagnostics, music composition, and natural language processing.
Using techniques in artificial intellegence, GMW builds human-like intelligent model systems that simulate actual reality, and uses the properties and mathematics of quantum mechanics to describe systems and dynamics of artificial neural networks, especially for bidirectional associative memory. Some applications involve predicting the flow of liquids, modeling of micro-structure, pattern recognition, neural machine translation, and model systems for quantum cognition. Other applications involve using combinations of artificial intelligence, musical set theory, cyclic sets, and interval class vectors, to produce both tonal and atonal structured compositions.
GMW is associated with the following organizations: