Waterland, AmosAppavoo, JonathanSchatzberg, Dan2015-06-242015-06-242012-04-15Waterland, Amos; Appavoo, Jonathan; Schatzberg, Dan. "Programmable Smart Machines", Technical Report BUCS-TR-2012-007, Computer Science Department, Boston University, April 15, 2012. [Available from: http://hdl.handle.net/2144/11395]https://hdl.handle.net/2144/11395In this paper we conjecture that a system can be constructed that exploits the general ability to learn through the counting, correlating, and memorizing of occurrences of events to fast-forward a programmable computer. In particular, we propose a signal based interpretation of a computer's execution that can be used to implement a form of system state memoization using a predictive associative memory. Such an approach may some day lead to a system that can utilize both traditional logic and neuromorphic or other biologically inspired mechanisms to be both programmable and smart.en-USTechnical Report