Visual programming of machine learning state machines

A system comprising one or more processors and memory storing instructions that, in response to execution of the instructions, cause the one or more processors to:

• cause one or more graphical user interfaces (GUIs) to be rendered on one or more displays, wherein each GUI of the one or more GUIs includes a working canvas on which a plurality of nodes corresponding to at least some of a plurality of available logical routines are manipulable to form a graph defining a machine learning state machine, wherein edges of the graph represent logical couplings between the logical routines of the plurality of available logical routines that are represented by the nodes of the graph;
• identify first and second partially redundant nodes in the graph, the first and second partially redundant nodes having at least one overlapping logical operation, the first partially redundant node having a first non-overlapping logical operation, the second partially redundant node having a second non-overlapping logical operation, wherein the at least one overlapping logical operation represents execution of one or more machine learning models;
• merge the at least one overlapping logical operation of the first and second partially redundant nodes into a consolidated logical routine;
• logically couple the first non-overlapping logical operation with the consolidated logical routine;
• and
• logically couple the second non-overlapping logical operation with the consolidated logical routine.

At least one non-transitory computer-readable medium comprising instructions that, in response to execution by one or more processors, cause the one or more processors to:

• cause one or more graphical user interfaces (GUIs) to be rendered on one or more displays, wherein each GUI of the one or more GUIs includes a working canvas on which a plurality of nodes corresponding to at least some of a plurality of available logical routines are manipulable to form a graph defining a machine learning state machine, wherein edges of the graph represent logical couplings between the logical routines of the plurality of available logical routines that are represented by the nodes of the graph;
• identify first and second partially redundant nodes in the graph, the first and second partially redundant nodes having at least one overlapping logical operation, the first partially redundant node having a first non-overlapping logical operation, the second partially redundant node having a second non-overlapping logical operation, wherein the at least one overlapping logical operation represents execution of one or more machine learning models;
• merge the at least one overlapping logical operation of the first and second partially redundant nodes into a consolidated logical routine;
• logically couple the first non-overlapping logical operation with the consolidated logical routine;
• and
• logically couple the second non-overlapping logical operation with the consolidated logical routine.