Comment by troelsSteegin

The Percepta stuff would seem to demonstrate a mechanism for implementing "thinking". I don't understand how foundation models implement "thinking", but my intuition is that models are specifically trained for matching on and following procedural patterns. A task in a given domain can be performed through an associated and encoded procedure. The model holds all the linkages, as weights, that allows a procedure to be conditionally incrementally generated and performed. Does anyone have any insights about how LLM "thinking" is trained and coded?