We identify objects after compensating for variability

Writing a paper about best model estimation and finally came to a very simple initial statement:

"Geometric invariants are considered important in mathematics as the quantities that identify geometric objects [Weyl]. They are also important in shape recognition and robotics where an object is to be identified or recognized independently of its position, distance, or angle of presentation to the viewer – which is to say independently of its variants. This paper assumes we can measure an object’s variants and expresses the simple idea that recognition is a composition of a variant factor with an invariant one. In terms of measuring the variants, it states the obvious: we identify what is left after taking out the variability. "

Converting syntax to semantics

Think of reading/understanding as a process of converting words into an overall meaning. As we progress through the (say) text, words are read into semantic "structure" creating anticipations for subsequent words and meanings. So syntax is transferred into semantics, one word at a time.