Try to first understand before commenting

Convolution of f and g at t is:

    integration of f(x) * g(t - x)

Cross correlation(which is termed convolution in DL) at t is:

    integration of f(x) * g(t + x)

See the figure in the wikipedia page you shared.

This is still very low level, the whole article (although very comprehensive) missed the simple definition which it should have mentioned first. Going into jargons only add to complications. Look it up in a dictionary first for English definition and then try to understand how it has been applied in different domains.

1 : a form or shape that is folded in curved or tortuous windings e.g the convolutions of the intestines

2 : one of the irregular ridges on the surface of the brain and especially of the cerebrum of higher mammals

3 : a complication or intricacy of form, design, or structure … societies in which the convolutions of power and the caprices of the powerful are ever-present dangers to survival.

After this is clear read the mathematical idea on wikipedia. After reading that, do google scholar search on the AI papers that first mentioned it. That is the way to go.