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Equation 33 · Part 2 · AI Feeds on the Distance Between an Intention and an Outcome

Symbol B

Wm(B)=∑(g,h)∈Gwgh 1{(g,h)∈Nm(B)}.W_m(B)=\sum_{(g,h)\in\mathcal{G}}w_{gh}\,\mathbf{1}\{(g,h)\in\mathcal{N}_m(B)\}.
BB

What this part means

B is an argument of the function-like quantity on the left; its role is set by that function’s stated inputs.

Its job in the formula

B is an argument of the function-like quantity on the left; its role is set by that function’s stated inputs.

The passage around this formula

To compare systems without pretending that this irregular region is a Euclidean animal range, bin the preregistered plane into cells and define width as Wm(B)=∑(g,h)∈Gwgh 1{(g,h)∈Nm(B)}W_m(B)=\sum_{(g,h)\in\mathcal{G}}w_{gh}\,\mathbf{1}\{(g,h)\in\mathcal{N}_m(B)\}. The unit is weighted grid cells, stated with the binning rule. Report its depth too: the greatest gap or horizon cell satisfying the reliability rule. A broad, shallow system has a large WmW_m but low maximum depth; a narrow, deep specialist may have small width yet persist at large g or h . Neither is “more intelligent” by definition. The map makes a tradeoff inspectable.

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Learn the underlying idea

A variable is a named place for a value. Its letter is a local label: x can mean position in one formula and a data point in another.

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