We now consider if the NNs can extrapolate for a configuration more similar to the training data. Consider the 𝑁 = 0 configuration in Fig. , which has two black and two white segments, similar to the 𝑁 = 1 configuration after starting from the single black-white initial condition (like 𝑁 = 1 in Fig. ), except that the two black and two white segments are of unequal length with the largest segments on the left side of the domain. The NN 10k realization appears to begin mixing in a similar fashion to the 𝑁 = 0 LS method for the leftmost black and white segments and then continues to apply the left to right pattern learned from the LS training data; this is most evident between 𝑁 = 6 and 𝑁 = 13 but is not followed strictly for 𝑁 = 3, 4. Although the cuts do not match the LS method, two new interfaces are created with each iteration and mixing progresses through at least 𝑁 = 15, though some of the new segments are quite narrow (e.g., the new black segment at 𝑁 = 9 in the fourth white segment from the left and the new white segment at 𝑁 = 13 in the rightmost black segment, both of which are visible only upon magnification). This success appears to result from positioning the largest segments on the left side of the domain, where the NN is trained to cut first.