Tom McGrath says nearby positive correlations and long-range anti-correlations in feature activations provide sufficient structure for fitting an Ising model.

“And so, you know, this pattern of like nearby positive correlation,”

“long range anti-correlation is enough structure for you to actually fit.”

“um to fit we we uh we fit an icing model to it which is rather a surprise to me when the team came back with that i was like cool um and the reason this is like a good model is that you can have both sort of positive and negative coupling strengths and fitting this allows us to like fit a spline through the through the data”