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No. Even for large models that a good mental model. This is parroted all over and is wrong. Its not going to generate out of distribution answers. Its a probabilistic function of the training set.

It's not widely known and mostly spun in MSM as fringe theory (thanks to marketing by big AI cos). this is a well written essay, and if it helps the discourse all the better.

Upton Sinclair: "It is difficult to get a man to understand something, when his salary depends upon his not understanding it."

If you don't have stakeholders I contend you probably don't have a product, or you're building the bare minimum MVP which upon becoming a product will be woefully inadequate, generating the aforementioned bottleneck.

re: your last point that is not true. we can measure arbitrarially quickly (Nottingham group does some 3d EVI at ~100ms TRs). You can also reduce volumes and just look at single slices etc, a lot of the fundamental research did this (wash U / Minnesota / etc in the 90s). Its just not all that useful because the SNR tanks and the underlying neurovascular response is inherently low-pass. There is a much faster 'initial-dip' where the bold signal swings the other way and crosses zero (from localized accumulation of DeoxyHg before the inrush of OxyHg from the vascular response). Its a lot better correlated with LFP / spiking measures but just very hard to measure on non-research scanners...

agree. especially the comments saying "just address it". Its a lot of technically complicated interactions between the physics, imaging parameters, and processing techniques. Unfortunately the end users (typically neuroscience/psych grad students in labs with minimal oversight) usually run studies that just "throw everything at the wall and see what sticks" not realizing that is the antithesis of the scientific method. No one goes in to a resting state study saying "we're going to test if the resting state signal in the <region> is <changed somehow> becuase of <underlying physiology>". They instead measure a bunch of stuff find some regions that pass threshold in a group difference and publish it as "neural correlates of X". Its not science, and its why its not reproducible. People have build whole research programs on noise.